Monitoring and analysis of eco-environmental quality in Yulin City from 2000 to 2020 based on Remote Sensing Ecological Index (RSEI) DOI
Xingcheng Wang,

Kailei Xu,

Shengjie Yang

et al.

Published: Jan. 19, 2024

Yulin City serves as an important coal industrial base in the Yellow River Basin,also a typical ecological fragile area China, and its eco-environmental quality changes have attracted much attention recent years. In order to effectively monitor of further assess effectiveness restoration City, research integrated multi sensors including Landsat TM, ETM, OLI MODIS land surface temperature products construct long time-series Remote Sensing Ecological Index (RSEI) based on Google Earth Engine (GEE) platform. Then, patterns spatial-temporal distribution from 2000—2020 were revealed driving force was discussed. Results show that: (1) The improved large extent 2000 2020, with significant improvement exceeding 56% whole study which mainly occurred southeast Yulin; Notably, potential risk degradation exists north southwest; (2) shows obvious geomorphological differences: Loess Plateau areas is better than that Windblown Sand Grassland north; (3) Transformation use types caused by implementation policies such returning farmland forests grasslands mine plays leading role process restoring environment, while extreme meteorological disasters droughts can lead rapid deterioration quality.

Language: Английский

Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability DOI Creative Commons
Danish Raza, Hong Shu, Muhsan Ehsan

et al.

Cogent Food & Agriculture, Journal Year: 2025, Volume and Issue: 11(1)

Published: Jan. 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.

Language: Английский

Citations

4
Mapping and spatiotemporal dynamics of land-use and land-cover change based on the Google Earth Engine cloud platform from Landsat imagery: A case study of Zhoushan Island, China DOI Creative Commons
Chao Chen,

Xuebing Yang,

Shenghui Jiang

et al.

Heliyon, Journal Year: 2023, Volume and Issue: 9(9), P. e19654 - e19654

Published: Sept. 1, 2023

Land resources are an essential foundation for socioeconomic development. Island land limited, the type changes particularly frequent, and environment is fragile. Therefore, large-scale, long-term, high-accuracy land-use classification spatiotemporal characteristic analysis of great significance sustainable development islands. Based on advantages remote sensing indices principal component in accurate classification, taking Zhoushan Archipelago, China, as study area, this work long-term satellite data were used to perform analysis. The results showed that types could be exactly classified, with overall accuracy Kappa coefficient greater than 94% 0.93, respectively. built-up forest areas increased by 90.00 km2 36.83 km2, respectively, while area cropland/grassland decreased 69.77 km2. water bodies, tidal flats, bare exhibited slight change trends. spatial coverage continuously expanded toward coast, encroaching nearby sea flats. was most transferred-out at up 108.94 transferred-in areas, 73.31 This provides a basis technical support scientific management resources.

Language: Английский

Citations

16
Analysis of the Spatiotemporal Characteristics and Influencing Factors of the NDVI Based on the GEE Cloud Platform and Landsat Images DOI Creative Commons
Zhisong Liu,

Yankun Chen,

Chao Chen

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(20), P. 4980 - 4980

Published: Oct. 16, 2023

Vegetation is an important type of land cover. Long-term, large-scale, and high-precision vegetation monitoring great significance for ecological environment investigation regional sustainable development in protected areas. This paper develops a long-term remote sensing method by calculating the normalized difference index (NDVI) based on Google Earth Engine (GEE) cloud platform Landsat satellite images. First, images GEE, spatiotemporal distribution map NDVI accurately drawn. Subsequently, classified, time trend analysis conducted mean graphs, transition matrices, etc. Then, combined with Moran’s I, high/low clusters, other methods, spatial pattern characteristics are analyzed. Finally, climate factors, terrain anthropologic factors considered comprehensively. An affecting evolution performed. Taking Zhoushan Island, China, as example, experiment conducted, results reveal that (1) average exhibits decreasing from 1985 to 2022, 0.53 0.46 2022. (2) Regarding transitions, high areas (0.6–1) exhibit most substantial shift toward moderately values (0.4–0.6), covering area 83.10 km2. (3) There obvious agglomeration phenomenon Island. The high-high clusters significant hot spots predominantly concentrated island’s interior regions, while low-low cold mainly situated along coastal (4) DEM, slope, temperature have greater influence among single 2015. differences between DEM precipitation, slope aspect population, gross domestic product (GDP). temperature, population three sets strong interaction. study provides data support scientific management resources Island island region.

