Spatio-temporal analysis and simulation of land cover changes and their impacts on land surface temperature in urban agglomeration of Bisha Watershed, Saudi Arabia

被引：14

作者：

Mallick, Javed ^{[1
]}

Singh, Vijay P. ^{[2
,3
]}

Almesfer, Mohammed K. ^{[4
]}

Talukdar, Swapan ^{[5
]}

Alsubhi, Majed ^{[1
]}

Ahmed, Mohd. ^{[1
]}

Khan, Roohul Abad ^{[1
]}

机构：

[1] King Khalid Univ, Coll Engn, Dept Civil Engn, Abha, Saudi Arabia

[2] Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX USA

[3] Texas A&M Univ, Zachry Dept Civil Engn, College Stn, TX USA

[4] King Khalid Univ, Coll Engn, Dept Chem Engn, Abha, Saudi Arabia

[5] Univ Gour Banga, Dept Geog, Malda, India

来源：

GEOCARTO INTERNATIONAL | 2022年 / 37卷 / 25期

关键词：

Machine learning; support vector machine; CA-ANN; projected LULC; land surface temperature; CELLULAR-AUTOMATA; SATELLITE DATA; CA-MARKOV; GROWTH; DYNAMICS; CLASSIFICATION; MODEL; PREDICTION; SPRAWL; URBANIZATION;

D O I：

10.1080/10106049.2021.1980616

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The present study investigates the spatiotemporal pattern of Land Use land cover (LULC) and land surface temperature (LST) in Abha for the years 1990, 2000, and 2018. This research also forecasts the future LULC and LST for the year 2028. The support vector machine (SVM) was utilised to classify the LULC for the periods 1990-. The LST for the same period was derived using the mono window algorithm. The artificial neural network-cellular automata model (ANN-CA) was employed to forecast LULC and LST for the year 2028. The results indicated that urban areas rose by 434.6% between 1990 and 2018, while the LST soared to 50 degrees C in 2018, covering half of the study area. The built-up area, as well as the high LST zone, will be expanded in 2028. As a result, sustainable management strategies should be implemented to limit uncontrolled urban sprawl and LST.

引用

页码：7591 / 7617

页数：27

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