Displaying 11 - 20 of 41
2022 Spring CO Boulder County Disasters Website Image

Mapping Forest Carbon Stocks to Understand Carbon Implications of Treatments and Wildfire

Topic
DEVELOP
Capacity Building
Disasters
Boulder County Disasters (Spring 2022) Team: Sarah Hettema (Project Lead), Jennifer Rogers, Ibuki Sugiura, Erin Twaddell Summary: In recent years, record-breaking wildfire activities in the...
Potential for land cover to change from trees to grass, forb, and herb between 1987 and 2020 in the Teton Mountain Range. Image created from LCMS land cover data which are derived from Landsat 4, 5, 7, and 8 imagery (1987 - 2020). High transition potential is depicted in yellow and low transition potential is indigo. Transition potentials help to forecast land cover and inform land managers on the locations of suitable bighorn sheep habitat.

Assessing Forage Change and Winter Habitat Availability for Bighorn Sheep that Employ a High-Elevation Overwintering Strategy to Identify Areas for Intervention

Topic
DEVELOP
Capacity Building
Ecological Conservation
Grand Teton Ecological Forecasting (Fall 2021) Team: Alex Posen (Project Lead), Allyson Earl, Sarah Hettema, and Michael Hitchner Summary: Grand Teton National Park provides habitat...
Forest cover and land surface temperature (LST) around Maine's Penobscot River during Summer 2021. The shades of green distinguish between evergreen (dark) and deciduous (light) forest which were classified using Landsat 8 OLI imagery. The purple gradient corresponds to LST derived from Terra MODIS where the warmest areas, including Bangor, are white. Changing land use and warming temperatures along Maine’s rivers are associated with reducing juvenile Atlantic salmon (Salmo salar) survivorship.

Utilizing Earth Observations to Monitor Federally Endangered Atlantic Salmon (Salmo Salar) Habitat in Maine: An Interactive Workshop 

Topic
DEVELOP
Capacity Building
Ecological Conservation
Maine Ecological Forecasting III (Summer 2022) Team: Jonathan Falciani (Project Lead), Colin Hogan, Linda Mitchell, Makario Sarsozo Summary: Shifting patterns in land use and land...
Annual max biomass calculated from 2021 daily Harmonized LandSat Sentinel-2 (HLS) dataset. Dark purple colors show low biomass while the bright orange show high biomass. Regions with high vegetation and tree canopy cover are shown in orange on the left of the image. High biomass values are of an interest to rangeland managers to help inform their grazing decisions based on which areas of the ranch produce the most biomass/vegetation.

Rangeland Monitoring to Inform Grazing Management in Eastern Colorado

Topic
DEVELOP
Capacity Building
Agriculture
Eastern Plains Agriculture (Fall 2022) Team: Jillian Joubert, Sarah Hettema, Deni Ranguelova, TR Ingram, Max Stewart Summary: Adaptive management on cattle ranches requires rangeland managers...
AppSci Week 2021 Header

2021 Earth Science Applications Week

Agosto 9, 2021
Agosto 12, 2021
2022 Spring PUP Mexico Disasters Website Image

Comparing Feasibility of Flood Detection Methods Using Google Earth Engine and Open Data Cube for Flood Mitigation in Mexico

Topic
DEVELOP
Capacity Building
Disasters
Mexico Disasters (Spring 2022) Team: Philip Casey (Project Lead), John Willis, Sean Nelsen, Zachary Silberman Summary: In this project, NASA DEVELOP partnered with Mexico’s National...
NDWI-processed imagery from Landsat 8 Operational Land Imager data. This mosaicked image was taken from January to December 2021 of Jekyll Island, Georgia. NDWI contrasts the water features in a satellite image to its surroundings by measuring the moisture content. Low moisture content is shown in white, and high moisture content is shown in blue.

Evaluating the Impacts of Hurricane Irma on Georgia Heirs Property Owners Using Earth Observations

Topic
DEVELOP
Capacity Building
Disasters
Georgia Disasters (Fall 2022) Team: Isabella Chittumuri (Project Lead), Nancee Uniyal, Nathan Tesfayi, Shakirah Rogers Summary: In September 2017, Hurricane Irma made landfall in southern...
NDVI over Mato Grosso, Brazil processed from March 2021 Landsat-8 OLI data. Calculated NDVI values correspond with colors shown to indicate plant health. High NDVI values (green to blue) indicate dense vegetation found in tropical and temperate forests or crops at their peak growth. Low values (yellow to red) depict barren land, water, and moisture-stressed vegetation. These data can support timely and efficient agricultural responses to ensure productive yields and food security.​

Enhancing Crop Classification Mapping Using Optical and Radar Satellite Sensors to Enhance Agricultural Management and Policymaking in Mato Grosso, Brazil  

Topic
DEVELOP
Capacity Building
Agriculture
Mato Grosso Agriculture (Summer 2022) Team: Max Rock (Project Lead), Elijah Dalton, Aidan Harvey, Kate Reynolds Summary: Ranked as the fourth largest food producer in...

TRANSFORMING EARTH OBSERVATIONS TO KNOWLEDGE THROUGH INCLUSIVE PARTICIPATION

Febrero 22, 2022
Febrero 22, 2022
NDWI-processed composite image from Landsat 8 OLI data of the Lower Illinois River Valley and surrounding landscapes from summer 2021. Shades of pale yellow indicate dry vegetation and dark teal represents open water, while brighter turquois values depict wet vegetation. Areas of high NDWI values are demonstrative of high presence of wet vegetation and are of interest to the Great Rivers Land Trust in identifying areas of interest for wetland conservation.

Inundation Mapping of the Lower Illinois River Valley Using Synthetic Aperture Radar and Optical Satellite Imagery for Wetland Conservation and Restoration Prioritization Efforts 

Topic
DEVELOP
Capacity Building
Ecological Conservation
Lower Illinois River Valley Ecological Forecasting (Summer 2022) Team: Vanessa Machuca (Project Lead), Dana Myers, Hannah Rigdon, Christiana Saldana Summary: The Lower Illinois River Valley...

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