Deleted Journal, Journal Year: 2024, Volume and Issue: 11(3), P. 0 - 0
Published: Dec. 1, 2024
Language: Английский
Deleted Journal, Journal Year: 2024, Volume and Issue: 11(3), P. 0 - 0
Published: Dec. 1, 2024
Language: Английский
Ecological Indicators, Journal Year: 2024, Volume and Issue: 162, P. 112051 - 112051
Published: April 23, 2024
Realizing the superior stability of natural resources for regional economic growth depends on construction Ecological Security Pattern (ESP)1. The ESP Hubei Province was determined based supply and demand ecosystem services (ESSD)2. main conclusions are as follows: (1) overall in exceeds demand, imbalance between Wuhan, Xiangyang Jingzhou is most serious. (2) largest ecological source area 2000 90,506 km2, followed by 86,946 km2 2020. (3) 11 long-term obstacles with a total 312.96 were identified, which mainly composed large areas cultivated land water. (5) protection restoration pattern "two axes, three belts, four districts five cores (two secondary)" has been constructed Province. results this study provide reference management response to problems
Language: Английский
Citations
18Resources Conservation and Recycling, Journal Year: 2024, Volume and Issue: 206, P. 107665 - 107665
Published: April 30, 2024
Language: Английский
Citations
9Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 349, P. 119528 - 119528
Published: Nov. 20, 2023
Language: Английский
Citations
13Ecological Indicators, Journal Year: 2023, Volume and Issue: 154, P. 110544 - 110544
Published: June 26, 2023
The ecosystem services value (ESV) is an important basis for measuring ecological environment quality and efficient management of ecosystems. Although there have been many studies devoted to the measurement ESV, research on key influencing factors ESV prediction future development scenarios still limited. This study coupled Deep Forest model Patch-generating Land Use Simulation (PLUS) identify simulated change trend under Shared Socioeconomic Pathways (SSPs). Taking cluster cities around Yellow River floodplain area as object, this quantitatively analyzed spatiotemporal evolution characteristics its from 2000 2020, identified affecting using model. results showed that: (1) overall upward with strong spatial heterogeneity; (2) were construction land ratio, distance railway, SHDI, etc.; (3) best pathway in 2025, 2030 2035 would be SSPs5, SSPs2 SSPs4 respectively. can provide theoretical support maximizing benefits area.
Language: Английский
Citations
11Journal of Geographical Sciences, Journal Year: 2024, Volume and Issue: 34(7), P. 1415 - 1436
Published: July 1, 2024
Language: Английский
Citations
4Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102208 - 102208
Published: Jan. 28, 2025
Language: Английский
Citations
0Land Degradation and Development, Journal Year: 2025, Volume and Issue: unknown
Published: March 30, 2025
ABSTRACT Ecological environment plays an indispensable role in sustaining and developing human society natural ecosystems, while it continually suffers from degradation caused by activities. Land Use Cover (LULC), which serves as a proxy of the intensity intervention, has been regarded equally important factor affecting habitat quality climate change. Despite exploring close relationship between LULC changes quality, current research remains largely theoretical does not delve into management measures following degradation. Consequently, its practical implications for ecological conservation are limited. In this study, taking Northeast China, prominent contradiction protection, study area, InVEST model was introduced to assess based on data 2000 2020. Then, Geographically Weighted Regression (GWR) employed analyze explanatory variables change terms The results indicated that China 2020 mainly occurred cultivated land, artificial grassland, forestland. Habitat demonstrated progressive decline yet remained at intermediate level exhibited significant spatio‐temporal heterogeneity whole. Furthermore, regression there correlation Finally, classified three functional zones K‐Means clustering analysis: coordinated development zone, key each with own characteristics priorities. findings can provide scientific reference rational use land zoning China.
Language: Английский
Citations
0Remote Sensing, Journal Year: 2025, Volume and Issue: 17(7), P. 1248 - 1248
Published: April 1, 2025
Under global climate change, the ecological vulnerability issue in Mongolia has become increasingly severe. However, change process of environment and dominant driving factors different periods sub-regions are not clear. In this paper, we propose a new index for using MODIS data, combined with Geographical Detector gravity center model, to reveal spatiotemporal changes mechanisms from 2000 2022. The results show following: (1) newly proposed remote sensing high applicability ecosystems mainly Mongolia, an accuracy rate 89.39%; (2) belongs category moderate vulnerability, average 1.57, is shifting toward southwest direction; (3) Tmax leading factor especially at altitudes arid regions, where it directly affects vegetation growth, desertification, water availability. interactive have shifted ∩ Tmin PRE, PRE being eastern, central, southern regions western region, northwestern region. This study provides system constructing offers scientific references regional protection Mongolia.
Language: Английский
Citations
0Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3708 - 3708
Published: April 19, 2025
The terrestrial spatial patterns were affected by human activities, primarily on regional land use (LU) changes, with habitat quality (HQ) serving as a prerequisite for achieving sustainable development. Assessing and predicting the spatiotemporal evolution characteristics of LU changes HQ is critical formulating strategies enhancing ecosystem service functions. Using Poyang Lake Region our research object, this employs data utilizes ‘InVEST’ model hot-spot analysis to quantitatively evaluate in during 2000–2020. PLUS then applied predict trends from 2020 2050. findings are follows: (1). From 2000 2020, areas forestland, shrubland, sparse woodland, paddy fields, dryland showed decreasing trend, reductions mainly occurring urban expansion zones such Nanchang City largely converted into construction land. (2). Since 2000, has shown slight retrogressive evolution, significant heterogeneity. spatially exhibits pattern improvement radiating outward major cities. (3). Predictions 2030 2050 indicate that will continue decline, most downward built-up their peripheries. reveal an ring around east–west corridor linking Pingxiang, Yichun, Xinyu, Nanchang, Fuzhou, Yingtan, Shangrao. This study provided basis direction planning policies its surrounding areas, while also contributing agrarian security enhancement levels region.
Language: Английский
Citations
0Land Degradation and Development, Journal Year: 2024, Volume and Issue: 35(6), P. 2256 - 2273
Published: Feb. 9, 2024
Abstract In the context of climate change and rapid urbanization, there have been unparalleled changes in land use cover (LULC), resulting substantial impacts on surrounding habitat quality (HQ), particularly ecologically vulnerable arid regions. However, previous studies influencing mechanisms HQ urban agglomerations future multi‐scenario simulations remain limited. To fill this knowledge gap, study aimed to reveal develop a assessment framework within agglomerations. We assessed spatiotemporal variations using InVEST model three periods LULC data for agglomeration northern slope Tianshan Mountains (UANSTM), partial least squares structural equation was introduced explore interactions between natural non‐natural factors their HQ. Additionally, we coupled multi‐objective programming PLUS models predict under different optimization scenarios (natural development scenario (NDS), ecological protection (EPS), ecological–economic coordinated scenario, economic scenario) UANSTM 2030, assess Results show that (1) index 0.507, 0.520, 0.495 2000, 2010, 2020 respectively, with spatial distribution pattern high values west, low east, central north south; (2) geomorphic, climatic, direct positive effects HQ, while socio‐economic negative effect addition, socio‐economic, climatic also influence through potential indirect paths. Climatic enhance geomorphic counteracting largest LULC; (3) according four highest (increased by 0.13%) found EPS, which aligns more closely SDGs. Conversely, NDS showed lowest (declined 2.59%). The research results could provide scientific basis promoting sustainable management conservation UANSTM.
Language: Английский
Citations
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