Intra-annual variations of vegetation status in a sub-tropical deciduous forest-dominated area using geospatial approach: a case study of Sali watershed, Bankura, West Bengal, India

Malik, Sadhan; Pal, Subodh Chandra; Das, Biswajit; Chakrabortty, Rabin

doi:10.1080/24749508.2019.1633219

Cited by 18 publications

(5 citation statements)

References 58 publications

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“…The research area's vegetation state varies throughout time. The variability of vegetation status in the irrigation-based region is quite high, and decreased in the forest region due to minor differences in quality of vegetation, and it can go very low for the remaining area [19]. Purulia's geology is characterised by Proterozoic hard granitic gneiss rocks, including mica schist and soft phyllite from the Singhbhum group, which is portion of the Chotanagpur plateau [20].…”

Section: Physiographic Characteristics Of the Study Areamentioning

confidence: 99%

Implication of Applying IPCC AR4 and AR5 Framework for Drought-based Vulnerability and Risk Assessment in Bankura and Purulia Districts, West Bengal

Singha

Pramanick

Acharyya

2023

IOP Conf. Ser.: Earth Environ. Sci.

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In the districts of Purulia and Bankura, this study offers a methodology for spatial assessment of vulnerable and risk-prone areas. These districts are adjacent in space and have identical geographic characteristics (other than the eastern portion of Bankura district). Vulnerability and risk assessment could be used to measure the interactions between individuals and their surroundings. This research aims to pinpoint the areas in these two districts that are particularly susceptible to natural, social, and meteorological disasters. The natural and climate-induced factors considered are rainfall distribution and vegetation conditions. The social factors are agricultural dependence, percentage of farmers, female population, labor dependence on agriculture, and literacy rate. The potential impacts of developmental and environmental degradation processes can be examined and assessed by classifying regions according to their vulnerability and risk levels. The fundamental factors impacting susceptibility and risk, which are recognized, and the associated thematic-based outputs are produced in this study based on the persistent phenomenon of drought within these two districts. The elements of vulnerability selected for this study are exposure, sensitivity, and adaptive capacity (IPCC AR4) and risk, which is the combined outcome of hazard, exposure, and vulnerability (IPCC AR5). The aim of this research is to create a simplified, scalable assessment model for evaluating both vulnerabilities and threats, which can help with drought mitigation. It has been observed from the results that the western portion of the study area (Arsha, Purulia-I, Baghmundi blocks of Purulia district) with relatively higher risk and vulnerability needs more attention for reducing the vulnerability and risk than the eastern part. As a result, this research can serve as a platform for district-level prioritizing efforts, emergency response protocols, and policy interventions aimed at reducing disaster susceptibility (mostly drought) in Bankura and Purulia districts.

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Section: Physiographic Characteristics Of the Study Areamentioning

confidence: 99%

Implication of Applying IPCC AR4 and AR5 Framework for Drought-based Vulnerability and Risk Assessment in Bankura and Purulia Districts, West Bengal

Singha

Pramanick

Acharyya

2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…The NDVI relationship with meteorological parameters, like precipitation and temperature, is mentioned as time-lag effects in the literature [61][62][63][64] and has been well studied [65][66][67]. However, the amount of time lag is different from region to region [68,69].…”

Section: Water Area and Ndvi Interrelationmentioning

confidence: 99%

A Simulation Optimization Approach for Wetland Conservation and Management in an Agricultural Basin

Hatamkhani,

Moridi

2023

Sustainability

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Decreasing water quantity and growth in water demand have increased the competition between satisfying societal water needs and protecting ecosystem requirements. Wetlands are some of the most productive ecosystems on Earth. They provide various services to people’s livelihoods, in addition to being suitable habitats for many plant and wildlife species. However, wetlands are under threat of loss and degradation due to anthropogenic activities, particularly the diversion of water for irrigation. The flow regime is usually considered the most crucial ecological factor and a key component of wetland management. So, determining the allocation of environmental requirements is a main factor for managing, restoring, and protecting wetlands, and it is crucial to reach a compromise for optimal water allocation between different sectors. For this purpose, in this research, a new approach is developed to achieve the optimal environmental flow of the wetland in an agricultural-dominated basin using a combination of remote sensing and the simulation optimization method. Waterbirds and vegetation are used as bioindicators of wetland ecosystems. First, using remote sensing data and analyses, we obtained the interrelation between the wetland water regime, vegetation, and waterbird characteristics using different time series of Landsat spectral indices. Then, by employing the long-term simulation optimization (WEAP-MOPSO) model, the optimal e-flow of the wetland is evaluated in such a way that the suitable ecological condition of the wetland is achieved and the wetland is able to provide its functions and services.

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“…The BSI was introduced to differentiate between the bare soil surface from vegetated land area [54]. This index has been widely used to understand the vegetation cover and canopy density of an area [55,56]. We used the BSI as a GECF to evaluate the GESM for better prediction analysis.…”

Section: Bare Soil Index (Bsi)mentioning

confidence: 99%

Implementation of Artificial Intelligence Based Ensemble Models for Gully Erosion Susceptibility Assessment

et al. 2020

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The Rarh Bengal region in West Bengal, particularly the eastern fringe area of the Chotanagpur plateau, is highly prone to water-induced gully erosion. In this study, we analyzed the spatial patterns of a potential gully erosion in the Gandheswari watershed. This area is highly affected by monsoon rainfall and ongoing land-use changes. This combination causes intensive gully erosion and land degradation. Therefore, we developed gully erosion susceptibility maps (GESMs) using the machine learning (ML) algorithms boosted regression tree (BRT), Bayesian additive regression tree (BART), support vector regression (SVR), and the ensemble of the SVR-Bee algorithm. The gully erosion inventory maps are based on a total of 178 gully head-cutting points, taken as the dependent factor, and gully erosion conditioning factors, which serve as the independent factors. We validated the ML model results using the area under the curve (AUC), accuracy (ACC), true skill statistic (TSS), and Kappa coefficient index. The AUC result of the BRT, BART, SVR, and SVR-Bee models are 0.895, 0.902, 0.927, and 0.960, respectively, which show very good GESM accuracies. The ensemble model provides more accurate prediction results than any single ML model used in this study.

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Intra-annual variations of vegetation status in a sub-tropical deciduous forest-dominated area using geospatial approach: a case study of Sali watershed, Bankura, West Bengal, India

Cited by 18 publications

References 58 publications

Implication of Applying IPCC AR4 and AR5 Framework for Drought-based Vulnerability and Risk Assessment in Bankura and Purulia Districts, West Bengal

Implication of Applying IPCC AR4 and AR5 Framework for Drought-based Vulnerability and Risk Assessment in Bankura and Purulia Districts, West Bengal

A Simulation Optimization Approach for Wetland Conservation and Management in an Agricultural Basin

Implementation of Artificial Intelligence Based Ensemble Models for Gully Erosion Susceptibility Assessment

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