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IEEE Geoscience and Remote Sensing Society – Earth Science Informatics Workshop and Hackathon on Remote Sensing Data Systems Held at SRM University, Chennai
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By NASA
8 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Return to 2024 SARP Closeout Faculty Advisors:
Dr. Tom Bell, Woods Hole Oceanographic Institution
Dr. Kelsey Bisson, NASA Headquarters Science Mission Directorate
Graduate Mentor:
Kelby Kramer, Massachusetts Institute of Technology
Kelby Kramer, Graduate Mentor
Kelby Kramer, graduate mentor for the 2024 SARP Ocean Remote Sensing group, provides an introduction for each of the group members and shares behind-the scenes moments from the internship.
Lucas DiSilvestro
Shallow Water Benthic Cover Type Classification using Hyperspectral Imagery in Kaneohe Bay, Oahu, Hawaii
Lucas DiSilvestro
Quantifying the changing structure and extent of benthic coral communities is essential for informing restoration efforts and identifying stressed regions of coral. Accurate classification of shallow-water benthic coral communities requires high spectral and spatial resolution, currently not available on spaceborne sensors, to observe the seafloor through an optically complex seawater column. Here we create a shallow water benthic cover type map of Kaneohe Bay, Oahu, Hawaii using the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) without requiring in-situ data as inputs. We first run the AVIRIS data through a semi-analytical inversion model to derive color dissolved organic matter, chlorophyll concentration, bottom albedo, suspended sediment, and depth parameters for each pixel, which are then matched to a Hydrolight simulated water column. Pure reflectance for coral, algae, and sand are then projected through each water column to create spectral endmembers for each pixel. Multiple Endmember Spectral Mixture Analysis (MESMA) provides fractional cover of each benthic class on a per-pixel basis. We demonstrate the efficacy of using simulated water columns to create surface reflectance spectral endmembers as Hydrolight-derived in-situ endmember spectra strongly match AVIRIS surface reflectance for corresponding locations (average R = 0.96). This study highlights the capabilities of using medium-fine resolution hyperspectral imagery to identify fractional cover type of localized coral communities and lays the groundwork for future spaceborne hyperspectral monitoring of global coral communities.
Atticus Cummings
Quantifying Uncertainty In Kelp Canopy Remote Sensing Using the Harmonized Landsat Sentinel-2 Dataset
Atticus Cummings
California’s giant kelp forests serve as a major foundation for the region’s rich marine biodiversity and provide recreational and economic value to the State of California. With the rising frequency of marine heatwaves and extreme weather onset by climate change, it has become increasingly important to study these vital ecosystems. Kelp forests are highly dynamic, changing across several timescales; seasonally due to nutrient concentrations, waves, and predator populations, weekly with typical growth and decay, and hourly with the tides and currents. Previous remote sensing of kelp canopies has relied on Landsat imagery taken with a eight-day interval, limiting the ability to quantify more rapid changes. This project aims to address uncertainty in kelp canopy detection using the Harmonized Landsat and Sentinel-2 (HLS) dataset’s zero to five-day revisit period. A random forest classifier was used to identify pixels that contain kelp, on which Multiple Endmember Spectral Mixture Analysis (MESMA) was then run to quantify intrapixel kelp density. Processed multispectral satellite images taken within 3 days of one another were paired for comparison. The relationship between fluctuations in kelp canopy density with tides and currents was assessed using in situ data from an acoustic doppler current profiler (ADCP) at the Santa Barbara Long Term Ecological Research site (LTER) and a NOAA tidal buoy. Preliminary results show that current and tidal trends cannot be accurately correlated with canopy detection due to other sources of error. We found that under cloud-free conditions, canopy detection between paired images varied on average by 42%. Standardized image processing suggests that this uncertainty is not created within the image processing step, but likely arises due to exterior factors such as sensor signal noise, atmospheric conditions, and sea state. Ultimately, these errors could lead to misinterpretation of remotely sensed kelp ecosystems, highlighting the need for further research to identify and account for uncertainties in remote sensing of kelp canopies.
