Displaying 131 - 140 of 305
Disasters

Radar Data Reveals How Earthquakes Move Land

By
Megan Gannon, Applied Sciences Program Writer
ARIA Damage Proxy Map (DPM) showing potentially damaged structures from Cyclone Harold
Disasters

NASA Aids World Food Programme in Identifying Damaged Buildings in Vanuatu from Cyclone Harold

By
Jacob Reed

Hurricane Iota 2020

Disaster Type
Hurricanes & Cyclones
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...

Assessing Estuarine Ecosystems in California for Improved Wetland Monitoring and Management

Topic
DEVELOP
Estuaries are vital ecosystems that serve important ecological functions. The Marine Life Protection Act aims to protect these ecosystems by establishing a network of marine...
Hurricane Isaias traveling northwest between Cuba and the Bahamas on Friday, July 31, 2020, as seen from the International Space Station. Credits: NASA/Astronaut Col. Doug Hurley

Hurricane Isaias 2020

Disaster Type
Hurricanes & Cyclones

Louisiana Flooding 2016

Disaster Type
Floods
Severe & Winter Weather

Evaluating Urban Heat Islands and Flooding to Enhance Green Infrastructure Initiatives in Coastal Communities in Mobile, Alabama

Topic
DEVELOP
This project utilized satellite Earth observations to assess locations in Mobile County, Alabama, that are vulnerable to the urban heat island effect (UHI) and flood...

TRANSFORMING EARTH OBSERVATIONS TO KNOWLEDGE THROUGH INCLUSIVE PARTICIPATION

February 22, 2022
February 22, 2022
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...

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