{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T08:55:07Z","timestamp":1769849707111,"version":"3.49.0"},"reference-count":32,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T00:00:00Z","timestamp":1714435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["202305AC160071"],"award-info":[{"award-number":["202305AC160071"]}]},{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["2021-MS4-105"],"award-info":[{"award-number":["2021-MS4-105"]}]},{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["YCIC-YF-2022-07"],"award-info":[{"award-number":["YCIC-YF-2022-07"]}]},{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["2023A02"],"award-info":[{"award-number":["2023A02"]}]},{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["2022NSFSC0414"],"award-info":[{"award-number":["2022NSFSC0414"]}]},{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["2023NSFSC0265"],"award-info":[{"award-number":["2023NSFSC0265"]}]},{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["ER3A2N100"],"award-info":[{"award-number":["ER3A2N100"]}]},{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["2023NSFSC1909"],"award-info":[{"award-number":["2023NSFSC1909"]}]},{"name":"Yunnan Academic and Technical Leader Reserve Talent Project","award":["SKLGP2020Z012"],"award-info":[{"award-number":["SKLGP2020Z012"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["202305AC160071"],"award-info":[{"award-number":["202305AC160071"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["2021-MS4-105"],"award-info":[{"award-number":["2021-MS4-105"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["YCIC-YF-2022-07"],"award-info":[{"award-number":["YCIC-YF-2022-07"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["2023A02"],"award-info":[{"award-number":["2023A02"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["2022NSFSC0414"],"award-info":[{"award-number":["2022NSFSC0414"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["2023NSFSC0265"],"award-info":[{"award-number":["2023NSFSC0265"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["ER3A2N100"],"award-info":[{"award-number":["ER3A2N100"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["2023NSFSC1909"],"award-info":[{"award-number":["2023NSFSC1909"]}]},{"name":"List of Key Science and Technology Projects in the Transportation Industry of the Ministry of Transport in 2021","award":["SKLGP2020Z012"],"award-info":[{"award-number":["SKLGP2020Z012"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["202305AC160071"],"award-info":[{"award-number":["202305AC160071"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["2021-MS4-105"],"award-info":[{"award-number":["2021-MS4-105"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["YCIC-YF-2022-07"],"award-info":[{"award-number":["YCIC-YF-2022-07"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["2023A02"],"award-info":[{"award-number":["2023A02"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["2022NSFSC0414"],"award-info":[{"award-number":["2022NSFSC0414"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["2023NSFSC0265"],"award-info":[{"award-number":["2023NSFSC0265"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["ER3A2N100"],"award-info":[{"award-number":["ER3A2N100"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["2023NSFSC1909"],"award-info":[{"award-number":["2023NSFSC1909"]}]},{"name":"Technological Innovation Plan Project of Yunnan Communications Investment &amp; Construction Group Co., Ltd.","award":["SKLGP2020Z012"],"award-info":[{"award-number":["SKLGP2020Z012"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["202305AC160071"],"award-info":[{"award-number":["202305AC160071"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["2021-MS4-105"],"award-info":[{"award-number":["2021-MS4-105"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["YCIC-YF-2022-07"],"award-info":[{"award-number":["YCIC-YF-2022-07"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["2023A02"],"award-info":[{"award-number":["2023A02"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["2022NSFSC0414"],"award-info":[{"award-number":["2022NSFSC0414"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["2023NSFSC0265"],"award-info":[{"award-number":["2023NSFSC0265"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["ER3A2N100"],"award-info":[{"award-number":["ER3A2N100"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["2023NSFSC1909"],"award-info":[{"award-number":["2023NSFSC1909"]}]},{"name":"Construction S&amp;T Project of Department of Transportation