Warming Trends in the Nile Delta: A High-Resolution Spatial Statistical Approach DOI Creative Commons

Faten Nahas,

Islam Hamdi, Mohamed E. Hereher

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 101408 - 101408

Published: Nov. 1, 2024

Language: Английский

Projecting Future Wetland Dynamics Under Climate Change and Land Use Pressure: A Machine Learning Approach Using Remote Sensing and Markov Chain Modeling DOI Creative Commons

Penghao Ji,

Rong Jun Su, Guodong Wu

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(6), P. 1089 - 1089

Published: March 20, 2025

Wetlands in the Yellow River Watershed of Inner Mongolia face significant reductions under future climate and land use scenarios, threatening vital ecosystem services water security. This study employs high-resolution projections from NASA’s Global Daily Downscaled Projections (GDDP) Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6), combined with a machine learning Cellular Automata–Markov (CA–Markov) framework to forecast cover transitions 2040. Statistically downscaled temperature precipitation data for two Shared Socioeconomic Pathways (SSP2-4.5 SSP5-8.5) are integrated satellite-based (Landsat, Sentinel-1) 2007 2023, achieving high classification accuracy (over 85% overall, Kappa > 0.8). A Maximum Entropy (MaxEnt) analysis indicates that rising temperatures, increased variability, urban–agricultural expansion will exacerbate hydrological stress, driving substantial wetland contraction. Although certain areas may retain or slightly expand their wetlands, dominant trend underscores urgency spatially targeted conservation. By synthesizing data, multi-temporal transitions, ecological modeling, this provides insights adaptive resource planning management ecologically sensitive regions.

Language: Английский

Citations

3
The Cutting Edge of AI in E-Marketing: How the Use of Digital Tools Boosts Performance in Jordan DOI
Jassim Ahmad Al-Gasawneh, Abdullah Alsokkar,

Ahmed Alamro

et al.

SN Computer Science, Journal Year: 2025, Volume and Issue: 6(1)

Published: Jan. 17, 2025

Language: Английский

Citations

2
Sensitivity assessment and simulation of ecosystem services in response to land use change in arid regions: Empirical evidence from Xinjiang, China DOI
Xiaoyun Li, Chunsheng Wu

Ecological Indicators, Journal Year: 2025, Volume and Issue: 171, P. 113150 - 113150

Published: Jan. 27, 2025

Language: Английский

Citations

2
Characterizing the dynamics of climate and native desert plants in Qatar DOI Creative Commons
Meshal M. Abdullah, Ammar Abulibdeh, Sophia Ghanimeh

et al.

Journal of Arid Environments, Journal Year: 2024, Volume and Issue: 225, P. 105274 - 105274

Published: Oct. 29, 2024

Language: Английский

Citations

4
The spatial and temporal evolution of habitat quality and driving factors in nature reserves: a case study of 33 forest ecosystem reserves in Guizhou Province DOI Creative Commons

Xuemeng Mei,

Yi Liu, Yue Li

et al.

PeerJ, Journal Year: 2025, Volume and Issue: 13, P. e19098 - e19098

Published: March 24, 2025

Background Biodiversity plays a crucial role for humanity, serving as foundation human survival and development. Habitat quality serves critical indicator assessing biodiversity holds significant importance in both theoretical practical domains. The unique natural geographical environment of Guizhou Province has fostered rich facilitated the establishment numerous nature reserves, predominantly centered on forest ecosystems. Analyzing habitat reserves its influencing factors is great significance maintaining regional ecosystem stability, promoting sustainable development, improving ecological environment. Method Therefore, taking 33 study area, we first quantified using Integrated Valuation Ecosystem Services Trade-offs (InVEST) model to analyze changes reserve from 2000 2020. Then, explored effects social spatiotemporal evolution optimal parameters-based detector (OPGD). Results Forests were identified primary land-use type area. However, saw an increase area cropland, impervious land by 5,001.39 ha 102.15 ha; decrease forests grasslands; slight watersheds. Rapid urbanization, therefore, negatively affected overall reserve. Although there declining trend reserve, magnitude change 2010 2020 (−0.04) smaller than that (−0.17), indicating management been somewhat effective. In national-level interactions between geographic socio-economic greater factors. Similarly, local-level outweighed among Conclusion variability was shaped combined protected areas is, furthermore, more significantly activities, which are cause their degradation.

Language: Английский

Citations

0
Analyzing the Influence of Climate and Anthropogenic Development on Vegetation Cover in the Coastal Ecosystems of GCC DOI Creative Commons

Abhilash Dutta Roy,

Midhun Mohan,

Aaron Althauser

et al.

Earth Systems and Environment, Journal Year: 2025, Volume and Issue: unknown

Published: April 18, 2025

Language: Английский

Citations

0
Deep learning-based modeling of land use/land cover changes impact on land surface temperature in Greater Amman Municipality, Jordan (1980–2030) DOI Creative Commons
Khaled F. Alkaraki, Khaled Hazaymeh,

Osama M. Al-Tarawneh

et al.

GeoJournal, Journal Year: 2024, Volume and Issue: 89(4)

Published: Aug. 5, 2024

Abstract Modeling the impacts of Land Use/Land Cover changes (LULCC) on Surface Temperature (LST) is crucial in understanding and managing urban heat islands, climate change, energy consumption, human health, ecosystem dynamics. This study aimed to model past, present, future LULCC Temperatures Greater Amman Municipality (GAM) Jordan between 1980 2030. A set maps for land cover, LST, Normalized Difference Vegetation Index (NDVI), Built-up (NDBI), topography was integrated into Cellular Automata-Artificial Neural Network (CA-ANN) Long-Short-Term Model (LSTM) models predict LULC LST The results showed an expansion areas GAM from 54.13 km 2 (6.6%) 374.1 (45.3%) 2023. However, agricultural decreased 152.13 (18.5%) 140.38 (17%) 2023, while barren lands 54.44 34.71 (4.22%) Forested declined 4.58 (0.56%) 4.35 (0.53%) Rangelands/ sparsely vegetated 557 (67.7%) 270.71 (32.9%) modeling increase average all cover types, with most significant increases evident within Rangelands/Sparsely areas. slightest forested as increased 28.42 °C 34.16 forecasts a continuous values types. These findings highlight impact surface dynamics their increasing temperature, which urges adoption more sustainable planning policies livable thermally comfortable cities.

Language: Английский

Citations

1
Dynamic environmental zoning using the CA–Markov model and multicriteria analysis in a Brazilian Cerrado Watershed DOI Creative Commons
Erivelton Pereira Vick, Bruno Henrique Machado da Silva, Amanda Ayumi de Souza Amede Sato

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 167, P. 112598 - 112598

Published: Sept. 23, 2024

Language: Английский

Citations

1
Warming Trends in the Nile Delta: A High-Resolution Spatial Statistical Approach DOI Creative Commons

Faten Nahas,

Islam Hamdi, Mohamed E. Hereher

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: unknown, P. 101408 - 101408

Published: Nov. 1, 2024

Language: Английский

Citations

0