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At least 595 records · Page 33

Bhutan Agriculture: Developing a Crop Mask for Rice and Creating a Data Collection Protocol Utilizing Remotely Sensed Data in Bhutan

Rice cultivation in Bhutan has been increasingly threatened by deteriorating soil health and outbreaks of diseases and pests associated with the global change in climate patterns. Field surveys, which the national government of Bhutan has relied on to monitor remote agricultural lands, are becoming increasingly overwhelmed by growing threats to agricultural health. To address these concerns, NASA DEVELOP partnered with the Department of Agriculture of Bhutan, the Bhutan Foundation, and the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER) and worked to increase the government of Bhutan’s agricultural monitoring capacity. Utilizing Earth observations including Landsat 8 Operational Land Imager (OLI), Sentinel-1 C-band Synthetic Aperture Radar (C-SAR), Shuttle Radar Topography Mission (SRTM), and Planet imagery, the DEVELOP team worked with NASA SERVIR and created a sampling protocol to identify rice plantations and supplement field surveys for more efficient agriculture monitoring. The analysis focused on districts Paro, Punakha, Samtse, Sarpang, Trongsa, Zhemgang, Wangdue Phodrang, and Samdrup Jongkhar in the year 2020 during the period of transplantation (June) to harvesting of rice (November). The team provided the partners with a sampling protocol for integrating NASA Earth observations into their crop monitoring methods, as well as a crop mask for rice identification and to aid crop management. The crop mask for rice was developed using the Random Forest (RF) classifier for the eight districts of Bhutan. Visually, the random forest model has proved to be more accurate and precise than the classification and Regression Tree model. Statistically, the Random Forest model was 91.8% accurate in identifying rice in Bhutan.

Yeshey Seldon↗

Rodent Research in Space: A Decadal Research Campaign

Studying the physiological effects of spaceflight in rodents is imperative to our understanding of adaptation and to providing countermeasures. We posit that studies of the reproductive system, development, stem cells, and behavior/cognition are critically important and provide outstanding opportunities as these are sentinel tissues and systems for radiation exposure and overall health. To improve understanding of the environmental stressors (weightlessness, space radiation, isolation/confinement) that impact space travelers, rodent research should be continued within and extended beyond LEO.

rodent research spaceflight↗

Casual Rerouting of AERONET Sun/Sky Photometers: Toward a New Network of Ground Measurements Dedicated to the Monitoring of Surface Properties?

This paper presents an innovative method for observing vegetation health at a very high spatial resolution (~5 × 5 cm) and low cost by upgrading an existing Aerosol RObotic NETwork (AERONET) ground station dedicated to the observation of aerosols in the atmosphere. This study evaluates the capability of a sun/sky photometer to perform additional surface reflectance observations. The ground station of Toulouse, France, which belongs to the AERONET sun/sky photometer network, is used for this feasibility study. The experiment was conducted for a 5-year period (between 2016 and 2020). The sun/sky photometer was mounted on a metallic structure at a height of 2.5 m, and the acquisition software was adapted to add a periodical (every hour) ground-observation scenario with the sun/sky photometer observing the surface instead of being inactive. Evaluation is performed by using a classical metric characterizing the vegetation health: the normalized difference vegetation index (NDVI), using as reference the satellite NDVI derived from a Sentinel-2 (S2) sensor at 10 × 10 m resolution. Comparison for the 5-year period showed good agreement between the S2 and sun/sky photometer NDVIs (i.e., bias = 0.004, RMSD = 0.082, and R = 0.882 for a mean value of S2A NDVI around 0.6). Discrepancies could have been due to spatial-representativeness issues (of the ground measurement compared to S2), the differences between spectral bands, and the quality of the atmospheric correction applied on S2 data (accuracy of the sun/sky photometer instrument was better than 0.1%). However, the accuracy of the atmospheric correction applied on S2 data in this station appeared to be of good quality, and no dependence on the presence of aerosols was observed. This first analysis of the potential of the CIMEL CE318 sun/sky photometer to monitor the surface is encouraging. Further analyses need to be carried out to estimate the potential in different AERONET stations. The occasional rerouting of AERONET stations could lead to a complementary network of surface reflectance observations. This would require an update of the software, and eventual adaptations of the measurement platforms to the station environments. The additional cost, based on the existing AERONET network, would be quite limited. These new surface measurements would be interesting for measurements of vegetation health (monitoring of NDVI, and also of other vegetation indices such as the leaf area and chlorophyll indices), for validation and calibration exercise purposes, and possibly to refine various scientific algorithms (i.e., algorithms dedicated to cloud detection or the AERONET aerosol retrieval algorithm itself). CIMEL is ready to include the ground scenario used in this study in all new sun/sky photometers.

