Identification of time-varying wetlands neglected in Pakistan through remote sensing techniques

• Published in: Environmental science and pollution research international 2023-06, Vol.30 (29), p.74031-74044
• Main Authors: Aslam, Rana Waqar, Shu, Hong, Yaseen, Andaleeb, Sajjad, Asif, Abidin, Syed Zain Ul
• Format: Article
• Language: English
• Subjects: Aquatic ecosystems; Aquatic Pollution; Artificial neural networks; Atmospheric Protection/Air Quality Control/Air Pollution; Change detection; Climate change; Developing countries; Earth and Environmental Science; Economic conditions; Ecosystem dynamics; Ecotoxicology; Environment; Environmental changes; Environmental Chemistry; Environmental Health; Environmental science; Hydrologic cycle; Hydrology; Image resolution; Lakes; Land surface temperature; LDCs; Moisture content; Neural networks; Quality assessment; Rainfall; Remote sensing; Research Article; Satellite imagery; Satellite technology; Turbidity; Waste Water Technology; Water content; Water Management; Water Pollution Control; Water quality; Water quality assessments; Wetlands
• ISSN: 1614-7499; 0944-1344; 1614-7499
• DOI: 10.1007/s11356-023-27554-5

Aside from Ramsar Convention awareness programs, the concept of wetlands is mostly ignored in developing countries. Wetland ecosystems are essential to hydrological cycles, ecosystem diversity, climatic change, and economic activity. Under the Ramsar Convention, there are 2414 wetlands that are internationally recognized, and Pakistan is home to 19 of them. The major goal of this study is to use the satellite image technology to locate Pakistan’s underutilized wetlands (Borith, Phander, Upper Kachura, Satpara, and Rama Lakes). The other goals are to understand how these wetlands are affected by climate change, ecosystem change, and water quality. We used analytical techniques including supervised classification and Tasseled Cap Wetness to identify the wetlands. To find changes caused by climate change, Quick Bird high-resolution images was used to create the change detection index. Tasseled Cap Greenness and the Normalized Difference Turbidity Index were also used to assess the water quality and changes in the ecology in these wetlands. Sentinel-2 was used to analyze data from 2010 and 2020. ASTER DEM was also used to do a watershed analysis. The land surface temperature (°C) of a few selected wetlands was calculated using Modis data. Rainfall (mm) data was taken from PERSIANN (precipitation estimation from remotely sensed information using artificial neural networks) databases. Results indicated that in 2010, the water content of Borith, Phander, Upper Kachura, Satpara, and Rama Lakes was 22.83%, 20.82%, 22.26%, 24.40%, and 22.91%. While in 2020, these lakes’ water ratios are 21.33%, 20.65%, 21.76%, 23.85%, and 22.59%, respectively. Therefore, the competent authorities must take precautions to ensure that these wetlands are preserved in the future in order to improve the dynamics of the ecosystem.