Detecting and Assessing the Spatio-Temporal Land Use Land Cover Changes of Bahrain Island During 1986-2020 Using Remote Sensing and GIS

被引:18
|
作者
Aljenaid, Sabah S. [1 ]
Kadhem, Ghadeer R. [1 ]
AlKhuzaei, Manaf F. [2 ]
Alam, Jobair B. [3 ]
机构
[1] Arabian Gulf Univ, Coll Postgrad Studies, Dept Geoinformat, POB 2766, Manama, Bahrain
[2] Univ Brighton, Sch Environm & Technol, Brighton, E Sussex, England
[3] IMS Engineers, Houston, TX USA
关键词
Remote sensing; GIS; Land use land cover; Change detection; Chord diagrams; Bahrain; USE/COVER CLASSIFICATION; SENSED IMAGERY; AUXILIARY DATA; ACCURACY; EXTRACTION; LANDSCAPE; AREA; TM; SEGMENTATION; INTEGRATION;
D O I
10.1007/s41748-022-00315-z
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Kingdom of Bahrain has experienced accelerated development growth since the 1980s. These rapid land demands increased the pressure on the country area to rebuild urban centers and cities surrounding the coast. The purpose of this research is to detect and investigate changes in land use and land cover (LULC), which is one of the most critical aspects of planning and managing the use of land as a natural resource. The massive growth in land demand, particularly in small-area countries like Bahrain, forces decision-makers to re-plan the main island areas (Bahrain, Muharraq, Sitra, and Nabih Saleh). The study focuses on mapping the LULC changes detection over 1986-2020. It employs an integrated approach of remote sensing and GIS (Geographic Information System) to analyze and evaluate the changes in the LULC area in the main islands using multi-temporal and multispectral Landsat satellite imagery acquired in 1986, 1994, 2000, 2005, 2013, and 2020. In addition, high-resolution satellite images of different dates IKONOS 2000, GeoEye1 2011, 2013, Worldview3 2019, ASTER 2012, 2013, and multiresolution seamless image database-MrSID 1994, 1998 were used to enhance the LULC classification. Furthermore, different ancillary data were utilized to adjust the decision of LULC classes. The images were supervised using Maximum Likelihood Classifier (MLC) algorithms to generate the seven LULC maps. The seven-raster classification maps revealed overall accuracies exceeding 85%, and overall Kappa statistics range between 87 and 95%. The results indicate that the increment in the built-up area was dominant over the last 3 decades.
引用
收藏
页码:787 / 802
页数:16
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