Language: Английский

Citations

16
Mapping of the Spatial Scope and Water Quality of Surface Water Based on the Google Earth Engine Cloud Platform and Landsat Time Series DOI Creative Commons

Haohai Jin,

Shiyu Fang, Chao Chen

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(20), P. 4986 - 4986

Published: Oct. 16, 2023

Surface water is an important parameter for resource management and terrestrial circulation research that closely related to human production livelihood. With the rapid development of remote sensing technology cloud computing platforms, use large-scale long-term surface monitoring investigation has become a trend. Based on Google Earth Engine (GEE) platform Landsat series satellite data, in this study, Emergency Geomatics Service (EGS) operational mapping algorithm index masking were utilized extract spatial scope body. The validated models Secchi disk depth (SDD), chlorophyll-a (Chl-a) suspended solids (SS) concentration applied quality inversion evaluation. extent extraction maps created analyze distribution body spatial–temporal evolution characteristics parameters. A verification experiment was carried out with Zhejiang Province as object. results show study area from 1990 2022 could be accurately extracted. kappa coefficients all greater than 0.90, overall accuracies extractions 95.31%. From 2022, total initially decreased then increased. minimum 2027.49 km2 occurred 2005, maximum 2614.96 2020, annual average variation 193.92 km2. Since 2015, proportion high SS Chl-a concentrations, low SDD bodies have decreased, better increased significantly. map parameters obtained provide valuable reference guidance regional management, disaster early warning, environmental protection, aquaculture.

Language: Английский

Citations

14
Evaluating the Influence of Biophysical Factors in Explaining Spatial Heterogeneity of LST: Insights from Brahmani-Dwarka Interfluve Leveraging Geodetector, GWR, and MGWR Models DOI
Bhaskar Mandal, Kaushalendra Prakash Goswami

Physics and Chemistry of the Earth Parts A/B/C, Journal Year: 2024, Volume and Issue: 138, P. 103836 - 103836

Published: Dec. 9, 2024

Language: Английский

Citations

4
Assessing the Influence of Urban Development on the Urban Heat Island Through Remote Sensing and Geospatial Techniques in Jhansi, India DOI
R. B. Singh, Neelkamal Kapoor

Advances in 21st century human settlements, Journal Year: 2025, Volume and Issue: unknown, P. 203 - 216

Published: Jan. 1, 2025

Language: Английский

Citations

0
Research on ecological quality and restoration of fragile mining areas in the Yellow River Basin—The case of Xiegou coal mine DOI
Xin Sui, Yiming Sun, Xuan Wang

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 174, P. 113426 - 113426

Published: April 21, 2025

Language: Английский

Citations

0
Assessing the impact of land use land cover change and urbanization on urban heat island through remote sensing and geospatial techniques in Jhansi, India (2001−2021) DOI
R. B. Singh, Neelkamal Kapoor

Urban Climate, Journal Year: 2025, Volume and Issue: 61, P. 102432 - 102432

Published: April 30, 2025

Language: Английский

Citations

0
Urban Environmental Degradation in Bangladesh: Insights from a Weighted Entropy Ecological Index DOI
Jayanta Biswas

Next research., Journal Year: 2025, Volume and Issue: unknown, P. 100386 - 100386

Published: May 1, 2025

Language: Английский

Citations

0
MTD-YOLOv5: Enhancing marine target detection with multi-scale feature fusion in YOLOv5 model DOI Creative Commons
Liansuo Wei,

Huang Shen-hao,

Ma Long-yu

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 10(4), P. e26145 - e26145

Published: Feb. 1, 2024

Underwater light attenuation leads to decreased image contrast. This reduction in contrast subsequently decreases target visibility. Additionally, marine detection is challenging due multi-scale problems from varying target-to-device distances, complex clustering, and noise waterborne particulates.To address these issues, we propose MTD-YOLOv5.Initially, enhance with grayscale equalization mitigate color shift issues through space transformation.We then introduce a novel feature extraction module, PCBR, combining max pooling convolution layers for more effective the background.Furthermore, present Multi-Scale Perceptual Hybrid Pooling (MHP) module.This module integrates horizontal vertical receptive fields establish long-range dependencies, thereby capturing hidden information deep network maps. In Labeled Fishes Wild test datasets, MTD-YOLOv5 achieves precision of 88.1% mean Average Precision (mAP[0.5:.95]) 49.6%.These results represent improvements 2.6% 0.4% mAP over original YOLOv5.

Language: Английский

Citations

3