Temporal and spatial variations of ecological security on the northeastern Tibetan Plateau integrating ecosystem health-risk-services framework DOI Creative Commons
Chenli Liu, Wenlong Li,

Jing Xu

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 158, P. 111365 - 111365

Published: Dec. 6, 2023

Ecological security is a critical guarantor of human and indeed survival closely associated with sustainable development. Yet exploration ecological assessment in alpine pastoral regions lacking, many studies have failed to perform validation analyses on results, weakening the reliability their results. In this study, an ecosystem health-risk-services framework developed assess Gannan region (GAPR) northeastern Tibetan Plateau from 2000 2020. Then, remote sensing index (RSEI) high-resolution images are then introduced verify compare results’ reliability. Our study results indicate: (1) The can better reflect actual state GAPR, correlation coefficient (R2) comprehensive (CESI) RSEI between 0.426 0.555 (p < 0.001). (2) CESI value GAPR shows fluctuating increasing trend 2020, spatial distribution pattern high values south low north. levels dominated by medium, medium-high levels. (3) centers gravity medium-low show northward movement trend, while that southward movement. provides new perspective for methods, which be extended other regions, contribute useful references decision-makers socioeconomic development eco-environmental protection GAPR.

Language: Английский

Forecasting urban expansion in Delhi-NCR: integrating remote sensing, machine learning, and Markov chain simulation for sustainable urban planning DOI

Shadman Nahid,

Ram Pravesh Kumar, Prasenjit Acharya

et al.

GeoJournal, Journal Year: 2025, Volume and Issue: 90(2)

Published: March 17, 2025

Language: Английский

Citations

1
Testing Accuracy of Land Cover Classification Algorithms in the Qilian Mountains Based on GEE Cloud Platform DOI Creative Commons
Yanpeng Yang, Dong Yang, Xufeng Wang

et al.

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(24), P. 5064 - 5064

Published: Dec. 14, 2021

The Qilian Mountains (QLM) are an important ecological barrier in western China. High-precision land cover data products the basic for accurately detecting and evaluating service functions of QLM. In order to study QLM performance different remote sensing classification algorithms mapping based on Google Earth Engine (GEE) cloud platform, higher spatial resolution images Sentinel-1 Sentinel-2; digital elevation data; three algorithms, including support vector machine (SVM), regression tree (CART), random forest (RF) were used perform supervised Sentinel-2 Furthermore, results obtained from process compared analyzed by using feature-variable combinations. indicated that: (1) accuracy acquired different, RF had highest accuracy, followed CART SVM; (2) feature variable combinations effects overall (OA) identification types; (3) with existing QLM, maps this a accuracy.

Language: Английский

Citations

53
Spatio-temporal classification and prediction of land use and land cover change for the Vembanad Lake system, Kerala: a machine learning approach DOI

Parthasarathy Kulithalai Shiyam Sundar,

Paresh Chandra Deka

Environmental Science and Pollution Research, Journal Year: 2021, Volume and Issue: 29(57), P. 86220 - 86236

Published: Nov. 12, 2021

Language: Английский

Citations

47
Land Use/Land Cover Mapping Based on GEE for the Monitoring of Changes in Ecosystem Types in the Upper Yellow River Basin over the Tibetan Plateau DOI Creative Commons
Senyao Feng, Wenlong Li, Jing Xu

et al.

Remote Sensing, Journal Year: 2022, Volume and Issue: 14(21), P. 5361 - 5361

Published: Oct. 26, 2022

The upper Yellow River basin over the Tibetan Plateau (TP) is an important ecological barrier in northwestern China. Effective LULC products that enable monitoring of changes regional ecosystem types are great importance for their environmental protection and macro-control. Here, we combined 18-class classification scheme based on with Sentinel-2 imagery, Google Earth Engine (GEE) platform, random forest method to present new a spatial resolution 10 m 2018 2020 Basin TP conducted types. results indicated that: (1) In 2020, overall accuracy (OA) maps ranged between 87.45% 93.02%. (2) Grassland was main first-degree class research area, followed by wetland water bodies barren land. For second-degree class, grassland, broadleaf shrub marsh. (3) types, largest area progressive succession (positive) grassland–shrubland (451.13 km2), whereas retrogressive (negative) grassland–barren (395.91 km2). areas were grassland–broadleaf (344.68 km2) desert land–grassland (302.02 shrubland–grassland (309.08 grassland–bare rock (193.89 northern southwestern parts study showed trend towards positive succession, south-central Huangnan, northeastern Gannan, central Aba Prefectures signs purpose this provide basis data basin-scale analysis more detailed categories reliable accuracy.

Language: Английский

Citations

37
Temporal and spatial variations of ecological security on the northeastern Tibetan Plateau integrating ecosystem health-risk-services framework DOI Creative Commons
Chenli Liu, Wenlong Li,

Jing Xu

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 158, P. 111365 - 111365

Published: Dec. 6, 2023

Ecological security is a critical guarantor of human and indeed survival closely associated with sustainable development. Yet exploration ecological assessment in alpine pastoral regions lacking, many studies have failed to perform validation analyses on results, weakening the reliability their results. In this study, an ecosystem health-risk-services framework developed assess Gannan region (GAPR) northeastern Tibetan Plateau from 2000 2020. Then, remote sensing index (RSEI) high-resolution images are then introduced verify compare results’ reliability. Our study results indicate: (1) The can better reflect actual state GAPR, correlation coefficient (R2) comprehensive (CESI) RSEI between 0.426 0.555 (p < 0.001). (2) CESI value GAPR shows fluctuating increasing trend 2020, spatial distribution pattern high values south low north. levels dominated by medium, medium-high levels. (3) centers gravity medium-low show northward movement trend, while that southward movement. provides new perspective for methods, which be extended other regions, contribute useful references decision-makers socioeconomic development eco-environmental protection GAPR.

Language: Английский

Citations

21