Predicting the land use and land cover change using Markov model: A catchment level analysis of the Bhagirathi-Hugli River

Das, Sanat Kr.; Sarkar, Rajib

doi:10.1007/s41324-019-00251-7

Cited by 49 publications

(35 citation statements)

References 12 publications

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“…It is noted by previous research, LULC changes have the prospective to have a significant environmental impact changing the urban climate (M. Ali et al, 2019). Different research has also confirmed the environmental effects on LULC changes (Cheema & Bastiaanssen, 2010;Das & Sarkar, 2019;Tan et al, 2020;B. Zoungrana et al, 2015).…”

Section: Introductionmentioning

confidence: 86%

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Hussain

Karuppannan

2021

Geology, Ecology, and Landscapes

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The aim of this research was to assess the land use/land cover (LULC) changes and its impact on land surface temperature (LST) using remote-sensing (RS) technique in the district Khanewal, Punjab, Pakistan. Data were pre-processed using ERDAS imagine 15 and Arc GIS 10.4 software for layer stacking, mosaicking, and sub-setting of Landsat images. After pre-processing, the supervised classification scheme was applied for the years 1980, 2000, and 2020, which explains the maximum likelihood algorithm to identify LULC changes observed in the study area. "Built-up area" in 1980 occupied 1.75% but in 2020, the build-up area increased (5.27%) compared to 2020. Vegetation area was decreased by 4.12% from 1980 to 2020 in district Khanewal. It was observed that there has been a rapid change in vegetation area to build-up area. The LST values were increased by 0.50°C from 1980 to 2020 due to the increasing build-up area from East to West direction in district Khanewal. Maximum and minimum normalized difference vegetation index (NDVI) values were observed 0.72 and −0.2 for 1980 and 2020. The regression line produced a definitive explanation, showing a strong negative correlation with NDVI and LST. The outcomes of this study indicated that a dramatic transformation took place in district Khanewal regarding a decrease in greenness due to a rapid increase in population density, urban growth, and other infrastructural developments. Thus, these results will be used in regional and urban planning and will be used for managing agriculture in the coming years of rapid environmental changes.

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Section: Introductionmentioning

confidence: 86%

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Hussain

Karuppannan

2021

Geology, Ecology, and Landscapes

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“…Model validation is the main part of the CA-Markov model. It consists of test models on data not used to build the model [2]. The predicted LULC is considered consistent only when it is validated using existing ground data sets.…”

Section: Ca-markov Model Validationmentioning

confidence: 99%

“…Land cover refers to natural structures such as vegetation and water surfaces, as well as manufactured structures that cover a certain region, whereas human activities that are related to the soil are called land use [1]. Change in land use and land cover (LULC) is an important factor in global environmental change, and it is crucial for regional development and land-use management to achieve sustainable development [2]. Due to rapid global economic and population growth and globalization, LULC is accelerating in many developing countries around the world [3].…”

Section: Introductionmentioning

confidence: 99%

Quantitatively Assessing the Future Land-Use/Land-Cover Changes and Their Driving Factors in the Upper Stream of the Awash River Based on the CA–Markov Model and Their Implications for Water Resources Management