of Sichuan Province","award":["SKLGP2020Z012"],"award-info":[{"award-number":["SKLGP2020Z012"]}]},{"name":"Natural Science Foundation of Sichuan","award":["202305AC160071"],"award-info":[{"award-number":["202305AC160071"]}]},{"name":"Natural Science Foundation of Sichuan","award":["2021-MS4-105"],"award-info":[{"award-number":["2021-MS4-105"]}]},{"name":"Natural Science Foundation of Sichuan","award":["YCIC-YF-2022-07"],"award-info":[{"award-number":["YCIC-YF-2022-07"]}]},{"name":"Natural Science Foundation of Sichuan","award":["2023A02"],"award-info":[{"award-number":["2023A02"]}]},{"name":"Natural Science Foundation of Sichuan","award":["2022NSFSC0414"],"award-info":[{"award-number":["2022NSFSC0414"]}]},{"name":"Natural Science Foundation of Sichuan","award":["2023NSFSC0265"],"award-info":[{"award-number":["2023NSFSC0265"]}]},{"name":"Natural Science Foundation of Sichuan","award":["ER3A2N100"],"award-info":[{"award-number":["ER3A2N100"]}]},{"name":"Natural Science Foundation of Sichuan","award":["2023NSFSC1909"],"award-info":[{"award-number":["2023NSFSC1909"]}]},{"name":"Natural Science Foundation of Sichuan","award":["SKLGP2020Z012"],"award-info":[{"award-number":["SKLGP2020Z012"]}]},{"name":"Japan Aerospace Exploration Agency","award":["202305AC160071"],"award-info":[{"award-number":["202305AC160071"]}]},{"name":"Japan Aerospace Exploration Agency","award":["2021-MS4-105"],"award-info":[{"award-number":["2021-MS4-105"]}]},{"name":"Japan Aerospace Exploration Agency","award":["YCIC-YF-2022-07"],"award-info":[{"award-number":["YCIC-YF-2022-07"]}]},{"name":"Japan Aerospace Exploration Agency","award":["2023A02"],"award-info":[{"award-number":["2023A02"]}]},{"name":"Japan Aerospace Exploration Agency","award":["2022NSFSC0414"],"award-info":[{"award-number":["2022NSFSC0414"]}]},{"name":"Japan Aerospace Exploration Agency","award":["2023NSFSC0265"],"award-info":[{"award-number":["2023NSFSC0265"]}]},{"name":"Japan Aerospace Exploration Agency","award":["ER3A2N100"],"award-info":[{"award-number":["ER3A2N100"]}]},{"name":"Japan Aerospace Exploration Agency","award":["2023NSFSC1909"],"award-info":[{"award-number":["2023NSFSC1909"]}]},{"name":"Japan Aerospace Exploration Agency","award":["SKLGP2020Z012"],"award-info":[{"award-number":["SKLGP2020Z012"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["202305AC160071"],"award-info":[{"award-number":["202305AC160071"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["2021-MS4-105"],"award-info":[{"award-number":["2021-MS4-105"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["YCIC-YF-2022-07"],"award-info":[{"award-number":["YCIC-YF-2022-07"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["2023A02"],"award-info":[{"award-number":["2023A02"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["2022NSFSC0414"],"award-info":[{"award-number":["2022NSFSC0414"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["2023NSFSC0265"],"award-info":[{"award-number":["2023NSFSC0265"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["ER3A2N100"],"award-info":[{"award-number":["ER3A2N100"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["2023NSFSC1909"],"award-info":[{"award-number":["2023NSFSC1909"]}]},{"name":"Sichuan Province Science Fund for Distinguished Young Scholars","award":["SKLGP2020Z012"],"award-info":[{"award-number":["SKLGP2020Z012"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["202305AC160071"],"award-info":[{"award-number":["202305AC160071"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["2021-MS4-105"],"award-info":[{"award-number":["2021-MS4-105"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["YCIC-YF-2022-07"],"award-info":[{"award-number":["YCIC-YF-2022-07"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["2023A02"],"award-info":[{"award-number":["2023A02"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["2022NSFSC0414"],"award-info":[{"award-number":["2022NSFSC0414"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["2023NSFSC0265"],"award-info":[{"award-number":["2023NSFSC0265"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["ER3A2N100"],"award-info":[{"award-number":["ER3A2N100"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["2023NSFSC1909"],"award-info":[{"award-number":["2023NSFSC1909"]}]},{"name":"State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project","award":["SKLGP2020Z012"],"award-info":[{"award-number":["SKLGP2020Z012"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The Baihetan reservoir region is characterized by complex