Dominique Carrer↗

Trees Outside Forests are an Underestimated Resource in a Country with Low Forest Cover

Trees outside forests (TOF) are an underrepresented resource in forest poor nations. As a result of their frequent omission from national forest resource assessments and a lack of readily available very-high-resolution remotely sensed imagery, TOF status and characterization has until now, been unknown. Here, we assess the capacity of openly available 10 m ESA Sentinel constellation satellite imagery for mapping TOF extent at the national level in Bangladesh. In addition, we estimate canopy height for TOF using a TanDEM-X DEM. We map 2,233,578 ha of TOF in Bangladesh with a mean canopy height of 7.3 m. We map 31 and 53% more TOF than existing estimates of TOF and forest, respectively. We find TOF in Bangladesh is nationally fragmented as a consequence of agricultural activity, yet is capable of maintaining connectedness between remaining stands. Now, TOF accounting is feasible at the national scale using readily available datasets, enabling the mainstream inclusion of TOF in national forest resource assessments for other countries.

Nathan Thomas↗

A Systematic Review and Meta-analysis of the Potential Non-human Animal Reservoirs and Arthropod Vectors of the Mayaro Virus

Improving our understanding of Mayaro virus (MAYV) ecology is critical to guide surveillance and risk assessment. We conducted a PRISMA-adherent systematic review of the published and grey literature to identify potential arthropod vectors and non-human animal reservoirs of MAYV. We searched PubMed/MEDLINE, Embase, Web of Science, SciELO and grey-literature sources including PAHO databases and dissertation repositories. Studies were included if they assessed MAYV virological/immunological measured occurrence in field-caught, domestic, or sentinel animals or in field-caught arthropods. We conducted an animal seroprevalence meta-analysis using a random effects model. We compiled granular georeferenced maps of non-human MAYV occurrence and graded the quality of the studies using a customized framework. Overall, 57 studies were eligible out of 1523 screened, published between the years 1961 and 2020. Seventeen studies reported MAYV positivity in wild mammals, birds, or reptiles and five studies reported MAYV positivity in domestic animals. MAYV positivity was reported in 12 orders of wild-caught vertebrates, most frequently in the orders Charadriiformes and Primate. Sixteen studies detected MAYV in wild-caught mosquito genera including Haemagogus, Aedes, Culex, Psorophora, Coquillettidia, and Sabethes. Vertebrate animals or arthropods with MAYV were detected in Brazil, Panama, Peru, French Guiana, Colombia, Trinidad, Venezuela, Argentina, and Paraguay. Among non-human vertebrates, the Primate order had the highest pooled seroprevalence

Mayaro virus↗

Carolina Coastal Plain Ecological Forecasting: Utilizing NASA Earth Observations to Map Suitable Venus Flytrap Habitat in an Effort to Inform Conservation, Seed Banking, and Reintroduction in the Carolina Coastal Plain and Sandhills Regions

Although the carnivorous plant Venus flytrap (Dionaea muscipula) is recognized globally, its native range is restricted to a small portion of the North and South Carolina Coastal Plain and Sandhills. Within this limited range, Venus flytrap populations are threatened by habitat loss, fire suppression, and poaching. NASA DEVELOP partnered with the North Carolina Botanical Garden (NCBG), the University of North Carolina Herbarium (NCU), and the North Carolina Natural Heritage Program (NCNHP) to support Venus flytrap conservation. The team developed models based on species presence data and environmental variables using the Software for Assisted Habitat Modeling (SAHM) to create a 2021 habitat suitability map for Venus flytrap. These models incorporated Earth observations collected by Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR), and Sentinel-2 Multispectral Instrument (MSI). To predict areas at high risk of development, the team produced a 2050 land-use change map using TerrSet Land Change Modeler. The team found potential areas of conflict between predicted habitat and forecasted future development. Many areas of suitable habitat were concentrated along the coast where development was likely to occur, placing populations there at risk of extirpation. Overlaying suitable habitat with forecasted land change also identified suitable habitats with minimal risk of development, which may serve as lasting Venus flytrap habitat. These results can inform the NCBG and NCNHP’s conservation decision-making, including targeted seed banking, reintroduction, and prioritization of enduring habitats for protection and management.

