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Summary of the 2023 GEDI Science Team Meeting

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Summary of the 2023 GEDI Science Team Meeting

Introduction

The 2023 Global Ecosystem Dynamics Investigation (GEDI) Science Team Meeting (STM) took place October 17–19, 2023, at the University of Maryland, College Park (UMD), in College Park, MD. Upwards of 80 people participated in the hybrid meeting (around 50 in-person and the rest virtually). Included among them were GEDI Science Team (ST) members, collaborators, and stakeholders – see Photo. The primary goals of the meeting included providing a status update on the GEDI instrument aboard the International Space Station (ISS), receiving final project updates from the inaugural cohort of the GEDI completed ST, and understanding the present status and future goals of data product development.

After a short mission status update, the remainder of this article will summarize the content of the STM. For those desiring more information on these topics, some of the full meeting presentations are posted online. Readers can also contact the GEDI ST with specific questions.

GEDI group photo
Photo. GEDI Science Team Meeting in-person and virtual attendees.
Photo credit: Talia Schwelling

Mission Status Update: GEDI Given New Lease on Life

A lot has changed since the publication of the last GEDI STM summary. (See Summary of the GEDI Science Team Meeting in the July–August 2022 issue of The Earth Observer [Volume 34, issue 4, pp. 20–24]). When the GEDI ST convened in November 2022, the fate of GEDI was hanging in the balance, with the plan being to release GEDI from the ISS at the end of its second extension period.

NASA saved the instrument, however, and a new plan went into effect: in order to extend its tenure on the ISS, the GEDI mission entered a temporary period of “hibernation” in March 2023 after nearly four years in orbit. This hibernation period and movement of the instrument from Exposed Facility Unit (EFU)-6 (operating location) to EFU-7 (storage location) made way for another mission – see Figure 1. (UPDATE: After being in storage for roughly 13 months, the GEDI instrument was returned to its original location on the Japanese Experiment Module–Exposed Facility (JEM–EF) on Earth Day this year, April 22, 2024, and is now once again back to normal science operations using its three lasers.)

GEDI figure 2
Figure 1. NASA’s GEDI instrument was moved from EFU-6 to EFU-7 on the ISS on March 17, 2023, where it remained in hibernation for 13 months until its recent reinstallation to EFU-6 on April 22, 2024. The instrument is once again back to normal science operations using its three lasers.
Figure credit: NASA

As The Earth Observer reported in 2023, data from GEDI are being used for a wide range of applications, including biomass estimation, habitat characterization, and wildfire prediction (See page 4 of The Editor’s Corner in the March–April 2023 issue of The Earth Observer [Volume 35,Issue 2, pp. 1–4]. This section also reports on GEDI’s extension via out-of-cycle Senior Review in 2022). GEDI data is used to develop maps to quantify biomass that are unique in both their accuracy and their explicit characterization of uncertainty and are a key component in the estimation of aboveground carbon stocks, as absorbed carbon is used to drive plant growth and is stored as biomass – see Figure 2. These estimations help quantify the impacts of deforestation and subsequent regrowth on atmospheric carbon dioxide (CO2) concentration. NASA’s choice to extend the GEDI mission has significantly broadened the capacity to collect more of these important data.

GEDI figure 1
Figure 2. Country-wide estimates of total aboveground biomass in petagrams (Pg) using GEDI Level-4B Version 2.1 dataset (GEDI_L4B_AGB).
Figure credit: ORNL DAAC

DAY ONE

GEDI Mission Operations, Instrument Status, and Data Level Updates

Ralph Dubayah [UMD—GEDI Principal Investigator (PI)] opened the meeting with a summary of the current status of the mission and GEDI data products. After reviewing the details of GEDI’s hibernation (described in the previous section) he went on to describe what GEDI has accomplished over the past 4.5 years of operations, noting that the instrument collected over 26 billion footprints over the land surface.

All the data collected by GEDI during its first epoch (i.e., before its hibernation) have been processed and released to the appropriate Distributed Active Archives Centers (DAACs) as Version 2 (V2) products. (To learn more about the DAACs and other aspects of Earth Science data collection and processing, see Earth Science Data Operations: Acquiring, Distributing, and Delivering NASA Data for the Benefit of Society, in the March–April 2017 issue of The Earth Observer, [Volume 29, Issue 2, pp. 4–18]. The DAACs – including URL links to each – are listed in a Table on page 7–8 of this issue). The two DAACs directly involved with GEDI data processing are the Land Processes DAAC (LP DAAC) and Oak Ridge National Laboratory (ORNL) DAAC. The LP DAAC houses GEDI Level-1 (L1) data, which consists of geolocated waveforms, and L2 data, which is broken down into L2A and L2B. L2A data includes ground elevation, canopy height, and relative height metrics. (Waveform measurements are described in detail in a sidebar on page 32 of the Summary of the Second GEDI Science Team Meeting in the November–December 2016 issue of The Earth Observer [Volume 28, Issue 6, pp. 31–36].) L2B data includes canopy cover fraction (CCF) and leaf area index (LAI). The ORNL DAAC houses GEDI L3 gridded land surface metrics data, L4A footprint level aboveground biomass density data, and L4B gridded aboveground biomass density data – e.g., see Figure 2.

Dubayah went on to explain that while GEDI hibernated, the mission team would work to enhance existing data products as well as produce new products. Version 3 (V3) datasets for all data products are expected to be released by the fall of 2024, and new data products are in development, including a waveform structural complexity index (WSCI) and a topography and canopy height product that blends data from GEDI and the Ice, Clouds, and land Elevation Satellite–2 (ICESat–2) mission. A new dataset, the GEDI L4C footprint level waveform structural complexity index (WSCI) product, was added to the ORNL DAAC catalogue in May 2024. To further improve data quality and coverage, the GEDI team is hoping to organize an airborne lidar field campaign to southeast Asia in the coming years. Dubayah concluded his updates by highlighting a set of six papers published in 2023 in Nature and Science family or partner journals that focused on the use of GEDI data. Visit our website for a comprehensive list of publications related to GEDI.

After receiving a general update from the mission PI, the next several presentations gave meeting participants a more in-depth look at GEDI science data planning and individual data products. Scott Luthcke [NASA’s Goddard Space Flight Center (GSFC)—GEDI Co-Investigator (Co-I)] presented status updates for the GEDI Science Operating Center (SOC), including the Science Planning System (SPS) and Science Data Processing System (SDPS) automation, development, and processing. In addition, he reported on the status of the L1 geolocated waveform data product and the L3 gridded land surface metrics product. At the time of this meeting, the SPS had completed operations through mission week 223 – almost 4.5 years of data – and was beginning to transition to improving processes on the back end while GEDI hibernates. The SDPS had completed processing and delivery of all V2 data products to the LP DAAC and ORNL DAAC.

Luthcke reported on GEDI’s current observed and estimated geolocation performance, including detailed summaries of component analysis and steps towards improving Precision Orbit Determination (POD), Precision Attitude Determination (PAD), Pointing Calibration, time-tag correction, and Oven Controlled Crystal Oscillator (OCXO) calibration. GEDI passes over Salar de Uyuni, the world’s largest salt flat located in Bolivia – see Figure 3, are being used to assess the PAD high-frequency and low-frequency errors. Estimated errors are shown to be consistent with observed geolocation errors. Finally, Luthcke gave a summary of completed L3 products and new wall-to-wall 1-km (0.62-mi) resolution and high-resolution products.

GEDI figure 3
Figure 3. Salar de Uyuni, the world’s largest salt flat as seen from the International Space Station.
Figure credit: Samantha Cristoforetti/ESA/NASA

John Armston [UMD—GEDI Co-I] updated attendees on GEDI L2 products. L2A consists of elevation and height metrics, and L2B consists of canopy cover and vertical profile metrics. To assess GEDI ground and canopy top measurement accuracy and improve algorithm performance, the mission team is using data collected from NASA Land, Vegetation, and Ice Sensor (LVIS) campaigns from 2016 to present. Armston reported that L2B estimates of canopy and ground reflectance were completed for the first mission epoch (April 2019–March 2023) and the GEDI team continues to work on algorithm improvements for cover estimates in challenging conditions (e.g., steep slopes). Data users can expect improved waveform processing for ground elevation and canopy height, new reflectance estimation, and revised quality metrics and flags in the L2A and L2B not-yet-released V3 products.

Jim Kellner [Brown University—GEDI Co-I] shared the current status of and planned algorithm improvements to the L4A data product, or the footprint-level aboveground biomass density product. The algorithm theoretical basis document for L4A data products was published in November 2022; it describes how models were developed and the importance of quality filtering. L4A data product development continues in tandem with updates to L2A data and improvements to existing calibration and validation data and ingestion of new data.