geomorphology, significant altitude differences, and rugged terrain. Geological hazards in such areas are often characterized by high concealment, wide distribution, and difficulty in field investigation. Traditional identification techniques are unable to detect and monitor geological hazards on a large scale with high efficiency and accuracy. In recent decades, interferometric synthetic aperture radar (InSAR) techniques, such as small baseline subset InSAR (SBAS-InSAR), have been widely applied to landslide identification. However, due to factors such as vegetation and the degree of landslide deformation, single-band synthetic aperture radar (SAR) still has certain limitations in detecting landslides. In this study, SBAS-InSAR was conducted based on ALOS-2 and Sentinel-1 ascending-descending images covering the Baihetan reservoir region. Deformation identification results were utilized to conduct a statistical analysis of the SAR detection performance and landslide characteristics, and the effect of vegetation on the detection effectiveness of different SAR bands was discussed. The study revealed that when surface vegetation coverage reaches a high degree, the percentage of areas with coverage greater than 0.6 is greater than 95%, the SAR coherence is mainly affected by vegetation thickness; the comparison of the difference change in the average coherence of the C\/L bands among the four vegetation types shows that the ratio of the average coherence of the L-bands to the C-bands increases by a factor of three with the increase in thickness and the transition from crops to shrubs and trees. The results showed that the L-band has better detectability than the C-band in alpine-canyon terrain with vegetation coverage and complex vegetation composition. However, considering the high temporal resolution and accessibility of Sentinel-1 SAR data, it is still the main data choice for wide-area identification of landslides in the reservoir area, while other satellite-borne SAR data with different wavelengths and resolutions, such as ALOS, can be used to assist in the identification and monitoring of landslide hazards with significant magnitude of deformations and dense vegetation coverage. Therefore, the combined utilization of multi-band SAR data has the potential to enhance the dependability of landslide identification and monitoring, resulting in more accurate detection results.<\/jats:p>","DOI":"10.3390\/rs16091591","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T04:01:52Z","timestamp":1714449712000},"page":"1591","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Potential Landslide Identification in Baihetan Reservoir Area Based on C-\/L-Band Synthetic Aperture Radar Data and Applicability Analysis"],"prefix":"10.3390","volume":"16","author":[{"given":"Rui","family":"Zhang","sequence":"first","affiliation":[{"name":"The State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"},{"name":"The College of Earth and Planet Science, Chengdu University of Technology, Chengdu 610059, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7326-6622","authenticated-orcid":false,"given":"Xin","family":"Zhao","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"},{"name":"Institute of International Rivers and Eco-Security, Yunnan University, Kunming 650050, China"},{"name":"Yunnan Key Laboratory of Digital Communications, Broadvision Engineering Consultants Co., Ltd., Kunming 650031, China"}]},{"given":"Xiujun","family":"Dong","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8989-3113","authenticated-orcid":false,"given":"Keren","family":"Dai","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"},{"name":"The College of Earth and Planet Science, Chengdu University of Technology, Chengdu 610059, China"}]},{"given":"Jin","family":"Deng","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}]},{"given":"Guanchen","family":"Zhuo","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"}]},{"given":"Bing","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-8582-6531","authenticated-orcid":false,"given":"Tingting","family":"Wu","sequence":"additional","affiliation":[{"name":"Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 610097, China"}]},{"given":"Jianming","family":"Xiang","sequence":"additional","affiliation":[{"name":"The State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China"},{"name":"The College of Earth and Planet Science, Chengdu University of Technology, Chengdu 610059, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1524","DOI":"10.1080\/19475705.2017.1347896","article-title":"A