Crop Monitor for AMIS
The GEOGLAM Crop Monitor  for the Agricultural Market Information System (AMIS) is a monthly bulletin on current growing conditions for the four major crops (wheat, maize,... More detail
Crop Monitor for Early Warning
The Crop Monitor for Early Warning (CM4EW) is a monthly, multi-source consensus bulletin assessing crop conditions in countries at risk for food insecurity, to anticipate... More detail
Rangelands and Pasture Productivity (RAPP)
The GEOGLAM RAPP initiative aims to improve global monitoring of rangelands and pastures, assessing their capacity to sustainably produce animal protein.   ... More detail
Asia Rice Crop Estimation and Monitoring (Asia-RiCE)
The Asia-RiCE initiative aims at improving operational rice crop monitoring and estimation using Earth observations in the Asian region.            ... More detail
Research and Development Towards Operations
The R&D component of GEOGLAM develops monitoring and reporting protocols, tools, and best practices suitable for monitoring the variety of global agricultural systems.... More detail
Earth Observation Data Acquisition and Dissemination Coordination
A close cooperation with Committee on Earth Observation (CEOS) to ensure provision of necessary satellite data for global crop monitoring, in a context of new satellites being... More detail
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National Monitoring Systems

Satellite imagery can provide synoptic information to national monitoring systems such as planted area, soil moisture, crop stage, vigor, or condition.

Scope & Background

Crop production information that is timely, accurate, and objective can inform markets, leading to better commodity allocation and price stabilization in real-time, and can help guide long-term policies such as those affecting trade and the environment. Many countries have some form of a national agricultural monitoring system, which range in robustness from assessing simple generalized field reports to including in-depth statistical probability surveys. They can be administered within-season, through the collection of information on crop condition and related production expectations, or run after harvest to generate finalized statistics. Satellite imagery are known to be able to provide complimentary synoptic information to these already established monitoring systems regarding questions such as planted area, soil moisture, and crop stage, vigor, or condition. As such, our objective is to promote a better integration and utilization of Earth observation assets, in conjunction with field data and market information, to significantly enhance current capabilities for monitoring at national and subnational scales. We intend to

1) identify national needs and priorities for crop monitoring,

2) adapt existing satellite-based monitoring systems into already operational systems,

3) assess next generation tools for the satellite monitoring of agriculture, and

4) strengthen linkages between the national institutes involved.

 

Major Achievements, Partnerships/Linkages, & Future Plans

Exemplary national-level systems engaged in GEOGLAM include: Argentina’s SEPA-Agricultural Production Tracking system which disseminates satellite products useful for making agricultural decisions; European Union’s research projects in Africa (AGRICAB-area estimates, crop modelling) and the European Commission SIGMA Project (similar activities and global networking); China’s Agriculture Remote Sensing Monitoring System (CHARMS), made operational in 1999 serving as a new source of Chinese crop forecasting and grasslands monitoring; and the United States Department of Agriculture (USDA-NASS) where over the last few years remote sensing-based area and yield information has become integrated into the crop production reporting alongside traditional survey information.  

The building and enhancement of national systems is more complex than disseminating products or adopting turnkey solutions. So, our strategy will be multifaceted and include

1) coordinating closely with Component 6 (Capacity Development), to facilitate national-level adoption and enhancements of EO-based methodologies,
2) supporting national systems in their pursuit of funding for prototyping and evaluating EO-based crop condition monitoring systems,
3) gaining sustained national institutional support for satellite monitoring,
4) ensuring data access, quality, and continuity, including regular updating of proposed tools (link to Component 4),
5) obtaining funding for regional coordination and methods/data sharing, and
6) building bridges between the policy and remote sensing communities and better understanding how EO-based information can impact and inform decisions at the national scale.

Leadership (Point of Contact)

  • Carlos Di Bella (INTA - Instituto de Clima y Agua, Argentina) - This email address is being protected from spambots. You need JavaScript enabled to view it.
  • David M. Johnson (USDA – National Agricultural Statistics Service, USA) – This email address is being protected from spambots. You need JavaScript enabled to view it.

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Figure 1. An example of a land cover classification produced operationally by the USDA
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Figure 2. A multi-annual, seasonal NDVI of corn over the US Corn Belt, where red is 2013 and green is 2012.
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Figure 3. USDA-NASS produced estimations of crop yield in over select croplands in the US