Changes in the economic value of ecosystem services in rapidly growing urban areas: the case of Dhaka, Bangladesh

Haque, Md. Nazmul; Mahi, Mahdi Mansur; Sharif, Md. Shahriar; Rudra, Rhyme Rubayet; Sharifi, Ayyoob

doi:10.1007/s11356-023-26096-0

Cited by 15 publications

(4 citation statements)

References 75 publications

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“…Also, erosion reduces soil quality and induces the degradation of forested areas. From then on, the slope degree (7) can cause potential soil erosion that can reduce the soil quality and induce the degradation of forested areas. From the point of view of socio-economic development, increasing population density (8) and manufacturing added value (9) lead to the extension of road and highway networks and worsening pressure on forested areas.…”

Section: Identifying Key Underlying Factorsmentioning

confidence: 99%

“…In arid regions, desertification is frequently associated with the deterioration of soil quality, which depends on various factors, including environmental changes and anthropogenetic effects. Forest clearing significantly affects the climate system and land-atmosphere interactions [6], leading to changes in land use and land cover (LULC), which can influence various ecosystems and have implications for natural habitats and human survival [7]. In Senegal's Sahel region, droughts and human activities, such as farming, cattle overgrazing, bushfires, and monoculture, have negatively impacted the delicate ecological balances [5,8].…”

Section: Introductionmentioning

confidence: 99%

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Lessons Learnt from the Influencing Factors of Forested Areas’ Vulnerability under Climatic Change and Human Pressure in Arid Areas: A Case Study of the Thiès Region, Senegal

Faye,

Du,

et al. 2024

Applied Sciences

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Understanding the factors influencing the vulnerability of forested areas is crucial for human well-being and effective governance of ecosystem supply and demand. Based on remote sensing data, this study also considered ten natural and human variables as indexes to explore the main influencing factors that may impact the vulnerability of the Thies region’s forested areas. The 2005, 2010, 2015, and 2020 satellite image data were processed using ArcGIS 10.6 and ENVI 5.1 software. The methodology includes using the transfer matrix approach and calculating the geographic landscape index to describe the dominant morphology of forested areas. Furthermore, a mixed linear regression model was built to establish the connection between forested areas and the potential contributing components. Our study revealed that the forested areas led to relative fragmentation, with an average of 88 patches for Aggregation Index (AI), 3.25 for Largest Patch Index (LPI), 2.50 for Patch Density (PD), and 112 for Landscape Shape Index (LSI) between 2005 and 2020. In addition, the transfer matrix indicated that the loss of forestry areas was about −78.8 km2 for agricultural land, −127.8 km2 for bare land, and −65.3 km2 for artificial surfaces. The most critical factors that influenced forested areas were agricultural and manufactural added value, rainfall (p < 0.05), slope, distance to the road, and agricultural sown area (p < 0.001). Overall, this investigation has revealed that the effective management of forested areas in the Thies region requires an understandable assessment. It was observed that both human anthropogenic and natural factors significantly contribute to the decline in forested areas.

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Section: Identifying Key Underlying Factorsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lessons Learnt from the Influencing Factors of Forested Areas’ Vulnerability under Climatic Change and Human Pressure in Arid Areas: A Case Study of the Thiès Region, Senegal

Faye,

Du,

et al. 2024

Applied Sciences

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“…Bangladesh is one of the most over populated countries in the world facing a lot of problems like climate change [ 10 , [45] , [46] , [47] , [48] , [49] ], deforestation [ 50 , 51 ], unplanned urbanization [ 50 , 52 ], pollution [ 34 , 38 , [53] , [54] , [55] ], manmade and natural disasters [ 15 , 56 ]. Bangladesh's coastline region has a more diversified and dynamic physical landscape than is often recognized.…”

Section: Introductionmentioning

confidence: 99%

Cyclone vulnerability assessment in the coastal districts of Bangladesh

Sarkar,

Rudra,

Santo

2024

Heliyon

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“… 6 , 47 – 49 . Additionally, the amount of agricultural land is constantly declining, and the increase in impermeable surfaces caused by vegetation has only made matters worse 50 – 52 . A sizeable population is hence regularly exposed to the risks caused by water shortages and poor water quality.…”

Section: Introductionmentioning

confidence: 99%

Future groundwater potential mapping using machine learning algorithms and climate change scenarios in Bangladesh

Sarkar,

Rudra,

Talukdar

et al. 2024

Sci Rep

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The aim of the study was to estimate future groundwater potential zones based on machine learning algorithms and climate change scenarios. Fourteen parameters (i.e., curvature, drainage density, slope, roughness, rainfall, temperature, relative humidity, lineament density, land use and land cover, general soil types, geology, geomorphology, topographic position index (TPI), topographic wetness index (TWI)) were used in developing machine learning algorithms. Three machine learning algorithms (i.e., artificial neural network (ANN), logistic model tree (LMT), and logistic regression (LR)) were applied to identify groundwater potential zones. The best-fit model was selected based on the ROC curve. Representative concentration pathways (RCP) of 2.5, 4.5, 6.0, and 8.5 climate scenarios of precipitation were used for modeling future climate change. Finally, future groundwater potential zones were identified for 2025, 2030, 2035, and 2040 based on the best machine learning model and future RCP models. According to findings, ANN shows better accuracy than the other two models (AUC: 0.875). The ANN model predicted that 23.10 percent of the land was in very high groundwater potential zones, whereas 33.50 percent was in extremely high groundwater potential zones. The study forecasts precipitation values under different climate change scenarios (RCP2.6, RCP4.5, RCP6, and RCP8.5) for 2025, 2030, 2035, and 2040 using an ANN model and shows spatial distribution maps for each scenario. Finally, sixteen scenarios were generated for future groundwater potential zones. Government officials may utilize the study’s results to inform evidence-based choices on water management and planning at the national level.

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Changes in the economic value of ecosystem services in rapidly growing urban areas: the case of Dhaka, Bangladesh

Cited by 15 publications

References 75 publications

Lessons Learnt from the Influencing Factors of Forested Areas’ Vulnerability under Climatic Change and Human Pressure in Arid Areas: A Case Study of the Thiès Region, Senegal

Lessons Learnt from the Influencing Factors of Forested Areas’ Vulnerability under Climatic Change and Human Pressure in Arid Areas: A Case Study of the Thiès Region, Senegal

Cyclone vulnerability assessment in the coastal districts of Bangladesh

Future groundwater potential mapping using machine learning algorithms and climate change scenarios in Bangladesh

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