A multi-layer perceptron–Markov chain based LULC change analysis and prediction using remote sensing data in Prayagraj district, India

Kumar, Vivek; Agrawal, Sonam

doi:10.1007/s10661-023-11205-w

Cited by 21 publications

(2 citation statements)

References 58 publications

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“…This model analyzed the tendency of land use change based on land use data from 2 time periods-namely 2015 and 2019 (Figure 2)-to gain temporal correlations. Then, the LMC analyzed the transition potential of possible land use and cover according to variables related to future changes using Multi-Layer Perceptron (MLP), which created potential maps of changes [35].…”

Section: Land Use Change Scenariosmentioning

confidence: 99%

Understanding the Interactions of Climate and Land Use Changes with Runoff Components in Spatial-Temporal Dimensions in the Upper Chi Basin, Thailand

Hormwichian,

Kaewplang,

Kangrang

et al. 2023

Water

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Climate and land use changes are major factors affecting runoff in regional basins. Understanding this variation through considering the interactions among hydrological components is an important process for water resource management. This study aimed to assess the variation of future runoff in the Upper Chi Basin, Northeastern Thailand. The QSWAT hydrological model was integrated into three CMIP6 GCMs—ACCESS-CM2, MIROC6, and MPI-ESM1-2-LR—under SSP245 and SSP585 scenarios for the period 2023–2100. The Land Change Modeler (LCM) was also used for future land use simulation. The results revealed that the future average long-term precipitation and temperature tended to increase while forest land tended to decrease and be replaced by sugarcane plantations. The accuracy assessment of the baseline year runoff calculation using QSWAT for the period 1997–2022 showed an acceptable result, as can be seen from the R2, NSE, RSR, and PBIAS indices. This result could lead to the temporal and spatial simulation of future runoff. Likewise, the runoff of the two SSP scenarios tended to increase consecutively, especially in the SSP585 scenario. In addition, in cases of long-term spatial changes in the subbasins scale, over 90% of the area—from upstream to the outlet point—tended to be higher due to two major factors; namely, future increased precipitation and changes in cultivation, which would be influential to groundwater and interflow components, respectively. The methodology and result of this study can be useful to stakeholders in understanding changes in hydrological systems so that they can apply it to developing a strategy for water resource management and to handling factors affecting different dimensions properly and sustainably.

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Section: Land Use Change Scenariosmentioning

confidence: 99%

Understanding the Interactions of Climate and Land Use Changes with Runoff Components in Spatial-Temporal Dimensions in the Upper Chi Basin, Thailand

Hormwichian,

Kaewplang,

Kangrang

et al. 2023

Water

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“…[21][22][23]. For example, the soil erosion characteristics of a basin can be analyzed in multiple scenarios based on PLUS models and RUSLE models [24]; an MLP-Markov model (a multi-layer perceptron-Markov chain) can be used to predict dynamic change in land use and land vulnerability in a region and obtain estimated values for different types of land in the future [25]; and Markov models can be used to simulate regional land use change and explore the relationship between urban growth and landscape change and population growth [26]. Among the different models, the system dynamics model [27] and the Markov model [28] mainly adopt numerical simulation model analysis, which has the advantage of quantitative prediction; the CLUE-S model belongs to the class of spatial prediction models, pays more attention to spatial data information, and has the ability to predict change in spatial locations [29], but it is based on the traditional logistic regression method, which may ignore the internal autocorrelation of spatial data during spatial analysis, affecting the simulation accuracy to a certain extent [30].…”

Section: Introductionmentioning

confidence: 99%

Multi-Scenario Simulation and Eco-Environmental Effects Analysis of Land Use/Cover Change in China by an Integrated Cellular Automata and Markov Model

Wang,

Xue,

Yang

et al. 2024

Land

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Land use transitions play a critical role in ecological environmental restoration, but they are also plagued by ecological environmental problems caused by excessive land resource development. In this study, we propose a methodological framework for unveiling the nexus profile of land use/cover change (LUCC) and eco-environmental effects. This study explored the spatiotemporal evolution patterns of LUCC over a long time series based on high-precision land use data from 1990 to 2020. Then, the ecological values (EVs) of various cities were calculated to obtain the ecological contribution rate of different land use types in the process of change. Finally, the future development trends of land use and ecological environmental quality were predicted under multiple scenarios using the cellular automata–Markov model, and scientific policy recommendations were proposed. The results showed that the expansion trajectory of the construction land in the urban agglomeration mainly expanded inwards along the mouth of the Pearl River, and the conversion of cultivated land to construction land was the most significant type of land use change. The overall ecological environmental quality of the study area showed a downwards trend, with Shenzhen exhibiting the largest decrease in EVs. Cultivated land contributed significantly to improving regional ecological environmental quality, while the land use transition types with relatively large contributions to environmental quality deterioration were conversions to construction land. Under the scenario of coordinated protection, the degree of cultivated land area reduction was significantly reduced, and the area of forestland showed a positive growth trend, with the expansion trend of construction land being reversed. These research findings can enrich the theoretical research on the sustainable development of urban agglomerations and provide reliable data support for policy-making.

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Prediction of soil erosion and sediment yield in an ungauged basin based on land use land cover changes

Sampath,

Radhakrishnan

2023

Environ Monit Assess

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A multi-layer perceptron–Markov chain based LULC change analysis and prediction using remote sensing data in Prayagraj district, India

Cited by 21 publications

References 58 publications

Understanding the Interactions of Climate and Land Use Changes with Runoff Components in Spatial-Temporal Dimensions in the Upper Chi Basin, Thailand

Understanding the Interactions of Climate and Land Use Changes with Runoff Components in Spatial-Temporal Dimensions in the Upper Chi Basin, Thailand

Multi-Scenario Simulation and Eco-Environmental Effects Analysis of Land Use/Cover Change in China by an Integrated Cellular Automata and Markov Model

Prediction of soil erosion and sediment yield in an ungauged basin based on land use land cover changes

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