Cited by Tracking land use and land cover changes in Ghaziabad district of India using machine learning and Google Earth engine

Effects of urban sprawl due to migration on spatiotemporal land use-land cover change: a case study of Bartın in Türkiye DOI

Gökhan Şen

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 4, 2025

Rapid urban growth is a subject of worldwide interest due to environmental problems. Population growth, especially migration from rural areas, leads land use and cover (LULCC) changes in centres. Therefore, LULCC analyses are among the studies that will help decision-makers achieve better sustainable management planning. The objective this study was ascertain impact urbanization, which resulted migration, on alterations LULCC, with particular focus forest areas surrounding Bartın city centre between 2000 2020. Spatial databases for two periods were used determine growth. spatial temporal patterns quantified by interpreting data. Remote sensing (RS) geographical information systems (GIS) have been data collection, analysis, presentation. assessed under nine classes using optical remote methods stand-type maps created aerial photos. To how affects status transition matrices each five sprawl zones around city. annual change determined "annual rate". results indicate urbanization 2020 increased approximately 19% (2510645.82 m2). However, did not harm forests; 10.32% (174729.65 m²) over same period. process particularly evident open agricultural zones. During period, there 37% reduction (2943229.85 59% (1265457.76 m²). can be attributed its demographic structure, mainly includes population emergence new job opportunities. Factors such as challenging living conditions, insecure environments because increase temporary foreign asylum seekers, retirees returning their hometowns believed contributed

Language: Английский

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The spatial impact of population semi-urbanization on sulfur dioxide emissions: Empirical evidence from China DOI

Zhenhua Zhang, Chao Hua, Xueli Chen

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 375, P. 124257 - 124257

Published: Jan. 25, 2025

Language: Английский

Citations

Evaluating urban climate resilience in the Yangtze River Delta urban agglomeration: A novel method integrating the DPSIR model and Sustainable Development Goals DOI

Ronghua Yi, Yanan Chen, An Chen

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 376, P. 124517 - 124517

Published: Feb. 18, 2025

Language: Английский

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Monitoring of wetland turbidity using multi-temporal Landsat-8 and Landsat-9 satellite imagery in the Bisalpur wetland, Rajasthan, India DOI

Raj Singh, Vara Saritha,

Chaitanya B. Pande

et al.

Environmental Research, Journal Year: 2023, Volume and Issue: 241, P. 117638 - 117638

Published: Nov. 14, 2023

Language: Английский

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Quantifying the Impacts of Climate and Land Cover Changes on the Hydrological Regime of a Complex Dam Catchment Area DOI

Muhammad Umer Masood, Saif Haider, Muhammad Rashid

et al.

Sustainability, Journal Year: 2023, Volume and Issue: 15(21), P. 15223 - 15223

Published: Oct. 24, 2023

In this study, hydrological modeling at the watershed level is used to assess impacts of climate and land use changes on catchment area Khanpur Dam, which an important water source for Rawalpindi Islamabad. The impact past anticipated precipitation in Dam was forecast by using a HEC-HMS model. After calibration, framework employed analyze effects cover regime. model information from three climatic gauge stations (Murree, Islamabad Zero Point, Dam) split into five sub-basins that encompass entire region, each with distinctive characteristics. evaluated checked 2016–2018 2019–2020, it produced excellent match actual flows. statistical downscaling CMhyd model, most effective performing GCM (MPI-ESM1-2-HR) among four GCMs chosen projections temperature within two shared socioeconomic pathways (SSP2 SSP5). predictions were incorporated calibrated evaluate potential change Dam. starting point era (1990–2015) projected period (2016–2100), encompassed basis present century, analyzed annually. results indicated spike SSPs, predicted boost inflows all year. Until end twenty-first SSP2 21 percent rise area, while SSP5 28% precipitation. Increased flows found be future. It could also effectively upcoming studies basin.

Language: Английский

Citations

Delineation of environmentally sustainable urban settlement using GIS-based MIF and AHP techniques DOI

Nitin Liladhar Rane,

Saurabh P. Choudhary,

Arjun Saha

et al.

Geocarto International, Journal Year: 2024, Volume and Issue: 39(1)

Published: Jan. 1, 2024

Choosing appropriate locations for built-up growth while maintaining natural balance has become necessary sustainable urban planning. To this end, two multi-criteria decision-making (MCDM) approaches—the multi-influencing factor (MIF) and the analytical hierarchy process (AHP)—have been applied in work. The MIF model results show that 23.546% of study region was very highly suitable newly areas, 18.786% restricted settlement, whereas, AHP model, 28.907% area suitable, 17.619% settlement. Finally, dependability efficiency models used were assessed through receiver operating curve (ROC) under (AUC) analysis. comparative analysis demonstrates approach (AUC 0.817) is more reliable than 0.783). present work provides new insights to integrate GIS tools with MCDM practical land suitability assessment.

