Monitoring landuse change in Uchhali and Khabeki wetland lakes, Pakistan using remote sensing data

Gondwana Research, Год журнала: 2024, Номер 129, С. 252 - 267

Опубликована: Янв. 4, 2024

Язык: Английский

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Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data

Remote Sensing, Год журнала: 2024, Номер 16(5), С. 928 - 928

Опубликована: Март 6, 2024

Wetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, ecologically significant wetland ecosystem in Pakistan, using advanced geospatial machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral water indices, land cover classification, change detection risk mapping examine moisture variability, modifications, area changes proximity-based threats over two decades. The random forest algorithm attained highest accuracy (89.5%) for classification based on rigorous k-fold cross-validation, with a training 91.2% testing 87.3%. demonstrates model’s effectiveness robustness vulnerability modeling area, showing 11% shrinkage open bodies since 2000. Inventory zoning revealed 30% present-day areas under moderate high vulnerability. cellular automata–Markov (CA–Markov) model predicted continued long-term declines driven by swelling anthropogenic like 29 million population growth surrounding Lake. research integrating satellite analytics, algorithms spatial generate actionable insights into guide conservation planning. findings robust baseline inform policies aimed at ensuring health sustainable management Lake wetlands human climatic that threaten functioning these ecosystems.

Язык: Английский

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Spatio-Temporal Dynamics of Rangeland Transformation using machine learning algorithms and Remote Sensing data

Rangeland Ecology & Management, Год журнала: 2024, Номер 94, С. 106 - 118

Опубликована: Март 23, 2024

Язык: Английский

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Assessing climatic impacts on land use and land cover dynamics in Peshawar, Khyber Pakhtunkhwa, Pakistan: a remote sensing and GIS approach

GeoJournal, Год журнала: 2024, Номер 89(5)

Опубликована: Авг. 31, 2024

Язык: Английский

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Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability

Cogent Food & Agriculture, Год журнала: 2025, Номер 11(1)

Опубликована: Янв. 7, 2025

Accurate insights into the spatial distribution of cultivated areas, land use for effective agricultural management, and improvement food security planning, especially in developing countries. Therefore, this study examined impact changes population growth on wheat crop productivity. First, by incorporating more than three decades satellite data (1990–2022) different Landsat missions with machine learning algorithms, high-confidence classes were defined features, including cropland. Second, grown area was identified using cropland extraction based acreage assessment method (CLE-WAAM). Third, dynamics applying an exponential model to forecast predict demand. These findings necessitate integrated methodological development demand supply mechanisms two-step floating catchment (2SFCA) approach a thorough analysis socioeconomic developments. The results revealed that transformed non-cropland, percentage 8.01. A 79% rise occured between 1990 2022, projected increase 112% 2030. Specifically, cultivation decreased 28%, despite stagnant parameters observed since 2000. proposed contributes efficiently United Nations' sustainable goal (02: Zero Hunger) satellite, geospatial, statistical integration.

Язык: Английский

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Integrated Assessment and Geostatistical Evaluation of Groundwater Quality through Water Quality Indices

Water, Год журнала: 2023, Номер 16(1), С. 63 - 63

Опубликована: Дек. 23, 2023

This study undertook an assessment of 24 physiochemical parameters at over 1094 sites to compute the water quality index (WQI) across upper and central Punjab regions Pakistan. Prior WQI calculation, analytical hierarchy process (AHP) was employed assign specific weights each parameter. The categorization into distinct classes achieved by constructing a pairwise matrix based on their relative importance utilizing Saaty’s scale. Additionally, groundwater status for irrigation drinking purposes various zones in area delineated through integration geostatistical methodologies. findings revealed discernible heavy metal issues Lahore division, with emerging microbiological contamination entire region, potentially attributed untreated industrial effluent discharge inadequately managed sewerage systems. computed indices Lahore, Sargodha, Rawalpindi divisions fell within marginal unfit categories, indicating concerns. In contrast, other were medium class, suggesting suitability purposes. Scenario analysis developing mitigation strategies indicated that primary treatment before wastewater disposal could rehabilitate 9% area, followed secondary (35%) tertiary (41%) treatments. Microbiological (27%) emerged as predominant challenge supply agencies. Given current trajectory deterioration, access potable is poised become significant public concern. Consequently, government agencies are urged implement appropriate measures enhance overall sustainable development.