Jasmine Sirvent
Kelp Us!: A Methods Analysis for Predicting Kelp Pigment Concentrations from Hyperspectral Reflectance
Jasmine Sirvent
Ocean color remote sensing enables researchers to assess the quantity and physiology of life in the ocean, which is imperative to understanding ecosystem health and formulating accurate predictions. However, without proper methods to analyze hyperspectral data, correlations between spectral reflectance and physiological traits cannot be accurately derived. In this study, I explored different methods—single variable regression, partial least squares regressions (PLSR), and derivatives—in analyzing in situ Macrocystis pyrifera (giant kelp) off the coast of Santa Barbara, California in order to predict pigment concentrations from AVIRIS hyperspectral reflectance. With derivatives as a spectral diagnostic tool, there is evidence suggesting high versus low pigment concentrations could be diagnosed; however, the fluctuations were within 10 nm of resolution, thus AVIRIS would be unable to reliably detect them. Exploring a different method, I plotted in situ pigment measurements — chlorophyll a, fucoxanthin, and the ratio of fucoxanthin to chlorophyll a—against hyperspectral reflectance that was resampled to AVIRIS bands. PLSR proved to be a more successful model because of its hyperdimensional analysis capabilities in accounting for multiple wavelength bands, reaching R2 values of 0.67. Using this information, I constructed a model that predicts kelp pigments from simulated AVIRIS reflectance using a spatial time series of laboratory spectral measurements and photosynthetic pigment concentrations. These results have implications, not only for kelp, but many other photosynthetic organisms detectable by hyperspectral airborne or satellite sensors. With these findings, airborne optical data could possibly predict a plethora of other biogeochemical traits. Potentially, this research would permit scientists to acquire data analogous to in situ measurements about floating matters that cannot financially and pragmatically be accessed by anything other than a remote sensor.
Isabelle Cobb
Correlations Between SSHa and Chl-a Concentrations in the Northern South China Sea
Isabelle Cobb
Sea surface height anomalies (SSHa)–variations in sea surface height from climatological averages–occur on seasonal timescales due to coastal upwelling and El Niño-Southern Oscillation (ENSO) cycles. These anomalies are heightened when upwelling plumes bring cold, nutrient-rich water to the surface, and are particularly strong along continental shelves in the Northern South China Sea (NSCS). This linkage between SSHa and nutrient availability has interesting implications for changing chlorophyll-a (chl-a) concentrations, a prominent indicator of phytoplankton biomass that is essential to the health of marine ecosystems. Here, we evaluate the long-term (15 years) relationship between SSHa and chl-a, in both satellite remote sensing data and in situ measurements. Level 3 SSHa data from Jason 1/2/3 satellites and chl-a data from MODIS Aqua were acquired and binned to monthly resolution. We found a significant inverse correlation between SSHa and chl-a during upwelling months in both the remote sensing (Spearman’s R=-0.57) and in situ data, with higher resolution in situ data from ORAS4 (an assimilation of buoy observations from 2003-2017) showing stronger correlations (Spearman’s R=-0.75). In addition, the data reveal that the magnitude of SSH increases with time during instances of high correlation, possibly indicating a trend of increased SSH associated with reduced seasonal chl-a concentrations. Thus, this relationship may inform future work predicting nutrient availability and threats to marine ecosystems as climate change continues to affect coastal sea surface heights.
Alyssa Tou
Exploring Coastal Sea Surface Temperature Anomalies and their effect on Coastal Fog through analyzing Plant Phenology
Alyssa Tou
Marine heat waves (MHW) have been increasing in frequency, duration and intensity, giving them substantial potential to influence ecosystems. Do these MHWs sufficiently enhance coastal precipitation such that plant growth is impacted? Recently, the Northeast Pacific experienced a long, intense MHW in 2014/2015, and another short, less intense MHW in 2019/2020. Here we investigate how the intensity and duration of MHWs influence the intensity and seasonal cycle of three different land cover types (‘grass’, ‘trees’, and a combination of both ‘combined’’) to analyze plant phenology trends in Big Sur, California. We hypothesize that longer intense MHWs decrease the ocean’s evaporative capacity, decreasing fog, thus lowering plant productivity, as measured by Normalized Difference Vegetation Index (NDVI). Sea surface temperature (SST) and NDVI data were collected from the NOAA Coral Reef Watch, and NASA MODIS/Terra Vegetation Indices 16-Day L3 Global 250m products respectively. Preliminary results show no correlation (R2=0.02) between SSTa and combined NDVI values and no correlation (R2=0.01) between SST and NDVI. This suggests that years with anomalously high SST do not significantly impact plant phenology. During the intense and long 2014/2015 MHW, peak NDVI values for ‘grass’ and ‘combined’ pixels were 2.0 and 1.7 standard deviations above the climatological average, while the shorter 2019/2020 MHW saw higher peaks of 3.2 and 2.4 standard deviations. However, the ‘grass’, ‘tree’ and ‘combined’ NDVI anomalies were statistically insignificant during both MHWs, showing that although NDVI appeared to increase during the shorter and less intense MHW, these values may be attributed to other factors. The data qualitatively suggest that MHW’s don’t impact the peak NDVI date, but more data at higher temporal resolution are necessary. Further research will involve analyzing fog indices and exploring confounding variables impacting NDVI, such as plant physiology, anthropogenic disturbance, and wildfires. In addition, it’s important to understand to what extent changes in NDVI are attributed to the driving factors of MHWs or the MHWs themselves. Ultimately, mechanistically understanding the impacts MHW intensity and duration have on terrestrial ecosystems will better inform coastal community resilience.