Monika Rock↗

Hawai‘i Island Disasters: Using NASA Earth Observations to Assess Coastal Flood Risk with Measures of Land Cover Change, Flood Extent, and Vulnerability for Adaptation and Mitigation Planning on Hawai‘i Island

As the County of Hawai‘i faces an increased risk of extreme flooding events, sea-level rise, and other hazards associated with climate change, the need for building geospatial capacity to make better-informed decisions is critical. The County of Hawai‘i and Arizona State University partnered with NASA DEVELOP to complete a macro-scale risk analysis for the island of Hawai‘i analyzing flooding, land cover, vulnerability, and exposure factors using Earth observations and socio-economic data. The team assessed the variation in urban coastal vulnerability around the entire island of Hawai‘i, using satellite imagery of coastal land cover typology from satellite products such as Landsat 8 Operational Land Imager (OLI), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Sentinel-1 Synthetic Aperture Radar (SAR). The team made a sharable geodatabase containing datasets modeling vulnerability to coastal flooding as well as the Hawai‘i Flood Risk Toolbox (HiFloRT) which contains multiple tools for the County to map land cover, extreme rainfall and flood extent across the Island. The end products will allow the County of Hawai‘i to establish a protocol and standard framework for the utilization of Earth observations in future planning.

Garren Kalter↗

An Efficient Area-Based Algorithm for SAR Radiometric Terrain Correction and Map Projection

This article presents a projection algorithm based on the representation of radar samples as area elements, rather than point elements as traditionally done in previous works. Each area element in the geographic grid (geogrid) is associated with a set of samples in the radar grid that intersect completely or partially the area element according to the topography and the radar geometry. Accurate geocoding with adaptive multi-looking is achieved by successively assigning the weighted average of the radar samples to the corresponding geogrid elements. Analogously, the slant-range projection of geocoded data is improved by projecting the geogrid pixels onto the radar grid according to their projected area. When our slant-range projection approach is used within previously-published radiometric terrain correction (RTC) algorithms, the processing time is significantly reduced, performing 3.6 to 5.2 times faster over multi-looked data and up to 8.9 over single-look data. We demonstrate the strength of the area projection algorithm for RTC and geocoding using UAVSAR and Sentinel-1 data, and evaluate the results in the context of the upcoming NISAR mission.

Shiroma, Gustavo H↗

Mapping Boreal Forest Spruce Beetle Health Status at the Individual Crown Scale Using Fused Spectral and Structural Data

The frequency and severity of spruce bark beetle outbreaks are increasing in boreal forests leading to widespread tree mortality and fuel conditions promoting extreme wildfire. Detection of beetle infestation is a forest health monitoring (FHM) priority but is hampered by the challenges of detecting early stage (“green”) attack from the air. There is indication that green stage might be detected from vertical gradients of spectral data or from shortwave infrared information distributed within a single crown. To evaluate the efficacy of discriminating “non-infested”, “green”, and “dead” health statuses at the landscape scale in Alaska, USA, this study conducted spectral and structural fusion of data from: (1) Unoccupied aerial vehicle (UAV) multispectral (6 cm) + structure from motion point clouds (~700 pts per sq. m); and (2) Goddard Lidar Hyperspectral Thermal (G-LiHT) hyperspectral (400 to 1000 nm, 0.5 m) + SWIR-band lidar (~32 pts per sq.m). We achieved 78% accuracy for all three health statuses using spectral + structural fusion from either UAV or G-LiHT and 97% accuracy for non-infested/dead using G-LiHT. We confirm that UAV 3D spectral (e.g., greenness above versus below median height in crown) and lidar apparent reflectance metrics (e.g., mean reflectance at 99th percentile height in crown), are of high value, perhaps capturing the vertical gradient of needle degradation. In most classification exercises, UAV accuracy was lower than G-LiHT indicating that collecting ultra-high spatial resolution data might be less important than high spectral resolution information. While the value of passive optical spectral information was largely confined to the discrimination of non-infested versus dead crowns, G-LiHT hyperspectral band selection (~400, 675, 755, and 940 nm) could inform future FHM mission planning regarding optimal wavelengths for this task. Interestingly, the selected regions mostly did not align with the band designations for our UAV multispectral data but do correspond to, e.g., Sentinel-2 red edge bands, suggesting a path forward for moderate scale bark beetle detection when paired with suitable structural data.