Sean Healey [U.S. Forest Service—GEDI Co-I] reviewed coverage and uncertainties of the recently produced V2 L4B data products – see Figure 4. Ongoing GEDI-relevant research includes:

  • investigating a statistical method called bootstrapping, which may allow more complex types of models;
  • conducting theoretical statistical studies aimed at decomposing mean square error for model-based methods; and
  • developing ways to estimate biomass change over time – which will become more important as the extended mission potentially stretches to a decade.
GEDI figure 4
Figure 4. Gridded mean aboveground biomass density [top] and standard error of the mean [bottom] from Version 2.1 of the GEDI L4B Gridded Aboveground Biomass Density product, published on October 29, 2023.
Figure credit: ORNL DAAC

Competed Science Team Presentations—Session 1

This GEDI STM was the last convergence of the first iteration of the GEDI competed ST. Attendees received final in-person updates on the cohort’s projects and plans for future research. Over the course of the three-day meeting, there were several sections dedicated to Competed ST Presentations. For purposes of organization in this report, each section has been given a session number. 

Taejin Park [NASA’s Ames Research Center (ARC) and Bay Area Environmental Research Institute (BAERI)] kicked off the ST presentations with an overview of his group’s progress in enhancing the predictions of forest height and aboveground biomass by incorporating GEDI L2, L3, and L4 data products into a process-based model, called Allometric Scaling Resource Limitation (ASRL), over the contiguous United States (CONUS). The ASRL model effectively captures large-scale, maximum tree size distribution and facilitates prognostic applications for predicting future aboveground biomass changes under various climate scenarios. Park also described collaborative research efforts with international partners  to map changes in aboveground biomass in tropical and temperate forests using a carbon management systems (CMS).

Kerri Vierling [University of Idaho] shared the results from her team’s projects demonstrating the use of GEDI data fusion products to describe patterns of bird and mammal distributions in western U.S. forests. The focal species for these projects include a suite of vertebrate forest carnivores, prey, and ecosystem engineer species that modify their environments in ways that create habitat for other creatures, e.g., woodpeckers – see Figure 5. Many of these species are of interest for management by a variety of state and federal agencies. Vierling also discussed ongoing analyses identifying biodiversity hotspots and land ownership patterns.

GEDI figure 5
Figure 5. A Female downy woodpecker creates a tree cavity that other organisms may use in the future for habitat. Woodpecker species are great examples of ecosystem engineers.
Figure credit: Doug Swartz/Macaulay Library at the Cornell Lab or Ornithology (ML 58304661)

Sean Healey presented on his competed ST research on Online Biomass Inference using Waveforms and iNventory (OBI-WAN), a Google Earth Engine application. This forest-carbon reporting tool harnesses GEDI waveforms, biomass models, and statistics to make estimates of mean biomass and biomass change for areas specified by online users. Healey explained the statistical methods applied to operate OBI-WAN and gave context for the use of sensor fusion to provide biomass change information that is critical for monitoring, reporting, and verification.

Keith Krause [Battelle] presented his work evaluating vertical structural similarity of LVIS classic and GEDI large-footprint waveforms. At the GEDI and LVIS footprint scale (20–23 m, or 65–75 ft, spot on the ground), lidar waveforms over forests represent canopies of leaves and branches from several trees. Krause presented results comparing waveforms against each other to show similarities in shape (i.e., if the trees in their footprints have a similar vertical structure). He also described how he used data clustering techniques to group similar waveforms into distinct structural classes. From there, he could map waveforms with similar vertical structure to better understand the spatial distribution of the structural groups.

Breakout Sessions—Session 1

GEDI STMs offer a rare opportunity for members of the competed and mission STs, a variety of stakeholders, and other individuals to convene and discuss ideas and goals for their own research and for the GEDI mission. Toward that end, breakout sessions were held on the first and second day of the meeting – referred to as Session 1 and Session 2 in this report. The individual breakout meetings used a hybrid format allowing in-person and online participants to join the discussion that was most relevant to their interests and expertise.

Chris Hakkenberg [Northern Arizona University (NAU)] led a breakout session on structural diversity, including the horizontal and vertical components. Different structural attributes, (e.g., stand structure, height, cover, and vegetation density) have different – but related – metrics and measurement approaches. Participants discussed biodiversity-structure relationships (BSRs), how to better characterize horizontal structural diversity, and how to define which metrics (i.e., scale, sampling unit, and spatial resolution) are most meaningful in different situations.

Jim Kellner led a session that focused on biomass calibration and validation and how to create the best data products given global environmental variation. Special cases – e.g., mangroves – pose challenges for calibration and validation because they don’t always have as much plot-level data as other environments. Participants discussed how to determine strata while considering climactic and environmental covariates as well as constraints of data availability and consistency.

Competed Science Team Presentations—Session 2

The FORest Carbon Estimation (FORCE) Project is exploring the use of GEDI-derived canopy structure metrics to map forest biomass in the U.S. and Canada. Daniel Hayes [University of Maine] presented comparisons of GEDI metrics and canopy height models derived from airborne lidar and photo point clouds over different forest types and disturbance history in managed forests of Maine. Co-PI Andy Finley [Michigan State University] presented new work that adjusts GEDI L4B biomass estimates to plot data over the continental U.S. from Forest Inventory and Analysis (FIA) program of the U.S. Department of Agriculture’s Forest Research and Development Branch. The project’s next steps are to fuse GEDI canopy structure metrics with other covariates in a spatial model to produce wall-to-wall estimates of biomass for boreal–temperate transition forests in northeast North America.

GEDI data is also being used to study tropical forests. Chris Doughty [NAU] described how he and his team analyzed GEDI L2A data across all tropical forests and found that tropical forest structure was less stratified and more exposed to sunlight than previously thought. Most tropical forests (80% of the Amazon and 70% of southeast Asia and the Congo Basin) have a peak in the number of leaves at 15 m (49 ft) instead of at the canopy top. Doughty and his team have found that deviation from more ideal conditions (i.e., lower fertility or higher temperatures) lead to shorter, less-stratified tropical forests with lower biomass.

Paul Moorcroft [Harvard University] reported on studies of current and future carbon dynamics across the Pacific Coast region based on forest structure and rates of carbon uptake. Moorcroft’s group examined how these ecosystems will behave in the future under different climate scenarios and have plans to conduct similar studies in other regions.

DAY TWO

Naikoa Aguilar-Amuchastegui [World Bank] kicked off day two with his perspective on the importance of streamlining the monitoring, reporting, and validation (MRV) process from scientific estimation to actual use of the data. Once scientific data is generated, end users are often faced with challenges related to transparency and understandability. Scientists can better communicate how to use their datasets properly, by familiarizing themselves with who wants to use their data, why they want to use it, and what their needs are. With this information in mind, data can be presented in more practical ways that allow for a variety of institutions with different standards and frameworks to integrate GEDI data more easily into their reporting. As the GEDI team continues to produce high-quality maps, efforts are underway to connect with end users and provide tutorials, workshops, and other resources.

GEDI Demonstrative Products

Demonstrative products show how GEDI data can be used in practice and in combination with other resources. Ecosystem modeling is one way that GEDI data are being used to address questions about aboveground carbon balance, future atmospheric CO2 concentrations, and habitat quality and biodiversity. George Hurtt [UMD—GEDI Co-I] shared his progress on integrating GEDI canopy height measurements with the Ecosystem Demography model to estimate current global forest carbon stocks and project future sequestration gaps under climate change – see Figure 6. Hurtt emphasized that this unprecedented volume of lidar data significantly enhances the ability of carbon models to capture spatial heterogeneity of forest carbon dynamics at 1 km (0.6 mi) scale, which is crucial for local policymaking regarding climate mitigation.

GEDI figure 6
Figure 6. [Top] Average lidar canopy height at 0.01° resolution, computed by gridding both GEDI and ICESat-2 together, and carbon stocks [middle] and fluxes [bottom] from ED-Lidar (GEDI and ICESat-2 combined). The insets highlight fine-scale spatial distribution and coverage gaps at selected regions (1.5° × 1.5°). Note that the three maps show grid-cell averages aggregated from sub-grid scale heterogeneity for each variable.
Figure credit: From a 2023 article in Global Change Biology.

There is also great potential for the development and application of methods for mapping forest structure, carbon stocks, and their changes by fusing data from GEDI and the Deutsches Zentrum für Luft- und Raumfahrt’s (DLR) [German Space Operations Center] TerraSAR-X Add-oN for Digital Elevation Measurement (TanDEM-X) satellite mission, which uses synthetic aperture radar (SAR) to gather three-dimensional (3D) images of Earth’s surface. This fusion product is being spearheaded by Wenlu Qi [UMD], who presented on efforts to create maps of pantropical canopy height, biomass, forest structure, and biomass change using the fusion product as well as maps of forests in temperate U.S. and Hawaii.

