Predicting changes in land use/land cover and seasonal land surface temperature using multi-temporal landsat images in the northwest region of Bangladesh

Kafy, Abdulla Al; Faisal, Abdullah-Al-; Rakib, Abdullah Al; Roy, Sumita; Ferdousi, Jannatul; Raikwar, Vinay; Kona, Marium Akter; Fatin, S.M. Abdullah Al

doi:10.1016/j.heliyon.2021.e07623

Cited by 35 publications

(11 citation statements)

References 55 publications

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“…Similarly, in Khulna city, the built-up growth was 28% between 1997 and 2017 [37]. On the other hand, mid-tier district towns like Comilla experienced a net increase of 7.8% in built-up area in the last two decades [38] while it was nearly 25% in Mymenshigh [39] and ~ 69% in Barisal [40].…”

Section: Discussionmentioning

confidence: 98%

Rapid and unplanned urbanization in the least developed districts of Bangladesh: a case study from Jamalpur using geospatial techniques

et al. 2022

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Sustainable urban development is a key compoment in the United Nation’s Sustainable Development Goals. Monitoring urbanization is critical for planners, governments and non-governmental organizations, and scientists to design policies that maximize the use of natural resources and accommodate development while reducing environmental effects. This research aims to analyze how urbanization patterns have changed in the largely unknown least developed regions of Bangladesh. Multispectral satellite imageries over 30 years (1991 to 2021) were used to analyze the urbanization pattern of Jamapur district. Utilizing object-based image classification and on-field validation for seven Land Use and Land Cover classes, it was found that built-up area expanded by 748.92% during the past three decades while depleting bare soil (− 97.65%), deep waterbody (− 79.33%), shallow waterbody (− 8.46%), light vegetation (− 14.28%) and agricultural land (− 26.33%).. Because of increased in built-ups, the land surface temperatures (LST) were also increased over the study period (the minimun recorded LST were 12.84 °C, 15.89 °C, 15.8 °C and 17 °C while the maximun LST were 17.93 °C, 23.7 °C, 23.79 °C and 26.73 °C for the year of 1991, 2001, 2013 and 2021 respectively). This study will act as a baseline for future studies It be insightful to urban planners and policymakers in developing countries regarding urban sustainability and minimizing urban risks and hazards in the least developed districts.

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Section: Discussionmentioning

confidence: 98%

Rapid and unplanned urbanization in the least developed districts of Bangladesh: a case study from Jamalpur using geospatial techniques

et al. 2022

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“…A simulated map for the forecast year is created in hard forecasting, with each pixel assigned to a certain land‐use category. Soft forecasts, on the other hand, are projection maps used to show weaknesses, with each pixel assigned a value ranging from 0 to 1 (Kafy et al, 2021; Leta et al, 2021). The CA‐MC model, on the other hand, is one of the most extensively used LULC modeling tools and methodologies, and it models both spatial and temporal changes (Girma et al, 2022; Hamad et al, 2018).…”

Section: Methodsmentioning

confidence: 99%

“…For this study, MLP-NN and CA-MC models were used to predict changes in LULC. The models also perform well due to their ability to project dynamically, use effective calibration methods, and simulate different types of LULC (Dey et al, 2021;Girma et al, 2022;Hakim et al, 2021;Kafy et al, 2021;Leta et al, 2021;Nath et al, 2020;Tadese et al, 2021). Due to the growth of rural populations and the settlement areas, land use practices in the Omo-Gibe basin (Chaemiso et al, 2021), particularly in the Ajora-Woybo watershed, have altered dramatically in the last 20 years and are no longer sustainable.…”

Section: Recommendations For Resource Managersmentioning

confidence: 99%

“…For this study, MLP‐NN and CA‐MC models were used to predict changes in LULC. The models also perform well due to their ability to project dynamically, use effective calibration methods, and simulate different types of LULC (Dey et al, 2021; Girma et al, 2022; Hakim et al, 2021; Kafy et al, 2021; Leta et al, 2021; Nath et al, 2020; Tadese et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Historical and future dynamics of land use land cover and its drivers in Ajora‐Woybo watershed, Omo‐Gibe basin, Ethiopia

Toma

Belete

Ulsido

2022

Natural Resource Modeling

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Land use land cover (LULC) dynamics have long been recognized as a significant driver of natural resource change. As a result, understanding the spatial and temporal variation of LULC in the watershed is essential for effective natural resource management and long‐term development. This study attempts to analyze the dynamics and change drivers from 1990 to 2020 and predict the situation for 2035 and 2050 in the Ajora‐Woybo watershed. ArcGIS 10.3 and ERDAS 2015 were used to analyze quantitative data from Landsat imagery. For supervised image classification, a Maximum‐Likelihood classification algorithm was used. To identify driver variables, focus groups and key informants' interviews were done. TerrSet 18.31 software was used to predict LULC utilizing the Multi‐Layer Perceptron Neural Network and Cellular Automata‐Markov Chain models incorporated in Land Change Modeler. Six LULC classes were discovered: cultivated land, built‐up, shrub land, forest land, bare land, and water body. Cultivated land, built‐up area, and bare land have increased at the expense of shrub land and forest land over the last three decades. Trends in water bodies show both decreasing and increasing trends. According to the predicted outcomes, cultivated land, built‐up and bare land has increased, while shrub land and forest land have declined. Finally, agricultural expansion, population growth, wood extraction, resettlement, urbanization, and lack of environmental consideration were identified as the major drivers of LULC change. The study demonstrated that there have been significant changes in the watershed LULC. As a result, reversing the predicted conditions is critical to ensuring the watershed long‐term viability.

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“…However, land use change has both manmade and natural causes. Significant landscape changes have been experienced in recent decades, mainly because of the speedy urbanization that has adverse consequences on the local surface temperature [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Machine learning-based assessment and simulation of land use modification effects on seasonal and annual land surface temperature variations

Khan,

Qasim,

Tahir

et al. 2023

Heliyon

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Predicting changes in land use/land cover and seasonal land surface temperature using multi-temporal landsat images in the northwest region of Bangladesh

Abstract: Predicting changes in land use land cover and seasonal land surface temperature using multi-temporal landsat images in the northwest region of Bangladesh, HELIYON,

Cited by 35 publications

References 55 publications

Rapid and unplanned urbanization in the least developed districts of Bangladesh: a case study from Jamalpur using geospatial techniques

Rapid and unplanned urbanization in the least developed districts of Bangladesh: a case study from Jamalpur using geospatial techniques

Historical and future dynamics of land use land cover and its drivers in Ajora‐Woybo watershed, Omo‐Gibe basin, Ethiopia

Machine learning-based assessment and simulation of land use modification effects on seasonal and annual land surface temperature variations

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