Multi-decade land cover/land use dynamics and future predictions for Zambia: 2000–2030

Discover Environment, Год журнала: 2024, Номер 2(1)

Опубликована: Апрель 20, 2024

Abstract Human LULCC is the many driver of environmental changes. Accurate and up-to-date current predicted information on important in land use planning natural resource management; however, Zambia, detailed insufficient. Therefore, this study assessed dynamics LULC change (2000–2020) future projections (2020–2030) for Zambia. The ESA CCI cover maps, which have been developed from Sentinel-2 images were used study. This dataset has a grid spatial resolution 300 m 2000, 2010 2020. 31 Classification reclassified into ten (10) local Classifications using r.class module QGIS 2.18.14. 2000 maps to simulate 2020 scenario Artificial Neural Network (Multi-layer Perception) algorithms Modules Land Use Change Evaluation (MOLUSCE) plugin predict 2030 classes. reference validate model. Predicted against observed map, Kappa (loc) statistic was 0.9869. patterns successfully simulated ANN-MLP with accuracy level 95%. classes 2010–2020 calibration period. types shows an increase built-up (71.44%) decrease cropland (0.73%) map. Dense forest (0.19%), grassland (0.85%) bare (1.37%) will reduce 2020–2030. However, seasonally flooded, sparse forest, shrub land, wetland water body marginally. largest other types. insights show that can be LULCC, generated employed National Adaptation Plans at regional national scale.

Язык: Английский

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Advanced FELA-ANN framework for developing 3D failure envelopes for strip foundations on anisotropic clays

Modeling Earth Systems and Environment, Год журнала: 2023, Номер 10(2), С. 2375 - 2392

Опубликована: Дек. 16, 2023

Язык: Английский

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Proposing a new optimized forecasting model for the failure rate of power distribution network thermal equipment for educational centers

Thermal Science and Engineering, Год журнала: 2023, Номер 6(2), С. 2087 - 2087

Опубликована: Окт. 19, 2023

To gain a deep understanding of maintenance and repair planning, investigate the weak points distribution network, discover unusual events, it is necessary to trace shutdowns that occurred in network. Many incidents happened due failure thermal equipment schools. On other hand, most important task electricity companies provide reliable stable electricity, which minimal blackouts standard voltage should accompany. This research uses seasonal time series artificial neural network approaches models predict rate one used two areas covered by greater Tehran company. These data were extracted weekly from April 2019 March 2021 ENOX incident registration software. For this purpose, after pre-processing data, appropriate final model was presented with help Minitab MATLAB Also, average air temperature, rainfall, wind speed selected as input variables The mean square error has been evaluate proposed models’ rate. results show performed better than multi-layer perceptron predicting target can be future periods.

Язык: Английский

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Rural Land Degradation Assessment through Remote Sensing: Current Technologies, Models, and Applications

Remote Sensing, Год журнала: 2024, Номер 16(16), С. 3059 - 3059

Опубликована: Авг. 20, 2024

Degradation and desertification represent serious threats, as they present severe environmental socio-economic consequences, demanding immediate action. Although a recognized methodology for assessing degradation is missing, remote sensing has been powerful support its accessibility efficacy. The aim of this study to examine the application land soil desertification. A total 278 research papers retrieved from Scopus/Web Science database published over past decade have analyzed. From analysis scientific publications, rising interest these topics dominance China registered. Established satellite data, Landsat, MODIS, despite limitations in accuracy resolution, remain popular due easy access. This restricts broader scales limits practical applications like management. prevalent use vegetation indexes, while convenient, can be misleading their indirect connection health. Consequently, vegetation-based models may not fully capture complexities involved. To improve understanding, suggests shift towards multi-indexes move away relying solely on readily available data products. Moreover, fusion methods could provide more holistic view.

Язык: Английский

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Quantifying LULC changes in Urmia Lake Basin using machine learning techniques, intensity analysis and a combined method of cellular automata (CA) and artificial neural networks (ANN) (CA-ANN)

Modeling Earth Systems and Environment, Год журнала: 2023, Номер 10(2), С. 2011 - 2030

Опубликована: Ноя. 26, 2023

Язык: Английский

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Application of Remote Sensing for Identifying Soil Erosion Processes on a Regional Scale: An Innovative Approach to Enhance the Erosion Potential Model

Remote Sensing, Год журнала: 2024, Номер 16(13), С. 2390 - 2390

Опубликована: Июнь 28, 2024

Soil erosion represents a complex ecological issue that is present on global level, with negative consequences for environmental quality, the conservation and availability of natural resources, population safety, material security, both in rural urban areas. To mitigate harmful effects soil erosion, map can be created. Broadly applied Balkan Peninsula region (Serbia, Bosnia Herzegovina, Croatia, Slovenia, Montenegro, North Macedonia, Romania, Bulgaria, Greece), Erosion Potential Method (EPM) an empirical model widely process creating maps. In this study, innovation identification mapping processes was made, coefficient types extent slumps (φ), representing one most sensitive parameters EPM. The (φ) consisted applying remote sensing methods satellite images from Landsat mission. research area which were obtained thematic maps (coefficient φ) created Federation Herzegovina Brčko District (situated Herzegovina). Google Earth Engine (GEE) platform employed to retrieve 7 Enhanced Thematic Mapper plus (ETM+) 8 Operational Land Imager Thermal Infrared Sensor (OLI/TIRS) imagery over period ten years (from 1 January 2010 31 December 2020). performed based Bare Index (BSI) by equation fractional bare cover. spatial–temporal distribution cover enabled definition values field. An accuracy assessment conducted 190 reference samples field using confusion matrix, overall (OA), user (UA), producer (PA), Kappa statistic. Using OA 85.79% obtained, while UA ranged 33% 100%, PA 50% 100%. Applying statistic, 0.82 indicating high level accuracy. time series multispectral each month crucial element monitoring occurrence various (surface, mixed, deep) Additionally, it contributes significantly decision-making, strategies, plans domain control work, development identifying erosion-prone areas, defense against torrential floods, creation at local, regional, national levels.

Язык: Английский

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Soil erosion vulnerability and soil loss estimation for Siran River watershed, Pakistan: an integrated GIS and remote sensing approach

Environmental Monitoring and Assessment, Год журнала: 2023, Номер 196(1)

Опубликована: Дек. 30, 2023

Язык: Английский

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Spatiotemporal change analysis of LULC using remote sensing and CA-ANN approach in the Hodna basin, NE of Algeria

Physics and Chemistry of the Earth Parts A/B/C, Год журнала: 2023, Номер 133, С. 103535 - 103535

Опубликована: Дек. 25, 2023

Язык: Английский

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Evaluating machine learning performance in predicting sodium adsorption ratio for sustainable soil-water management in the eastern Mediterranean

Journal of Environmental Management, Год журнала: 2024, Номер 370, С. 122640 - 122640

Опубликована: Сен. 27, 2024

Язык: Английский

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Robust models to predict the secondary compression index of fine-grained soils using multi objective evolutionary polynomial regression analysis

Modeling Earth Systems and Environment, Год журнала: 2023, Номер 10(1), С. 157 - 165

Опубликована: Апрель 21, 2023

Язык: Английский

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