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Last Updated Nov 22, 2024 Related Terms
General Explore More
10 min read SARP East 2024 Atmospheric Science Group
Article 21 mins ago 10 min read SARP East 2024 Hydroecology Group
Article 21 mins ago 11 min read SARP East 2024 Terrestrial Fluxes Group
Article 22 mins ago View the full article
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By NASA
10 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
Return to 2024 SARP Closeout Faculty Advisors:
Dr. Guanyu Huang, Stony Brook University
Graduate Mentor:
Ryan Schmedding, McGill University
Ryan Schmedding, Graduate Mentor
Ryan Schmedding, graduate mentor for the 2024 SARP Atmospheric Science group, provides an introduction for each of the group members and shares behind-the scenes moments from the internship.
Danielle Jones
Remote sensing of poor air quality in mountains: A case study in Kathmandu, Nepal
Danielle Jones
Urban activity produces particulate matter in the atmosphere known as aerosol particles. These aerosols can negatively affect human health and cause changes to the climate system. Measures for aerosols include surface level PM2.5 concentration and aerosol optical depth (AOD). Kathmandu, Nepal is an urban area that rests in a valley on the edge of the Himalayas and is home to over three million people. Despite the prevailing easterly winds, local aerosols are mostly concentrated in the valley from the residential burning of coal followed by industry. Exposure to PM2.5 has caused an estimated ≥8.6% of deaths annually in Nepal. We paired NASA satellite AOD and elevation data, model meteorological data, and local AirNow PM2.5 and air quality index (AQI) data to determine causes of variation in pollutant measurement during 2023, with increased emphasis on the post-monsoon season (Oct. 1 – Dec. 31). We see the seasonality of meteorological data related to PM2.5 and AQI. During periods of low temperature, low wind speed, and high pressure, PM2.5 and AQI data slightly diverge. This may indicate that temperature inversions increase surface level concentrations of aerosols but have little effect on the total air column. The individual measurements of surface pressure, surface temperature, and wind speed had no observable correlation to AOD (which was less variable than PM2.5 and AQI over the entire year). Elevation was found to have no observable effect on AOD during the period of study. Future research should focus on the relative contributions of different pollutants to the AQI to test if little atmospheric mixing causes the formation of low-altitude secondary pollutants in addition to PM2.5 leading to the observed divergence in AQI and PM2.5.
Madison Holland
Analyzing the Transport and Impact of June 2023 Canadian Wildfire Smoke on Surface PM2.5 Levels in Allentown, Pennsylvania
Madison Holland
The 2023 wildfire season in Canada was unparalleled in its severity. Over 17 million hectares burned, the largest area ever burned in a single season. The smoke from these wildfires spread thousands of kilometers, causing a large population to be exposed to air pollution. Wildfires can release a variety of air pollutants, including fine particulate matter (PM2.5). PM2.5 directly affects human health – exposure to wildfire-related PM2.5 has been associated with respiratory issues such as the exacerbation of asthma and chronic obstructive pulmonary disease. In June 2023, smoke from the Canadian wildfires drifted southward into the United States. The northeastern United States reported unhealthy levels of air quality due to the transportation of the smoke. In particular, Pennsylvania reported that Canadian wildfires caused portions of the state to have “Hazardous” air quality. Our research focused on how Allentown, PA experienced hazardous levels of air quality from this event. To analyze the concentrations of PM2.5 at the surface level, NASA’s Hazardous Air Quality Ensemble System (HAQES) and the EPA’s Air Quality System (AQS) ground-based site data were utilized. By comparing HAQES’s forecast of hazardous air quality events with recorded daily average PM2.5 with the EPA’s AQS, we were able to compare how well the ensemble system was at predicting total PM2.5 during unhealthy air quality days. NOAA’s Hybrid Single-Particle Lagrangian Integrated Trajectory model, pyrsig, and the Canadian National Fire Database were used. These datasets revealed the trajectory of aerosols from the wildfires to Allentown, Pennsylvania, identified the densest regions of the smoke plumes, and provided a map of wildfire locations in southeastern Canada. By integrating these datasets, we traced how wildfire smoke transported aerosols from the source at the ground level.