New Approach for Landslide-Induced Damage Assessment","volume":"8","author":"Bianchini","year":"2017","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1007\/s10346-019-01265-w","article-title":"Heifangtai Loess Landslide Type and Failure Mode Analysis with Ascending and Descending Spot-Mode TerraSAR-X Datasets","volume":"17","author":"Liu","year":"2020","journal-title":"Landslides"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10064-006-0080-z","article-title":"The Third Hans Cloos Lecture. Urban Landslides: Socioeconomic Impacts and Overview of Mitigative Strategies","volume":"66","author":"Schuster","year":"2007","journal-title":"Bull. Eng. Geol. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Chen, C., Dai, K., Tang, X., Cheng, J., Pirasteh, S., Wu, M., Shi, X., Zhou, H., and Li, Z. (2022). Removing InSAR Topography-Dependent Atmospheric Effect Based on Deep Learning. Remote Sens., 14.","DOI":"10.3390\/rs14174171"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1117\/12.578989","article-title":"Concepts and Technologies for Synthetic Aperture Radar from MEO and Geosynchronous Orbits","volume":"Volume 5659","author":"Edelstein","year":"2005","journal-title":"Proceedings of the Enabling Sensor and Platform Technologies for Spaceborne Remote Sensing"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1007\/s10346-020-01475-7","article-title":"Identification and Monitoring Landslides in Longitudinal Range-Gorge Region with InSAR Fusion Integrated Visibility Analysis","volume":"18","author":"Guo","year":"2021","journal-title":"Landslides"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1952","DOI":"10.1126\/science.1098821","article-title":"Dynamics of Slow-Moving Landslides from Permanent Scatterer Analysis","volume":"304","author":"Hilley","year":"2004","journal-title":"Science"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1007\/s11069-019-03726-w","article-title":"Analysis of Deformation Characteristics for a Reservoir Landslide before and after Impoundment by Multiple D-InSAR Observations at Jinshajiang River, China","volume":"98","author":"Li","year":"2019","journal-title":"Nat. Hazards"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/j.rse.2012.05.025","article-title":"Large-Area Landslide Detection and Monitoring with ALOS\/PALSAR Imagery Data over Northern California and Southern Oregon, USA","volume":"124","author":"Zhao","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/j.scitotenv.2019.04.140","article-title":"Mapping and Characterizing Displacements of Active Loess Slopes along the Upstream Yellow River with Multi-Temporal InSAR Datasets","volume":"674","author":"Shi","year":"2019","journal-title":"Sci. Total Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"2375","DOI":"10.1109\/TGRS.2002.803792","article-title":"A New Algorithm for Surface Deformation Monitoring Based on Small Baseline Differential SAR Interferograms","volume":"40","author":"Berardino","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","unstructured":"Canuti, P., Casagli, N., Catani, F., Falorni, G., and Farina, P. (2007). Progress in Landslide Science, Springer."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"314","DOI":"10.1016\/j.geomorph.2014.11.031","article-title":"Landslide Deformation Monitoring with ALOS\/PALSAR Imagery: A D-InSAR Geomorphological Interpretation Method","volume":"231","author":"Doubre","year":"2015","journal-title":"Geomorphology"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"458","DOI":"10.1126\/science.282.5388.458","article-title":"Migration of Fluids beneath Yellowstone Caldera Inferred from Satellite Radar Interferometry","volume":"282","author":"Thatcher","year":"1998","journal-title":"Science"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.rse.2014.09.029","article-title":"Slope Deformation Prior to Zhouqu, China Landslide from InSAR Time Series Analysis","volume":"156","author":"Sun","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_16","first-page":"102812","article-title":"A New Algorithm for Landslide Dynamic Monitoring with High Temporal Resolution by Kalman Filter Integration of Multiplatform Time-Series InSAR Processing","volume":"110","author":"Cai","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_17","first-page":"253","article-title":"Using Advanced InSAR Time Series Techniques to Monitor Landslide Movements in Badong of the Three Gorges Region, China","volume":"21","author":"Liu","year":"2013","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"104895","DOI":"10.1016\/j.catena.2020.104895","article-title":"Long-Term Retrospective Investigation of a Large, Deep-Seated, and Slow-Moving Landslide Using InSAR Time Series, Historical Aerial Photographs, and UAV Data: The Case of Devrek Landslide (NW Turkey)","volume":"196","author":"Eker","year":"2021","journal-title":"Catena"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2540","DOI":"10.1007\/s11629-021-6686-6","article-title":"Landslide Mapping and Analysis along the China-Pakistan Karakoram Highway Based on SBAS-InSAR Detection in 2017","volume":"18","author":"Su","year":"2021","journal-title":"J. Mt. Sci."