Volume 6, Issue 23 (Volume 6; Number 23; Spring 2016)                   2016, 6(23): 50-63 | Back to browse issues page

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Damavandi A A, Rahimi M, Yazdani M R, Noroozi A A. Spatial Monitoring of Agriculture Drought Using Vegetation Temperature Condition Index (VTCI) from Terra/MODIS Satellite Data-case study: Markazi Province. Arid Regions Geographic Studies. 2016; 6 (23) :50-63
URL: http://journals.hsu.ac.ir/jarhs/article-1-883-en.html
Semnan university , mrahimi@profs.semnan.ac.ir@gmail.com
Abstract:   (8405 Views)

Drought is one of the natural disasters which cause economic damages especially in agriculture and natural resources sections. Because of creeper nature of drought, its assessment and monitoring is very complex and difficult. Using of drought indices is one of the most important methods in drought monitoring and evaluation. Because of suitable capabilities of remote sensing technology and its good spatial and temporal resolutions which compensate of meteorological point methods, using of satellite indices approach are developing and progressing. One of the best these indices is Vegetation Temperature Condition Index (VTCI) which constituted basis of simultaneous of NDVI and LST. For spatial monitoring of agricultural drought with VTCI in this research, NDVI and LST products of MODIS sensor of Terra satellite for July of 2000 to 2014 retrieved and after preprocessing prepared for making of VTCI. Main challenge of using this method is determination of warm and cold edges in LST and NDVI scattergram .Based up results of this research, year of 2006 had best regression coefficient (R2=0.73 for warm edge and R2=0.86 for cold edge). In continue based of regression coefficient of each year, their VTCI extracted and map of VTCI drought classes to five classes (High, Medium, Light, Normal and Wet) constituted. Results showed significant relations between VTCI and LST, NDVI and LST/NDVI indices finally, these agriculture drought classes compared from their area in length of study period. Results showed that highest and lowest drought class belonged to medium, light (more than 84%) and wet(less than 1%) classes, respectively. Also years of 2013 and 2011 had most area percent of high drought and wet classes.

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Type of Study: Research | Subject: gis و سنجش از دور
Received: 16/Oct/15 | Accepted: 16/Apr/16 | Published: 11/Nov/16

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