Asia-Rice Crop Estimation & Monitoring (Asia-RiCE) component for the GEO Global Agricultural Monitoring (GEOGLAM) initiative. it aims to:

    • To ensure that Asian countries receive the full potential benefits of GEOGLAM, and that they are suitably engaged and prepared to do so;
    • To ensure that rice crop monitoring issues are given suitable priority and attention within the scope of the full GEOGLAM initiative, including in the development of the observing requirements; and
    • To establish a framework for the coordination necessary to engage, manage and support the various stakeholders.
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Horizon2020: ECoLaSS

The Horizon2020 project, “Evolution of Copernicus Land Services based on Sentinel data” (ECoLaSS) aims at developing innovative methods, algorithms and prototypes to improve and invent future pre-operational Copernicus Land services from 2020 onwards, for the pan-European and Global Components. ECoLaSS will make full use of dense Sentinel time series of optical (S-2, S-3) and Synthetic Aperture Radar (SAR) data (S-1). These prototypes shall be suggested to EC and the relevant decision-makers for qualifying as candidates for operational integration into the future Copernicus Land Monitoring Service from 2020 onwards. Rapidly evolving scientific as well as user requirements will be analyzed in support of a future pan-European roll-out of new/improved Copernicus Land Monitoring services, and the transfer to global applications.


The overall duration of the project will be 36 months (Jan 2017 – Dec 2019), with two development cycles of 18 months each. Service requirements assessment will be performed involving the main Copernicus Land stakeholders and users, and will thus steer methodological developments, such as: (i) Sentinel-1/-2/-3 time series integration, (ii) time series pre-processing methods, (iii) thematic classification and (iv) change detection from time series analysis, and (v) the development of an incremental update methodology for the Copernicus Land High Resolution Layers (HRLs). These methods will be applied on test sites, located both in Europe and Africa, prior to a prototyping phase. Larger demonstration sites representing various bio-geographic regions were selected to implement the following innovative prototypes: (i) indicators and variables from high spatial and temporal resolution data, for both the Continental and Global Component products; (ii) incremental update strategies for the main pan-European products (i.e. the HRLs); (iii) improved permanent grassland identification; (iv) crop area and crop status/parameters monitoring; (v) further novel LC/LU products.


Finally, the main target to assess/benchmark all operational products in view of their innovation potential and technical excellence will be performed, leading to a strategy for an operationalization framework for a future pan-European roll-out of improved or newly developed Copernicus Land Monitoring services. It is expected that such new services will provide a variety of inter-linkages with other LC/LU projects, and bring new opportunities for a wide range of dedicated applications to the market from 2020 onwards.

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Horizon2020: Sensagri

  • H2020 SENSAGRI (2016-2019) is developing and validating three prototypes for Copernicus Pan-European Land core services, for agricultural applications
  • Surface soil moisture (SSM), green and brown LAI and seasonal crop type mapping prototypes are based in the combined use of Sentinel-1 and Sentinel-2
  • Four proof-of-concept for agricultural monitoring services are also being developed and validated: Regional-national detailed crop maps, tillage change detection, actual irrigation and yield estimation
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SAR Inter-Comparison

Welcome to the Synthetic Aperture Radar (SAR) Inter-Comparison Experiment page. Here you will find up-to-date details regarding the project including the Project Plan, Journal Articles, Webinar Videos, and much more! Check back frequently for all the latest news and highlights of the Experiment.

Field Protocol Documents

Ground Measurement Guideline for LAI  & Biomass

CAN-EYE User Manual

CAN-EYE Output Variables

BBCH Staging Manual

Guidelines for Cropland and Crop Type Definition and Field Data 

Project Plan & Participation Form

Project Plan

Participation Form

Journal Article Links

Estimation of Leaf Area Index (LAI) in corn and soybeans using multi-polarization C- and L-band radar data.

Using multi-polarization C- and L-band synthetic aperture radar to estimate biomass and soil moisture of wheat fields.

Integration of optical and Synthetic Aperture Radar (SAR) imagery for delivery operational annual crop inventories.

A bootstrap method for assessing classification accuracy and confidence for agricultural land use mapping in Canada.

Annual space-based crop inventory for Canada: 2009-2014.

Data Policy & Authorship Guidelines

Data Policy

Authorship Guideline

Author List (Coming Soon)


July 2017

August 2017

September 2017

October 2017

November 2017

December 2017

January 2018

February 2018

March 2018

April/May 2018

June/July 2018

August/September 2018

October/November 2018

December 2018

January/February 2019

Summer 2019

Webinar Videos

Click this link to view the webinar slides!

Click this link to view recorded webinar!

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Sentinel-2 for Agriculture (Sen2-Agri) project has been launched by ESA, as a major contribution to the R&D and national capacity building components of the GEOGLAM initiative and to the JECAM network activities.

The Sen2-Agri project is designed to develop, demonstrate and facilitate the Sentinel-2 time series contribution to the satellite EO component of agriculture monitoring. The project will demonstrate the benefit of the Sentinel-2 mission for the agriculture domain across a range of crops and agricultural practices.

The project objectives are to provide validated algorithms, open source code and best practices to process Sentinel-2 data in an operational manner for major worldwide representative agriculture systems distributed all over the world.

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SIGMA is part of Europe’s contribution to GEOGLAM, actively networking expert organizations world-wide, in a common effort to enhance current remote sensing based agricultural monitoring techniques. 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.

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STARS is a research project which is looking for ways to use remote sensing technology to improve agricultural practices in Sub-Saharan Africa and South Asia. Supported by the Bill & Melinda Gates Foundation, the project hopes to significantly advance the livelihoods of smallholder farmers in some of the world’s poorest countries.

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