Erosion vulnerable area assessment of Jamuna River system in Bangladesh using a multi-criteria-based geospatial fuzzy expert system and remote sensing

被引:3
|
作者
Alam, Kazi Faiz [1 ]
Ahamed, Tofael [1 ,2 ]
机构
[1] Univ Tsukuba, Grad Sch Sci & Technol, Tsukuba, Japan
[2] Univ Tsukuba, Fac Life & Environm Sci, Tsukuba, Japan
关键词
Riverbank erosion; Multi-criteria analysis; Fuzzy expert system; Remote sensing; MULTICRITERIA DECISION-ANALYSIS; ANALYTIC HIERARCHY PROCESS; FREQUENCY RATIO; RANK REVERSAL; LAND-USE; GIS; SUITABILITY; DELINEATION; BIVARIATE; MODEL;
D O I
10.1007/s41685-023-00292-9
中图分类号
F [经济];
学科分类号
02 ;
摘要
Jamuna, a dynamic and unstable braided river system in Bangladesh, is approximately 240 km long and becomes extremely unstable during the rainy season resulting in serious bank erosion. Therefore, this study aimed to assess the erosion-prone areas adjacent to the Jamuna River system. Change detection analysis was carried out using Landsat 8 (OLI) images captured in 2020 by multi-criteria analysis using a geospatial fuzzy expert system and state-of-the-art remote sensing technology. Normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), normalized difference water index (NDWI), distance from the river, land use and land cover (LULC), and slope and elevation were selected as criteria for this analysis. All criteria maps were standardized using fuzzy membership functions and reclassification of each criteria performed. Furthermore, expert judgments were included to rank the criteria influencing vulnerable areas based on an analytical hierarchy process (AHP) approach. Finally, a weighted overlay map was prepared for erosion vulnerability assessment from the reclassified maps. From these analyses, we found that water bodies covered 1003 km(2) (10.94%), high-to-moderate erosion-prone areas were 7401.21 km(2) (77.39%), marginal erosion-prone areas 1065 km(2) (11.61%) and nonerosion-prone areas only 5.9 km(2) (0.06%), respectively. To verify the vulnerable areas, 150 reference points of water bodies from the mainstream of the Jamuna River were taken using Google Earth Pro images captured in 2020. These points were plotted on the NDWI maps of 2020 and 1990 to verify the detection of changes in the riverbank shifts for 30-year intervals. This confirmed the bank shifted from 3 to 4 km in more than 20 points during this span of time. Our analysis also confirmed that high-to-moderately erosion-vulnerable areas fall between 3 and 7 km. Therefore, we recommend the adoption of new agricultural land use planning, considering erosion venerable areas to ensure agricultural production and livelihood security.
引用
收藏
页码:433 / 454
页数:22
相关论文
共 50 条
  • [31] Assessment of soil erosion risk using RUSLE model, SATEEC system, remote sensing, and GIS techniques: a case study of Navroud watershed
    Fallah, Mahboobeh
    Bahrami, Hosseinali
    Asadi, Hossein
    ENVIRONMENTAL EARTH SCIENCES, 2023, 82 (17)
  • [32] Risk assessment for the integrated energy system using a hesitant fuzzy multi-criteria decision-making framework
    Xu, Fangqiu
    Gao, Kaiye
    Xiao, Bowen
    Liu, Jicheng
    Wu, Zixuan
    ENERGY REPORTS, 2022, 8 : 7892 - 7907
  • [33] Identification and analysis of groundwater potential zones in Ken-Betwa river linking area using remote sensing and geographic information system
    Avtar, Ram
    Singh, C. K.
    Shashtri, Satyanarayan
    Singh, Amit
    Mukherjee, Saumitra
    GEOCARTO INTERNATIONAL, 2010, 25 (05) : 379 - 396
  • [34] Ensemble machine-learning-based geospatial approach for flood risk assessment using multi-sensor remote-sensing data and GIS
    Mojaddadi, Hossein
    Pradhan, Biswajeet
    Nampak, Haleh
    Ahmad, Noordin
    bin Ghazali, Abdul Halim
    GEOMATICS NATURAL HAZARDS & RISK, 2017, 8 (02) : 1080 - 1102
  • [35] Using a Remote-Sensing-Based Piecewise Retrieval Algorithm to Map Chlorophyll-a Concentration in a Highland River System
    Ma, Yuanxu
    Sun, Dongqi
    Liu, Weihua
    You, Yongfa
    Wang, Siyuan
    Sun, Zhongchang
    Wang, Shaohua
    REMOTE SENSING, 2022, 14 (23)
  • [36] Recommended System for Cluster Head Selection in a Remote Sensor Cloud Environment Using the Fuzzy-Based Multi-Criteria Decision-Making Technique
    Mukherjee, Proshikshya
    Pattnaik, Prasant Kumar
    Al-Absi, Ahmed Abdulhakim
    Kang, Dae-Ki
    SUSTAINABILITY, 2021, 13 (19)
  • [37] System Structure-Based Drought Disaster Risk Assessment Using Remote Sensing and Field Experiment Data
    Cui, Yi
    Tang, Huiyan
    Jin, Juliang
    Zhou, Yuliang
    Jiang, Shangming
    Chen, Menglu
    REMOTE SENSING, 2022, 14 (22)
  • [38] Determination of Soil Erosion Risk in the Mustafakemalpasa River Basin, Turkey, Using the Revised Universal Soil Loss Equation, Geographic Information System, and Remote Sensing
    Gokhan Ozsoy
    Ertugrul Aksoy
    M. Sabri Dirim
    Zeynal Tumsavas
    Environmental Management, 2012, 50 : 679 - 694
  • [39] Determination of Soil Erosion Risk in the Mustafakemalpasa River Basin, Turkey, Using the Revised Universal Soil Loss Equation, Geographic Information System, and Remote Sensing
    Ozsoy, Gokhan
    Aksoy, Ertugrul
    Dirim, M. Sabri
    Tumsavas, Zeynal
    ENVIRONMENTAL MANAGEMENT, 2012, 50 (04) : 679 - 694
  • [40] Reversible Decision Support System: Minimising Cognitive Dissonance in Multi-Criteria Based Complex System Using Fuzzy Analytic Hierarchy Process
    Hasan, Md Mahmudul
    Abu-Hassan, Kamal
    Lwin, Khin
    Hossain, M. A.
    2016 8TH COMPUTER SCIENCE AND ELECTRONIC ENGINEERING CONFERENCE (CEEC), 2016, : 210 - 215