Ecosystem Service Value Assessment of the Yellow River Delta Based on Satellite Remote Sensing Data

Land, Journal Year: 2024, Volume and Issue: 13(3), P. 276 - 276

Published: Feb. 22, 2024

The Yellow River Delta (YRD) stands as a globally significant wetland, playing pivotal role in sustaining regional ecosystem stability and offering crucial services to humanity. However, anthropogenic activities, particularly resource development, unavoidably disrupt the ecosystem, leading degradation of these vital services. Utilizing satellite remote sensing data, InVEST model, energy analysis, this study introduces concept ‘emergy’ an ‘intermediate variable’ investigate spatiotemporal changes service value YRD. Five distinct types are selected for quantitative assessment analysis YRD’s evolution from 1990 2020. Results indicate 63.7% decline total 2010, followed by 16.5% increase 2010 also unveils spatial shifts high- low-value areas attributes rapid urbanization alterations land use cover. values concretizes intangible functions natural resources. This lays foundation establishing mechanism that combines positive incentives reverse pressure achieve economic valuation service.

Language: Английский

---

Synergies and trade-offs of ecosystem services affected by land use structures of small watershed in the Loess Plateau

Journal of Environmental Management, Journal Year: 2023, Volume and Issue: 350, P. 119589 - 119589

Published: Nov. 29, 2023

Language: Английский

---

Land use and land cover changes and their effect on ecosystem service values in the Bale Ecoregion, southeastern Ethiopia

Frontiers in Environmental Science, Journal Year: 2024, Volume and Issue: 12

Published: June 27, 2024

The Bale Ecoregion (BER) is known for its global importance in biodiversity and as a water tower East African drylands. Land use land covers (LULC) have been changing decades, affecting forest ecosystem service values (ESVs), but available information limited. present study addresses these gaps by using contrasting watersheds representing the highland, midland, lowland agroecologies BER. LULC classifications were performed GIS remote sensing tools. Multisite imagery data (using Landsat image resolution 30 m × m) generated four observation periods: 1992, 2002, 2012, 2022. A recently updated ESV coefficient value transfer valuation method applied to estimate changes ESVs related changes. result demonstrates that between 1992 2022, has decreased 3%, 63%, 22% areas, respectively. Different degrees of loss observed across periods LULC. Of 21 specific investigated, highest annual losses recorded services both midland landscape positions. Increased cultivated could not offset food at scale agroecology. Significant impacts on services, such water, natural connectivity highland areas observed. suggests stakeholders need co-plan manage This evidence provides scientific underpinning understanding connection change supports informed policy decisions.

Language: Английский

---

Responses of surface runoff and soil water-erosion to changes in seasonal land cover and rainfall intensity; the case of Shilansha watershed, Rift Valley Basin of Ethiopia

Journal of Hydrology Regional Studies, Journal Year: 2025, Volume and Issue: 58, P. 102289 - 102289

Published: March 10, 2025

Language: Английский

---

Modeling soil erosion for sustainable landscape management using RUSLE in the landscapes of Abaya-Chamo Sub-Basin, Ethiopia

Modeling Earth Systems and Environment, Journal Year: 2025, Volume and Issue: 11(3)

Published: March 12, 2025

Language: Английский

---

Cultivated Ecosystem Services in the Yangtze River Economic Belt: Distinguishing Characteristics and Underlying Drivers Over the Past 20 Years

Land Degradation and Development, Journal Year: 2025, Volume and Issue: unknown

Published: April 8, 2025

ABSTRACT Protecting cultivated land in China is crucial for both food security and ecological sustainability. However, research on protection from the perspective of ecosystem services (CESs) remains limited, particularly regarding assessment CESs, complex trade‐offs between them, identification their driving forces to inform policy‐making. This study develops a multi‐dimensional evaluation framework assess eight analyze dynamics trade‐offs, identify CES bundles, examine influencing factors Yangtze River Economic Belt (YREB), China. Results indicate that grain production exhibited steady increase over past two decades, with slight decline after 2015. Water conservation related fluctuated, initially declining, peaking 2015, then decreasing again. In contrast, landscape aesthetics consistently declined, while habitat maintenance improved 2000 2010 but weakened thereafter. Five pairs CESs maintained stable whereas some synergies diminished time. Seven distinct bundles were identified, reflecting site‐specific conditions support multifunctional management. Key negative affecting most included temperature, precipitation, elevation, urbanization rate, rural residents' disposable income, population density, primary industry share, road network density positively influenced several CESs. enriches analytical through an service lens offers insights policies such as trinity system land, natural resource asset assessment, degradation prevention.

