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The Role of Earth Observation in Achieving Sustainable Agricultural Production in Arid and Semi-Arid Regions of the World

期刊

REMOTE SENSING
卷 13, 期 17, 页码 -

出版社

MDPI
DOI: 10.3390/rs13173382

关键词

agriculture; arid and semi-arid regions; crop monitoring; remote sensing; crop yield

资金

  1. UK Research and Innovation GCRF [323036/ARCP011217]
  2. Wellcome Trust [211208]

向作者/读者索取更多资源

This study demonstrates the effectiveness of using remote sensing data to monitor agricultural activities in ASA regions and predict crop area and yield in advance. It also discusses the challenges associated with ensuring food security in ASA regions and recent advances in remote sensing technology that can be used for monitoring cropland and forecasting crop production and yield.
Crop production is a major source of food and livelihood for many people in arid and semi-arid (ASA) regions across the world. However, due to irregular climatic events, ASA regions are affected commonly by frequent droughts that can impact food production. In addition, ASA regions in the Middle East and Africa are often characterised by political instability, which can increase population vulnerability to hunger and ill health. Remote sensing (RS) provides a platform to improve the spatial prediction of crop production and food availability, with the potential to positively impact populations. This paper, firstly, describes some of the important characteristics of agriculture in ASA regions that require monitoring to improve their management. Secondly, it demonstrates how freely available RS data can support decision-making through a cost-effective monitoring system that complements traditional approaches for collecting agricultural data. Thirdly, it illustrates the challenges of employing freely available RS data for mapping and monitoring crop area, crop status and forecasting crop yield in these regions. Finally, existing approaches used in these applications are evaluated, and the challenges associated with their use and possible future improvements are discussed. We demonstrate that agricultural activities can be monitored effectively and both crop area and crop yield can be predicted in advance using RS data. We also discuss the future challenges associated with maintaining food security in ASA regions and explore some recent advances in RS that can be used to monitor cropland and forecast crop production and yield.

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