Data from the GEDI mission are also being used to quantify the spatial and temporal distribution of habitat structure, which influences habitat quality and biodiversity. Scott Goetz [NAU—GEDI Deputy PI] presented on biodiversity-related activities, citing a 2023 paper in Nature that examined the effectiveness of protected areas (PAs) across southeast Asia using GEDI data to compare canopy structure within and outside of PAs – see Figure 7. He also presented an analysis of tree and plant diversity across U.S. National Ecological Observation Network (NEON) sites that showed similar capabilities of GEDI with airborne laser scanning (ALS) for tree diversity.

GEDI figure 7
Figure 7. [Top] Protected Areas (PAs) such as national parks can reduce habitat loss and degradation (from logging) and extractive behaviors such as hunting (shown in red circle), but this figure shows there are a wide range of real-world outcomes based on management effectiveness. [Middle] PAs are aimed at safeguarding multiple facets of biodiversity, including species richness (SR), functional richness (FR) and phylogenetic diversity (PD). PAs often focus on vertebrate conservation, owing to their threat levels and value to humans – including for tourism. This study focused on wildlife in southeast Asia, with mammals shown here representing a variation of feeding guilds and sizes. The same approach is repeated for birds. [Bottom] Wildlife communities inside PAs and in the surrounding landscape may exhibit distinct levels and types of diversity.
Figure credit: From a 2023 article in Nature.

Competed Science Team Presentations—Session 3

One unique application of GEDI data is using lidar height to improve radiative transfer models for snow processes. Steven Hancock [University of Edinburgh, Scotland] reported on his group’s work studying snow, forest structure, and heterogeneity in forests, explaining that the majority of land surface models used for climate and weather forecasting use one-dimensional (1D) radiative transfer (RT) models driven by leaf area alone. Heterogeneous forests cast shadows and cause the surface albedo to depend upon sun angle and tree height for moderate leaf area indices (LAI), i.e., LAI values from  1-3 – which are common in snow-affected areas. This complexity cannot be represented in 1D models. An RT model can represent the effect of tree height and horizontal heterogeneity to simulate the observed change in albedo with height, which itself spatially varies.

In contrast to a snowy study area, Ovidiu Csillik [NASA/Jet Propulsion Laboratory] and his team are developing statistical models to link GEDI relative height metrics to tropical forest characteristics traceable to inventory measurements. This dataset of forest structure variables over the Amazon will be used to initialize a demographic ecosystem model to produce projections of future potential tropical forest carbon, as demonstrated by Amazon-wide simulations using initializations from airborne lidar sampling.

Wenge Ni-Meister [Hunter College of the City University of New York] is working on improving aboveground biomass estimates using GEDI waveform measurements. Ni-Meister and her team are testing models in both domestic and international tropical and temperate forests.

Breakout Sessions—Session 2

Two more breakout sessions occurred on day two:  

Sean Healey led a discussion on modes of inference for GEDI data. Inference – formally derived uncertainty for area estimates of biomass, height, or other metrics – can take different forms, each of which includes specific assumptions. In this breakout session, participants considered the strengths and limitations of different inference types (e.g., intensity of computation or the ability to use different models).

Laura Duncanson [UMD—GEDI Co-I] led a discussion about facilitation of open science, in other words, how to make GEDI data more accessible and digestible for data users. While GEDI data area free and publicly available via the LP DAAC and ORNL DAAC, gaining access to said data can be intimidating. Sharing more about existing resources and creating new ones can help remove barriers. The LP DAAC and ORNL DAAC have excellent tutorials on GitHub (a cloud-based software development platform that is primarily Python-based), and Google Earth Engine applications are available for accessing and visualizing GEDI data. Future endeavors may include more webinars, R-based tutorials, workshops, and trainings on specific topics and ways to use GEDI data. More information is available via an online compilation of GEDI-related tutorials.

Perspective: A NUVIEW of Earth’s Land Surface

For the second perspective presentation of day two, meeting attendees heard from Clint Graumann, CEO and co-founder of NUVIEW, a company whose mission is to build a commercial satellite constellation of lidar-imaging satellites that will produce 3D maps of the Earth’s entire land surface. Graumann shared NUVIEW’s intent to produce land surface maps on an annual basis and provide a variety of products and services, including digital surface models (DSMs), digital terrain models (DTMs), and a point cloud generated by laser pulses.

Competed Science Team Presentations—Session 4

Laura Duncanson began the second round of science presentations with her group’s research on global forest carbon hotspots. She discussed her 2023 paper in Nature Communications on the effectiveness of global PAs for climate change mitigation – see Figure 8, which found that the creation of PAs led to more biomass – especially in the Amazon. Within GEDI-domain terrestrial PAs, total aboveground biomass (AGB) storage was found to be 125 Pg, which is around 26% of global estimated AGB. Without the existence of PAs, 19.7 Gt of the 125 Pg would have likely been lost.

GEDI figure 8
Figure 8. PAs effectively preserve additional aboveground carbon (AGC) across continents and biomes, with forest biomes dominating the global signal, particularly in South America. The additional preserved AGC (Gt) in WWF biome classes (total Gt + /− SEM*area). World base map made with Natural Earth. The full set of analyzed GEDI data are represented in this figure (n = 412,100,767).
Figure credit: From a 2023 article in Nature Communications.

Another unique application of GEDI data has to do with water on the Earth’s surface. Kyungtae Lee [UMD], who works with Michelle Hofton [UMD—GEDI Co-I], reported that GEDI appears to capture the monthly annual cycle of lake elevation, showing good correlation with the ground-based observations. Lee explained that even though the GEDI lake elevation estimates show systematic biases relative to the local gauges, GEDI captures lake elevation dynamics well – especially the annual cycle variations. This work has the potential to expand knowledge of hydrological significance of lakes, particularly in data-limited areas of the world. Stephen Good [Oregon State University] presented a survey of his team’s recent work integrating observations from GEDI into hydrology and hydraulics studies of how vegetation can block and intercept moving water. The team found important nonlinear relationships between inferred canopy storage and canopy biomass and were able to estimate canopy water storage capacities and map these globally.

Finally, Patrick Burns [NAU], who works with Scott Goetz, presented results using GEDI canopy structure metrics in mammal species distribution models across southeast Asia (specifically focusing on Borneo and Sumatra). The team’s early results indicate that GEDI canopy structure metrics are important in many mammal distribution models and improve model performance for another smaller subset of species. In other words, when looking at predictors like mean annual precipitation or forest structure (forest structure being a metric that GEDI data provide), the GEDI-derived structure metrics are more intuitive and help us understand distributional changes and fine-scale habitat suitability. In a region like southeast Asia, for example, which has undergone high rates of deforestation in the recent decades, forest structure may be a more relevant predictor in a species distribution model (SDM) than other metrics like climate or vegetation composition. The team will continue to produce models for additional species and expand the extent of the analysis to include mainland Asia.

DAY THREE

Competed Science Team Presentations—Session 5

Day three began with the meeting’s last round of competed ST presentations. John Armston presented the progress of GEDI L2B Plant Area Volume Density (PAVD) product validation using a global Terrestrial Laser Scanning (TLS) database and fusion of the L2B product with Landsat time-series for quantifying change in canopy structure from the Australian wildfires of 2019–2020. Participants then heard from Jim Kellner on using machine-learning algorithms for L4A aboveground biomass density (AGBD). The performance of machine-learning algorithms on a testing data set was comparable to linear regressions used for the first releases of GEDI AGBD data products on average – although there were important geographical differences associated with machine learning. One application under investigation is using machine learning to identify new potential stratifications for GEDI footprint aboveground biomass density.

Lastly, Jingyu Dai [New Mexico State University (NMSU)], who works with Niall Hanan [NMSU], presented on her analysis of the global limits to tree height. Her study shows that hydraulic limitation is the most important constraint on maximum canopy height globally. This result is mediated by plant functional type. In addition, rougher terrain promotes forest height at sub-landscape scales by enriching local niche diversity and probability of larger trees.

Perspective from the Data Side

As described in the summary of Ralph Dubayah’s introductory remarks, the LP DAAC and ORNL DAAC play essential roles in the dissemination of GEDI data and the success of the GEDI program. Representatives from each of these DAACs addressed the ST to summarize recent GEDI-related activities.

Aaron Friesz [United States Geological Survey (USGS)] represented the LP DAAC and gave an update on the current archive size, distribution metrics, and outreach activities. He also discussed plans to support the growth and sustainability of the community through collaboration activities that will leverage the GitHub application; he described some of the resources that are available. Friesz then highlighted the USGS Eyes on Earth podcast and the Institute of Electrical and Electronics Engineers (IEEE) Geoscience and Remote Sensing Society (GRSS)’s Down to Earth podcast, which have featured Ralph Dubayah and Laura Duncanson, and shared plans to update the current GitHub tutorials and how-to guides in the Earthdata Cloud of GEDI V2 and V3.

