GEOGLAM is the Group on Earth Observations Global Agricultural Monitoring Initiative. Launched in June 2011 by the Group of Twenty (G20) Agriculture Ministers and reaffirmed in January 2017, GEOGLAM is an international program geared toward enhancing the use of Earth observations to strengthen decision making, action taking, and policy in the realms of food security and sustainable agriculture.

Initiated between NASA, University of Maryland and the USDA Foreign Agriculture Service (FAS). The project’s objective is to enhance the agricultural monitoring and the crop-production estimation capabilities of the FAS using the new generation of NASA satellite observations.

The Group on Earth Observations (www.earthobservations.org) developed its Global Agricultural Monitoring (GEOGLAM) initiative in response to the growing calls for improved agricultural information.

Area estimation of croplands is a challenge, made difficult by the variety of cropping systems, including crop types, management practices and field sizes. The goal of the project is to work towards a standard method for estimating cultivated crop area at the global scale. Two approaches, one employing sampling and another mapping, will be examined for application at the global scale.

Pakistan is a country of diverse agro-climatic regions. Agriculture plays a pivotal role as it contributes to more than 20% of the GDP and provides employment to 45% of the labor force. The major crop during the winter season (Rabi) is wheat, during the summer season (Kharif) cotton, rice, sugarcane and maize.

Information about the distribution and condition of the maize crop in East Africa is central for making food security assessments. Collecting this information on the ground is necessary but expensive, labor-intensive and data delivery often leads to significant delays.

This project is comprised of three interdisciplinary and integrated components:

   i) Development of an EO-based generalized approach to wheat yield forecasting that is nationally tuned for implementation in the primary wheat exporting countries;

   ii) A simulation and empirically based assessment to explore the potential impact of timely EO-based forecasts on reducing price volatility

GeoODK provides a way to collect and store geo-referenced information, along with a suite of tools to visualize, analyze and manipulate ground data for specific needs. It enables an understanding of the data for decision-making, research, business, disaster management, agriculture and more. As a multi-dimensional application, GeoODK?s goal is to provide an open source platform that can be expanded to address current and future needs of data collection.

The USDA Foreign Agricultural Service (FAS) is a global agricultural monitoring system, providing critical information on global crop production in the context of global markets and food security. Since the 1970's, NASA and the USDA have been working together to develop the capability to monitor global agriculture with satellite remote sensing.

This study will support USGS land cover research to generate and validate continuous field global land cover datasets. The continuous field data will be produced for percent tree, percent barren, percent water, and percent other vegetation. This procedure requires extensive reserach on satellite data pre-processing, image classification and results validation using Landsat 30m and entails developing innovative techniques to automatically process and characterize large volumes of data.

Dr. Shunlin Liang has led a group of research scientists and graduate students to conduct the agricultural remote sensing in the following areas: 1) crop growth monitoring using the Global LAnd Surface Satellite (GLASS) products, 2) drought monitoring based on evapotranspiration, 3) crop productivity, and 4 climate effects.

Oil crops play an important role in food supply in China. Currently, China heavily depends on import for edible oil supply and this dependence will carry increasing risk in the foreseen future. On the other hand, the growing oil crops are quite sensitive to climate conditions and climate change may add additional risk to the security of edible oil supply.

In the process of industrial development and urbanization, countries have often experienced a land use transition, with the contraction and concentration of agricultural land and an expansion of forest and grassland, creating a 'win-win' situation for society due to fast economic development on one hand and enhanced ecological conservation on the other, as human pressure on remote and ecologically sensitive areas was reduced in such a process.

Researchers in the Department of Geographical Sciences, University of Maryland (UMD), in collaboration with researchers at Texas AgriLife Research, Texas A&M University (TAMU) employ the terrestrial ecosystem model EPIC (Environmental Policy Integrated Climate) to characterize possible impacts of climate change on crop yields and ecosystem services at site, regional, and global scales.

GEOGLAM’s over-arching goal is to enhance the international community’s capacity to lever Earth observations to produce and disseminate 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 observations, including satellite-based data drawn from both the commercial and civil space agencies.

The primary goal of this project is to create a prototype of a Cropland Carbon Monitoring System (CCMS) that improves the existing cropland C storage and flux estimates developed under previous NASA CMS activities in terms of spatial and temporal scales as well as completeness.

Remote sensing data is the essential source of information for enabling monitoring and quantification of crop state at global and regional scales. Crop mapping, state assessment, area estimation and yield forecasting are the main tasks that are being addressed within GEOGLAM. Efficiency of agriculture monitoring can be improved when heterogeneous multi-source remote sensing datasets are integrated.

Crop residue burning in agricultural areas of the world adversely impacts public health, Greenhouse Gas Emissions (GHGs), and other aerosol emissions affecting regional air quality. The burning of crop residues contributes to at least one-third of global biomass burning emissions. While research has characterized emissions from burning of many types of crop residue across the globe, these analyses only provide rough estimates.

Accurate and timely production forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. We developed a method (Becker-Reshef et al., 2010; Franch et al., 2015), based on remote sensing data, which is is capable of producing wheat yield estimations over the major wheat producing countries up to two months before its harvest.

In a world where climate variability and human-induced climate change threaten global progress towards a food secure future, sustained food production combined with trade and well-functioning markets will play a key role in making the world’s interlinked food systems resilient to climate-related shocks and disruptions.

The climate change community has increasingly focused on the impact of changing precipitation and temperature on agricultural livelihoods of the poorest citizens. Given the complexity of food security and analytical methods used to connect community, agricultural and institutional resources to food security outcomes, indicators that can be compared across nations and continents are increasingly important.

Leveraging the massive expansion of mobile smartphone technology across the world, we seek to put the power of remote satellite monitoring and the convenience of digital note taking into the hands of farmers in Africa, Asia and Europe.