Analysis of Land Use and Land Cover Changes in Urban Areas Using Remote Sensing: Case of Blantyre City

Discrete Dynamics in Nature and Society, Journal Year: 2021, Volume and Issue: 2021, P. 1 - 17

Published: Dec. 23, 2021

Blantyre City has experienced a wide range of changes in land use and cover (LULC). This study used Remote Sensing (RS) to detect quantify LULC that occurred the city throughout twenty-year period, using Landsat 7 Enhanced Thematic Mapper (ETM+) images from 1999 2010 8 Operational Land Imager (OLI) 2019. A supervised classification method an Artificial Neural Network (ANN) was classify map types. The kappa coefficient overall accuracy were ascertain accuracy. Using classified images, postclassification comparison approach between revealed built-up agricultural increased their respective areas by 28.54 km2 (194.81%) 35.80 (27.16%) with corresponding annual change rates 1.43 km·year−1 1.79 km·year−1. area bare land, forest herbaceous waterbody, respectively, decreased 0.05%, 90.52%, 71.67%, 6.90%. attributed urbanization, population growth, social-economic climate change. findings this provide information on driving factors, which authorities can utilize develop sustainable development plans.

Language: Английский

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The relationship between land use land cover and land surface temperature using remote sensing: systematic reviews of studies globally over the past 5 years

Environmental Science and Pollution Research, Journal Year: 2022, Volume and Issue: 29(28), P. 42493 - 42508

Published: April 2, 2022

Language: Английский

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Deep learning for the prediction and classification of land use and land cover changes using deep convolutional neural network

Ecological Informatics, Journal Year: 2021, Volume and Issue: 65, P. 101412 - 101412

Published: Aug. 24, 2021

Language: Английский

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Detection of land use/land cover and land surface temperature change in the Suha Watershed, North-Western highlands of Ethiopia

Environmental Challenges, Journal Year: 2022, Volume and Issue: 7, P. 100523 - 100523

Published: April 1, 2022

Human-induced land use cover changes resulted in adverse impacts on the environment at various spatial and temporal scales. The Highland regions of Ethiopia are typical examples these phenomena. objective this study was to analyze spatiotemporal use/ their surface temperature suha watershed, northwestern highlands Ethiopia. Multi-temporal Landsat images (1985–2019) were used LU/LC LST using GIS remote sensing techniques. Image preprocessing, supervised classification, accuracy assessment, change detection conducted identify classes, area coverage, transitions. Thermal bands satellite also extract LST. Significant use/land (spatial temporal) observed watershed during periods. Agricultural has got largest proportion all barren built expanded greatly 35 years period. increased by 15417.6 ha (34.8%) bare 5297.2 (373.6%). However, grazing shrub lands reduced by18568.4 (72.1%) 3544.2 (47.6%), respectively. Spatial variation same highest mean values found impervious surfaces (built-up areas land), lowest recorded forest land. A negative correlation between NDVI. Undesirable put greater pressure environmental resources, resulting an effect them. Therefore, reverse situation create a balanced ecosystem, management strategies should be applied that mainly focus soil conservation technologies steep slope areas, improve afforestation apply proper land-use policies. outcomes research useful designing implementing appropriate can address critical social problems. It provides new knowledge helps us better understand

Language: Английский

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Spatio-temporal analysis of land use land cover change and its impact on land surface temperature of Sialkot City, Pakistan

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Dec. 13, 2023

Abstract The dynamic interplay between urbanization and its impacts on climate is a subject of recent concern, particularly in rapidly urbanizing cities Pakistan. This research investigated the spatio-temporal effects urban growth terms Land Use Cover changes thermal environment (Land Surface Temperature) Sialkot city, Pakistan using satellite data spanning four distinct time periods (1989, 2000, 2009 2020) predicted for year 2030 by employing Cellular Automata Markov Chain Model. Satellite imagery (Landsat 5, 7 8) was processed, maximum likelihood supervised classification done to generate LULC maps each aforementioned years. In addition classification, bands (for summer winter) were processed compute Temperature (LST) city. prediction LST accuracy classified checked Kappa Index. analysis revealed 4.14% increase built-up area 3.43% decrease vegetation cover city during 1989 2020. Both land covers are expected change future (year 2030) + 1.31% (built-up) − 1.1% (vegetation). Furthermore, declining trend barren water bodies also observed over time. These found affecting study area. transformation into resulted an A notable rise 4.5 °C (summer) 5.7 (winter) mean 2020 further increases anticipated 2030. calls attention policy makers reduce human impact local will help developers analyzing population trend, finding suitable location built new infrastructure governmental authorities how rising temperature can affect energy demand agriculture production future.