Language: Английский

---

Spatial Pattern of Ecosystem Services and the Mechanism of Eco-Industry Formation in South China Karst Nature Reserves

Forests, Journal Year: 2024, Volume and Issue: 15(3), P. 493 - 493

Published: March 6, 2024

Karst nature reserve (NR) ecosystems are vulnerable, and the development of regulatory cultural services industries is still in its infancy. Realization ecological product value (EPV) a crucial way to promote integration eco-protection industrial reserves (NRs). This study calculates EPV using modified equivalent factor, analyzes spatial pattern fishnet tool Arc GIS, constructs model for realizing EPV. Finally, driving factors formation eco-industry identified grey correlation analysis (GCA) method. The results show that (1) service products karst NRs play decisive role EPV, forest have significant potential; (2) high-value grids concentrated core buffer zones distribution experimental zone highly heterogeneous, with high low-value mixed distribution; (3) realization follows logic “preservation, transformation, appreciation”; (4) human resources (0.813), ecology (0.798), industry (0.693), policy (0.783), market (0.778), economy (0.715) essential drivers NRs. Overall, can through planning regulation land use, based on interaction between internal external factors, coordinated provides reference scientific management eco-resources sustainable

Language: Английский

---

Machine-Learning Algorithms for Mapping LULC of the uMngeni Catchment Area, KwaZulu-Natal

Published: April 10, 2024

Analysis of land use/land cover (LULC) in the catchment areas is first action toward safeguarding freshwater resources. The LULC information watershed has gained popularity natural science field as it helps water resource managers and environmental health specialists develop conservation strategies based on available quantitative information. Thus, remote sensing cornerstone addressing environmental-related issues at level. In this study, performance four machine learning algorithms (MLAs), such Random Forests (RF), Support Vector Machine (SVM), Artificial Neural Networks (ANN), Naïve Bayes (NB) was investigated to classify into nine relevant classes undulating landscape using Landsat 8 Operational Land Imager (L8-OLI) imagery. assessment MLAs were visual inspection analyst commonly used metrics, user’s accuracy (UA), producers’ (PA), overall (OA), kappa coefficient. produced good results, where RF (OA= 97.02%, Kappa= 0.96), SVM 89.74 %, 0.88), ANN 87%, 0.86), NB 68.64 0.58). results show outstanding model over with a small margin. While yielded satisfactory which could be primarily influenced by its sensitivity limited training samples. contrast, robust due an ability high-dimensional data data.

Language: Английский

---

Evaluating Machine-Learning Algorithms for Mapping LULC of the uMngeni Catchment Area, KwaZulu-Natal

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(12), P. 2219 - 2219

Published: June 19, 2024

Analysis of land use/land cover (LULC) in catchment areas is the first action toward safeguarding freshwater resources. LULC information watershed has gained popularity natural science field as it helps water resource managers and environmental health specialists develop conservation strategies based on available quantitative information. Thus, remote sensing cornerstone addressing environmental-related issues at level. In this study, performance four machine learning algorithms (MLAs), namely Random Forests (RFs), Support Vector Machines (SVMs), Artificial Neural Networks (ANNs), Naïve Bayes (NB), were investigated to classify into nine relevant classes undulating landscape using Landsat 8 Operational Land Imager (L8-OLI) imagery. The assessment MLAs was a visual inspection analyst commonly used metrics, such user’s accuracy (UA), producers’ (PA), overall (OA), kappa coefficient. produced good results, where RF (OA = 97.02%, Kappa 0.96), SVM 89.74%, 0.88), ANN 87%, 0.86), NB 68.64%, 0.58). results show outstanding model over with significant margin. While yielded satisfactory its sensitivity limited training samples could primarily influence these results. contrast, robust be due an ability high-dimensional data data.

Language: Английский

---

Spatio-temporal evolution and driving factors of regulating ecosystem service value: a case study of Poyang Lake Area, China

Frontiers in Ecology and Evolution, Journal Year: 2024, Volume and Issue: 12

Published: Feb. 22, 2024

Clarifying the driving mechanisms of spatial and temporal changes in regulating ecosystem service value (RESV) is an important part realizing goal sustainable development. Existing studies have focused on specific factors, ignoring complex interactions between factors their regional differences. In this regard, RESV its different zones (core area, fringe peripheral area) were explored Poyang Lake Area, China. The results showed that spatially distribution characteristics area > core while lakes influenced provision services, showing per unit was higher gradually declined with increase distance from lakes, presenting decreasing trend area. From 2000 to 2020, study lost 70.5988 billion CNY for RESV, which most affected. Further analysis mechanism areas found there are differences paths factors: Population density mainly affects precipitation GDP land

Language: Английский

---