Rupesh Shrestha [ORNL] represented the ORNL DAAC and shared the status of GEDI L3, L4A, and L4B datasets archived there. He gave an overview of data tools and services for the GEDI datasets, which can be found on the GEDI website and GitHub tutorials website. GEDI L3, L4A, and L4B are available on NASA’s Earthdata Cloud and various enterprise-level services, such as NASA’s WorldView, Harmony, and OpenDAP. GEDI data usage metrics, data tutorials and workshops, and outreach activities, as well as other published community and related datasets were also highlighted. GEDI L3, L4A, and L4B have been downloaded over four million times collectively.

Neha Hunka [UMD] gave the final presentation of the meeting on biomass harmonization activities. She reported that the GEDI estimates of aboveground biomass are capable of directly contributing to the United Nations Framework Convention on Climate Change Global Stocktake. Hunka and her colleagues’ research is aimed at bridging the science–policy gap to enable the use of space-based aboveground biomass estimates for policy reporting and impact – see Figure 9.

GEDI figure 9
Figure 9. Forest biomass estimates in the format of Intergovernmental Panel on Climate Change (IPCC) Tier 1 values from NASA GEDI and ESA Climate Change Initiative (CCI) maps.
Figure credit: Neha Hunka

Conclusion

Overall, the 2023 GEDI STM showcased an exceptional array of scientific research that is highly relevant to addressing pressing global challenges and answering key questions about global forest structure, carbon balance, habitat quality, and biodiversity among other topics. As the GEDI instrument enters its second epoch, we are excited to welcome a new competed GEDI science team cohort and look forward to the release of V3 data products later this year.

Ralph Dubayah concluded the STM with a summary of hibernation period goals and a farewell to this iteration of the competed ST. He extended a heartfelt thank you and farewell to Hank Margolis [NASA Headquarters, emeritus] who has been the NASA Program Scientist for the GEDI mission since 2015. Thank you, Hank. We will miss you.

