Please use this identifier to cite or link to this item:
https://idr.nitk.ac.in/jspui/handle/123456789/7380Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Pathak, A.A. | |
| dc.contributor.author | Dodamani, B.M. | |
| dc.date.accessioned | 2020-03-30T09:58:58Z | - |
| dc.date.available | 2020-03-30T09:58:58Z | - |
| dc.date.issued | 2019 | |
| dc.identifier.citation | Proceedings of SPIE - The International Society for Optical Engineering, 2019, Vol.11156, , pp.- | en_US |
| dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/7380 | - |
| dc.description.abstract | The present study aims to assess agricultural drought using remote sensing based NDVI and soil moisture products in a drought prone river basin of India. The study is conducted in the Ghataprabha river basin which is a sub basin of river Krishna, in India and is agriculturally dominated. Major portion of the basin is semiarid and rainfall is the major sources of water for agriculture. Gridded soil moisture data from Modern-Era Retrospective analysis for Research and Applications (MERRA) from 1980 to 2015 is considered to derive Standardized Soil moisture Index (SSI) at different time scales. The Vegetation Condition Index (VCI) was calculated from MODIS NDVI products from 2000-2013. The results of VCI and SSI indicated significant number of drought episodes during the study period while severe agricultural drought was observed during 2001-2003. A Good agreement between SSI and VCI was observed during drought year. � 2019 SPIE. | en_US |
| dc.title | Application of remotely sensed NDVI and soil moisture to monitor long-term agricultural drought | en_US |
| dc.type | Book chapter | en_US |
| Appears in Collections: | 2. Conference Papers | |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.