Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of Lahore district Pakistan

Environmental Monitoring and Assessment, Journal Year: 2022, Volume and Issue: 195(1)

Published: Nov. 17, 2022

Language: Английский

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Modelling of land use and land cover changes and prediction using CA-Markov and Random Forest

Geocarto International, Journal Year: 2023, Volume and Issue: 38(1)

Published: May 3, 2023

We used the Cellular Automata Markov (CA-Markov) integrated technique to study land use and cover (LULC) changes in Cholistan Thal deserts Punjab, Pakistan. plotted distribution of LULC throughout desert terrain for years 1990, 2006 2022. The Random Forest methodology was utilized classify data obtained from Landsat 5 (TM), 7 (ETM+) 8 (OLI/TIRS), as well ancillary data. maps generated using this method have an overall accuracy more than 87%. CA-Markov forecast usage 2022, were projected 2038 by extending patterns seen A CA-Markov-Chain developed simulating long-term landscape at 16-year time steps 2022 2038. Analysis urban sprawl carried out (RF). Through Chain analysis, we can expect that high density low-density residential areas will grow 8.12 12.26 km2 18.10 28.45 2038, inferred occurred 1990 showed there would be increased urbanization terrain, with probable development croplands westward northward, growth centers. findings potentially assist management operations geared towards conservation wildlife eco-system region. This also a reference other studies try project arid are undergoing land-use comparable those study.

Language: Английский

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Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms

Frontiers in Environmental Science, Journal Year: 2023, Volume and Issue: 10

Published: Jan. 5, 2023

The landscape of Pakistan is vulnerable to flood and periodically affected by floods different magnitudes. aim this study was aimed assess the flash susceptibility district Jhelum, Punjab, using geospatial model Frequency Ratio Analytical Hierarchy Process. Also, considered eight most influential flood-causing parameters are Digital Elevation Model, slop, distance from river, drainage density, Land use/Land cover, geology, soil resistivity (soil consisting rocks formation) rainfall deviation. data collected weather stations in vicinity area. Estimated weight allotted each flood-inducing factors with help AHP FR. Through use overlay analysis, were brought together, value density awarded maximum possible score. According several areas region based on have been classified zones viz, very high risk, moderate low risk. In light results obtained, 4% area that accounts for 86.25 km 2 at risk flood. like Bagham, Sohawa, Domeli, Turkai, Jogi Tillas, Chang Wala, Dandot Khewra located elevation. Whereas Potha, Samothi, Chaklana, Bagrian, Tilla Jogian, Nandna, Rawal high-risk damaged badly history This first its kind conducted Jhelum District provides guidelines disaster management authorities response agencies, infrastructure planners, watershed management, climatologists.

Language: Английский

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Identification of time-varying wetlands neglected in Pakistan through remote sensing techniques

Environmental Science and Pollution Research, Journal Year: 2023, Volume and Issue: 30(29), P. 74031 - 74044

Published: May 18, 2023

Language: Английский

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Assessing climatic impacts on land use and land cover dynamics in Peshawar, Khyber Pakhtunkhwa, Pakistan: a remote sensing and GIS approach

GeoJournal, Journal Year: 2024, Volume and Issue: 89(5)

Published: Aug. 31, 2024

Language: Английский

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Agricultural land suitability analysis of Southern Punjab, Pakistan using analytical hierarchy process (AHP) and multi-criteria decision analysis (MCDA) techniques

Cogent Food & Agriculture, Journal Year: 2024, Volume and Issue: 10(1)

Published: Jan. 16, 2024

Agricultural Land Suitability Analysis plays a pivotal role in sustainable land use planning, aiding decision-makers identifying areas most conducive to agriculture. This study employs systematic approach integrating Analytical Hierarchy Process and Multi-Criteria Decision techniques assess prioritize the suitability of agricultural Southern Punjab (Multan region). The methodology involves defining clear objectives, relevant criteria sub-criteria, establishing hierarchical structure conducting pairwise comparisons determine relative importance each factor. Our outcomes indicated that almost 43% area was highly suitable for agriculture, 27% moderately suitable, 16% marginally 8% less 6% not agriculture area. All lands had silty clay or type soil, which sandy loam soil Multan region. output is comprehensive map identifies Sensitivity analysis validation are incorporated enhance robustness reliability results. provides valuable tool planners policymakers make informed decisions regarding allocation, contributing practices resource management.