Language: Английский

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Identifying Urban Hotspots and Cold Spots in Delhi Using the Biophysical Landscape Framework

Ecology Economy and Society–the INSEE Journal, Journal Year: 2024, Volume and Issue: 7(1), P. 137 - 155

Published: Jan. 23, 2024

Urban heat islands (UHIs), which are formed by biophysical landscape transformations, have significant adverse effects on environmental quality as well human health, resources, and facilities. Variations in UHI intensity give rise to urban hotspots (UHSs) cold spots different parts of the city. This study identifies such Delhi classifying city into zones intensities using landscapes. The data selected landscapes were obtained from satellite images secondary sources. impact was calculated weighted overlay method performed ArcGIS software. thus divided four zones, based intensity. It found that UHSs cover about 45% total area mostly located eastern central Delhi. While built-up areas form major source landscape, vegetation is sink per land surface temperature (LST) findings this will help planners policymakers identify adopt suitable policies measures mitigate UHIs zones.

Language: Английский

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An integrated and multidimensional approach for analyzing vulnerability of water resources under territorial climate conditions

Environmental and Sustainability Indicators, Journal Year: 2024, Volume and Issue: 22, P. 100383 - 100383

Published: April 5, 2024

Several factors comprising climate variability, increasing water demand, and agricultural industrial activities, have put pressure on resources, making them more vulnerable, compromising quality. The present study uses geographic information system (GIS) to develop a multidimensional index of territorial vulnerability scarcity variability in the Saïss plain, Morocco. main objective is identify most vulnerable areas basin. In this approach, conceptual framework consists integrated analysis, based four components (Resources, Socio-demographic, Environment Infrastructure) 21 indicators. Two government agencies, namely, Agence du Bassin Hydraulique Sebou Haut-Commissariat au Plan Maroc are primary sources data for study. An aggregation method was used produce each component, as well overall index. A spatial assessment carried out very high within area, requiring priority intervention. findings indicated that degree 51% communes area low low, 25% moderate, while 23% level vulnerability. According geographical distribution vulnerability, rural communities northeast northwest than those center south. Based mapping resources change human Saiss mitigation adaptation measures proposed mitigate risks associated with conditions scarcity.

Language: Английский

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Spatio-temporal pattern of land use and land cover and its effects on land surface temperature using remote sensing and GIS techniques: a case study of Bhubaneswar city, Eastern India (1991–2021)

GeoJournal, Journal Year: 2021, Volume and Issue: 87(S4), P. 765 - 795

Published: Nov. 15, 2021

Language: Английский

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The Impact of Industrial Activities on The Surrounding Environment Based on Hybrid Filter and Machine Learning

Remote Sensing Applications Society and Environment, Journal Year: 2025, Volume and Issue: unknown, P. 101599 - 101599

Published: May 1, 2025

Language: Английский

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Thirty Years of Land Use/Land Cover Changes and Their Impact on Urban Climate: A Study of Kano Metropolis, Nigeria

Land, Journal Year: 2021, Volume and Issue: 10(11), P. 1106 - 1106

Published: Oct. 20, 2021

Rapid urban expansion and the alteration of global land use/land cover (LULC) patterns have contributed substantially to modification climate, due variations in Land Surface Temperature (LST). In this study, LULC change dynamics Kano metropolis, Nigeria, were analysed over last three decades, i.e., 1990–2020, using multispectral satellite data understand impact urbanization on LST study area. The Maximum Likelihood classification method Mono-window algorithm utilised classifying uses retrieving data. Spectral indices comprising Normalized Difference Vegetation Index (NDVI) Built-up (NDBI) also computed. A linear regression analysis was employed order examine correlation between surface temperature various spectral indices. results indicate significant changes 152.55 sq. km from 1991 2020. During period, city’s barren water bodies declined by approximately 172.58 26.55 km, respectively, while vegetation increased slightly 46.58 km. Further showed a negative NDVI with Pearson determination coefficient (R2) 0.6145, 0.5644, 0.5402, 0.5184 1991, 2000, 2010, 2020 respectively. NDBI correlated positively LST, having an R2 0.4132 0.3965 0.3907 0.3300 findings provide critical climatic useful policy- decision-makers optimizing use mitigating heat through sustainable development.

Language: Английский

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