Язык: Английский

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Efficient knowledge distillation for hybrid models: A vision transformer‐convolutional neural network to convolutional neural network approach for classifying remote sensing images

IET Cyber-Systems and Robotics, Год журнала: 2024, Номер 6(3)

Опубликована: Июль 10, 2024

Abstract In various fields, knowledge distillation (KD) techniques that combine vision transformers (ViTs) and convolutional neural networks (CNNs) as a hybrid teacher have shown remarkable results in classification. However, the realm of remote sensing images (RSIs), existing KD research studies are not only scarce but also lack competitiveness. This issue significantly impedes deployment notable advantages ViTs CNNs. To tackle this, authors introduce novel hybrid‐model approach named HMKD‐Net, which comprises CNN‐ViT ensemble CNN student. Contrary to popular opinion, posit sparsity RSI data distribution limits effectiveness efficiency transfer. As solution, simple yet innovative method handle variances during phase is suggested, leading substantial enhancements The assessed performance HMKD‐Net on three datasets. findings indicate outperforms other cutting‐edge methods while maintaining smaller size. Specifically, exceeds KD‐based with maximum accuracy improvement 22.8% across ablation experiments indicated, has cut down time expenses by about 80% process. study validates technique can be more effective efficient if RSIs well handled.

Язык: Английский

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Impact assessment of agricultural droughts on water use efficiency in different climatic regions of Punjab Province Pakistan using MODIS time series imagery

Hydrological Processes, Год журнала: 2024, Номер 38(7)

Опубликована: Июль 1, 2024

Abstract Drought is the most destructive phenomenon that distresses terrestrial carbon cycle balance and crop production. The variation in evapotranspiration (ET) gross primary productivity (GPP) a significant cause of agricultural drought effects on water use efficiency. This study aims to evaluate impact WUE it's anomalies different climate regions. standard vegetation index was used measure extent drought. calculated using ratio ET, GPP, classification De Martonne method. conducted over last 22 years, from 2001 2022. Meanwhile, 2001, 2002, 2014, 2018 were considered high years based 22‐year analysis. According remote sensing analysis ET increased throughout all regions more strongly arid zone than humid Humid areas vital due ones. badge with severity across climates except very zone. saw faster recovery times ones, experienced severe droughts. findings this research are essential for understanding cycles agriculture management. helped analyse varying change. significance includes informing agricultural, resource, management planning Punjab Province, an region vulnerable holds important learnings worldwide. It has practical scientific importance regarding systems' specific stresses responses

Язык: Английский

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Integrated Geospatial and Geostatistical Multi-Criteria Evaluation of Urban Groundwater Quality Using Water Quality Indices

Water, Год журнала: 2024, Номер 16(17), С. 2549 - 2549

Опубликована: Сен. 9, 2024

Groundwater contamination poses a severe public health risk in Lahore, Pakistan’s second-largest city, where over-exploited aquifers are the primary municipal and domestic water supply source. This study presents first comprehensive district-wide assessment of groundwater quality across Lahore using an innovative integrated approach combining geographic information systems (GIS), multi-criteria decision analysis (MCDA), indexing techniques. The core objectives were to map spatial distributions critical pollutants like arsenic, model their impacts on overall potability, evaluate targeted remediation scenarios. analytic hierarchy process (AHP) methodology was applied derive weights for relative importance diverse parameters based expert judgments. Arsenic received highest priority weight (0.28), followed by total dissolved solids (0.22) hardness (0.15), reflecting significance as hazards. Weighted overlay GIS delineated localized hotspots, unveiling severely degraded areas with very poor index values (>150) urban industrial zones Cantt, Model Town, parts City. corroborates reports unregulated effluent discharges contributing aquifer pollution. Prospective improvement scenarios projected that reducing heavy metals arsenic 30% could enhance indices up 20.71% critically localities Shalimar. Simulating advanced multi-barrier treatment processes showcased over 95% potential reduction levels, indicating requirement deploying oxidation filtration infrastructure aligned local contaminant profiles. support tool enables visualization complex patterns, evaluation options, prioritizing risk-mitigation investments distribution hazard exposures. framework equips planners utilities insights developing restoration policies through strategic interventions encompassing facilities, drainage improvements, pollutant discharge regulations. Its replicability other regions allows tackling widespread challenges robust data synthesis quantitative scenario modeling capabilities.

Язык: Английский

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Multi-temporal image analysis of wetland dynamics using machine learning algorithms

Journal of Environmental Management, Год журнала: 2024, Номер 371, С. 123123 - 123123

Опубликована: Ноя. 10, 2024

Язык: Английский

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