Land use change impacts on red slate soil aggregates and associated organic carbon in diverse soil layers in subtropical China DOI
Jiang Wansong, Zhenwei Li,

Hongxia Xie

et al.

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 856, P. 159194 - 159194

Published: Oct. 1, 2022

Language: Английский

Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review DOI Creative Commons
Swapan Talukdar, Pankaj Singha, Susanta Mahato

et al.

Remote Sensing, Journal Year: 2020, Volume and Issue: 12(7), P. 1135 - 1135

Published: April 2, 2020

Rapid and uncontrolled population growth along with economic industrial development, especially in developing countries during the late twentieth early twenty-first centuries, have increased rate of land-use/land-cover (LULC) change many times. Since quantitative assessment changes LULC is one most efficient means to understand manage land transformation, there a need examine accuracy different algorithms for mapping order identify best classifier further applications earth observations. In this article, six machine-learning algorithms, namely random forest (RF), support vector machine (SVM), artificial neural network (ANN), fuzzy adaptive resonance theory-supervised predictive (Fuzzy ARTMAP), spectral angle mapper (SAM) Mahalanobis distance (MD) were examined. Accuracy was performed by using Kappa coefficient, receiver operational curve (RoC), index-based validation root mean square error (RMSE). Results coefficient show that all classifiers similar level minor variation, but RF algorithm has highest 0.89 MD (parametric classifier) least 0.82. addition, visual cross-validation (correlations between normalised differentiation water index, vegetation index built-up are 0.96, 0.99 1, respectively, at 0.05 significance) comparison other adopted. Findings from literature also proved ANN classifiers, although non-parametric like SAM (Kappa 0.84; area under (AUC) 0.85) better consistent than algorithms. Finally, review concludes classifier, among examined it necessary test morphoclimatic conditions future.

Language: Английский

Citations

885
Application of photovoltaics on different types of land in China: Opportunities, status and challenges DOI
Chenchen Song, Zhiling Guo, Zhengguang Liu

et al.

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 191, P. 114146 - 114146

Published: Dec. 2, 2023

Language: Английский

Citations

45
Land use and land cover changes in Morocco: trends, research gaps, and perspectives DOI
Mariem Ben-Said, Abdelazziz Chemchaoui, Issam Etebaai

et al.

GeoJournal, Journal Year: 2025, Volume and Issue: 90(1)

Published: Feb. 12, 2025

Language: Английский

Citations

2
Estimation of soil erosion risk in southern part of Syria by using RUSLE integrating geo informatics approach DOI Creative Commons
Safwan Mohammed, Karam Alsafadi, Swapan Talukdar

et al.

Remote Sensing Applications Society and Environment, Journal Year: 2020, Volume and Issue: 20, P. 100375 - 100375

Published: Aug. 28, 2020

Soil erosion is one of the major problems that threatens agricultural production and sustainability natural resources in Syria. More than 85% Syrian land exposed to soil at different rates. The present study estimated eastern part Yarmouk Basin Al-Swida governorate (Southern Syria), by integrating Revised Universal Loss Equation (RUSLE) model Geographic Information System (GIS) approach. parameters used for RUSLE were prepared from climatic data, field satellite imageries. Results showed average erosivity was 374.19 MJ mm ha−1 h−1 yr−1, while K-factor ranged 0.22 0.36 ton.ha.MJ−1.mm−1, LS-factor reached 45% some places. potential 1.26 350.5 t ha− 1 yr− 1, with an 137.4 1. Meanwhile, ninety-five percent area experienced acceptable rate loss, which between 0 5 While, rest unacceptable rate, 350 Therefore, areas are need immediate conservation plan water point view.

Language: Английский

Citations

106
Role of groundcover management in controlling soil erosion under extreme rainfall in citrus orchards of southern China DOI
Jian Duan, Yaojun Liu, Jie Yang

et al.

Journal of Hydrology, Journal Year: 2019, Volume and Issue: 582, P. 124290 - 124290

Published: Nov. 1, 2019

Language: Английский

Citations

102
Agricultural land use and management weaken the soil erosion induced by extreme rainstorms DOI
Jianqiao Han, Wenyan Ge,

Zhe Hei

et al.

Agriculture Ecosystems & Environment, Journal Year: 2020, Volume and Issue: 301, P. 107047 - 107047

Published: June 8, 2020

Language: Английский

Citations

88
Soil erosion modeling using erosion pins and artificial neural networks DOI
Vahid Gholami, Hossein Sahour,

Mohammad Ali Hadian Amri

et al.

CATENA, Journal Year: 2020, Volume and Issue: 196, P. 104902 - 104902

Published: Sept. 12, 2020

Language: Английский

Citations

75
Long-term effects of living grass mulching on soil and water conservation and fruit yield of citrus orchard in south China DOI
Anguo Tu,

Songhua Xie,

Haijin Zheng

et al.

Agricultural Water Management, Journal Year: 2021, Volume and Issue: 252, P. 106897 - 106897

Published: April 8, 2021

Language: Английский

Citations

58
Quantification of the effects of conservation practices on surface runoff and soil erosion in croplands and their trade-off: A meta-analysis DOI
Joy Rajbanshi,

Sharmistha Das,

Roni Paul

et al.

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 864, P. 161015 - 161015

Published: Dec. 19, 2022

Language: Английский

Citations

44
How climate change and land-use evolution relates to the non-point source pollution in a typical watershed of China DOI
Yuanyuan Li, Hua Wang,

Yanqing Deng

et al.

The Science of The Total Environment, Journal Year: 2022, Volume and Issue: 839, P. 156375 - 156375

Published: May 31, 2022

Language: Английский

Citations

40