Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Ruilong Wei"'
Dependence of debris flow susceptibility maps on sampling strategy with data-driven grid-based model
Publikováno v:
Ecological Indicators, Vol 166, Iss , Pp 112534- (2024)
Different sampling strategies produce varying sample data, serve as the primary input data and directly affect the accuracy of predictions in data-driven grid-based susceptibility models. This study analyzes the accuracy and variation of debris flow
Externí odkaz:
https://doaj.org/article/960dd75379504b0998b748cf20e01b63
Publikováno v:
Diversity, Vol 16, Iss 5, p 300 (2024)
China’s Ecological Protection Red Lines (ERLs) policy has proven effective in constructing regional ecological security patterns and protecting ecological space. However, the existing methods for the identification of high conservation value areas
Externí odkaz:
https://doaj.org/article/1f296803bd224bda9bc8ddf3197e8319
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 124, Iss , Pp 103542- (2023)
Accurate landslide segmentation is crucial for obtaining damage information in disaster mitigation and relief efforts. This study aims to develop a deep learning network for accurate point cloud landslide segmentation. The proposed dynamic graph atte
Externí odkaz:
https://doaj.org/article/ba8370e82b77454a89de102f04c87c05
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 124, Iss , Pp 103521- (2023)
Accurate landslide detection is essential for disaster mitigation and relief. In this study, we develop a feature enhancement framework that integrates attention and multiscale mechanisms with U-Net (AMU-Net) for landslide detection. The framework ha
Externí odkaz:
https://doaj.org/article/4567271bbc75474caa3d5ddfd8349790
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Detecting and analyzing changes of water resources is critical for human survival and societal development in the Qinghai Tibet Plateau (QTP). We implemented the cosine similarity method to complete the migration of samples and achieve a more accurat
Externí odkaz:
https://doaj.org/article/d83079fc0f4e44c0a7023e2725f76d29
Publikováno v:
Frontiers in Earth Science, Vol 10 (2023)
The accuracy of data-driven landslide susceptibility mapping (LSM) is closely affected by the quality of non-landslide samples. This research proposes a method combining a self-organizing-map (SOM) and a one-class SVM (SOM-OCSVM) to generate more rea
Externí odkaz:
https://doaj.org/article/7e4747b44988472c8485c4be17f97ec7
Publikováno v:
Remote Sensing, Vol 15, Iss 18, p 4498 (2023)
The lack of high-resolution training sets for intelligent landslide recognition using high-resolution remote sensing images is a major challenge. To address this issue, this paper proposes a method for reconstructing low-resolution landslide remote s
Externí odkaz:
https://doaj.org/article/be24c00fb1a04c9493297b2882101964
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 12492-12503 (2021)
Point cloud filtering is a preliminary and essential step in various applications of airborne light detection and ranging (LiDAR) data, with progressive triangulated irregular network (TIN) densification (PTD) being one of the classic methods for fil
Externí odkaz:
https://doaj.org/article/ba9c764277e0462f97962fb64d648549
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 107, Iss , Pp 102681- (2022)
Reliable landslide susceptibility mapping (LSM) is essential for disaster prevention and mitigation. This study develops a deep learning framework that integrates spatial response features and machine learning classifiers (SR-ML). The method has thre
Externí odkaz:
https://doaj.org/article/bcf1ddca2cca41fcbf6fbc548e405f80
Publikováno v:
Landslides. 19:1087-1099
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5dd4a894e0cc8bc10dcb018709bbf64
https://doi.org/10.1007/s10346-021-01841-z
https://doi.org/10.1007/s10346-021-01841-z