Language: Английский

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Changing pattern of urban landscape and its impact on thermal environment of Lahore; Implications for climate change and sustainable development

Environmental Monitoring and Assessment, Journal Year: 2025, Volume and Issue: 197(2)

Published: Jan. 9, 2025

Language: Английский

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Monitoring the population change and urban growth of four major Pakistan cities through spatial analysis of open source data

Annals of GIS, Journal Year: 2023, Volume and Issue: 29(3), P. 355 - 367

Published: Jan. 17, 2023

Cities are complex and dynamic entities in close proximity of people, implying multi temporal observations to analyse understand the urban context. At present, open-source data geospatial intelligence becoming important means exploring, monitoring predicting status area growth population increase. In last few decades, unemployment absence infrastructures rural areas promoted unplanned haphazard urbanization across centres Pakistan. This study focuses on exploring potential open-source/freely available datasets for city mapping spatially. The gives a spatial perspective rapidly growing cities Pakistan using Google Earth Engine classify Landsat images over four discovers sprawl patterns cities. works out that built-up is significantly increasing with decades there strong positive correlation between expansion. Using Open-Source Data (Landsat LandScan data), this has offered technical solution Engine-supported analysis statistics machine learning spatially change major It undoubted our working results will provide timely cost-effective information policymakers, Govt Officials citizens more sustainable urbanization.

Language: Английский

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Land subsidence analysis using synthetic aperture radar data

Heliyon, Journal Year: 2023, Volume and Issue: 9(3), P. e14690 - e14690

Published: March 1, 2023

Land subsidence is considered a threat to developing cities and triggered by several natural (geological seismic) human (mining, groundwater withdrawal, oil gas extraction, constructions) factors. This research has gathered datasets consisting of 80 Sentinel-1A ascending descending SLC images from July 2017 2019. dataset, concerning InSAR PS-InSAR, processed with SARPROZ software determine the land in Gwadar City, Balochistan, Pakistan. Later, maps were created ArcGIS 10.8. Due InSAR’s limitations measuring millimeter-scale surface deformation, Multi-Temporal techniques, like are introduced provide better accuracy, consistency, fewer errors deformation analysis. remote-based SAR technique helpful area; for researchers, city mobility constrained become more restricted post-Covid-19. requires multiple acquired same place at different times estimating per year, along uplifting subsidence. The results showed maximum Koh-i-Mehdi Mountain PS-InSAR up −92 mm/year track −66 area Mountain, −48 −32 deep seaport. From our experimental results, high rate been found newly evolving City. very beneficial country’s economic development because its deep-sea port, developed China-Pakistan Economic Corridor (CPEC). associated detailed analysis identifying areas significant subsidence, enlisting possible causes that needed be resolved before further developments. Our findings urban disaster monitoring as being promoted next seaport start CPEC.

Language: Английский

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GIS-based flood susceptibility mapping using bivariate statistical model in Swat River Basin, Eastern Hindukush region, Pakistan

Frontiers in Environmental Science, Journal Year: 2023, Volume and Issue: 11

Published: July 6, 2023

Frequent flooding can greatly jeopardize local people’s lives, properties, agriculture, economy, etc. The Swat River Basin (SRB), in the eastern Hindukush region of Pakistan, is a major flood-prone basin with long history devastating floods and substantial socioeconomic physical damages. Here we produced flood susceptibility map SRB, using frequency ratio (FR) bivariate statistical model. A database was created that comprised inventory as dependent variable causative factors (slope, elevation, curvature, drainage density, topographic wetness index, stream power land use cover, normalized difference vegetation rainfall) independent variables association between them were quantified. Data collected remote sensing sources, field surveys, available literature, all studied resampled to 30 m resolution spatially distributed. results show about 26% areas are very high highly susceptible flooding, 19% moderate, whereas 55% low SRB. Overall, southern SRB compared their northern counterparts, while slope, curvature vital susceptibility. Our model’s success prediction rates 91.6% 90.3%, respectively, based on ROC (receiver operating characteristic) curve. findings this study will lead better management control risk region. study’s assist decision-makers make appropriate sustainable strategies for mitigation future damage

Language: Английский

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