Daba

Suning

2022

Sustainability

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Despite the rapid economic and population growth, the risks related to the current dynamics of land use and land cover (LULC) have attracted a lot of attention in Ethiopia. Therefore, a complete investigation of past and future LULC changes is essential for sustainable water resources and land-use planning and management. Since the 1980s, LULC change has been detected in the upper stream of the Awash River basin. The main purpose of this research was to investigate the current dynamics of LULC and use the combined application of the cellular automata and the Markov chain (CA–Markov) model to simulate the year 2038 LULC in the future; key informant interviews, household surveys, focus group discussions, and field observations were used to assess the consequences and drivers of LULC changes in the upstream Awash basin (USAB). This research highlighted the importance of remote sensing (RS) and geographic information system (GIS) techniques for analyzing the LULC changes in the USAB. Multi-temporal cloud-free Landsat images of three sequential data sets for the periods (1984, 2000, and 2019) were employed to classify based on supervised classification and map LULC changes. Satellite imagery enhancement techniques were performed to improve and visualize the image for interpretation. ArcGIS10.4 and IDRISI software was used for LULC classification, data processing, and analyses. Based on Landsat 5 TM-GLS 1984, Landsat 7 ETM-GLS 2000, and Landsat 8 2019 OLI-TIRS, the supervised maximum likelihood image classification method was used to map the LULC dynamics. Landsat images from 1984, 2000, and 2019 were classified to simulate possible LULC in 2019 and 2038. The result reveals that the maximum area is covered by agricultural land and shrubland. It showed, to the areal extent, a substantial increase in agricultural land and urbanization and a decrease in shrubland, forest, grassland, and water. The LULC dynamics showed that those larger change rates were observed from forest and shrubland to agricultural areas. The results of the study show the radical changes in LULC during 1984–2019; the main reasons for this were agricultural expansion and urbanization. From 1984 to 2019, agriculture increased by 62%, urban area increased by 570.5%, and forest decreased by 88.7%. In the same year, the area of shrubland decreased by 68.6%, the area of water decreased by 65.5%, and the area of grassland decreased by 57.7%. In view of the greater increase in agricultural land and urbanization, as well as the decrease in shrubland, it means that the LULC of the region has changed. This research provides valuable information for water resources managers and land-use planners to make changes in the improvement of future LULC policies and development of sub-basin management strategies in the context of sustainable water resources and land-use planning and management.

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“…(4) Per capita GDP was obtained from the 2016 Hangzhou Statistical Yearbook [30] and converted to the raster layer. (5) Population density was from LandScan, a statistical analysis database of global population dynamics (spatial resolution of about 1 km) developed by the Oak Ridge National Laboratory (ORNL).…”

Section: Datamentioning

confidence: 99%

“…In the past few decades, domestic and foreign researchers created many different mathematical models to simulate and predict future land-use development, such as the system dynamic model [3,4], Markov chain model [5], cellular-automata (CA) model [6], accelerating the modernization and internationalization of the host city. It also promotes a great transition of Hangzhou's urban planning and development from the West Lake Era towards the Qiantang River Era [28,29].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Impact of Mega-Sports Events on Urbanization Focusing on Land-Use Changes Using a Scenario-Based Model

Fan

Zhu

et al. 2021

Sustainability

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Mega-sports events have a profound impact on promoting the urbanization process, optimizing the urban spatial structure, and improving the competitiveness of the host city. Taking the 19th Asian Games Hangzhou 2022 (AGH) as an example, we used remote sensing data and a scenario-based model to simulate land-use changes and developments from 2005 to 2025. By setting two scenarios, natural development and AGH-driven development, we explored the impact of AGH on urban development and its driving factors. The results show that (1) cultivated land areas decreased by 369.96 km2, while construction land areas increased by 488.33 km2 among the main land-use types in Hangzhou from 2005 to 2020. Urban areas quickly expanded with the West Lake as the center. (2) Urban sprawl intensity under the AGH-driven scenario is expected to increase by 0.91% compared to in the natural-development scenario, indicating that hosting AGH would accelerate the expansion of urban land, particularly in districts set with sports venues such as Binjiang, Xiaoshan, and Yuhang. The strategic trend of supporting the Qiantang River is obvious. (3) Under the influence of AGH, the centroid of urban construction land shifted towards the southeast, and the spatial direction was remarkable. The construction of venues and supporting facilities, and construction land for public rail transit, are the main direct driving forces of urban expansion. The AGH enhances the pace of urbanization, significantly altering the urban spatial structure and helping the city achieve a major transition from the West Lake Era to the Qiantang River Era. Furthermore, our research can provide insights into other cities that will host mega-sports events.

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Predicting the land use and land cover change using Markov model: A catchment level analysis of the Bhagirathi-Hugli River

Cited by 49 publications

References 12 publications

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Land use/land cover changes and their impact on land surface temperature using remote sensing technique in district Khanewal, Punjab Pakistan

Quantitatively Assessing the Future Land-Use/Land-Cover Changes and Their Driving Factors in the Upper Stream of the Awash River Based on the CA–Markov Model and Their Implications for Water Resources Management

Evaluating the Impact of Mega-Sports Events on Urbanization Focusing on Land-Use Changes Using a Scenario-Based Model

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