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No Thumbnail AvailableBook (stand-alone)Irrigation scheduling: From theory to practice. Proceedings 1996
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BookletGeospatial cropland monitoring and crop type mapping of the Gezira irrigation scheme in the Sudan
2019/20-2023/24 (September to March)
2024Also available in:
No results found.Sudan is facing an increasing risk of severe food insecurity due to the ongoing conflict that began in April 2023, which has significantly impacted the agricultural sector. Irrigated farming is vital to Sudan's agricultural system, and the Gezira project stands as the largest and most important irrigation scheme. Recognizing the critical role of the Gezira irrigation scheme in Sudan’s agriculture and food security sector, this report presents an assessment of changes in cultivated cropland areas within the scheme. The analysis focuses on the growing cycle of dominant crops from September to March over the period from 2019/20 to 2023/24. By monitoring the extent of cropland for three major crops—wheat, sorghum, and cotton—this analysis reveals trends and shifts in crop cultivation and productivity, with a particular focus on wheat production.Utilizing remote sensing data from Sentinel-2 satellite imagery, an innovative methodology was developed to address challenges in data collection in conflict-affected areas. Time-series analyses of vegetation indices and crop calendars throughout different periods of the crop growth cycle were employed to classify crop types and monitor crop rotation. Very high-resolution imagery was specifically used for verification purposes to ensure accuracy.The analysis revealed a reduction in the cultivated area and a shift from wheat to sorghum cultivation. Alongside a sharp decline in wheat yield, overall crop production is expected to exacerbate food insecurity levels throughout Sudan. This situation highlights the urgent need for integrated strategies to enhance agricultural resilience and food security under these challenging conditions. -
Book (stand-alone)WaPOR Database methodology: Level 3 data
Using remote sensing in support of solutions to reduce agricultural water productivity gaps
2019Also available in:
No results found.This documents describes the methodology applied for producing the WaPOR database at sub-national level (Level 3, 30 m resolution). WaPOR is the FAO portal to monitor Water Productivity through Open access of Remotely sensed derived data, and it monitors and reports on agriculture water productivity over Africa and the Near East through a dedicated online portal: http://www.fao.org/in-action/remote-sensing-for-water-productivity/wapor/en/ The aim of this document is to provide the theory that underlies the methods used to produce the different data components published through WaPOR. This document complements the methodology behind Level 1 and 2 data, published in September and October 2018 respectively, with Level 3 methodology.
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