Carbon storage and sequestration in a eucalyptus productive zone in the Brazilian Cerrado, using the Ca-Markov/Random Forest and InVEST models

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 444, P. 141291 - 141291

Published: Feb. 15, 2024

Language: Английский

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Modeling and Estimating the Land Surface Temperature (LST) Using Remote Sensing and Machine Learning (Case Study: Yazd, Iran)

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(3), P. 454 - 454

Published: Jan. 24, 2024

The pressing issue of global warming is particularly evident in urban areas, where thermal islands amplify the effect. Understanding land surface temperature (LST) changes crucial mitigating and adapting to effect heat islands, ultimately addressing broader challenge warming. This study estimates LST city Yazd, Iran, field high-resolution image data are scarce. assessed through parameters (indices) available from Landsat-8 satellite images for two contrasting seasons—winter summer 2019 2020, then it estimated 2021. modeled using six machine learning algorithms implemented R software (version 4.0.2). accuracy models measured root mean square error (RMSE), absolute (MAE), logarithmic (RMSLE), standard deviation different performance indicators. results show that gradient boosting model (GBM) algorithm most accurate estimating LST. albedo NDVI features with greatest impact on both (with 80.3% 11.27% importance) winter 72.74% 17.21% importance). 2021 showed acceptable seasons. GBM each seasons useful modeling based learning, support decision-making related spatial variations temperatures. method developed can help better understand island mitigation strategies improve human well-being enhance resilience climate change.

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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Advanced CMD predictor screening approach coupled with cellular automata-artificial neural network algorithm for efficient land use-land cover change prediction

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 449, P. 141822 - 141822

Published: March 19, 2024

Language: Английский

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Investigation of changes in land use/land cover using principal component analysis and supervised classification from operational land imager satellite data: a case study of under developed regions, Pakistan

Discover Sustainability, Journal Year: 2024, Volume and Issue: 5(1)

Published: April 22, 2024

Abstract Monitoring and understanding Land Use/Land Cover (LU/LC) is critical for sustainable development, as it can impact various environmental, social, economic systems. For example, deforestation land degradation lead to soil erosion, loss of biodiversity, greenhouse gas emissions, affecting the quality soil, air, water resources. The present research examined changes in within underdeveloped regions Balochistan Sindh provinces, which are situated Pakistan. In order monitor temporal variations LU/LC, we employed Geographic Information System (GIS) technique, conduct an analysis satellite imagery obtained from Landsat 8 Operational Imager (OLI) during time period spanning 2013 2023. obtain accurate LU/LC classification, used principal component (PCA) a supervised classification approach using maximum likelihood algorithm (MLC). According results our study, there was decrease extent bodies (− 593.24 km 2 ) vegetation 68.50 by − 3.43% 0.40% respectively. contrast, area occupied settlements investigated region had 2.23% rise, reaching total 385.66 square kilometers. Similarly, barren also expanded 1.60%, encompassing 276.04 kilometers, course last decade. overall accuracy (94.25% 95.75%) K value (91.75% 93.50%) were achieved year 2023 enhancement agricultural output Pakistan utmost importance improve income farmers, mitigate food scarcity, stimulate growth, facilitate expansion exports. To enhance productivity, recommended that government undertake targeted initiatives aimed at enhancing infrastructure optimizing use foster ecological framework. Integrating framework provides foundation informed decision-making effective resource management. By identifying areas urban expansion, intensification, or alterations natural stakeholders design conservation strategies, mitigating potential environmental promoting biodiversity conservation. conclusion, integration GIS Remote Sensing (RS) may effectively monitoring patterns over time. This combined offers valuable insights recommendations judicious optimal management resources, well informing policy decisions.

