{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T00:25:10Z","timestamp":1770769510233,"version":"3.50.0"},"reference-count":52,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T00:00:00Z","timestamp":1650326400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2018YFC1508903"],"award-info":[{"award-number":["2018YFC1508903"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ministry of Science and Technology of China","award":["2019QZKK0906"],"award-info":[{"award-number":["2019QZKK0906"]}]},{"name":"International Center for Collaborative Research on Disaster Risk Reduction","award":["ICCRDRR"],"award-info":[{"award-number":["ICCRDRR"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Landslide susceptibility assessment serves as a critical scientific reference for geohazard control, land use, and sustainable development planning. The existing research has not fully considered the potential impact of the spatial agglomeration and dispersion of landslides on assessments. This issue may cause a systematic evaluation bias when the field investigation data are insufficient, which is common due to limited human resources. Accordingly, this paper proposes two novel strategies, including a clustering algorithm and a preprocessing method, for these two ignored features to strengthen assessments, especially in high-susceptibility regions. Multiple machine learning models are compared in a case study of the city of Bijie (Guizhou Province, China). Then we generate the optimal susceptibility map and conduct two experiments to test the validity of the proposed methods. The primary conclusions of this study are as follows: (1) random forest (RF) was superior to other algorithms in the recognition of high-susceptibility areas and the portrayal of local spatial features; (2) the susceptibility map incorporating spatial feature messages showed a noticeable improvement over the spatial distribution and gradual change of susceptibility, as well as the accurate delineation of critical hazardous areas and the interpretation of historical hazards; and (3) the spatial distribution feature had a significant positive effect on modeling, as the accuracy increased by 5% and 10% after including the spatial agglomeration and dispersion consideration in the RF model, respectively. The benefit of the agglomeration is concentrated in high-susceptibility areas, and our work provides insight to improve the assessment accuracy in these areas, which is critical to risk assessment and prevention activities.<\/jats:p>","DOI":"10.3390\/ijgi11050269","type":"journal-article","created":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T02:39:31Z","timestamp":1650335971000},"page":"269","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Landslide Susceptibility Assessment Considering Spatial Agglomeration and Dispersion Characteristics: A Case Study of Bijie City in Guizhou Province, China"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4455-2600","authenticated-orcid":false,"given":"Kezhen","family":"Yao","sequence":"first","affiliation":[{"name":"Key Laboratory of Environmental Change and Natural Disaster, Faculty of Geographical Science, Ministry of Education\/Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3390-8264","authenticated-orcid":false,"given":"Saini","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Environmental Change and Natural Disaster, Faculty of Geographical Science, Ministry of Education\/Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing Normal University, Beijing 100875, China"},{"name":"State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"},{"name":"School of National Safety and Emergency Management, Beijing Normal University, Beijing 100875, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5880-244X","authenticated-orcid":false,"given":"Shengnan","family":"Wu","sequence":"additional","affiliation":[{"name":"Center of Emergency Management, Chongqing Institute of Public Administration, Chongqing 400041, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Tong","sequence":"additional","affiliation":[{"name":"China Institute of Geo-Environment Monitoring, China Geology Survey, Beijing 100081, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s100640050066","article-title":"Landslide hazard assessment: Summary review and new perspectives","volume":"58","author":"Aleotti","year":"1999","journal-title":"Bull. 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