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Forest disturbances from bark beetle outbreaks are a major concern in Bhutan, known to cause extensive tree mortality to pine and spruce forests. The NASA DEVELOP team partnered with the Ugyen Wangchuck Institute of Conservation and Environmental Research (UWICER), the Bhutan Foundation, and the Karuna Foundation to assess forest changes for the districts of Bumthang and Haa from 2000 to 2018. The project used preprocessed meteorological data from the Climate Hazards Center Infrared Precipitation with Station (CHIRPS) and Famine Early Warning System Network Land Data Assimilation System (FLDAS), along with Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper plus (ETM+), and Landsat 8 Operational Land Imager (OLI) to assess apparent forest disturbance occurrences and observed climate trends. Shuttle Radar Topography Mission (SRTM) was used to resolve variations in elevation and slope for mountainous regions. Using the Google Earth Engine LandTrendr (LT) code algorithm, along with Landsat data, the team developed an app called Forest Disturbances Detection Toolbox (FDDT) to assess forest changes in Bhutan. The app includes climate variables for the focus districts, along with LT variables, which allows the end users to further examine the cause of disturbances. The team compared geocoordinates for known disturbances with LT disturbance detection products. Although additional work is needed in the future to validate the project end products from the FDDT, the tool will be provided to the project partners to aid forest management efforts in Bhutan.
The barrier islands of Louisiana’s Breton National Wildlife Refuge (BNWR) are disappearing due to sea level rise, extreme hurricanes, sediment starvation, and the Deepwater Horizon oil spill. This decline in land area has damaged important bird habitat and reduced the islands’ ability to protect coastal Louisiana from storm surges. The persistence of the islands is synergetic to that of the surrounding seagrass beds; seagrass binds together land, protecting the islands from erosion, and the loss of land exposes the seagrass and accelerates its decline. Furthermore, seagrass is independently important, absorbing excess nutrients and providing habitat for marine ecosystems. Here we present the Tool for Coastal Remote Ecological Observations in Louisiana (Tool CREOL), a Google Earth Engine Tool built to easily access data from Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI, and Aqua and Terra MODIS. We show, using time series and maps generated using the tool, how land area and seagrass have responded to destructive events from the past 36 years (1984-2021). In only 7 years, Hurricane Georges (1998), Ivan (2004), and Katrina (2005) reduced land area by approximately 85%, accompanied by a major decline in seagrass extent. Tool CREOL will have strategic utility in planning upcoming restoration and revegetation efforts planned by Louisiana’s Coastal Protection and Restoration Authority in the Breton National Wildlife Refuge and will provide up-to-date monitoring of the results of that project. The tool serves as a basic model which can be adapted to study similar coastal regions in the world.
Since its introduction in the late 1800s, Elaeagnus augustifolia (Russian olive) has become a widespread invasive shrub that poses a threat to native riparian species in the United States by competing with native riparian plants for space and resources. To date, limited information on the distribution of Russian olive in the Powder River Basin of Montana and Wyoming have hampered management efforts and decision making. Here, we detect and model the distribution of Russian Olive using field surveys, ocular sampling, and variables from Landsat 8 Operational Land Imager (OLI), Sentinel-2 MultiSpectral Instrument (MSI), and Shuttle Radar Topography Mission (SRTM) using the Random Forest algorithm. We derived topographic, spectral, and hydrological variables from Landsat 8 OLI, Sentinel-2 MSI, and SRTM to utilize as model inputs. The team was able to successfully create a spectral Russian olive detection map for the Powder River Basin (RMSE =15.44%, R2 = 0.6482). The team also examined change in stream channel geomorphology from 1984-2020 in a time-series analysis using Landsat visible imagery and the RivMap MATLAB package and found little change. Our results will help our partners at the Powder River County Weed Board, Gay Ranch, United States Geological Survey, and University of Northern Colorado to locate and prioritize areas for riparian habitat restoration and to understand the region’s hydrology and geomorphology.
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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.
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Pinyon-juniper woodlands (PJW) are a vital habitat and food source for several wildlife species and a source of both utility and cultural importance for Indigenous groups. In 2021, amidst a decades-long drought, an extensive juniper mortality event occurred at Wupatki National Monument (WNM) in Arizona. In response, the National Park Service (NPS) is evaluating which land management practices will be beneficial. In partnership with the NPS, the NASA DEVELOP team used remote sensing data to map PJW mortality and analyze the relation of tree mortality to stand density, climate, and topography in north-central Arizona from 2015 to 2021. To identify the extent of PJW, the team performed an unsupervised classification using National Agricultural Imagery Program (NAIP) data with validation sources including NPS-created land cover maps, Landscape Fire and Resource Management Planning Tools (LANDFIRE), NPS and United States Forest Service (USFS) vegetation maps, and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) data. Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), and Landsat 8-derived Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI) were used to analyze factors contributing to pinyon-juniper mortality. Although no relationships were found in the broader study region, PJW mortality was weakly correlated to elevation, soil moisture, and land surface temperature within WNM. Results from this study can inform NPS vegetation management that best protects natural and cultural resources.