Talia Schwelling
University of Maryland, College Park
tschwell@umd.edu

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      Summary of the Joint NASA LCLUC–SARI Synthesis Meeting
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      Summary of the Joint NASA LCLUC–SARI Synthesis Meeting
      Introduction
      The NASA Land-Cover and Land-Use Change (LCLUC) is an interdisciplinary scientific program within NASA’s Earth Science program that aims to develop the capability for periodic global inventories of land use and land cover from space. The program’s goal is to develop the mapping, monitoring and modeling capabilities necessary to simulate the processes taking place and evaluate the consequences of observed and predicted changes. The South/Southeast Asia Research Initiative (SARI) has a similar goal for South/Southeast Asia, as it seeks to develop innovative regional research, education, and capacity building programs involving state-of-the-art remote sensing, natural sciences, engineering, and social sciences to enrich land use/cover change (LUCC) science in South/Southeast Asia. Thus it makes sense for these two entities to periodically meet jointly to discuss their endeavors.
      The latest of these joint meetings took place January 1–February 2, 2024, in Hanoi, Vietnam. A total of 85 participants attended the three-day, in-person meeting—see Photo.  A total of 85 participants attended the three-day, in-person meeting. The attendees represented multiple international institutions, including NASA (Headquarters and Centers), the University of Maryland, College Park (UMD), other American academic institutions, the Vietnam National Space Center (VNSC, the event host), the Vietnam National University’s University of Engineering and Technology, and Ho Chi Minh University of Technology, the Japanese National Institute of Environmental Studies (NIES), Center for Environmental Sciences, and the University of Tokyo. In addition, several international programs participated, including GEO Global Agricultural Monitoring (GEOGLAM), the System for Analysis, Research and Training (START), Global Observation of Forest and Land-use Dynamics (GOFC–GOLD), and NASA Harvest.
      Photo. A group picture of the meeting participants on the first day of the 2024 LCLUC SARI meeting in Hanoi, Vietnam. Photo credit: Hotel staff (Hanoi Club Hotel, Hanoi, Vietnam) Meeting Overview
      The purpose of the 2024 NASA LCLUC–SARI Synthesis meeting was to discuss LUCC issues – with a particular focus on their impact on Southeast Asian countries. Presenters highlighted ongoing projects aimed to advance our understanding of the spatial extent, intensity, social consequences, and impacts on the environment in South/Southeast Asian countries. While presenters reported on specific science results, they also were intentional to review and synthesize work from other related projects going on in Southeast Asia. 
      Meeting Goal
      The meeting’s overarching goal was to create a comprehensive and holistic understanding of various LUCC issues by examining them from multiple angles, including: collating information; employing interdisciplinary approaches; integrating research; identifying key insights; and enhancing regional collaborations. The meeting sought to bring the investigators together to bridge gaps, promote collaborations, and advance knowledge regarding LUCC issues in the region. The meeting format also provided ample time between sessions for networking to promote coordination and collaboration among scientists and teams. 
      Meeting and Summary Format
      The meeting consisted of seven sessions that focused on various LUCC issues. The summary report that follows is organized by day and then by session. All presentations in Session I and II are summarized (i.e., with all speakers, affiliations, and appropriate titles identified). The keynote presentation(s) from Sessions III–VI are summarized similarly. The technical presentations in each of these sessions are presented as narrative summaries. Session VII consisted of topical discussions to close out the meeting and summaries of these discussions are included herein. Sessions III–VI also included panel discussions, but to keep the article length more manageable, summaries of these discussions have been omitted. Readers interested in learning more about the panel discussions or viewing any of these presentations in full can access the information on the Joint LCLUC–SARI Synthesis meeting website.
      DAY ONE
      The first day of the meeting included welcoming remarks from the U.S. Ambassador to Vietnam (Session I), program executives of LCLUC and SARI,  as well as from national space agencies in South and Southeast Asia (Session II), and other LCLUC-thematic/overview presentations (Session III).
      Session 1: Welcoming Remarks
      Garik Gutman [NASA Headquarters—LCLUC Program Manager], Vu Tuan [VNSC’s Vietnam Academy of Science and Technology (VAST)—Vice Director General], Chris Justice [University of Maryland, College Park (UMD)—LCLUC Program Scientist], Matsunaga Tsuneo [National Institute of Environmental Studies (NIES), Japan], and Krishna Vadrevu [NASA’s Marshall Space Flight Center—SARI Lead] delivered opening remarks that highlighted collaborations across air pollution, agriculture, forestry, urban development, and other LUCC research areas. While each of the speakers covered different topics, they emphasized common themes, including advancing new science algorithms, co-developing products, and fostering applications through capacity building and training.
      After the opening remarks, special guest Marc Knapper [U.S. Ambassador to Vietnam] gave a presentation in which he emphasized the value of collaborative research between U.S. and Vietnamese scientists to address environmental challenges – especially climate change and LUCC issues. He expressed appreciation to the meeting organizers for promoting these collaborations and highlighted the joint initiatives between NASA and the U.S. Agency for International Development (USAID) to monitor environmental health and climate change, develop policies to reduce emissions, and support adaptation in agriculture. The U.S.–Vietnam Comprehensive Strategic Partnership emphasizes the commitment to address climate challenges and advance bilateral research. He concluded by encouraging active participation from all attendees and stressed the need for ongoing international collaboration to develop effective LUCC policies.
      Session-II: Programmatic and Space Agency Presentations
      NOTE: Other than Ambassador Knapper, the presenters in Session I gave welcoming remarks and programmatic and/or space agency presentations in Session II,.
      Garik Gutman began the second session by presenting an overview of the LCLUC program, which aims to enhance understanding of LUCC dynamics and environmental implications by integrating diverse data sources (i.e., satellite remote sensing) with socioeconomic and ecological datasets for a comprehensive view of land-use change drivers and consequences. Over the past 25 years, LCLUC has funded over 325 projects involving more than 800 researchers, resulting in over 1500 publications. The program’s focus balances project distribution that spans detection and monitoring, and impacts and consequences, including drivers, modeling, and synthesis. Gutman highlighted examples of population growth and urban expansion in Southeast Asia, resulting in environmental and socio-economic impacts. Urbanization accelerates deforestation, shifts farming practices to higher-value crops, and contributes to the loss of wetlands. This transformation alters the carbon cycle, degrades air quality, and increases flooding risks due to reduced rainwater absorption. Multi-source remote sensing data and social dimensions are essential in addressing LUCC issues, and the program aims to foster international collaborations and capacity building in land-change science through partnerships and training initiatives. (To learn more about the recent activities of the LCLUC Science Team, see Summary of the 2024 Land Cover Land Use Change Science Team Meeting.)
      Krishna Vadrevu explained how SARI connects regional and national projects with researchers from the U.S. and local institutions to advance LUCC mapping, monitoring, and impact assessments through shared methodologies and data. The initiative has spurred extensive activities, including meetings, training sessions, publications, collaborations, and fieldwork. To date, the LCLUC program has funded 35 SARI projects and helped build collaborations with space agencies, universities, and decision-makers worldwide. SARI Principal Investigators have documented notable land-cover and land-use transformations, observing shifts in land conversion practices across Asia. For example, the transition from traditional slash-and-burn practices for subsistence agriculture to industrial oil palm and rubber plantations in Southeast Asia. Rapid urbanization has also reshaped several South and Southeast Asian regions, expanding both horizontally in rural areas and vertically in urban centers. The current SARI solicitation funds three projects across Asia, integrating the latest remote sensing data and methods to map, monitor, and assess LUCC drivers and impacts to support policy-making.
      Vu Tuan provided a comprehensive overview of Vietnam’s advances in satellite technology and Earth observation capabilities, particularly through the LOTUSat-1 satellite (name derived from the “Lotus” flower), which is equipped with an advanced X-band Synthetic Aperture Radar (SAR) sensor capable of providing high-resolution imagery [ranging from 1–16 m (3–52 ft)]. This satellite is integral to Vietnam’s efforts to enhance disaster management and climate change mitigation, as well as to support a range of applications in topography, agriculture, forestry, and water management, as well as in oceanography and environmental monitoring. The VNSC’s efforts are part of a broader strategy to build national expertise and self-reliance in satellite technology, such as developing a range of small satellites (e.g., NanoDragon, PicoDragon, and MicroDragon) that progress in size and capability. Alongside satellite development, the VNSC has established key infrastructure, facilities, and capacity building in Hanoi, Nha Trang, and Ho Chi Minh City to support satellite assembly, integration, testing, and operation. Tuan showcased the application of remotely sensed LUCC data to map and monitor urban expansion in Ha Long city from 2000–2023 and the policies needed to manage these changes sustainably – see Figure 1.
      Figure 1. Urban expansion area in Ha Long City, Vietnam from 2000–2023 from multidate Landsat satellite imagery. Figure credit: Vu Tuan [VNSC] Tsuneo Matsunaga provided a detailed overview of Japan’s Greenhouse Gases Observing Satellite (GOSAT) series of satellites, data from which provide valuable insights into global greenhouse gas (GHG) trends and support international climate agreements, including the Paris Agreement.
      Matsunaga reviewed the first two satellites in the series: GOSAT and GOSAT-2, then previewed the next satellite in the series: GOSAT-GW, which is scheduled to launch in 2025. GOSAT-GW will fly the Total Anthropogenic and Natural Emissions Mapping Observatory–3 (TANSO-3) – an improved version of TANSO-2, which flies on GOSAT-2. TANSO-3 includes a Fourier Transform Spectrometer (FTS-3) that has improved spatial resolution [10.5 km (6.5 mi)] over TANSO-FTS-2 and precision that matches or exceeds that of its predecessor. TANSO-FTS-3 will allow estimates with precision better than 1 ppm for carbon dioxide (CO2) and 10 ppb for methane (CH4), as well as enabling nitrogen dioxide (NO2) measurements. GOSAT–GW will also fly the Advanced Microwave Scanning Radiometer (AMSR3) that will monitor water cycle components (e.g., precipitation, soil moisture) and ocean surface winds. AMSR3 builds on the heritage of three previous AMSR instruments that have flown on NASA and Japan Aerospace Exploration Agency (JAXA) missions.
      Matsunaga also highlighted the importance of ground-based validation networks, such as the Total Carbon Column Observing Network, COllaborative Carbon Column Observing Network, and the Pandora Global Network, to ensure satellite data accuracy.
      Son Nghiem [NASA/Jet Propulsion Laboratory (JPL)] addressed dynamic LUCC in Cambodia, Laos, Thailand, Vietnam, and Malaysia. The synthesis study examined the factors that evolve along the rural–urban continuum (RUC). Nghiem showcased this effort using Synthetic Aperture Radar (SAR) data from the Copernicus Sentinel-1 mission to map a typical RUC in Bac Lieu, Vietnam – see Figure 2.
