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All Projects

Project Title Organization Lead Project Summary
Emerging Technologies in Earth Observations for Agricultural Monitoring USDA

We utilize this bi-annual workshop to bring the cutting edge of agricultural monitoring from the research community to the operational user community. 

USAID - Feed the Future intersections with NASA Harvest USAID Kiersten Johnson, James Verdin

Feed the Future, the U.S. Government’s Global Food Security initiative, takes an integrated approach to combating the root causes of hunger, malnutrition, and poverty. This program intersects with NASA Harvest to promote and further the use of Earth observations data for addressing food insecurity. 

GLAD - Evaluating Landsat and Rapid Eye data for winter wheat mapping and area estimation, Soy yield field to national University of Maryland, GLAD Matthew C. Hansen

Our project advances global crop type area estimation and mapping, integrating yield estimation as feasible, focusing on commodity crops, including wheat, soybeans and corn.

CEOS & GEOGLAM: Working with the world's space agencies to advance agricultural monitoring University of Maryland, GEOGLAM, CEOS Alyssa Whitcraft

GEOGLAM’s overarching goal is to enhance the international community’s capacity to utilize Earth observations to produce and distribute timely, accurate, reliable, and actionable information on food production for both stabilizing markets and providing early warnings of food shortages. At the core of GEOGLAM’s activities is the coordination of Earth observation (EO) data (acquisition, preprocessing, and access)  including satellite-based data drawn from both the commercial and civil space agencies. In the latter case, this is accomplished through a strong relationship with the Committee on Earth Observation Satellites (CEOS), an organization of the world’s space agencies in operation since 1984. Dr. Alyssa Whitcraft serves as both the lead of the GEOGLAM Thematic Coordination Team on EO Data, as well as the agricultural lead point of contact for CEOS. Since 2018, the focus of the group has expanded from data requirements to defining Essential Agricultural Variables for GEOGLAM, an effort co-led by Dr. Whitcraft and Sven Gilliams (VITO).

Agricultural Land Use Change in Central and Northeast Thailand: Effects on Biomass Emissions, Soil Quality and Rural Livelihoods University of Maryland Varaprasad Bandaru

This project aims to understand the impacts of recent changes in rice and sugarcane production practices in central and northeast Thailand on biomass emissions from residue burning, soil quality and rural well-being.

Cropland Carbon Monitoring System (CCMS): A satellite-based system to estimate carbon fluxes on U.S croplands University of Maryland R. César Izaurralde, Varaprasad Bandaru

This project creates a prototype of a Cropland Carbon Monitoring System (CCMS) that improves the existing cropland carbon storage and flux estimates in terms of spatial and temporal scale and completeness.

GLAM System - Cloud-Based Global Agricultural Monitoring University of Maryland Alyssa Whitcraft

The project’s objective is to enhance the agricultural monitoring and the crop-production estimation capabilities of the USDA Foreign Agriculture Service (FAS) using the new generation of NASA satellite observations. The GLAM system can be access here.

The GEOGLAM Crop Monitor for Early Warning University of Maryland Inbal Becker-Reshef, Christina Jade Justice

The G20 Group on Earth Observations Global Agriculture Monitoring (GEOGLAM) Crop Monitor for Early Warning (CM4EW) is an international initiative that provides monthly transparent, multi-source, consensus assessments of the crop growing conditions, status, and agro-climatic conditions which are likely to impact production in countries vulnerable to food insecurity in order to strengthen agricultural, humanitarian intervention and food security decision making and policy implementations.

The GEO Global Agricultural Monitoring (GEOGLAM) Initiative University of Maryland Christopher Justice, Inbal Becker-Reshef, Alyssa Whitcraft, Ian Jarvis

GEOGLAM is an international G20-endorsed program geared toward enhancing the use of Earth observations (EO) to strengthen decision making, action taking, and policy in the realms of food security and sustainable agriculture. As major contributions to GEOGLAM, NASA Harvest funds co-chairpersonship of GEOGLAM (C.O. Justice), the coordination and leadership of the GEOGLAM Crop Monitor (I. Becker-Reshef et al.), and leadership of the EO Data Thematic Coordination Team and co-leadership of the Essential Agriculture Variables for GEOGLAM working group (A.K. Whitcraft).

