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Journal of Arid Land  2017, Vol. 9 Issue (3): 319-330    DOI: 10.1007/s40333-017-0014-6
Orginal Article     
A remote sensing-based agricultural drought indicator and its implementation over a semi-arid region, Jordan
HAZAYMEH Khaled1,2, K HASSAN Quazi1,*
1 Department of Geomatics Engineering, Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada
2 Department of Geography, Faculty of Arts, Yarmouk University, Irbid 21163, Jordan
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The objective of the study was to develop a remote sensing (i.e., Landsat-8 and MODIS)-based agricultural drought indicator (ADI) at 30-m spatial resolution and 8-day temporal resolution and also to evaluate its performance over a heterogeneous agriculture dominant semi-arid region in Jordan. Firstly, we used principal component analysis (PCA) to evaluate the correlations among six commonly used remote sensing-derived agricultural drought related variables. The variables included normalized difference water index (NDWI), normalized difference vegetation index (NDVI), visible and shortwave drought index (VSDI), normalized multiband drought index (NMDI), moisture stress index (MSI), and land surface temperature (LST). Secondly, we integrated the relatively less correlated variables (that were found to be NDWI, VSDI, and LST) to generate four agricultural drought categories/conditions (i.e., wet, mild drought, moderate drought, and severe drought). Finally, we evaluated the ADI maps against a set of 8-day ground-based standardized precipitation index values (i.e., SPI-1, SPI-2, …, SPI-8) by use of confusion matrices and observed the best results for SPI-4 (i.e., overall accuracy and Kappa-values were 83% and 76%, respectively) and SPI-5 (i.e., overall accuracy and Kappa-values were 85% and 78%, respectively). The results demonstrated that the method would be valuable for monitoring agricultural drought conditions in semi-arid regions at both a reasonably high spatial resolution (i.e., 30-m) and a short time period (i.e., 8-day).

Key wordsspatio-temporal image fusion model (STI-FM)      land surface temperature (LST)      surface reflectance      standardized precipitation index (SPI)      Landsat-8      MODIS     
Received: 02 July 2016      Published: 10 May 2017
Corresponding Authors: K HASSAN Quazi   
Cite this article:

HAZAYMEH Khaled, K HASSAN Quazi. A remote sensing-based agricultural drought indicator and its implementation over a semi-arid region, Jordan. Journal of Arid Land, 2017, 9(3): 319-330.

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