Janice Cessna↗

Fire Island Water Resources: Assessing Sediment Dynamics and Turbidity Changes Along Fire Island National Seashore Using Satellite Data

Fire Island National Seashore has experienced damaging effects as a result of coastal erosion. Erosion has become an increasingly damaging problem that has led to the destruction of park and community infrastructure, contributed to rising groundwater tables, and posed a serious threat to a globally rare holly maritime forest. Beach nourishment project efforts have been made to mitigate damage, but dredging is expensive and can be thwarted by high rates of erosion. The NASA DEVELOP team partnered with the National Park Service and Fire Island National Seashore and used imagery from Landsat 5 Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI), and Sentinel-2 MultiSpectral Instrument (MSI) to analyze turbidity and sediment dynamics through surface reflectance data from 2000-2021. Imagery was atmospherically corrected using Atmospheric Correction for OLI Lite (ACOLITE) and visualized in SeaWiFS Data Analysis Systems (SeaDAS). Additionally, shoreline change was analyzed using high-resolution imagery from WorldView-2 acquired from Maxar for pre-Hurricane Sandy on July 25th, 2010 and post-Hurricane Sandy on December 18th, 2019. The results of this analysis showed that turbidity is highest in the winter seasons. The shoreline analysis estimated total shoreline loss of about 62 acres on the ocean side, and 11 acres on the bay side of the island. These results will be used to better inform future partner-designed shoreline management projects in the face of further erosion and sea level rise.

Kelly Young↗

Oklahoma Health and Air Quality: Mapping Air Quality Using NASA Earth Observations to Investigate Recent Increases in Ozone Concentrations

Tropospheric ozone (O3) is formed by anthropogenic pollutants interacting with sunlight and is considered harmful to human health in high concentrations. In the summer of 2018, the Oklahoma Department of Environmental Quality (DEQ) measured unexpected spikes in O3 in Seiling, Oklahoma, with concentrations exceeding those measured in bustling Oklahoma City and Tulsa. The DEQ tracks air quality using ground monitors and does not utilize Earth observation data in its monitoring or analysis. This project used remotely sensed data to investigate these2018 air quality anomalies, identifying possible causes. We analyzed atmospheric data from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), and Sentinel-5P Tropospheric Ozone Monitoring Instrument (TROPOMI) in conjunction with ground-based measurements of tropospheric ozone (O3), nitrogen dioxide (NO2), methane (CH4), carbon monoxide (CO), formaldehyde (HCHO) and aerosol optical depth (AOD). We compared Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model simulations and Earth observation visualizations to pinpoint ozone spike causes. We also generated models to identify contributing factors to variations in ground ozone concentrations in our study area. The results point to a variety of ozone spike causes, primarily from outside of the state, and support the placement of additionalNO2, O3, and CO monitors to the southeast of Seiling. These analyses can help guide the placement of future monitors in the ground monitoring network and inform air quality regulations in Oklahoma.

Carolina Rosales↗

Towards a program of record of inland water quality: Exploiting present and heritage multispectral sensors for maximum information extraction

Degradation of Earth’s inland water resources due to anthropogenic perturbations and climate anomalies at both local and global scales continues to place human health at substantial risk. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This research exploits recent advancements in bio-optical modeling, cloud computing, and machine learning to enhance our capacity to leverage present and heritage satellite data. Recent research suggests that sensors with low spectral resolution, such as Sentinel 2 and Landsat missions, contain enough hidden spectral variation which can be exploited using data-driven approaches. The availability of three decades of archival imagery will open doors to discover global trends of eutrophication and increased cyanobacteria dominance and provide valuable insight to the development of predictive methodologies. Preliminary efforts in synthetic emulation of global natural inland waters will be discussed and contextualized against satellite radiometric measurement uncertainty, satellite data product uncertainties and causal signal ambiguity over the visible wavelength range, supported by high quality field and image data for selected inland aquatic sites. Insights on water quality estimation via data-driven machine learning models versus matrix inversions will be discussed, and how we can exploit spectral-spatial relationships in high spatial resolution data. A cross-sensor synergistic approach with detailed uncertainty analysis based on optical water types, will allow for unprecedented global snapshots of fine scale ecological dynamics of inland waters.