      Figure 2. Land cover map of Bae Lieu, Vietnam, and surrounding rural areas. The image shows persistent building structures (red), agricultural areas (light green), aquacultural (light blue), tree cover (dark green), and water bodies (dark blue). Land-use classes used on this map are derived from Sentinel-1 Synthetic Aperture Radar (SAR) for the rural urban continuum around Bac Lieu. Figure credit: Son Nghiem [JPL] Nghiem described the study, which examined the role of rapid urbanization, agricultural conversion, climate change, and environment–human feedback processes in causing non-stationary and unpredictable impacts. This work illustrates how traditional trend analysis is insufficient for future planning. The study also examined whether slower or more gradual changes could inform policy development. To test these hypotheses, his research will integrate high-resolution radar and hyperspectral data with socioeconomic analyses. The study highlights the need for policies that are flexible and responsive to the unique challenges of different areas, particularly in “hot-spot” regions experiencing rapid changes.
      Peilei Fan [Tufts University] presented a study that synthesizes the complex patterns of LUCC, identifying both the spatial and temporal dynamics that characterize transitions in urban systems. The study explores key drivers, including economic development, population growth, urbanization, agricultural expansion, and policy shifts. She emphasized the importance of understanding these drivers for sustainable land management and urban planning. For example, the Yangon region of Myanmar has undergone rapid urbanization – see Figure 3. Her work reveals the need for integrated approaches that consider both urban and rural perspectives to manage land resources effectively and mitigate negative environmental and social impacts. Through a combination of case studies, statistical analysis, and policy review, Fan and her team aim to provide a nuanced understanding of the interactions between human activities and environmental changes occurring in the rapidly transforming landscapes of Southeast Asia.
      Figure 3. Landsat data can be used to track land cover change over time. For example, Thematic Mapper data have been used to track urban expansion around Yangon, Myanmar. The data show that the built-up area expanded from 161 km2 (62 mi2) in 1990 to 739 km2 (285 mi2) in 2020. Figure credit: Peleli Fan [Tufts University] Session III: Land Cover/Land Use Change Studies
      Tanapat Tanaratkaittikul [Geo-Informatics and Space Technology Development Agency (GISTDA), Thailand] highlighted GISTDA activities, which play a crucial role in advancing Thailand’s technological capabilities and addressing both national and global challenges, including Thailand Earth Observation System (THEOS) and its successors: THEOS-2 and THEOS-2A. THEOS-1, which launched in 2008, provides 2-m (6-ft) panchromatic and 15-m (45-ft) multispectral resolution with a 26-day revisit cycle, which can be reduced to 3 days with off-nadir pointing. Launched in 2023, THEOS-2 includes two satellites – THEOS-2A [a very high-resolution satellite with 0.5-m (1.5-ft) panchromatic and 2-m (6-ft) multispectral imagery] and THEOS-2B [a high-resolution satellite with 4-m (12-ft) multispectral resolution] – with a five-day revisit cycle. GISTDA also develops geospatial applications for drought assessment, flood prediction, and carbon credit calculations to support government decision-making and climate initiatives. GISTDA partners with international collaborators on regional projects, such as the Lancang-Mekong Cooperation Special Fund Project.
      Eric Vermote [NASA’s Goddard Space Flight Center] presented a keynote that focused on atmospheric correction of land remote sensing data and related algorithm updates. He highlighted the necessity of correcting surface imaging for atmospheric effects, such as molecular scattering, aerosol scattering, and gaseous absorption, which can significantly distort the satellite spectral signals and lead to potential errors in applications, such as land cover mapping, vegetation monitoring, and climate change studies.
      Vermote explained that the surface reflectance algorithm uses precise vector radiative transfer modeling to improve accuracy by incorporating atmospheric parameter inversion. It also adjusts for various atmospheric conditions and aerosol types – enhancing corrections across regions and seasons. He explained that SkyCam – a network of ground-based cameras – provides real-time assessments of cloud cover that can be used to validate cloud masks, while the Cloud and Aerosol Measurement System (CAMSIS) offers additional ground validation by measuring atmospheric conditions. He said that together, SkyCam and CAMSIS improve satellite-derived cloud masks, supporting more accurate climate models and environmental monitoring. Vermote’s work highlights the ongoing advancement of atmospheric correction methods in remote sensing.
      Other presentations in this session included one in which the speaker described how Yangon, the capital city in Myanmar, is undergoing rapid urbanization and industrial growth. From 1990–2020, the urban area expanded by over 225% – largely at the expense of agricultural and green lands. Twenty-nine industrial zones cover about 10.92% of the city, which have attracted significant foreign direct investment, particularly in labor-intensive sectors. This growth has led to challenges with land confiscations, inadequate infrastructure, and environmental issues (e.g., air pollution). Additionally, rural migration for employment has resulted in informal settlements, emphasizing the need for comprehensive urban planning that balances economic development with social equity and sustainability.
      Another presentation highlighted varying LUCC trends across Vietnam. In the Northern and Central Coastal Uplands, for example, swidden systems are shifting toward permanent tree crops, such as rubber and coffee. Meanwhile, the Red River Delta is seeing urban densification and consolidation of farmland – transitioning from rice to mixed farming with increased fruit and flower production. Similarly, the Central Coastal Lowlands and Southeastern regions are experiencing urban growth and a shift from coastal agriculture – in this case, to shrimp farming – leading to mangrove loss. The Central Highlands is moving from swidden to tree crops, particularly fruit trees, while the Mekong River Delta is increasing rice cropping and aquaculture. These changes contribute to urbanization, altered farming practices, and biodiversity loss. Advanced algorithms (e.g., the Time-Feature Convolutional Neural Network model) are being used to effectively map these varied LUCC changes in Vietnam.
      Another presenter explained how 10-m (33-ft) resolution spatially gridded population datasets are essential to address LUCC in environmental and socio-demographic research. There was also a demonstration of PopGrid, which is a collaborative initiative that provides access to various global-gridded population databases, which are valuable for regional LUCC studies and can support informed decision-making and policy development.
      DAY TWO
      The second day’s presentations centered around urban LUCC (Session IV) as well as interconnections between agriculture and water resources. (Session V).
      Session IV: Urban Land Cover/Land Use Change
      Gay Perez [Philippines Remote Sensing Agency (PhilSA)] presented a keynote focused on PhilSA’s mission to advance Philippines as a space-capable country by developing indigenous satellite and launch technologies. He explained that PhilSA provides satellite data in various categories, including sovereign, commercial, open-access, and disaster-activated. He noted that the ground infrastructure – which includes three stations and a new facility in Quezon – supports efficient data processing. For example, Perez stated that in 2023, PhilSA produced over 10,000 maps for disaster relief, agricultural assessments, and conservation planning.
      Perez reviewed PhilSA’s Diwata-2 mission, which launched in 2018 and operates in a Sun-synchronous orbit around 620 km (385 mi) above Earth. With a 10-day revisit capability, it features a high-precision telescope [4.7 m (15ft) resolution], a multispectral imager with four bands, an enhanced resolution camera, and a wide-field camera. Since launch, Diwata-2 has captured over 100,000 global images, covering 95% of the Philippines. Looking to the near future, Perez reported that PhilSA’s launch of the Multispectral Unit for Land Assessment (MULA) satellite is planned for 2025. He explained that MULA will capture images with a 5-m (~16-ft) resolution and 10–20-day revisit time, featuring 10 spectral bands for vegetation, water, and urban analysis.
      Perez also described the Drought and Crop Assessment and Forecasting project, which addresses drought risks and mapping ground motion in areas, e.g., Baguio City and Pangasinan. Through partnerships in the Pan-Asia Partnership for Geospatial Air Pollution Information (PAPGAPI) and the Pandora Asia Network, PhilSA monitors air quality across key locations, tracking urban pollution and cross-border particulate transport. PhilSA continues to strengthen Southeast Asian partnerships to drive sustainable development in the region.
      Jiquan Chen [Michigan State University] presented the second keynote address, which focused on the Urban Rural Continuum (URC). Chen emphasized the importance of synthesizing studies that explore factors such as population dynamics, living standards, and economic development in the URC. Key considerations include differentiating between two- and three-dimensional infrastructures and understanding constraints from historical contexts. Chen highlighted critical variables from his analysis including net primary productivity, household income, and essential infrastructure elements, such as transportation and healthcare systems. He advocated for integrated models that combine mechanistic and empirical approaches to grasp the dynamics of URC changes, stressing their implications for urban planning, environmental sustainability, and social equity. He concluded with a call for collaboration to enhance these models and tackle challenges arising from the changing urban–rural landscape.
      Tep Makathy [Cambodian Institute For Urban Studies] discussed urbanization in Phnom Penh, Cambodia. He explained that significant LUCC and infrastructure developments have been fueled by direct foreign investment; however, this development has resulted in environmental degradation, urban flooding, and infrastructure strain. Tackling pollution, congestion, preservation of green spaces, and preserving the historical heritage of the city will require sustainable urban planning efforts.
      Nguyen Thi Thuy Hang [Vietnam Japan University, Vietnam National University, Hanoi] explained how flooding poses a significant annual threat to infrastructure and livelihoods in Can Tho, Vietnam. Therefore, it is essential to incorporate climate change considerations into land-use planning by enhancing the accuracy of vegetation layer classifications. Doing so will improve the representation of land-cover dynamics in models that decision-makers use when planning urban development. In addition, Hang reported that a more comprehensive survey of dyke systems will improve flood protection and identify areas needing reinforcement or redesign. These studies could also explore salinity intrusion in coastal agricultural areas that could impact crop yields and endanger food security.
      In this session, two presenters highlighted how SAR data, which uses high backscatter to enhance the radar signal, is being used to assist with mapping urban areas in their respective countries. The phase stability and orientation of building structures across SAR images aid in consistent monitoring and backscatter, producing distinct image textures specific to urban settings. Researchers can use this heterogeneity and texture to map urban footprints, enabling automated discrimination between urban and non-urban areas. The first presenters showed how Interferometric Synthetic Aperture Radar techniques, such as Small Baseline Subset (SBAS) and Persistent Scatterer (PS) have been highly effective for mapping and monitoring land subsidence in coastal and urban areas in Vietnam. This approach has been applied to areas along the Saigon River as well as in Ho Chi Minh, Vietnam. The second presenter described an approach (using SAR data with multitemporal coherence and the K-means classification method) that has been used effectively to study urban growth in the Denpasar Greater Area of Indonesia between 2016 and 2022. The technique identified the conversion of 4376 km2 (1690 mi2) of rural to built-up areas, averaging 72.9 hectares (0.3 mi2) per year. Urban sprawl was predominantly observed in the North Kuta District, where the shift from agricultural to built-up land use has been accompanied by severe traffic congestion and other environmental issues.
      Another presenter showed how data from the QuikSCAT instrument, which flew on the Quick Scatterometer satellite, and from the Sentinel-1 C-band SAR can be combined to measure and analyze urban built-up volume, specifically focusing on the vertical growth of buildings across various cities. By integrating these datasets, researchers can assess urban expansion, monitor the development of high-rise buildings, and evaluate the impact of urbanization on infrastructure and land use. This information is essential for urban planning, helping city planners and policymakers make informed decisions to accommodate growing populations and enhance sustainable urban development.