The GEOGLAM Crop Monitor for AMIS University of Maryland Inbal Becker-Reshef, Brian Barker

This project brings together international partners on a monthly bases to develop a convergence of evidence-based assessment on current crop conditions in the major producer and exporter countries for the four main global food crops (wheat, maize, rice, and soybeans) and provide a report to AMIS.

Agriculture Monitoring in the Americas (AMA) University of Maryland Alyssa Whitcraft

The Americas are critical contributors to the global food system and home to a rich array of natural resources which provide a critical buffer against global climate change. Agriculture in the Americas is vital to local and regional economies, as well.  Land management for agriculture is of great import to the region and beyond, but there remain key gaps in understanding of the regions’ intricacies, and remote sensing-based agricultural monitoring can help.


Meanwhile, the G20 GEOGLAM initiative is organized around thematic areas and is implemented at national, regional, and global levels. The regional network for the Americas is known as “Agricultural Monitoring in the Americas,” and is a joint contribution to both GEOGLAM and AmeriGEO. The group focuses on strengthening national systems’ monitoring capabilities through Earth observations (EO) as well as on fostering with-in-region international collaboration around research and development and operational implementation of monitoring tools for the main crops types and rangeland/pasture areas in the Americas. Through facilitating contact and coordination between researchers and decision-makers at the ministerial level, we can best lever EO data to confront challenges around food production, food security, climate change, and sustainable development. AMA broadly focuses on:


  • Assessing data-to-information needs in the Americas
  • Fostering research collaborations toward operational methods (including participation in the JECAM and RAPP networks)
  • Capacity development and technology transfer in the use and management of EO datasets toward producing actionable information
  • Moving EO information into the hands of decision-makers
NASA Harvest Portal University of Maryland Michael Humber

NASA Harvest Portal: A tool for food security and agricultural data discovery and analysis.

Crop Yield and Condition Forecasting from Field to Global Scales University of Maryland Ritvik Sahajpal, Inbal Becker-Reshef, Brian Barker

We monitor and forecast agricultural yields and conditions globally, ranging from single fields to entire countries, by applying machine learning algorithms to earth observation data.

National Crop Monitors University of Maryland Catherine Nakalembe, Inbal Becker-Reshef

A combined effort from multiple projects supporting national agencies to develop and maintain Earth observations-based agricultural monitoring systems. 

Status and Opportunities for Tanzania Agrometeorological Services University of Maryland Catherine Nakalembe

This project supports the Tanzania Meteorological Agency (TMA) in improving their capability to deliver actionable agrometeorological data products to farmers and other end users. 

Earth Observation for National Agricultural Monitoring University of Maryland Catherine Nakalembe

This project aims to advance national agriculture monitoring with Earth Observations (EO) data in East and Southern Africa using machine learning tools and open source data to develop baseline datasets.

Crop monitoring and production forecasting using optical and SAR satellite data University of Maryland Mehdi Hosseini, Inbal Becker-Reshef

We are studying optical and Synthetic Aperture Radar (SAR) applications for crop monitoring and production forecasting for both large scale agricultural systems and smallholder systems at the field to national scales. This involves developing and refining models for yield forecasting, cropland and crop type mapping, and crop condition assessments.

In-Season Field-Scale Mapping of Crop Types and Delays with Machine Learning University of Maryland Hannah Kerner, Inbal Becker-Reshef

We are developing systems that use machine learning analysis of remote sensing data to predict where specific crops are planted and when at different stages during the growing season.

Using satellite data to help farmers improve field-scale nutrient management University of Illinois at Urbana Champaign Kaiyu Guan

This project will develop actionable data products and/or tools for Midwest farmers regarding better field-scale nutrient management, using NASA satellite data, process-based models, and domain knowledge.

Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) University of California Santa Barbara (UCSB), Climate Hazards Center Greg Husak, Chris Funk

This project seeks to develop new forecasting datasets and exploratory tools to help identify and anticipate agroclimatic shocks.

Earth Observations for Field Level Agricultural Resource Mapping (EO-FARM) Swiss Re Foundation Inbal Becker-Reshef, Catherine Nakalembe

The EO-FARM project is a collaboration with Swiss Re Foundation, using Earth observations data to enhance food security and resilience in small-holder dominated regions by revolutionizing fundamental datasets needed for agricultural monitoring and enhancing government Crop Insurance programs.

Field Scale Crop Type Mapping and Yield Estimation Stanford Center on Food Security and the Environment David Lobell

We develop globally robust approaches for mapping crop locations and yields to inform agricultural management and food security efforts.

Wheat Yield for Major Producing Countries NASA, UMD Eric Vermote

This project develops crop type mapping and area estimation for soybean, wheat, and maize, as well as in-season estimates of wheat area with corresponding uncertainties to major wheat producing/export countries. In-season national-scale forecasts build on previous work to forecast national wheat yields two months before harvest within 10% of final yields. 

Famine Early Warning System Network (FEWS NET) Land Data Assimilation System (LDAS) NASA GSFC Hydrologic Science Laboratory Amy McNally, Kimberly Slinski

The FLDAS is a hydrologic modeling system developed to meet the needs of food and water security applications.

Relief 2 Resilience in the Sahel Lutheran World Relief Catherine Nakalembe, Tim McCully

Lutheran World Relief is working with NASA Harvest in Mali to gather valuable on-the-ground information about crop conditions so that relevant government agencies can better interpret satellite imagery and advise farmers about potential challenges. The Relief to Resilience in the Sahel (R2R) project will help more than 8,200 farming families in Burkina Faso, Mali and Niger recover from devastating food crises and better prepare for future challenges. 

Spatial Production Allocation Model (SPAM) for 2010 IFPRI

This project provides global area, production and yield maps for 40+ major crops at 5 by 5 minutes resolution. 

Mapping production and loss using satellite data and drones IFPRI Soonho Kim

IFPRI and UMD are working as partners to understand how satellite data can help us better understand crop production and loss in Tanzania, using drones for ground truthing.

Estimating the value of improved crop production forecasts utilizing EO data IFPRI Joe Glauber

We identify major sources of global production forecast error and are developing a methodology and model to provide a valuation of improved market information for improvement of crop forecasts and early warning systems.

Gro Web App Gro Intelligence Sara Menker

Easily navigate the industry's most comprehensive agricultural data platform powering unparalleled insights and forecasts and perform robust analysis through the creation of dynamic visual displays using a variety of charts and maps.

Sub-National Agricultural Production Archive FEWS NET Gary Eilerts

Working with USAID FEWS NET and Harvest members, this project compiles an archive of historic sub-national agricultural statistics for the globe, with an emphasis on non-European/North American countries.

Supporting crop water management with multi-scale Earth Observations Applied GeoSolutions

Farmers need to make decisions on irrigation and soil moisture, tillage practices, cover crops, and crop rotations, which all take time and cost money. This project centers on using satellite remote sensing and field IoT devices to support crop water management decision making.

A Case Study of Earth Observations Data Usage 6th Grain, University of Vermont

This case study examined how satellite data informs decisions at various points along the agricultural value chain from the perspective of those associated with a cutting-edge digital agriculture company.

Satellite-based Monitoring and Assessment of Smallholder Agriculture System Meghavi Prashnani, Christopher Justice

This project aims to improve the earth observation monitoring of monsoon and winter crops in smallholder agriculture system using advanced methods, field visits and satellite data.