Inland↗

Generating Landslide Density Heatmaps for Rapid Detection Using Open-access Satellite Radar Data in Google Earth Engine

Rapid detection of landslides is critical for emergency response, disaster mitigation, and improving our understanding of landslide dynamics. Satellite-based synthetic aperture radar (SAR) can be used to detect landslides, often within days of a triggering event, because it penetrates clouds, operates day and night, and is regularly acquired worldwide. Here we present a SAR backscatter change approach in the cloud-based Google Earth Engine (GEE) that uses multi-temporal stacks of freely available data from the Copernicus Sentinel-1 satellites to generate landslide density heatmaps for rapid detection. We test our GEE-based approach on multiple recent rainfall- and earthquake-triggered landslide events. Our ability to detect surface change from landslides generally improves with the total number of SAR images acquired before and after a landslide event, by combining data from both ascending and descending satellite acquisition geometries and applying topographic masks to remove flat areas unlikely to experience landslides. Importantly, our GEE approach does not require downloading a large volume of data to a local system or specialized processing software, which allows the broader hazard and landslide community to utilize and advance these state-of-the-art remote sensing data for improved situational awareness of landslide hazards.

Alexander L Handwerger↗

Configuration and Projected Capabilities of the Common Habitat Medical Care Facility

The Common Habitat is a large, long-duration habitat being explored as part of a conceptual study (not an active NASA program) that uses an SLS core stage Liquid Oxygen (LOX) tank as its primary structure. It is intended for use on the Moon as part of a permanently occupied outpost, on Mars as part of an outpost that will be occupied for hundreds of days at a time, and in deep space as part of the Deep Space Exploration Vehicle where it will support crewed missions up to 1200 days in duration. A study of internal orientation and crew size resulted in a Common Habitat configuration sized for a crew of eight with a three-deck horizontal orientation. Additional work outside the scope of this paper is developing a vertical translation system, a crew mobility aids system based on wearable gecko-derived grippers, and a crew seating/restraint system. These systems are all assumed for use in conjunction with the Medical Care Facility, which is needed to maintain crew well-being during these missions, where distance from Earth precludes the possibility of evacuation to Earth. This paper describes recent improvements in the Common Habitat Medical Care Facility and associated benefits for crew survivability in long duration missions beyond Earth orbit. These improvements were made with the assistance of a NASA Pathways intern whose experience includes a tour of duty in Afghanistan as an Army combat medic with the 691st GHOST-T, attached to the 1st and 7th US Special Forces Groups as part of Operation Freedom’s Sentinel, where he helped provide far-forward surgical capabilities in austere combat environments. The initial baseline Medical Care Facility was developed working in conjunction with University of Houston Space Architecture graduate students. The facility was placed on the upper deck of the Common Habitat in a location that provided privacy, operational volume, and was close to the vertical translation pathway. The notional outfitting repurposed component CAD models from unrelated studies and notionally indicated a level of care roughly equivalent to that aboard the International Space Station. The CAD modeling provided notional stowage volumes, a deployable surface, some fixed equipment, an ultrasound, and a potentially reconfigurable treatment table. While this facility is clearly a competent arrangement, it was desired to leverage available expertise and upgrade the station given the vast distances from Earth to be experienced by the Common Habitat. Key driving requirements applied to the upgrade included to provide Medical Level of Care V, offer enhanced telemedicine capabilities, provide patient physical accommodation, provide caregiver access to the patient from all sides, include sliding pocket doors for access to hygiene and to the Vertical Translation System, and to add any additional capability possible for the best achievable medical care. The first step in the facility upgrade was to quantify the current medical inventory on the International Space Station and ensure that sufficient stowage volume was present for this purpose. To that end, the ISS medical kits were reviewed, and eight full size mid deck lockers were placed in the facility. A number of additional devices were also added, based on the intern’s combat medic experience. Also, two fixed shelves and one horizontal work surface were added to the Medical Care Facility, with the shelves providing storage space for the additional devices and the work surface providing a location for the caregiver to work or stage equipment. Four display monitors were added to the wall above the horizontal work surface, supporting data display, telemedicine, conferencing, or other needs. The existing treatment table was replaced with a mobile surgical stretcher-chair. Two additional doors were added to the Medical Care Facility. One leads directly to the hygiene compartment, allowing it to support medical operations in addition to providing galley/wardroom support. The other door leads directly into the Vertical Translation System. The wall adjacent to the subsystems bay was moved, adding additional volume to the Medical Care Facility. This improved caregiver access to the patient and allowed for a larger number of caregivers to be present. It also provided options for relocation of support equipment relative to the patient as needed. In the upgraded Medical Care Facility, the Surgical Stretcher-Chair and the Vertical Translation System can work together to provide incapacitated crew member transport from a site of injury on any deck of the Common Habitat to the Medical Care Facility. It can also support patient treatment in a variety of positions including a variety of sitting postures and a supine posture at a variety of pitch angles. The facility can also support caregiver office work for review of examination results, private consultation, inventory and maintenance, and a variety of other purposes. A forward activity will be to conduct evaluations of the Medical Care Facility with different medical scenarios. Additionally, ambient and task lighting selections remain as forward work. The eight mid deck lockers can be augmented to use as portable equipment carts, similar to a manner in which maintenance facility stowage was used as portable carts during the NASA Desert Research and Technology Studies in the Constellation Program. Trash accommodation will also need forward work to assess, including provision for wet trash, dry trash, and biological waste. It will be important to assess a redesign of the surgical stretcher-chair. The commercial version used in the upgrade can only enable vertical translation in the seated configuration, requiring the patient to bend both hips and knees. A possible redesign of the chair will allow for vertical translation without requiring any bending at the hip or knees. Also, the commercial version is wheeled, making it mobile in gravity but unanchored in microgravity. Work will be needed to adapt the chair for gravity-independent performance. The hygiene compartment can be redesigned for dual-use medical scrub and galley handwash facility. Pending sufficient volume, it may also be possible to place sanitation equipment in this location to clean medical tools. Finally, most space architectures have never allowed for more than one incapacitated crew member, but several scenarios could potentially injure two or more crew in the same incident. This facility could be assessed to determine its present ability to address two or more injured crew in parallel and determine the potential upper limit for number of treatable crew in a multi-crew injury scenario, or to treat polytrauma of a single patient.