Michele Iraci
Trends and Transport of Tropospheric Ozone From New York City to Connecticut in the Summer of 2023
Michele Iraci
Tropospheric Ozone, or O₃, is a criteria pollutant contributing to most of Connecticut and New York City’s poor air quality days. It has adverse effects on human health, particularly for high-risk individuals. Ozone is produced by nitrogen oxides and volatile organic compounds from fuel combustion reacting with sunlight. The Ozone Transport Region (OTR) is a collection of states in the Northeast and Mid-Atlantic United States that experience cross-state pollution of O₃. Connecticut has multiple days a year where O₃ values exceed the National Ambient Air Quality Standards requiring the implementation of additional monitoring and standards because it falls in the OTR. Partially due to upstream transport from New York City, Connecticut experiences increases in O₃ concentrations in the summer months. Connecticut has seen declines in poor air quality days from O₃ every year due to the regulations on ozone and its precursors. We use ground-based Lidar, Air Quality System data, and a back-trajectory model to examine a case of ozone enhancement in Connecticut caused by air pollutants from New York between June and August 2023. In this time period, Connecticut’s ozone enhancement was caused by air pollutants from New York City. As a result, New York City and Connecticut saw similar O₃ spikes and decline trends. High-temperature days increase O₃ in both places, and wind out of the southwest may transport O₃ to Connecticut. Production and transport of O₃ from New York City help contribute to Connecticut’s poor air quality days, resulting in the need for interstate agreements on pollution management.
Stefan Sundin
Correlations Between the Planetary Boundary Layer Height and the Lifting Condensation Level
Stefan Sundin
The Planetary Boundary Layer (PBL) characterizes the lowest layer in the atmosphere that is coupled with diurnal heating at the surface. The PBL grows during the day as solar heating causes pockets of air near the surface to rise and mix with cooler air above. Depending on the type of terrain and surface albedo that receives solar heating, the depth of the PBL can vary to a great extent. This makes PBL height (PBLH) a difficult variable to quantify spatially and temporally. While several methods have been used to obtain the PBLH such as wind profilers and lidar techniques, there is still a level of uncertainty associated with PBLH. One method of predicting seasonal PBLH fluctuation and potentially lessening uncertainty that will be discussed in this study is recognizing a correlation in PBLH with the lifting condensation level (LCL). Like the PBL, the LCL is used as a convective parameter when analyzing upper air data, and classifies the height in the atmosphere at which a parcel becomes saturated when lifted by a forcing mechanism, such as a frontal boundary, localized convergence, or orographic lifting. A reason to believe that PBLH and LCL are interconnected is their dependency on both the amount of surface heating and moisture that is present in the environment. These thermodynamic properties are of interest in heavily populated metropolitan areas within the Great Plains, as they are more susceptible to severe weather outbreaks and associated economic losses. Correlations between PBLH and LCL over the Minneapolis-St. Paul metropolitan statistical area during the summer months of 2019-2023 will be discussed.
Angelica Kusen
Coupling of Chlorophyll-a Concentrations and Aerosol Optical Depth in the Subantarctic Southern Ocean and South China Sea (2019-2021)
Angelica Kusen
Air-sea interactions form a complex feedback mechanism, whereby aerosols impact physical and biogeochemical processes in marine environments, which, in turn, alter aerosol properties. One key indicator of these interactions is chlorophyll-a (Chl-a), a pigment common to all phytoplankton and a widely used proxy for primary productivity in marine ecosystems. Phytoplankton require soluble nutrients and trace metals for growth, which typically come from oceanic processes such as upwelling. These nutrients can also be supplied via wet and dry deposition, where atmospheric aerosols are removed from the atmosphere and deposited into the ocean. To explore this interaction, we analyze the spatial and temporal variations of satellite-derived chl-a and AOD, their correlations, and their relationship with wind patterns in the Subantarctic Southern Ocean and the South China Sea from 2019 to 2021, two regions with contrasting environmental conditions.
