Assessing the impacts of forest cover change on carbon stock and soil moisture dynamics using geospatial techniques: a case study of Nensebo forest, Southern Ethiopia

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

Published: Jan. 14, 2025

Language: Английский

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Research Overview on Urban Heat Islands Driven by Computational Intelligence

Land, Journal Year: 2024, Volume and Issue: 13(12), P. 2176 - 2176

Published: Dec. 13, 2024

In recent years, the intensification of urban heat island (UHI) effect has become a significant concern as urbanization accelerates. This survey comprehensively explores current status surface UHI research, emphasizing role land use and cover changes (LULC) in environments. We conducted systematic review 8260 journal articles from Web Science database, employing bibliometric analysis keyword co-occurrence using CiteSpace to identify research hotspots trends. Our investigation reveals that vegetation types are two most critical factors influencing intensity. analyze various computational intelligence techniques, including machine learning algorithms, cellular automata, artificial neural networks, used for simulating expansion predicting effects. The study also examines numerical modeling methods, Weather Research Forecasting (WRF) model, while examining application Computational Fluid Dynamics (CFD) microclimate research. Furthermore, we evaluate potential mitigation strategies, considering planning approaches, green infrastructure solutions, high-albedo materials. comprehensive not only highlights relationship between dynamics UHIs but provides direction future intelligence-driven climate studies.

Language: Английский

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Developing a Semi-Automated Technique of Surface Water Quality Analysis Using GEE And Machine Learning: A Case Study for Sundarbans

Heliyon, Journal Year: 2025, Volume and Issue: 11(3), P. e42404 - e42404

Published: Feb. 1, 2025

This study presents a semi-automated approach for assessing water quality in the Sundarbans, critical and vulnerable ecosystem, using machine learning (ML) models integrated with field remotely-sensed data. Key parameters-Sea Surface Temperature (SST), Total Suspended Solids (TSS), Turbidity, Salinity, pH-were predicted through ML algorithms interpolated Empirical Bayesian Kriging (EBK) model ArcGIS Pro. The predictive framework leverages Google Earth Engine (GEE) AutoML, utilizing deep libraries to create dynamic, adaptive that enhance prediction accuracy. Comparative analyses showed ML-based effectively captured spatial temporal variations, aligning closely measurements. integration provides more efficient alternative traditional methods, which are resource-intensive less practical large-scale, remote areas. Our findings demonstrate this technique is valuable tool continuous monitoring, particularly ecologically sensitive areas limited accessibility. also offers significant applications climate resilience policy-making, as it enables timely identification of deteriorating trends may impact biodiversity ecosystem health. However, acknowledges limitations, including variability data availability inherent uncertainties predictions dynamic systems. Overall, research contributes advancement monitoring techniques, supporting sustainable environmental management practices Sundarbans against emerging challenges.

Language: Английский

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Urban Expansion-Induced Land Use Land Cover Changes and the Subsequent Changes in Ecosystem Service and Land Surface Temperature in the Central Highland of Ethiopia

Environmental and Sustainability Indicators, Journal Year: 2025, Volume and Issue: unknown, P. 100626 - 100626

Published: Feb. 1, 2025

Language: Английский

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The last urban frontier—assessing hotspots of urban change associated with LCLUC in Africa

Frontiers in Sustainable Cities, Journal Year: 2025, Volume and Issue: 7

Published: Feb. 28, 2025

Urbanization is one of the leading drivers Land Cover Use Change (LCLUC) globally, and African countries are at forefront urban expansion trends, specifically in small medium sized cities. Multiresolution spatial datasets can be used to guide sustainable management assess progress towards U.N. Sustainable Development Goals (SDGs), SDG 11.3.1 indicator (the relationship between land consumption rate population growth rate) track change. We present a two-tiered imaging approach identifying change hotspots three 2016 2020 characterize secondary cities that have an ratio greater two (Mekelle, Ethiopia; Polokwane, South Africa, Benin City, Nigeria). This indicates outpaces where patterns include leapfrog development, infill, corridors revealing dynamic administrative boundaries. propose “pixels people” defines not only form but includes function multiple scales fine resolution depictions local engagement create more robust, comprehensive for planning.

Language: Английский

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Spatial analysis of urban expansion and its effects on land surface temperature using geospatial techniques in Addis Ababa and Shaggar Cities, Ethiopia

All Earth, Journal Year: 2025, Volume and Issue: 37(1), P. 1 - 23

Published: April 17, 2025

Language: Английский

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Spatial Analysis of Land Use and Cover Changes: Implications of Green Legacy initiative on climate action in Upper Awash Basin, Ethiopia

Trees Forests and People, Journal Year: 2025, Volume and Issue: unknown, P. 100875 - 100875

Published: April 1, 2025

Language: Английский

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Synergistic effects of carbon and heat under disturbance of human activities: Evidence from a resource-based city of China

Environmental Pollution, Journal Year: 2024, Volume and Issue: unknown, P. 125424 - 125424

Published: Dec. 1, 2024

Language: Английский

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Evaluating ecological impacts through geospatial analysis of land use land cover dynamics in Jarmet wetland ecosystems in Western Ethiopia

ENVIRONMENTAL SYSTEMS RESEARCH, Journal Year: 2024, Volume and Issue: 13(1)

Published: Dec. 18, 2024

Language: Английский

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