Language: Английский

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Peri-urban dynamics: assessing expansion patterns and influencing factors

Ecological Processes, Journal Year: 2024, Volume and Issue: 13(1)

Published: Aug. 7, 2024

Abstract Background Peri-urbanization, the expansion of large metropolitan centers into adjacent peri-urban regions, is a growing concern due to land scarcity and escalating housing costs. These zones, blend rural urban features, blur line between areas, creating new landscapes. This study examines historical, present, potential growth trends in area surrounding Durgapur Municipal Corporation (DMC). Analytical techniques spatial metrics are used track development intensity changes over time, including built-up density, Shannon’s entropy, Landscape index, Average Weighted Mean Expansion Index, Annual Built-Up Rate, Intensity Difference Index. indices like Patch Density, Edge Shape Largest Ratio Open Space, Area Fractal understand fragmentation, connectivity, relationships. The Logistic Regression Model (LRM) identify influencing factors CA-Markov modeling for future areas. Results Between 1991 2001, region increased significantly, primarily near industrial roadways, mining was concentrated western sector National Highway-2 (NH-2). Urban sprawl continuous trend, with highest density South-South-East (SSE) direction from 2011. Additionally, key determinant distance city core. By 2031, expected concentrate southeast reaching 177.90 km 2 . Conclusions attributed other infrastructure. identifies center as significant factor development. results emphasize need inclusive planning methods prioritizing sustainable principles prudent resource management efficient DMC’s area.

Language: Английский

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Comparative analysis of land use changes modeling based-on new hybrid models and CA-Markov in the Urmia Lake basin

Advances in Space Research, Journal Year: 2024, Volume and Issue: 74(8), P. 3749 - 3764

Published: July 6, 2024

Language: Английский

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Monitoring and modeling vulnerability of land use changes in the current flood hazard conditions using novel hybrid GIS-based approaches and remote sensing data

Earth Science Informatics, Journal Year: 2025, Volume and Issue: 18(2)

Published: Jan. 18, 2025

Language: Английский

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Defining Urban Growth Boundary in Semarang City: Integrating Spatial Planning and Predictive Modeling Techniques

IOP Conference Series Earth and Environmental Science, Journal Year: 2025, Volume and Issue: 1443(1), P. 012037 - 012037

Published: Jan. 1, 2025

Abstract Understanding the maximum percentage of urban area within an administrative region, such as Semarang City, necessitates examination spatial planning schemes, development regulations, and local government policies. Concurrently, cellular automata Markov chain approaches can be used to predict how cities will grow in future accurately. This study aims define growth boundary City by integrating with predictive modeling techniques. The Cellular automata-Markov (CA-MC) method predicts developments based on current land use patterns. seeks delineate areas suitable for using data analysis while preserving critical ecological agricultural zones. findings this research contribute formulating informed policies aimed at achieving balanced expansion environmental conservation Semarang, thus fostering resilient inclusive landscapes city.

Language: Английский

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Influence of Avocado Plantations as Driver of Land Use and Land Cover Change in Chile’s Aconcagua Basin

Land, Journal Year: 2025, Volume and Issue: 14(4), P. 750 - 750

Published: April 1, 2025

Land use and land cover (LULC) change is a dynamic process influenced by various factors, including agricultural expansion. In Chile’s Aconcagua Basin, avocado plantations are potentially driving territorial transformations. However, current data lacks the resolution required to accurately assess this impact. Accordingly, our study used advanced geospatial analysis techniques address gap. Through detailed of spatial temporal changes, it was determined that most significant expansion occurred between 2003 2013, with an increase 402%. This growth primarily took place at expense native vegetation, particularly sclerophyllous shrubland, as well other lands, near urban lands. By 2023, changes in plantation were significantly slower, minimal alterations LULC (5%), suggesting possible influence drought on small-scale farmers. small loss mainly replaced fruit farm land. Moreover, findings suggest while have become larger, more dominant, isolated, vegetation has fragmented reduced patch size. Based these results, sustainable management practices proposed. These provide crucial foundation for developing strategies balance production environmental sustainability, landscape transformation well-being local communities.

Language: Английский

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