المملكة العربية السعودية

الجمعية الجغرافية السعودية

المجلة العربية لنظم المعلومات الجغرافية

Spatio-temporal Land Cover Changes Monitoring using Remotely Sensed Techniques in Hail Region, KSA

عدد المشاهدات 77 

Dr. Wafa Saleh Alkhuraiji *

Vol. (14), No. (2), 1442 / 2021

p.p. 1– 18 

Abstract

     Hail region is located to the northwest of Saudi Arabia. It represents a promising area for agricultural activity due to their land suitability and availability of ground water. The main objective of this study was to monitor changes of land cover in Hail region based on remote sensing data. Accordingly, Landsat images were acquired at three different periods of time (1984, 2002 and 2019) to study these changes in land cover. These images were manipulated and analyzed. The soil adjusted vegetation index (SAVI) was also used to principally evaluate vegetation in this low vegetated area. Also, the maximum likelihood image classification method was used to study land covers and their changes during these three periods of time.     Hail region was classified into four land covers (sand dunes, agriculture, plains and mountains). The agricultural area was high accurately classified using the SAVI when compared with the maximum likelihood classification method. This area was significantly increased over time from 1984 to 2019; however the highest increase was obvious during the last two decades (from 2002 to 2019).  It was about 56.53, 326.73 and 813.67 km2 in 1984, 2002 and 2019, respectively. In general, agricultural area was less than 1% of the total region area. Sand dunes were the dominant land cover in the northern parts of Hail region. These areas were also increased over time from 42.23% in 1984 to 45.66% in 2019. This indicates sand dunes encroachment over the nearby area. In conclusion, Hail region represents a promising area for many activities such as agriculture, tourism and mining. However, soil productivity and suitability, ground water quality and quantity, and sand dunes encroachment need to be studied in details.

Keywords: Remote sensing, land cover, SAVI, Maximum likelihood method, Hail region.

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* Geography Department, Princess Noura bint Abdul Rahman University, Riyadh, Saudi Arabia

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