Wetland identification through remote sensing: Insights into wetness, greenness, turbidity, temperature, and changing landscapes

被引:69
作者
Aslam, Rana Waqar [1 ]
Shu, Hong [1 ]
Javid, Kanwal [2 ]
Pervaiz, Shazia [3 ]
Mustafa, Farhan [4 ,5 ]
Raza, Danish [1 ]
Ahmed, Bilal [6 ]
Quddoos, Abdul [1 ]
Al-Ahmadi, Saad [7 ]
Hatamleh, Wesam Atef [7 ]
机构
[1] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & Re, Wuhan 430079, Peoples R China
[2] Govt Coll Univ, Dept Geog, Lahore 54000, Pakistan
[3] Environm Protect Agcy, Lahore, Punjab, Pakistan
[4] Hong Kong Univ Sci & Technol HKUST, Jiangmen Lab Carbon Sci & Technol, Jiangmen 529199, Guangdong, Peoples R China
[5] Guangzhou HKUST Fok Ying Tung Res Inst FYTRI, Guangzhou 511458, Peoples R China
[6] Silesian Tech Univ, Fac Civil Engn, Doctoral Sch, Dept Struct Engn, Akad 2,Akad St 5, PL-44100 Gliwice, Poland
[7] King Saud Univ, Coll Comp & Informat Sci, Dept Comp Sci, POB 51178, Riyadh 11543, Saudi Arabia
关键词
Climate Change; Biodiversity; Ramsar Convention on Wetland; Sentinel-2; Remote Sensing; PARAMETERS; TOLERANCE; ATTENTION; ECOSYSTEM; PROVINCE; CROPS; YIELD; BASIN;
D O I
10.1016/j.bdr.2023.100416
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Wetlands are important in many ways, including hydrological cycles, ecosystem diversity, climate change, and economic activity. Despite the Ramsar Convention's awareness programmes, the importance of wetlands is frequently disregarded in underdeveloped countries. The Ramsar Convention recognises 2491 wetlands world-wide, 19 of which are in Pakistan. The goal of this study is to use satellite sensor technology to identify neglected wetlands in Pakistan. The key goals of this research are to analyse water quality, monitor ecological changes, and comprehend the impact of climate change on the aforementioned wetlands. We used approaches like supervised classification and TCW to identify wetlands. To detect climate-induced changes, a change detection index was used to Quick Bird imagery. TCG and the NDTI were also employed to examine the water quality and ecological changes in these wetlands. Sentinel-2 data between 2016 and 2019 were used in the analysis. Furthermore, watershed analysis was carried out using ASTER DEM data. Modis data was used to calculate the LST (degrees C) of the selected wetlands, while rainfall (mm) data was collected from ANN databases. According to the study's findings, in 2016, Borith, Phander, Upper Kachura, Satpara, and Rama Lake held 22.73%, 20.79%, 23.01%, 24.63%, and 23.03% water, respectively. In 2019, the water ratios for these lakes were 23.40%, 22.10%, 22.43%, 25.01%, and 24.56%. These findings emphasise the need of taking preventative actions to protect these wetlands in order to improve ecosystem dynamics in the future. As a result, it is critical that the relevant authorities implement the necessary conservation measures.
引用
收藏
页数:16
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