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

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.

Scope & Background

The implementation of any operational monitoring system is built upon a foundation of research and development. Further, operational systems could benefit from ongoing improvements based on emerging research and ever-improving and changing satellite data streams and in situ data networks. Consequently, research and development must remain at the core of the operational system throughout and beyond implementation. This is particularly evident as the GEOGLAM community helps develop a global system of systems for agricultural monitoring, building on decades of R&D, while looking forward to new opportunities offered by significant advances in open data access and computing technology.

In the context of GEOGLAM, the overarching goal of the R&D component is to reach a convergence of approaches and to develop monitoring and reporting protocols, tools, and best practices suitable for monitoring a variety of global agricultural systems. The R&D component enables the global agricultural monitoring community to compare results based on disparate sources of data, using various methods, over a variety of global cropping systems. Ultimately the objective is to provide proven operational solutions to the GEOGLAM community and to constantly improve them along with the new satellite missions, IT, social network advances, and expanding open data policies.


GEOGLAM R&D is made of a number of initiatives working together in a coordinated fashion to address key needs. So far these initiatives include:

  • Joint Experiments for Crop Assessment and Monitoring (JECAM). JECAM, established in 2009, is a network of over 30 research sites globally distributed looking at key research questions around crop area, type, and condition.
  • SIGMA, as part of Europe’s contribution to GEOGLAM, financed through the EC’s Research Framework programme (FP7). Its aim is to develop innovative methods and indicators to monitor and assess progress towards sustainable agriculture, focused on the assessment of longer term impact of agricultural dynamics on the environment and vice versa.
  • Sen2Agri is another European contribution to the GEOGLAM R&D component supported by the European Space Agency (ESA) to prepare for the operational exploitation of the Sentinel-2 mission for agriculture monitoring.
  • The Asia-RiCE team, as a part of the Asian regional contribution to GEOGLAM led by JAXA, actively networks with agriculture and space expert organizations in Asia in a common effort to enhance current remote sensing-based agricultural monitoring techniques.
  • The AgriSense –STARS project funded by the Bill and Melinda Gates Foundation is undertaking research to develop and test methods to improve agricultural monitoring in sub-saharan Africa to the benefit of smallholder farmers.
  • NASA, ESA and the USGS have recently embarked on a coordinated research initiative for multi-use of satellite data from different sources e.g. US Landsat and Sentinel 2/Sentinel 1.

Major Achievements:

Interactions between CEOS and Agriculture Community of Practice (link to Component 4)

  • Development of satellite information requirements for operational agriculture monitoring systems to address the global diversity of agro-ecosystems
  • Development of mechanisms to order satellite time series over the JECAM site network and to report to CEOS about the scientific use of the data (annual reports, and science meetings)
  • Preparation of a multi-license data form to facilitate sharing of restricted datasets throughout the JECAM network
  • Set up and coordinate data acquisitions with CEOS and commercial data providers (DEIMOS, FenYung, Radarsat-2, Pleiades, SPOT 5, RapidEye, Sentinel-1&2…)

Development of Standards & Best Practices for Cropland & Agricultural Productivity Assessments

  • Development of a common cropland definition (endorsed by JECAM community) and framed in the context of the LCML standards (UN FAO) through SIGMA
  • Development of guidelines for fieldwork and definition of the minimum EO dataset for crop monitoring (endorsed by JECAM community)
  • Development of guidelines for field survey to validate rice crop monitoring by Asia Rice team
  • Rice crop land mapping, rice crop area estimation method using SAR and crop calendar for Asia by Asia-RiCE team with IRRI
  • Inter-comparison of existing crop land maps, resulting in the development and release of a “best-available” harmonized product, with first results for Africa
  • Identification of priority areas for cropland mapping
  • Produced country needs report on agricultural statistics capacity
  • Peer-reviewed publications on algorithm benchmarking across JECAM sites (Sen2Agri, SIGMA)
  • Developed soil moisture, evapotranspiration, and high resolution datasets time series
  • Prototyped satellite-based yield assessment (Argentina, China, Ukraine, US)

Future Challenges:

  • Bridging between the Remote sensing and Agromet Crop monitoring community
  • Combined used of Optical and Radar imagery
  • Sharing near real-time data processing streams capitalizing on state-of-the-art methods to support operational crop monitoring and Processing massive EO datasets (high resolution time series and archive) using cloud computing and open data / crowd sourcing information
  • Development of robust methods for area estimates or area change indicators
  • Extraction of crop specific biophysical variable and operational use in crop models and monitoring systems

Leadership (Point of Contact)

  • Ian Jarvis (AAFC, Canada); This email address is being protected from spambots. You need JavaScript enabled to view it. and,
  • Pierre Defourny (UCL, Belgium); This email address is being protected from spambots. You need JavaScript enabled to view it.

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Figure 1. Map of JECAM sites
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Figure 2. Cropland Mapping Priority Areas, produced in the context of the SIGMA project.
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Figure 3. Cropland proportion from the SIGMA Unified Cropland Layer at 250-m for the year 2014.