In the Near East and Northern Arica (NENA) region, the monitoring of croplands is imperative for estimating crop water productivity, drought management and estimating water consumption. Reliable data on accurate crop area and extent are not available and are affected by serious discontinuities across the countries.

Updated and reliable seasonal crop map are needed to analyze and increase trusts in the results of the models and methodologies applied to determine the water accounting, estimate the crop water productivity and assess the water sustainability.

An important contribution by the project to the countries will be the adoption of advances in space technology (satellite Remote Sensing) particularly for the determination of water consumption (ET) and crop mapping. Crop mapping at 10 to 30 m resolution will enable to analyze results of models and remote sensing based information along with ground validation technique to support water accounting and the determination of crop (biomass and yield) water productivity.

Approach adopted (based on Wapor approach with the use of ODK collect for field level data collection)

Activity: Build capacity at country level to create crop maps using remote sensing and use them for verification and analysis of models and methodologies, including the Wapor database to assess ET and water productivity.

The target group: qualified staff and agricultural engineers with a deep knowledge of the main crops cultivated in the country and with basic knowledge of remote sensing and geographic information system (GIS).

A long training was designed in a pilot country (Tunisia) and then regionalized with 8 countries with the objective of reinforcing staff capacities on crop mapping to be able to autonomously produce consistent and unbiased estimates of agricultural cropland areas, crop types, crop watering method, at high resolutions, using multi-sensor, multi-date remote sensing and mature cropland mapping algorithms (CMAs).

The training was implemented as a long training over a period of 6 months. The full course was made of 5 blocks and was designed and developed to ensure that the training form a consistent training package, building up from basic to more advanced remote sensing knowledge and skills needed for the production of land cover classifications.

The full training course was designed and developed in close collaboration with IHE Delft, Nieuwland and eLEAF and built on the methodologies developed for the WaPOR project.

The training aimed to be practical – each country worked on a site in their country and did extensive data collection to validate the results and increase the accuracy of the crop maps. The field guide used is the FRAME methodology and an open source tools such as ODK collect (field validation) and QGIS/GEE for image classification.

Details on the crop mapping activities at country level are available at the Country pages.

This activity supports the analysis of results available: