Glacial lake mapping using remote sensing Geo-Foundation Model

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2025, Volume and Issue: unknown, P. 104371 - 104371

Published: Jan. 1, 2025

Language: Английский

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Regional differences and distribution dynamic evolution of rural digital economy development under the background of sustainable development

GeoJournal, Journal Year: 2025, Volume and Issue: 90(2)

Published: Feb. 20, 2025

Language: Английский

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Spatio-temporal analysis of urban expansion and land use dynamics using google earth engine and predictive models

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

Published: Feb. 27, 2025

Urban expansion and changes in land use/land cover (LULC) have intensified recent decades due to human activity, influencing ecological developmental landscapes. This study investigated historical projected LULC urban growth patterns the districts of Multan Sargodha, Pakistan, using Landsat satellite imagery, cloud computing, predictive modelling from 1990 2030. The analysis images was grouped into four time periods (1990–2000, 2000–2010, 2010–2020, 2020–2030). Google Earth Engine cloud-based platform facilitated classification 5 ETM (1990, 2000, 2010) 8 OLI (2020) Random Forest model. A simulation model integrating Cellular Automata an Artificial Neural Network Multilayer Perceptron MOLUSCE plugin QGIS employed forecast resulting maps showed consistently high accuracy levels exceeding 92% for both across all periods. revealed that Multan's built-up area increased 240.56 km2 (6.58%) 440.30 (12.04%) 2020, while Sargodha experienced more dramatic 730.91 (12.69%) 1,029.07 (17.83%). Vegetation remained dominant but significant variations, particularly peri-urban areas. By 2030, is stabilize at 433.22 km2, primarily expanding southeastern direction. expected reach 1,404.97 showing balanced multi-directional toward northeast north. presents effective analytical method processing, GIS, change modeling evaluate spatiotemporal changes. approach successfully identified main transformations trends areas highlighting potential urbanization zones where opportunities exist developing planned managed settlements.

Language: Английский

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Digital Economy Driving Rural Revitalization: Current Status, Challenges, and Future Pathways

Published: Feb. 25, 2025

With the rapid development of information technology, digital economy has become a significant driver global economic growth. In China, not only fosters urban but also plays crucial role in rural revitalization. This paper, based on detailed analysis elements such as public infrastructure, level digitalization services, and transformation industries, explores foundational realities implementation pathways empowering The study summarizes successful experiences supporting revitalization provides policy recommendations for future development. research dictates that is gradually becoming core driving force revitalization, aiding sustainable areas China.

Language: Английский

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A Portable Electronic Nose Based on Convolutional Neural Network for Beer Identification

Food Control, Journal Year: 2025, Volume and Issue: unknown, P. 111371 - 111371

Published: April 1, 2025

Language: Английский

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Snow cover variability assessment and its interplay with hydro-climatic characteristics in data scarce region of Gilgit-Baltistan, Pakistan

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 382, P. 125375 - 125375

Published: April 16, 2025

Language: Английский

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Estimation of Flood Inundation Area Using Soil Moisture Active Passive Fractional Water Data with an LSTM Model

Sensors, Journal Year: 2025, Volume and Issue: 25(8), P. 2503 - 2503

Published: April 16, 2025

Accurate flood monitoring and forecasting techniques are important continue to be developed for improved disaster preparedness mitigation. Flood estimation using satellite observations with deep learning algorithms is effective in detecting patterns environmental relationships that may overlooked by conventional methods. Soil Moisture Active Passive (SMAP) fractional water (FW) was used as a reference estimate areas long short-term memory (LSTM) model combination of soil moisture information, rainfall forecasts, floodplain topography. To perform modeling LSTM, datasets different spatial resolutions were resampled 30 m resolution bicubic interpolation. The model’s efficacy quantified validating the LSTM-based inundation area mask from Senti-nel-1 SAR images regions topographic characteristics. average under curve (AUC) value LSTM 0.93, indicating high accuracy FW. confusion matrix-derived metrics validate had high-performance ~0.9. SMAP FW showed optimal performance low-covered vegetation, seasonal variations flat regions. estimates show methodological promise proposed framework resilience.

Language: Английский

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Community perceptions of potable water quality and public health implications in flood-affected areas of Nowshera District, Pakistan

World Development Perspectives, Journal Year: 2025, Volume and Issue: 38, P. 100679 - 100679

Published: April 18, 2025

Language: Английский

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Enhancing soil moisture retrieval in semi-arid regions using machine learning algorithms and remote sensing data

Applied Soil Ecology, Journal Year: 2024, Volume and Issue: 204, P. 105687 - 105687

Published: Oct. 16, 2024

Language: Английский

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Assessing the Cost of Hospital Building Materials: Effects of Temperature-Precipitation-Flood Dynamics on Landuse and Landcover

Rangeland Ecology & Management, Journal Year: 2024, Volume and Issue: 99, P. 1 - 17

Published: Dec. 31, 2024

Language: Английский

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