In the Subantarctic Southern Ocean, a positive correlation (r²= 0.26) between AOD and Chl-a was found, likely due to dust storms following Austrian wildfires. Winds deposit dust aerosols rich in nutrients, such as iron, to the iron-limited ocean, enhancing phytoplankton photosynthesis and increasing chl-a. In contrast, the South China Sea showed no notable correlation (r² = -0.02) between AOD and chl-a. Decreased emissions due to COVID-19 and stricter pollution controls likely reduced the total AOD load and shifted the composition of aerosols from anthropogenic to more natural sources.
These findings highlight the complex interrelationship between oceanic biological activity and the chemical composition of the atmosphere, emphasizing that atmospheric delivery of essential nutrients, such as iron and phosphorus, promotes phytoplankton growth. Finally, NASA’s recently launched PACE mission will contribute observations of phytoplankton community composition at unprecedented scale, possibly enabling attribution of AOD levels to particular groups of phytoplankton.
Chris Hautman
Estimating CO₂ Emission from Rocket Plumes Using in Situ Data from Low Earth Atmosphere
Chris Hautman
Rocket emissions in the lower atmosphere are becoming an increasing environmental concern as space exploration and commercial satellite launches have increased exponentially in recent years. Rocket plumes are one of the few known sources of anthropogenic emissions directly into the upper atmosphere. Emissions in the lower atmosphere may also be of interest due to their impacts on human health and the environment, in particular, ground level pollutants transported over wildlife protected zones, such as the Everglades, or population centers near launch sites. While rockets are a known source of atmospheric pollution, the study of rocket exhaust is an ongoing task. Rocket exhaust can have a variety of compositions depending on the type of engine, the propellants used, including fuels, oxidizers, and monopropellants, the stoichiometry of the combustion itself also plays a role. In addition, there has been increasing research into compounds being vaporized in atmospheric reentry. These emissions, while relatively minimal compared to other methods of travel, pose an increasing threat to atmospheric stability and environmental health with the increase in human space activity. This study attempts to create a method for estimating the total amount of carbon dioxide released by the first stage of a rocket launch relative to the mass flow of RP-1, a highly refined kerosene (C₁₂H₂₆)), and liquid oxygen (LOX) propellants. Particularly, this study will focus on relating in situ CO₂ emission data from a Delta II rocket launch from Vandenberg Air Force Base on April 15, 1999, to CO₂ emissions from popular modern rockets, such as the Falcon 9 (SpaceX) and Soyuz variants (Russia). The findings indicate that the CO₂ density of any RP-1/LOX rocket is 6.9E-7 times the mass flow of the sum of all engines on the first stage. The total mass of CO₂ emitted can be further estimated by modeling the volume of the plume as cylindrical. Therefore, the total mass can be calculated as a function of mass flow and first stage main engine cutoff. Future CO₂ emissions on an annual basis are calculated based on these estimations and anticipated increases in launch frequency.
Return to 2024 SARP Closeout Share
Details
Last Updated Nov 22, 2024 Related Terms
General Explore More
8 min read SARP East 2024 Ocean Remote Sensing Group
Article 21 mins ago 10 min read SARP East 2024 Hydroecology Group
Article 21 mins ago 11 min read SARP East 2024 Terrestrial Fluxes Group
Article 22 mins ago View the full article
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By European Space Agency
Image: This Copernicus Sentinel-2 image from 13 November 2024 shows the Lewotobi Laki Laki volcano eruption on the island of Flores in southern Indonesia. View the full article
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By Space Force
In partnership with the Air Force Research Laboratory, the United States Space Force is currently accepting proposals for USSF University Consortium/Space Strategic Technology Institute 4, focused on Advanced Remote Sensing.
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By European Space Agency
Video: 00:02:18 At ESA, through the Advanced Research in Telecommunications Systems programme, we’re addressing solutions for when safety and security of communication services cannot be guaranteed by the terrestrial networks alone. With our programme Space systems for Safety and Security, or 4S, we are pioneering cutting-edge development of secure and resilient satellite communication systems, technologies and services to improve life on Earth.
Picture a world where our critical infrastructure is protected from cyber threats, and where communication links work when the world around them doesn't. A transportation network where safety is not just a priority, but a guarantee. Where air traffic flows completely efficiently, reliable and connected. Railways operate without interruption, and shipping can navigate safely and securely.
Imagine that our first responders are coordinating via seamless communications, and institutional agencies are acting rapidly and decisively when there's a crisis. All thanks to secure and safe satellite communication systems, orbiting above the planet. This is the future we're building with the 4S programme. A future where space systems safeguard our security, making sure that connectivity remains our greatest strength. Join us as we continue to push the boundaries of innovation.
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