      Session V – LUCC, Agriculture, and Water Resources
      Chris Justice presented the keynote for this session, in which he addressed the GEOGLAM initiative and the NASA Harvest program. GEOGLAM, initiated by the G20 Agriculture Ministers in 2011, focuses on agriculture and food security to increase market transparency and improve food security. These efforts leverage satellite-based Earth observations to produce and disseminate timely, relevant, and actionable information about agricultural conditions at national, regional, and global scales to support agricultural markets and provide early warnings for proactive responses to emerging food emergencies. NASA Harvest uses satellite Earth observations to benefit global food security, sustainability, and agriculture for disaster response, climate risk assessments, and policy support. Justice also emphasized the use of open science and open data principles, promoting the integration of Earth observation data into national and international agricultural monitoring systems. He also discussed the development and application of essential agricultural variables, in situ data requirements, and the need for comprehensive and accurate satellite data products.
      During this session, another presentation focused on how VNSC is engaged in several agricultural projects, including mapping rice crops, estimating yields, and assessing environmental impacts. VNSC has created high-accuracy rice maps for different seasons that the Vietnamese government uses to monitor and manage agricultural production. Current initiatives involve using satellite data to estimate CH4 emissions from rice paddies, biomass mapping, and monitoring rice straw burning. For example, in the Mekong Delta, numerous environmental factors, including climate change-induced stress (e.g., sea-level rise), flooding, drought, land subsidence, and saltwater intrusion, along with human activities like dam construction, sand mining, and groundwater extraction, threaten the sustainability of rice farming and farmer livelihoods. To address these challenges, sustainable agricultural practices are essential to improving rice quality, diversify farming systems, adopt low-carbon techniques, and enhance water management.
      Presentations highlighted the importance of both optical and SAR data for LUCC studies, particularly in mapping agricultural areas. A study using Landsat time-series data demonstrated its value in monitoring agricultural LUCC in Houa Phan Province, Laos, and Son La Province, Vietnam. Land cover types were classified through spectral pattern analysis, identifying distinct classes based on Landsat reflectance values. The findings revealed significant natural forest loss alongside increases in cropland and forest plantations due to agricultural expansion. High-resolution imagery validated these results, indicating the scalability of this approach for broader regional and global land-cover monitoring. Another study showcased the effectiveness of SAR data from the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) on the Japanese Advanced Land Observing Satellite-2 (ALOS-2) for mapping and monitoring agricultural land use in Suphanburi, Thailand. This data proved particularly useful for capturing seasonal variations and diverse agricultural practices. Supervised machine learning methods, such as Random Forest classifiers, combined with innovative spatial averaging techniques, achieved high accuracy in distinguishing various agricultural conditions.
      In the session, presenters also discussed the use of Sentinel-1 SAR data for mapping submerged and non-submerged paddy soils was highlighted, demonstrating its effectiveness in understanding water management issues see – Figure 4. Additionally, large-scale remote sensing data and cloud computing were shown to provide unprecedented opportunities for tracking agricultural land-use changes in greater detail. Case studies from India and China illustrated key challenges, such as groundwater depletion in irrigated agriculture across the Indo-Ganges region and the impacts on food, water, and air quality in both countries.
      Figure 4. Series of Sentinel-1 radar data images showing submerged paddy soil (blue) and non-submerged paddy soil (red) in the Mekong Delta, Vietnam. Figure credit: Hiranori Arai [International Rice Research Institute] The session also focused on Water–Energy–Food (WEF) issues related to the Mekong River Basin’s extensive network of hydroelectric dams, which present both benefits and challenges. While these dams support sectors such as irrigated agriculture and hydropower, they also disrupt vital ecosystem services, including fish habitats and biodiversity. Collaborative studies integrating satellite and ground data, hydrological models, and socio-economic frameworks highlight the need to balance these benefits with ecological and social costs. Achieving sustainable management requires cross-sectoral and cross-border cooperation, as well as the incorporation of traditional knowledge to address WEF trade-offs and governance challenges in the region.
      DAY THREE
      The third day included a session that explored the impacts of fire, GHG emissions, and pollution (Session VI) as well as a summary discussion on synthesis (Session VII).
      Session VI: Fires, Greenhouse Gas Emissions, and Pollution
      Chris Elvidge [Colorado School of Mines] presented a keynote on the capabilities and applications of the Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire [VNF] system, an advanced satellite-based tool developed by the Earth Observation Group. VIIRS Nightfire uses four near- and short-wave infrared channels, initially designed for daytime imaging, to detect and monitor infrared emissions at night. The system identifies various combustion sources, including both flaming and non-flaming activities (e.g., biomass burning, gas flaring, and industrial processes). It calculates the temperature, source area, and radiant heat of detected infrared emitters using physical laws to enable precise monitoring of combustion events and provide insight into exothermic and endothermic processes.
      Elvidge explained that VNF has been vital for near-real-time data in Southeast Asia. The system has been used to issue daily alerts for Vietnam, Thailand, and Indonesia. Recent updates in Version 4 (V4) include atmospheric corrections and testing for secondary emitters with algorithmic improvements – with a 50% success rate in identifying additional heat sources. The Earth Observation Group maintains a multiyear catalog of over 20,000 industrial infrared emitters available through the Global Infrared Emitter Explorer (GIREE) web-map service. With VIIRS sensors expected to operate until about 2040 on the Joint Polar Satellite System (JPSS) platforms, this system ensures long-term, robust monitoring and analysis of global combustion events, proving essential for tracking the environmental impacts of industrial activities and natural combustion processes on the atmosphere and ecosystems.
      Toshimasa Ohara [Center for Environmental Science, Japan—Research Director] continued with the second keynote and provided an in-depth analysis of long-term trends in anthropogenic emissions across Asia. The regional mission inventory in Asia encompasses a range of pollutants and offers detailed emissions data from 1950–2020 at high spatial and temporal resolutions. The study employs both bottom-up and top-down approaches for estimating emissions, integrating satellite observations to validate data and address uncertainties. Notably, emissions from China, India, and Japan have shown signs of stabilization or reduction, attributed to stricter emission control policies and technological advancements. Ohara also highlighted Japan’s effective air pollution measures and the importance of extensive observational data in corroborating emission trends. His presentation emphasized the need for improved methodologies in emission inventory development and validation across Asia, aiming to enhance policymaking and environmental management in rapidly industrializing regions.
      Several presenters during this session focused on innovative approaches to understand and mitigate GHG emissions and air pollution. One presenter showed how NO2 data from the TROPOspheric Monitoring Instrument (TROPOMI) on the European Sentinel-5 Precursor have been validated against ground-based observations from Pandora stations in Japan, highlighting the influence of atmospheric conditions on measurement accuracy. Another presenter described an innovative system that GISTDA used to combine satellite remote sensing data with Artificial Intelligence (AI). This system was used to monitor and analyze the concentration of fine particulate matter (PM) in the atmosphere in Thailand. (In this context fine is defined as particles with diameters ≤ 2.5 µm, or PM2.5.) These applications, which are accessible through online, cloud-based platforms and mobile applications for iOS and Android devices, allow users, including citizens, government officers, and policymakers, to access PM2.5 data in real-time through web and mobile interfaces.
      A project under the United Nations Economic and Social Commission for Asia and the Pacific in Thailand is focused on improving air quality monitoring across the Asia–Pacific region by integrating satellite and ground-based data. At the core of this effort, the Pandora Asia Network, which includes 30 ground-based instruments measuring pollutants such as NO₂ and sulfur dioxide (SO₂), is complemented by high-resolution observations from the Geostationary Environment Monitoring Spectrometer (GEMS) aboard South Korea’s GEO-KOMPSAT-2B (GK-2B) satellite. The initiative also provides training sessions to strengthen regional expertise in remote sensing technologies for air quality management and develops decision support systems for evidence-based policymaking, particularly for monitoring pollution sources and transboundary effects like volcanic eruptions. Future plans include expanding the Pandora network and enhancing data integration to support local environmental management practices.
      PM2.5 levels in Vietnam are influenced by both local emissions and long-range pollutant transport, particularly in urban areas.The Vietnam University of Engineering and Technology, in conjunction with VNSC, continues to map and monitor PM2.5 using satellites and machine learning while addressing data quality issues that stem from missing satellite data and limited ground monitoring stations – see Figure 5.
      In addition to mapping and monitoring pollutants, another presentater explained that significant research is underway to address their health impacts. In Hanoi, exposure to pollutants ( e.g., PM2.5, PM10, and NO2) has led to increased rates of respiratory diseases (e.g., pneumonia, bronchitis, and asthma) among children,  as well as elevated instances of cardiovascular diseases among adults. A substantial mortality burden is attributable to fine particulate matter – particularly in densely populated areas like Hanoi. Compliance with stricter air quality guidelines could potentially prevent thousands of premature deaths. For example, preventive measures enacted during the COVID-19 pandemic resulted in reduced pollution levels that were associated with a decrease in avoidable mortality rates. In response to these challenges, Vietnam has implemented air quality management policies, including national technical regulations and action plans aimed at controlling emissions and enhancing monitoring; however, current national standards still fall short of the more stringent guidelines recommended by the World Health Organization. Improved air quality standards and effective policy interventions are needed to mitigate the health risks associated with air pollution in Vietnam.
      Figure 5. Map of particulate matter (PM 2.5) variations observed across Vietnam, using multisatellite aerosol optical depth (AOD) data from the Moderate Resolution Imaging Spectrogradiometer (MODIS) on NASA’s Aqua and Terra platforms, and from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the NASA–NOAA Suomi NPP platform, combined with ground-based AOD and meteorological data. Figure credit: Thanh Nguyen [Vietnam National University of Engineering and Technology, Vietnam] Another presenter explained how food production in Southeast Asia contributes about 40% of the region’s total GHG emissions – with rice and beef production identified as the largest contributors for plant-based and animal-based emissions, respectively. Another presentation focused on a study that examined GHG emissions from agricultural activities, which suggests that animal-based food production – particularly beef – generates substantially higher GHG emissions per kg of food produced compared to plant-based foods, such as wheat and rice. Beef has an emission intensity of about 69 kg of CO2 equivalent-per-kg, compared to 2 to 3 kg of CO2 equivalent-per-kg for plant-based foods. The study points to mitigation strategies (e.g., changing dietary patterns, improving agricultural practices) and adopting sustainable land management. Participants agreed that a comprehensive policy framework is needed to address the environmental impacts of food production and reduce GHG emissions in the agricultural sector.
