Spatio-temporal assessment and prediction of wetlands: Examining the changes in ecosystem service value of RAJUK DAP area using Artificial Neural Network and Geospatial Techniques

被引:0
|
作者
Khan, Mohd Fardeen [1 ]
Islam, Md Kamrul [1 ]
Chowdhury, Md Arif [2 ]
机构
[1] Chittagong Univ Engn & Technol, Dept Urban & Reg Planning, Chittagong 4349, Bangladesh
[2] Jashore Univ Sci & Technol, Dept Climate & Disaster Management, Jashore 7408, Bangladesh
关键词
Ecosystem service; Spatio-temporal assessment; Wetlands; Artificial Neural Network; RAJUK DAP; URBANIZATION; MODELS;
D O I
10.1016/j.heliyon.2024.e34327
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Wetlands are a crucial component of the earth's socio-ecological structure, providing significant ecosystem services to people. Changes in wetlands, driven by both natural and manmade causes, are altering these ecosystem services. Although Bangladesh is developing, natural resources like wetlands are changing in the country at different scales, with urban areas experiencing significant impacts. This study intends to evaluate the past, present, and future scenarios of wetlands and examine the changes in ecosystem service value (ESV) of the RAJUK (Rajdhani Unnayan Kartripakkha or Capital Development Authority) Detailed Area Plan (DAP) region. This research examined the effects of five different Land Use and Land Cover (LULC) classes on ESVs for 27 years from 1995 to 2022. Findings reveal that the current wetland area is 80.16 km2 2 in the post- monsoon season and 306.67 km2 2 in the pre-monsoon season. Composite post-monsoon wetland map from 1995 to 2015 that 19.48 km2 2 of wetlands are classified as hydro-ecologically consistent wetlands. Wetland area has decreased by 140.926 km2 2 between 1995 and 2022, according to simulations, and is predicted to do so by another 27.11 km2 2 during the following eight years. The total ESV of wetlands dropped by about 26.72 percent between 1995 and 2022, primarily due to conversion to habitation and agricultural use. Also, the projection of LULC and associated ESV for the year 2030 demonstrates how ESV evolves throughout this period and which LULC classes are more susceptible to change, while the kappa coefficient was used to compare the simulated models to the actual wetland area. The current study will undoubtedly be helpful to decision- makers who make a substantial contribution to preserving ecosystem services and the wetland landscape.
引用
收藏
页数:16
相关论文
共 8 条
  • [1] Spatio-temporal Dynamics of Land Use Land Cover Changes and Future Prediction Using Geospatial Techniques
    Alka Abraham
    Subrahmanya Kundapura
    [J]. Journal of the Indian Society of Remote Sensing, 2022, 50 : 2175 - 2191
  • [2] Spatio-temporal Dynamics of Land Use Land Cover Changes and Future Prediction Using Geospatial Techniques
    Abraham, Alka
    Kundapura, Subrahmanya
    [J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2022, 50 (11) : 2175 - 2191
  • [3] Spatio-Temporal Changes in Forest Area and Its Ecosystem Service Value in Ganzi Prefecture, China, in the Period 1997-2017
    Wang, Yanru
    Li, Qingquan
    Geng, Jijin
    Bie, Xiaojuan
    Peng, Peihao
    Wu, Guofeng
    [J]. FORESTS, 2023, 14 (09):
  • [4] Spatio-temporal prediction of suspended sediment concentration in the coastal zone using an artificial neural network and a numerical model
    Bhattacharya, B.
    van Kessel, T.
    Solomatine, D. P.
    [J]. JOURNAL OF HYDROINFORMATICS, 2012, 14 (03) : 574 - 584
  • [5] Assessment of Ecosystem Service Value in Response to LULC Changes Using Geospatial Techniques: A Case Study in the Merbil Wetland of the Brahmaputra Valley, Assam, India
    Lahon, Durlov
    Sahariah, Dhrubajyoti
    Debnath, Jatan
    Nath, Nityaranjan
    Meraj, Gowhar
    Kumar, Pankaj
    Hashimoto, Shizuka
    Farooq, Majid
    [J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2023, 12 (04)
  • [6] Spatio-temporal prediction of leaf area index of rubber plantation using HJ-1A/1B CCD images and recurrent neural network
    Chen, Bangqian
    Wu, Zhixiang
    Wang, Jikun
    Dong, Jinwei
    Guan, Liming
    Chen, Junming
    Yang, Kai
    Xie, Guishui
    [J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2015, 102 : 148 - 160
  • [7] Prediction of spatio-temporal (2030 and 2050) land-use and land-cover changes in Koch Bihar urban agglomeration (West Bengal), India, using artificial neural network-based Markov chain model
    Debnath, Manoj
    Islam, Nazrul
    Gayen, Shasanka Kumar
    Roy, Piyal Basu
    Sarkar, Bappa
    Ray, Sheuli
    [J]. MODELING EARTH SYSTEMS AND ENVIRONMENT, 2023, 9 (03) : 3621 - 3642
  • [8] Prediction of spatio-temporal (2030 and 2050) land-use and land-cover changes in Koch Bihar urban agglomeration (West Bengal), India, using artificial neural network-based Markov chain model
    Manoj Debnath
    Nazrul Islam
    Shasanka Kumar Gayen
    Piyal Basu Roy
    Bappa Sarkar
    Sheuli Ray
    [J]. Modeling Earth Systems and Environment, 2023, 9 : 3621 - 3642