Title of article :
Drought Monitoring and Corn Yield Estimation in Southern Africa from AVHRR Data
Author/Authors :
L. Unganai، نويسنده , , Leonard S and Kogan، نويسنده , , Felix N، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 1998
Pages :
14
From page :
219
To page :
232
Abstract :
Drought is one of the major environmental disasters in southern Africa. In recent years, the damage from droughts to the environment and economies of some countries was extensive, and the death toll of livestock and wildlife was unprecedented. Weather data often come from a very sparse meteorological network, incomplete and/or not always available in good time to enable relatively accurate and timely large scale drought detection and monitoring. Therefore, data obtained from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board the NOAA polar-orbiting satellites have been studied as a tool for drought monitoring and climate impact assessment in southern Africa. The AVHRR-based vegetation condition index (VCI) and temperature condition index (TCI) developed recently were used in this study because in other parts of the globe they showed good results when used for drought detection and tracking, monitoring excessive soil wetness, assessment of weather impacts on vegetation, and evaluation of vegetation health and productivity. The results clearly show that temporal and spatial characteristics of drought in southern Africa can be detected, tracked, and mapped by the VCI and TCI indices. These results were numerically validated by in situ data such as precipitation, atmospheric anomaly fields, and agricultural crop yield. In the later case, it was found that usable corn yield scenarios can be constructed from the VCI and TCI at approximately 6 (in some regions up to 13) weeks prior to harvest time. These indices can be especially beneficial when used together with ground data.
Journal title :
Remote Sensing of Environment
Serial Year :
1998
Journal title :
Remote Sensing of Environment
Record number :
1572551
Link To Document :
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