      In another presentation, the speaker highlighted the fact that Southeast Asian countries need an advanced monitoring, reporting, and verification system to track GHG emissions – particularly within high-carbon reservoirs like rice paddies. To achieve this, cutting-edge technologies (e.g., satellite remote sensing, low-cost unmanned aerial vehicles, and Internet of Things devices) can be beneficial in creating sophisticated digital twin technology for sustainable rice production and GHG mitigation.
      Another presentation featured a discussion about pollution resulting from forest and peatland fires in Indonesia, which is significantly impacting air quality. Indonesia’s tropical peatlands – among the world’s largest and most diverse – face significant threats from frequent fires. Repeated burning has transformed forests into shrubs and secondary vegetation regions, with fires particularly affecting forest edges and contributing to a further retreat of intact forest areas. High-resolution data is essential to map and monitor changes in forest cover, including pollution impacts.
      Another speaker described a web-based Geographic Information Systems (GIS) application that has been developed to support carbon offsetting efforts in Laos – to address significant environmental challenges, e.g., deforestation and climate change. Advanced technologies (e.g., remote sensing, GIS, and Global Navigation Satellite Systems) are used to monitor land-use changes, carbon sequestration, and ecosystem health. By integrating various spatial datasets, the web GIS app enhances data collection precision, streamlines monitoring processes, and provides real-time information to stakeholders for informed decision-making. This initiative fosters collaboration among local communities, government agencies, and international partners, while emphasizing the importance of government support and international partnerships. Ultimately, the web GIS application represents a significant advancement in Laos’s commitment to environmental sustainability, economic growth, and the creation of a greener future.
      Session VII. Discussion Session on Synthesis
      The meeting concluded with a comprehensive discussion on synthesizing themes related to LUCC. The session focused on three themes: LUCC, agriculture, and air pollution. The session focused on trends and projections as well as the resulting impacts in the coming years. It also highlighted research related to these topics to inform more sustainable land use policies. A panel of experts from different Southeast Asian countries addressed these topics. A summary of the key points shared by the panelists for each theme during the discussion is provided below.
      LUCC Discussions
      This discussion focused on the challenges of balancing economic development with environmental sustainability in Southeast Asian countries, e.g., mining in Myanmar, agriculture in Vietnam, and rising land prices in Thailand. More LUCC research is needed to inform decision-making and improve land-use planning during transitions from agriculture to industrialization while ensuring food security. The panelists also discussed urban sprawl and infrastructure development along main roads in several Southeast Asian countries, highlighting the social and environmental challenges arising from uncoordinated growth. It was noted that urban infrastructure lags behind population increases, resulting in traffic congestion, pollution, and social inequality. Cambodia, for example, has increased foreign investments, which presents similar dilemmas of economic growth accompanied by significant environmental degradation. Indonesia is another example of a Southeast Asian nation facing rapid urbanization and inadequate spatial planning, leading to flooding, groundwater depletion, and pollution. These issues further highlight the need for integrated satellite monitoring to inform land-use policies. Finally, recognizing the importance of public infrastructure in growth management, it was reported that the Thai government is already using technology to manage urban development alongside green spaces.
      Panelists agreed that LUCC research is critical for guiding policymakers toward sustainable land-use practices – emphasizing the necessity for improved communication between researchers and policymakers. While the integration of technologies (e.g., GIS and remote sensing) is beginning to influence policy decisions, room for improvement remains. In summary, the discussions stressed the importance of better planning, technology integration, and policy-informed research to reconcile economic growth with sustainability. Participants also highlighted the need to engage policymakers, non-government organizations, and the private sector in using scientific evidence for sustainable development. Capacity building in Laos, Cambodia, and Myanmar, where GIS and remote sensing technologies are still developing, is crucial. Community involvement is essential for translating research findings into actionable policies to address real-world challenges and social equity.
      Agriculture Discussions
      These discussions explored the intricate relationships between agricultural practices, economic growth, and environmental sustainability in Southeast Asia. As an example, despite national policies to manage the land transition in Vietnam, rapid conversions from forest to agricultural land and further to residential and industrial continue. While it is recognized that strict land management plans may hinder future adaptability, further regulation is needed. These rapid shifts in land use have increased land for economic development – especially in industrial and residential sectors – and contribute to environmental degradation, e.g., pollution and soil erosion. In Thailand, land is distributed among agriculture (50%), forest (30%), and urban (20%) areas. Despite a long history of agricultural practices, Vietnam faces new challenges from climate change and extreme weather.
      Thailand, meanwhile, is exploring carbon credits to incentivize sustainable farming practices – although this requires significant investment and time. The nation is well-equipped with a robust water supply system, and ongoing efforts to enhance crop yields on Vietnam’s Mekong Delta, salinity levels, and flooding intensity have increased as a result of the rise in incidents of extreme weather, prompting advancements in rice farming mechanization to be implemented that are modeled after practices that have been successfully used in the Philippines.
      Despite these advances, issues (e.g., over-application of rice seeds) remain. The dominant land cover type in Malaysia is tropical rainforest, although agriculture – particularly oil palm plantations – also plays a significant role in land use. While stable, it shares environmental concerns with Indonesia. The country is integrating solar energy initiatives, placing solar panels on former agricultural lands and recreational areas, which raises coastal environmental concerns. In Taiwan, substantial land use changes have stemmed from solar panel installations to support green energy goals but have led to increased temperatures and altered wind patterns.
      All panelists agreed that remote sensing technologies are vital to inform agricultural policy across the region. They emphasized the need to transition from academic research to actionable insights that directly inform policy. Panelists also discussed the challenge of securing funding for actionable research – underlining the importance of recognizing the transition required for research to inform operational use. Some countries (e.g., Thailand) have established operational crop monitoring systems, while others (e.g., Vietnam) primarily depend on research projects. Despite progress in Malaysia’s monitoring of oil palm plantations, a comprehensive operational monitoring system is still lacking in many areas. The participants concluded that increased efforts are needed to promote the wider adoption of remote sensing technologies for agricultural and environmental monitoring, with emphasis on developing operational systems that can be integrated into policy and decision-making processes.
      Air Pollution Discussions
      The discussion on air pollution focused on various sources in Southeast Asia, which included both local and transboundary factors. Panelists highlighted that motor vehicles, industrial activities, and power plants are major contributors to pollutants, such as PM2.5, NO2, ozone (O3), and carbon monoxide (CO). Forest fires in Indonesia – particularly from South Sumatra and Riau provinces – are significantly impacting neighboring countries, e.g., Malaysia. A study found that most PM2.5 pollution in Kuala Lumpur originates from Indonesia. During the COVID-19 pandemic, pollution levels dropped sharply due to reduced economic activity; however, data from 2018–2023 shows that PM2.5 levels have returned to pre-pandemic conditions.
      The Indonesian government is actively working to reduce deforestation and emissions, aiming for a 29% reduction by 2030. Indonesia is also participating in carbon markets and receiving international payments for emission reductions. Indonesia’s emissions also stem from energy production, industrial activities, and land-use changes, including peat fires. The Indonesian government reports anthropogenic sources – particularly from the energy sector and industrial activities, forest and peat fires, waste, and agriculture – continue to escalate. While Indonesia is addressing these issues, growing population and energy demands continue to drive pollution levels higher.
      Vietnam and Laos are facing similar challenges related to air pollution – particularly from agricultural residue burning. Both governments are working on expanding air quality monitoring, regulating waste burning, and developing policies to mitigate pollution. Vietnam has been developing provincial air quality management plans and expanding its monitoring network. Laos has seen increased awareness of pollution, accompanied by government measures aimed at restricting burning and improving waste management practices.
      The panelists agreed that collaborative efforts for regional cooperation are essential to address air pollution. This will require collaboration in research and data sharing to inform policy decisions. There is a growing interest in leveraging satellite technology and modeling approaches to enhance air quality forecasting and management. To ensure that research translates into effective policy, communication of scientific findings to policymakers is essential – particularly by clearly communicating complex research concepts in accessible formats. All panelists agreed on the importance of improving governance, transparency, and scientific communication to better translate research into policy actions, highlighting collaborations with international organizations – including NASA – to address air quality issues. While significant challenges related to air pollution persist in Southeast Asia, noteworthy efforts are underway to improve awareness, research, and collaborative governance aimed at enhancing air quality and reducing emissions.
      Conclusion
      The LCLUC–SARI Synthesis meeting fostered collaboration among researchers and provided valuable updates on recent developments in LUCC research, exchange of ideas, integration of new data products, and discussions on emerging science directions. This structured dialogue (particularly the discussions in each session) helped the attendees identify priorities and needs within the LUCC community. All panelists and meeting participants commended the SARI leadership for their proactive role in facilitating collaborations and discussions that promote capacity-building activities across the region. SARI activities have significantly contributed to enhancing the collective ability of countries in South and Southeast Asia to address pressing environmental challenges. The meeting participants emphasized the importance of maintaining and expanding these collaborative efforts, which are crucial for fostering partnerships among governments, research institutions, and local communities. They urged SARI to continue organizing workshops, training sessions, and knowledge-sharing platforms that can equip stakeholders with the necessary skills and resources to tackle environmental issues such as air pollution, deforestation, climate change, and sustainable land management.
      Krishna Vadrevu
      NASA’s Marshall Space Flight Center
      krishna.p.vadrevu@nasa.gov
      Vu Tuan
      Vietnam National Science Center, Vietnam
      vatuan@vnsc.org.vn
      Than Nguyen
      Vietnam National University Engineering and Technology, Vietnam
      thanhntn@vnu.edu.vn
      Son Nghiem
      Jet Propulsion Laboratory
      son.v.nghiem@jpl.nasa.gov
      Tsuneo Matsunaga
      National Institute of Environmental Studies, Japan
      matsunag@nies.go.jp
      Garik Gutman
      NASA Headquarters
      ggutman@nasa.gov
      Christopher Justice
      University of Maryland College Park
      cjustice@umd.edu
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