A Parameter Optimized Method for InVEST Model in Sub-Pixel Scale Integrating Machine Learning Algorithm and Vegetation–Impervious Surface–Soil Model DOI Creative Commons
Linlin Wu, Fenglei Fan

Land, Journal Year: 2024, Volume and Issue: 13(11), P. 1876 - 1876

Published: Nov. 10, 2024

The InVEST model, with its ability to perform spatial visualization and quantification, is an important tool for mapping ecosystem services. However, the accuracy simulating performance of model are deeply influenced by land use parameter, which often relies on use/cover data. To address this issue, we propose a novel method optimizing parameter based vegetation–impervious surface–soil (V–I–S) machine learning algorithm. optimized called Sub-InVEST, it improves assessing services sub-pixel scale. conceptual steps (i) extracting V–I–S fraction remote sensing images spectral unmixing method; (ii) determining relationship between type using algorithm field observation data; (iii) inputting into original instead model. evaluate Sub-InVEST employed habitat quality module multi-source data, were applied acquire estimate central Guangzhou city from 2000 2020 help LSMA ISODATA methods. experimental results showed that robust in sets complex ground scenes. distribution both models revealed consistent increasing trend southwest northeast. Meanwhile, linear regression analyses observed correlation trends, R2 values 0.41, 0.35, 0.42, 0.39, 0.47 years 2000, 2005, 2010, 2015, 2020, respectively. Compared had more favorable estimating Guangzhou. depictions numerical Sub-InVSET manifest greater detail better concordance imagery show seamless density curve substantially enhanced probability across interval ranges.

Language: Английский

Integrating key ecosystem services to study the spatio-temporal dynamics and determinants of ecosystem health in Wuhan’s central urban area DOI Creative Commons
Pingyang Han, Haozhi Hu, Jiayan Zhou

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112352 - 112352

Published: July 11, 2024

Language: Английский

Citations

7
Change and driving factors of eco-environmental quality in Beijing green belts: From the perspective of Nature-based Solutions DOI Creative Commons
Hao Zhang,

Qingping Zhou,

Jianzan Yang

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112581 - 112581

Published: Sept. 1, 2024

Language: Английский

Citations

4
Mountainous landscapes and tree species diversity enhance ecosystem multifunctionality in an urban green heart area DOI
Wenwen Deng, Jiaxiang Li, David I. Forrester

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: 119, P. 106130 - 106130

Published: Jan. 8, 2025

Language: Английский

Citations

0
The Influences of Land Use and Economic Policy on Main Ecosystem Services in Rural East China DOI Open Access
Kun Zhang,

Xuehui Sun,

Tingjing Zhang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1529 - 1529

Published: Feb. 12, 2025

The growing need for food provision and materials challenges the maintenance of ecosystem services. Understanding composition services factors that affect are critical to improving rural development. An assessment in densely populated areas East China has been conducted. results show average value was 34.99 thousand RMB/ha. 30.01 RMB/ha, which main part relationships between were complex. Provision (nutrition) had no significant correlation with regulation (material) mainly influenced by forest cover, proportion arable land, population (adjusted R2 = 0.36). Social land use also a impact on nutrition material Land economic policies could regulate service changing types, mobility, income. Our findings may shed light synergetic development services, village worldwide.

Language: Английский

Citations

0
Ecosystem Service Trade-Offs and Synergies in a Temperate Agricultural Region in Northeast China DOI Creative Commons
Yuhong Li, Yu Cong, Zhang Jin

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(5), P. 852 - 852

Published: Feb. 28, 2025

Ecosystem services (ESs) are essential for balancing environmental sustainability and socio-economic development. However, the of ESs their relationships increasingly threatened by global climate change intensifying human activities, particularly in ecologically sensitive agriculturally-intensive regions. The Songnen Plain, a crucial agricultural region Northeast China, faces considerable challenges sustaining its due to overexploitation land, degradation, variability. This study assessed five key Plain from 2000 2020 across multiple scales: habitat quality (HQ), soil conservation (SC), water yield (WY), food production (FP), windbreaking sand fixing (WS). We evaluated trade-offs synergies between these ESs, as well driving factors main ES trade-offs. Our findings indicate that provisioning (WY FP) regulating (SC WS) improved over time, with FP exhibiting most significant increase at 203.90%, while supporting (HQ) declined 32.61%. primary ecosystem service multifunctionality areas were those provided FP, SC, WY, accounting 58% total. varied spatial scales, stronger being observed pixel scale more pronounced county scale. Climate factors, precipitation temperature, played role shaping than anthropogenic factors. provides valuable insights into restoration sustainable management temperate regions, implications protection northeastern black safeguarding national security.

Language: Английский

Citations

0
Exploration of the multi-scenario spatiotemporal evolution, trade-off and synergy relationships, and driving factors of ecosystem services in Henan Province, China, under the background of land use change DOI Creative Commons
Yunwei Sun, Qi Ma, Weiye Wang

et al.