Habitat↗

Thermal Hydraulic Disaggregation of SMAP Soil Moisture Over the Continental United States

Thermal Hydraulic disaggregation of Soil Moisture (THySM) algorithm was implemented to downscale NASA’s Soil Moisture Active Passive (SMAP) Enhanced soil moisture (SM) product to 1 km over the continental United States (CONUS). This algorithm was developed by combining thermal inertia theory with a soil hydraulic-based approach that considers fine-scale SM spatial distribution driven by both heat fluxes and hydraulic conductivity in soils. Relative soil wetness values were estimated using land surface temperature and normalized difference vegetation index for the thermal inertia model and using soil properties for the hydraulic model. The relative soil wetness values at 1 km from both models were then combined by using weighting functions whereby the spatial distribution of SM was governed more by thermal fluxes during times of strong heat transport and infiltration during moisture abundant soil conditions. THySM values were evaluated using in situ SM measurements from SMAP Core Validation Sites (CVS), the USDA Soil Climate Analysis Network, and the NOAA Climate Reference Network over CONUS. THySM shows higher accuracy than the SMAP / Sentinel-1 (SPL2SMAP_S) 1 km SM product when compared to in situ measurements. The accuracy of THySM is 0.048 m3/m3 based on unbiased root mean square error (ubRMSE), outperforming SPL2SMAP_S by 0.01-0.02 m3/m3. The ubRMSE of THySM 1km SM over the SMAP grassland/rangeland-dominated CVS sites is better than 0.04 m3/m3, which meets the SMAP mission SM accuracy requirement applied at 9 and 36 km.