Helmets Labeling Crops Catherine Nakalembe

This project will create unprecedented ML-ready labeled datasets for crop type, crop pest and disease, and market prices in the main food production regions in five African countries. The team will use novel and innovative approaches that include rapid point data collection with cameras mounted on the hoods of vehicles—“helmets”—combined with crowdsourcing to create point and polygon labels. By partnering with local universities, this project will create opportunities for training future African researchers to use remote sensing and machine learning.

In-Situ Sensors and SAR for Soil Moisture Monitoring Inbal Becker-Reshef, Mehdi Hosseini

This project is coordinated in collaboration with CropX, a global leader in soil analytics for agriculture. Beginning with a yearlong pilot study on several alfalfa fields in the western United States, the team will work together to combine in-situ data from CropX soil sensors with synthetic aperture radar (SAR) information in order to provide accurate and scalable irrigation and fertilization metrics.

Using Machine-Learning Models for Field-Scale Crop Yield and Condition Modeling in Argentina Estefania Puricelli, Ritvik Sahajpal, Mehdi Hosseini

NASA Harvest and SIMA, a private sector digital agtech platform provider, have partnered to use Earth observations and remote sensing technology to accurately determine crop yields at field-scale. NASA Harvest has developed a novel tool that has been integrated into SIMA’s platform which became operational in late 2020. The tool is targeted towards supporting farmers in improving their profits through better predictability of crop yields on their farms.

Agricultural Estimates and Agroindustrial Educational Establishments Estefania Puricelli, Inbal Becker-Reshef, Hannah Kerner, Blake Munshell

Led by our partners of the Buenos Aires Grain Exchange (Bolsa de Cereales), NASA Harvest and the Bolsa jointly implemented an educational program beginning in 2021 for high school scholars throughout Argentina. Spanning the academic year, the program includes several instructional lecture-style course modules on the use and importance of Earth observation data for agricultural assessments followed by hands-on field work training. At the end of the semester, participating students give a final presentation on their results and receive a certificate of completion from NASA Harvest.

Agrometeorological Earth Observations Indicators Ritvik Sahajpal, Christina Jade Justice, Inbal Becker-Reshef

The GEOGLAM-NASA Harvest Agrometeorological (AGMET) Earth Observation Indicators utilize a wealth of Earth observation data to provide valuable insights on in-season crop development and current crop conditions at the sub-national scale. Each AGMET Indicator consists of several EO data plots that quantify critical indicators of crop health for a specific region over the cropping season. The AGMET Indicators are being produced for all GEOGLAM Crop Monitor countries and are updated every 7-12 days to ensure that users are provided with the most up to date information.

Niche William Salas, Inbal Becker-Reshef, Jonathan Ojeda

“Niche” is a project that aims to optimize crop variety placement in Sub-Saharan Africa, led by Regrow Ag with NASA Harvest, One Acre Fund, and the University of Nebraska - Lincoln as key implementation partners. The project, which has been awarded a $5M, 4-year grant from the Bill & Melinda Gates Foundation, will bring together several key agriculture and climate tech partners to build an assessment framework and digital tools that will:

  1. Define and characterize the current and future performance of crop and variety adaptation zones in Sub-Saharan Africa, to advance the knowledge of seed breeders on climate adaptation in those specific zones
  2. Identifiy optimal variety placement for novel and existing crop varieties, so they can be effectively distributed to farmers
Harvest2Market: NASA Harvest’s Agricultural Supply Chains Dashboard Inbal Becker-Reshef, Michael Humber, Gary Eilerts, Joe Glauber

Harvest2Market is NASA Harvest’s openly available online tool for analysis of crop conditions, market, and supply chain logistics. The onset of the COVID-19 pandemic highlighted the urgent need to make the connections between crop production prospects (as afforded by remote sensing) to disruptions across the complex food supply chains and ultimately to food availability to people across the globe. Synthesis of global and timely multi-source information relevant to agricultural supply chains is more important than ever. This novel interdisciplinary research initiative addresses a major disconnect in linking satellite-based estimates of global crop production to how global food supply flows and becomes available across the World including the most vulnerable countries to food insecurity.