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Zhao, F., Meng, X., Zhang, Y., Chen, G., Su, X., and Yue, D. (2019). Landslide Susceptibility Mapping of Karakorum Highway Combined with the Application of SBAS-InSAR Technology. Sensors, 19.","DOI":"10.3390\/s19122685"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1016\/j.aej.2022.10.042","article-title":"Study of the Impact of Reservoir Water Level Decline on the Stability Treated Landslide on Reservoir Bank","volume":"65","author":"Wang","year":"2023","journal-title":"Alex. Eng. J."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ran, P., Li, S., Zhuo, G., Wang, X., Meng, M., Liu, L., Chen, Y., Huang, H., Ye, Y., and Lei, X. (2023). Early Identification and Influencing Factors Analysis of Active Landslides in Mountainous Areas of Southwest China Using SBAS-InSAR. Sustainability, 15.","DOI":"10.3390\/su15054366"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Westerhoff, R., and Steyn-Ross, M. (2020). Explanation of InSAR Phase Disturbances by Seasonal Characteristics of Soil and Vegetation. Remote Sens., 12.","DOI":"10.3390\/rs12183029"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Guo, Q., Tong, L., and Wang, H. (2022). A Monitoring Method Based on Vegetation Abnormal Information Applied to the Case of Jizong Shed-Tunnel Landslide. Remote Sens., 14.","DOI":"10.3390\/rs14225640"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1016491","DOI":"10.3389\/feart.2022.1016491","article-title":"Quantitative Estimation of Sentinel-1A Interferometric Decorrelation Using Vegetation Index","volume":"10","author":"Pan","year":"2022","journal-title":"Front. Earth Sci."},{"key":"ref_26","first-page":"496","article-title":"Surface Deformation Associated with the 2008 Ms8.0 Wenchuan Earthquake from ALOS L-Band SAR Interferometry","volume":"12","author":"Liu","year":"2010","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_27","first-page":"157","article-title":"Study on the relationship between landslide creep and vegetation cover in mountainous areas with complex vegetation","volume":"48","author":"Yang","year":"2023","journal-title":"Sci. Surv. Mapp."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.1007\/s10346-022-01898-4","article-title":"The Initial Impoundment of the Baihetan Reservoir Region (China) Exacerbated the Deformation of the Wangjiashan Landslide: Characteristics and Mechanism","volume":"19","author":"Yi","year":"2022","journal-title":"Landslides"},{"key":"ref_29","first-page":"1717","article-title":"Research Progress and Methods of InSAR for Deformation Monitoring","volume":"46","author":"Zhu","year":"2017","journal-title":"Acta Geod. Cartogr. Sin."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0034-4257(97)00104-1","article-title":"On the Relation between NDVI, Fractional Vegetation Cover, and Leaf Area Index","volume":"62","author":"Carlson","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_31","unstructured":"Yan, K., Li, J., Xu, Q., Wu, N., Zhang, J., Gong, T., and Liu, Y. (2023). Accurate Interpretation of Four-Dimensional Characteristics of RedBed Rock Landslide by Comprehensive Remote Sensing\u2014Taking Kualiangzi Landslide as an Example. Geomat. Inf. Sci. Wuhan Univ."},{"key":"ref_32","first-page":"812","article-title":"The Analysis of Conditions for InSAR in the Field of Deformation Monitoring","volume":"56","author":"Tian","year":"2013","journal-title":"Chin. J. Geophys."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/9\/1591\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:36:50Z","timestamp":1760107010000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/9\/1591"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,30]]},"references-count":32,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["rs16091591"],"URL":"https:\/\/doi.org\/10.3390\/rs16091591","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,4,30]]}}}