SMAP↗

Boulder County Disasters: Mapping Forest Carbon Stocks to Understand Carbon Implications of Treatment and Wildfire

In recent years, record-breaking wildfire activities in the western US illustrate the need for fire mitigation efforts, such as forest fuels reduction treatments. Forests serve as crucial carbon sinks that combat the increasing effects of climate change while fuels reduction treatments may remove carbon from forested systems. As a result, forest managers need to find a balance between fire mitigation and carbon preservation. This project partnered with Boulder County Parks and Open Space (BCPOS) and the University of Colorado, Denver to investigate the 2020 Cal-Wood fire in Boulder County, Colorado. Using remote sensing data from Landsat 8 OLI, SRTM, Sentinel-2 MSI, and LiDAR, we mapped post-fire forest carbon pools and compared these values with values derived from measurements from plots on the ground. Results indicate that the correlations are R2=0.76 for aboveground live carbon, R2=0.44 for standing carbon, and R2=0.43 for aboveground dead carbon (R2=0.43), and R2=0.35 for total carbon (R2=0.35). Additionally, 38.5% of total carbon was stored in dead carbon and 14.4% was stored in live carbon. We next compared the post-fire pools between treated and untreated areas. Our analysis suggests fuels reduction treatments did not reduce carbon loss in the presence of wildfire enough to clearly distinguish the post-fire carbon in the treated and untreated areas. However, our final carbon maps still provide BCPOS and researchers with an opportunity to explore carbon estimation models based on remotely sensed data as well as a framework to evaluate fuels reduction treatment effectiveness and impact on forest carbon stocks for future wildfire events.

Sarah Hettema↗

Haiti Agriculture: Utilizing NASA Earth Observations to Evaluate the Success of Reforestation Practices in Haiti

Haiti is one of the world’s most deforested and environmentally degraded countries. Over the past 30 years, the Haiti Reforestation Partnership (HRP) has provided resources, education, and expertise to support reforestation work in Haiti. The HRP has planted over 15 million trees through their partnership with Comprehensive Development Program (CODEP). However, they have yet to conduct a comprehensive analysis of forest stand survival. The NASA DEVELOP team partnered with the HRP to aid their future silvicultural decisions using satellite imagery. Through the creation of the Monitoring of Vegetation Presence (MVP) tool in Google Earth Engine, the team produced a time series showing trends in enhanced vegetation index (EVI) from 1984 to 2021, as well as a habitat suitability map using a general model for all tree species. These provided the partner with visuals to communicate their reforestation efforts and guidance on where to apply their future efforts. The team utilized Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), Landsat 9 OLI-2 and Sentinel-2 Multispectral Instrument (MSI) vegetation indices as indicators of stand success over time. The team also incorporated WorldClim bioclimatic variables such as precipitation and temperature, Centre National de L’Information Geo-Spatiale (CNIGS) Airborne Lidar elevation, and ancillary datasets areas suitable for future reforestation efforts. Overall, the time series showed that the demonstration forest increased in EVI at a greater rate than the surrounding area and the habitat model suggested there are 49,000 hectares of suitable habitat for planting using slope, aspect and temperature as predictor variables.

Kelli Roberts↗

Padre Island Water Resources: Monitoring Historic Shoreline Change and Suspended Sediment Patterns along Padre Island National Seashore

Land loss along Padre Island National Seashore threatens the safety of the recreational beach for the general public and endangers wildlife habitats and nesting sites. Historically, the Army Corps of Engineers has conducted dredging efforts to thwart erosion. Quantifying spatial and temporal variations of shoreline change is vital to understanding the interaction of land loss and historical dredging efforts. NASA DEVELOP collaborated with the National Park Service to use remote sensing to investigate the impact of dredging on Padre Island National Seashore’s shoreline. The team utilized high-resolution imagery from Maxar and Planet to create a time series of shoreline changes between 2011 and 2020, conduct shoreline extraction, and quantify shoreline changes. Additionally, the team monitored turbidity and sediment dynamics using Landsat 8 Operational Land Imager (OLI), Landsat 4 Thematic Mapper (TM), Landsat 5 TM, and Sentinel-2 MultiSpectral Instrument (MSI). Shoreline change results demonstrated an average change between 4.5 to 32 meters annually. Meanwhile, the dredging area directly north of the seashore’s Port Mansfield Channel experienced an areal gain of 152,000 m² between 2010 and 2021. The team also observed that turbidity values increased in areas close to the channel where dredging occurred, especially in the 2018 and 2021 dredging years. Dredging years corresponded with less shoreline change than years without dredging. These results will be used to better inform future partner-designed shoreline management projects in the face of continued erosion and sea level rise.

Lisa Tanh↗