Language: Английский

Citations

A Comprehensive Assessment of Climate Change and Anthropogenic Effects on Surface Water Resources in the Lake Urmia Basin, Iran DOI

Mohammad Kazemi Garajeh, Rojin Akbari,

Sepide Aghaei Chaleshtori

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(11), P. 1960 - 1960

Published: May 29, 2024

In recent decades, the depletion of surface water resources within Lake Urmia Basin (LUB), Iran, has emerged as a significant environmental concern. Both anthropogenic activities and climate change have influenced availability distribution in this area. This research endeavors to provide comprehensive evaluation impacts on across LUB. Various critical climatic factors affecting bodies, such air temperature (AT), cropland (CL), potential evapotranspiration (PET), snow cover, precipitation, built-up areas, groundwater salinity, were analyzed from 2000 2021 using Google Earth Engine (GEE) cloud platform. The JRC-Global mapping layers V1.4, with spatial resolution 30 m, employed monitor patterns. Additionally, Mann–Kendall (MK) non-parametric trend test was utilized identify statistically trends time series data. results reveal negative correlations −0.56, −0.89, −0.09, −0.99, −0.79 between AT, CL, salinity resources, respectively. Conversely, positive 0.07 0.12 observed precipitation PET Notably, findings indicate that approximately 40% bodies LUB remained permanent over past four decades. However, there been loss around 30% transitioning into seasonal which now account for nearly 13% total. our also December January are months most presence 1984 2021. is because these align winter LUB, during no consumption agriculture sector. driest study area August, September, October, almost at zero percent. These coincide summer autumn seasons summary, underscore impact human compared variables.

Language: Английский

Citations

Impact of land use/land cover changes on evapotranspiration and model accuracy using Google Earth engine and classification and regression tree modeling DOI

Chaitanya B. Pande,

Pranaya Diwate, Israel R. Orimoloye

et al.

Geomatics Natural Hazards and Risk, Journal Year: 2023, Volume and Issue: 15(1)

Published: Dec. 22, 2023

This research uses a Classification and Regression Tree (CART) model with Google Earth Engine (GEE) to assess the winter season's land cover change detection mapping impact on evapotranspiration (crop water requirement) parameters. Winter seasons, crucial for agricultural planning, irrigation requirement challenges in accurately detecting changes due dynamic nature of farming practices during this period. In study, Landsat-8 OLI images have been combined map Land use (LULC) other Akola Block, Maharashtra, India, 2018–2022 season. As an discoverer researcher that found detailed information LULC classes last 2018 2022 CART combination cloud-computing GEE demonstrates be practical approach accurate classification maps create pixel-based seasons study area. The novelty lies its innovative GEE, powerful platform remote sensing geospatial analysis, remarkable accuracy. Achieving 100% training accuracy across four years under consideration is exceptional feat, highlighting reliability stability methodology. Furthermore, validation values, ranging from 89 94% 2022, underscore robustness approach. Such consistently high over time groundbreaking achievement offers new dimension field hydrology. For hydrological community, implications are profound. Accurate provide critical data modeling analyzing effects resources, watershed management, quality. User, Kappa, Producer metrics used highlight model's performance suitability applications. These can aid development models, forecasting, decision-making processes, ultimately contributing more effective resource management environmental conservation. summary, study's mapping, relevance community demonstrate potential advanced tools significantly improve our understanding their resources management.

Language: Английский

Citations

High-resolution remote sensing data-based urban heat island study in Chongqing and Changde City, China DOI

Tao Hai, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Mou Leong Tan

et al.

Theoretical and Applied Climatology, Journal Year: 2024, Volume and Issue: 155(7), P. 7049 - 7076

Published: June 11, 2024

Language: Английский

Citations

Evaluation of the intensity of urban heat islands during heat waves using local climate zones in the semi-arid, continental climate of Tehran DOI

Gholamreza Roshan,

Saleh Arekhi,

Zainab Bayganeh

et al.

Urban Climate, Journal Year: 2024, Volume and Issue: 56, P. 102079 - 102079

Published: July 1, 2024

Language: Английский

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