Displaying 91 - 100 of 118
Turbidity calculated from a 5/11/2022 Landsat 8 OLI scene. The dark blue, purple, and pink pixels indicate low to high levels of turbidity respectively in Lake Winnipesaukee, New Hampshire and surrounding water bodies. This is layered over an SRTM DEM dataset, acquired 2/11/2000 and published 9/23/2014, showing varying elevations. More turbid waters are less suitable for loon habitats and are thus of interest to monitor loon preservation.

Predicting Future Conflicts between Loon Habitats and Human Development in New Hampshire using NASA Earth Observations

Topic
DEVELOP
Ecological Conservation
New Hampshire Ecological Conservation (2023 Spring) Team: Jane Zugarek (Project Lead), Madison Arndt, Jessica Gray, Amelia Untiedt Summary: Bioindicator species monitoring allows researchers to infer...
The green areas show stable forest in NW Alabama classified by both National Land Cover Dataset (2016-2019) and Landscape Change Monitoring System(2016-2021), and the pink areas are areas where forest cover loss was sensed by NLCD, LCMS, LandTrendr (2016-2021), and Global Forest Watch (2016-2021). These datasets and the basemap were made with Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 8 Operational Land Imager.

Leveraging Earth Observations to Estimate Carbon Dioxide Emissions from Forest Cover Loss in Alabama and Tennessee

Topic
DEVELOP
Climate
Southeast US Climate II (2023 Spring) Team: Cassie Ferrante (Project Lead), Katherine Scott, James Karroum, Cate Lull Summary: The balancing of atmospheric CO2 sources and...
The data for this image comes from NASA satellite Landsat 8 Operational Land Imager. Normalized Difference Vegetation Index and Cropland Data Layers were used to create the image. The black, brown, and bright green specks represent the different crops growing near Wheeler Lake Watershed in North Alabama. NDVI and cropland data can be used to predict and evaluate the effects of flash drought on agricultural crops.

Evaluating the Spatial and Temporal Distribution of Flash Droughts within Agricultural Areas and Regional Crop Calendars in the Southeast using Earth Observations

Topic
DEVELOP
Agriculture
Southeast US Agriculture (2023 Spring) Team: Kindrea Gibbons (Project Lead), Michaela Gooch, Quinton Deppert, Casey Mills Summary: A flash drought refers to the rapid onset...
Normalized Difference Snow Index (NDSI) Image calculated from a May 2021 Landsat 8 top-of-atmosphere (TOA) reflectance image. The purple area depicts areas without snow and the yellow area represents areas with snow cover. This information can be used by refuge managers to monitor snow conditions and prepare for the ecological, cultural, and landscape impacts caused by snow.

Using Earth Observations to Evaluate Snow Variability through a Climatological Analysis to Support Ecological Monitoring in Northeast Alaska

Topic
DEVELOP
Climate
Northeast Alaska Climate (2023 Spring) Team: Kristin Anderson (Project Lead), Omeed Arooji, Isabella Chittumuri, Tom Germann Summary: Alaska is experiencing climate change at an unprecedented...
The InVEST urban flood model produces various outputs, like the runoff retention seen here. The model output was derived from GPM IMERG, land cover, soil type, and curve number data. This image is from the extreme rainfall storm event on August 22, 2017. This image shows where the runoff is being retained in Kansas City, KA. The dark purple represents extremely high runoff retention while the yellow represents low retention with the green and blue representing increasing amounts of retention. The background

Incorporating Earth Observation Data into the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Flood Risk Mitigation Model Python API

Topic
Urban Development
DEVELOP
InVEST Urban Development (2023 Spring) Team: Son Do & Jessica Besnier Summary: Urban flooding poses as one of the biggest issues for cities today as...
Normalized Difference Snow Index (NDSI) processed image using Landsat 8 OLI data from January 2022 and SUOMI-NPP VIIRS snow cover data from January 2019, overlaid on a Landsat 8 RGB image, colorized purple. NSDI is shown in yellow-orange-red and SUOMI-NPP VIIRS is depicted in shades of blue. Snow cover data was used to identify melt events causing high turbidity in Wyoming’s Shoshone River basin. PlanetScope-derived turbidity (May 2019) also highlights the river in green.

Quantifying Sediment Input in the Shoshone River in Wyoming using the Soil and Water Assessment Tool for Enhanced Water Quality Monitoring

Topic
DEVELOP
Water Resources
Shoshone River Water Resources II (2023 Spring) Team: Robyn Holmes (Project Lead), Christian Bitzas, Jillian Greene, Isabella St. John Summary: The Willwood Dam, an irrigation...
Color composite image portraying Wupatki Basin in northwestern Arizona, derived from 2021 LANDSAT 8 OLI/TIRS imagery. This image depicts Pinyon-Juniper Woodlands (PJW), among other vegetation, between the river and mountains in a light green color. Thermal Infrared (TIR) occupies the red band, while the green and blue bands represent the Modified Normalized Difference Water Index (MNDWI) and the Modified Soil-Adjusted Vegetation Index (MSAVI), respectively. The reduced correlation between bands in this comp

Utilizing NASA Earth Observations and Aerial Imagery to Assess Pinyon-Juniper Tree Mortality in Flagstaff, AZ

Topic
DEVELOP
Capacity Building
Water Resources
Arizona Water Resources II (Fall 2022) Team: Arina Morozova (Project Lead), Jamal Jeffer, Jessica Birk, Greg Peargin Summary: Pinyon-juniper woodlands (PJW) provide critical and resilient...
DEVELOP Day Banner image of gridded remote sensing pictures with the DEVELOP anniversary logo in the center
Applied Sciences
DEVELOP

NASA DEVELOP: 25 Years of Science Serving Society

By
Julianne Liu
,
Caroline Williams
,
Laramie Plott
,
Katie Caruso
,
Karen Allsbrook
Sophie Krautmann smiles, wearing her grey National Park Ranger buttoned shirt and brown hat. She stands in a high place with the red rock formations visible in the canyon behind her.
DEVELOP
Wildfires
Climate
Capacity Building
Ecological Conservation
Health & Air Quality
Water Resources

Getting Satellite Data into the Hands of Park Rangers

By
This is a visualization of ECOSTRESS’ Evaporative Stress Index in Marin County, CA. The data is an average of summer months from 2018 – 2022. Scores closer to 0, or red/orange areas, indicate plants are in stress, meaning they are not meeting their potential evapotranspiration, while scores closer to 1, or blue areas, indicate plants are thriving and closer to reaching potential evapotranspiration.

Improving Fire Suppression Modeling to Inform Fire Prevention and Suppression Decisions in Marin County, CA

Topic
DEVELOP
Wildfires
Marin County Wildland Fires II (2023 Summer) Team: Harrison Raine (Project Lead), Katherine Scott, Nikitha Shivakumar, Tiffany Mar, Anai Tene Summary: A future of increased...

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