Frontiers in Ecology and Evolution, Journal Year: 2025, Volume and Issue: 13

Published: April 7, 2025

Introduction Ecosystem services (ESs) assessment plays a significant role in managing ecological resources. From the perspective of land use, this research aims to uncover complex interdependence between ESs and their key drivers clarify optimize function zoning region. Methods This focuses on Henan Province China, quantifying five ESs, namely, carbon storage (CS), habitat quality (HQ), soil conservation (SC), water (WC), yield (WY), assessing interactions from 2000 2020 2035. Moreover, study explores social - driving factors influencing these ESs. Finally, it classifies types ecosystem service bundles (ESBs). Results (1) 2020, use evolution was characterized by large expansion construction land, continuous decrease cultivated area, relatively stable changes other types. In protection (EP) scenario 2035, area decreased most, forest increased slightly. CS HQ showed trend degradation, while SC, WY, WC first fluctuated then increased. (2) The synergistic relationship each main one, among which WC-WY, CS-HQ HQ-SC relationships, CS-WC HQ-WC change trade-off relationship, were mainly relationships. Meanwhile, most B4 central part region dominated, rest volatility. (3) Elevation slope are dominant restricting spatiotemporal distribution CS, HQ, SC. Temperature precipitation primary conditions affecting differentiation WY WC. interaction topographic climatic has greater impact than single factor. Discussion conclusion, during period there spatio-temporal heterogeneity various functions Province. Approaches such as exploring relationships different ecosystems classifying clusters, discussing potential can provide references for territorial space governance environment

Language: Английский

Citations

0
Characteristics of Ecosystem Services in Megacities Within the Yellow River Basin, Analyzed Through a Resilience Perspective: A Case Study of Xi’an and Jinan DOI Open Access
Bowen Zhang,

Xianglong Tang,

J. J. Cui

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3371 - 3371

Published: April 10, 2025

Megacities in developing countries are still undergoing rapid urbanization, with different cities exhibiting ecosystem services (ESs) heterogeneity. Evaluating ESs among various and analyzing the influencing factors from a resilience perspective can effectively enhance ability of to deal react quickly risks uncertainty. This approach is also crucial for optimizing ecological security patterns. study focuses on Xi’an Jinan, two important megacities along Yellow River China. First, we quantified four both cities: carbon storage (CS), habitat quality (HQ), food production (FP), soil conservation (SC). Second, analyzed synergies trade-offs between these using bivariate local spatial autocorrelation Spearman’s rank correlation coefficient. Finally, conducted driver analysis Geographic Detector. Results: (1) The temporal distribution Jinan quite different, but show lower ES levels urban core area. (2) showed strong synergistic effect. Among them, CS-HQ had strongest synergy 0.93. In terms space, north dominated by low–low clustering, while south high–high clustering. FP-SC trade-off effect −0.35 2000, which gradually weakened over time was mainly distributed northern area city where cropland construction were concentrated. (3) Edge density, patch NDVI have greatest influence CS Jinan. DEM, slope, density HQ. Temperature, edge impact temperature FP cities. SC. Landscape fragmentation has great CS, HQ, SC Due insufficient research data, this focused only middle reaches River. However, results provide new solving problem regional sustainable development directions ideas follow-up field.

Language: Английский

Citations

0
A Spatial Study on the Impact of Habitat Quality on Geological Disaster Susceptibility: A Case Study in Pingshan County, China DOI Creative Commons
Miao Zhang,

Aihong Zhou,

Siyuan Cao

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(12), P. 5151 - 5151

Published: June 13, 2024

Habitat quality is a comprehensive index reflecting ecological conditions, land use impact, and human survival. Susceptibility to geological disasters influenced by factors such as ecology, the environment, activities. Analyzing effects of habitat on disaster susceptibility its spatial dynamics crucial for protection assessing risks. This research focused Pingshan County, using InVEST 3.7.0 model ArcGIS evaluate 2020. The relationships were examined with GeoDa investigate impact susceptibility. findings are follows: (1) County generally exhibits high quality, showing significant clustering susceptibility—predominantly high–high in west low–low east. (2) environment significantly influences relationship between susceptibility, an overall positive correlation but negative correlations certain areas. Geological primarily governed rather than quality. (3) In mountainous regions comparable variations chiefly driven Including activities metric enhances evaluation accuracy. study provides scientific foundation protection, assessment development mitigation policies.

Language: Английский

Citations

2
Identification and Spatial Characterization of suburban areas in Chengdu DOI

Lingli Mou,

Heping Li,

Yuxuan Rao

et al.

Applied Geography, Journal Year: 2024, Volume and Issue: 172, P. 103428 - 103428

Published: Oct. 5, 2024

Language: Английский

Citations

1
A greener Green Belt? Co-developing exploratory scenarios for contentious peri-urban landscapes DOI Creative Commons
Matthew Kirby, Alister Scott, Claire Walsh

et al.

Landscape and Urban Planning, Journal Year: 2024, Volume and Issue: 255, P. 105268 - 105268

Published: Nov. 29, 2024

Language: Английский

Citations

1