{"title":"预测入侵物种潜在地理分布的空间集合学习","authors":"Wentao Yang, Xiafan Wan, Min Deng","doi":"10.1080/13658816.2024.2376325","DOIUrl":null,"url":null,"abstract":"Understanding the geographical distribution of invasive species is beneficial for preventing and controlling biological invasions. A global model is often constructed with existing species distribu...","PeriodicalId":14162,"journal":{"name":"International Journal of Geographical Information Science","volume":"39 1","pages":""},"PeriodicalIF":4.3000,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Spatial ensemble learning for predicting the potential geographical distribution of invasive species\",\"authors\":\"Wentao Yang, Xiafan Wan, Min Deng\",\"doi\":\"10.1080/13658816.2024.2376325\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Understanding the geographical distribution of invasive species is beneficial for preventing and controlling biological invasions. A global model is often constructed with existing species distribu...\",\"PeriodicalId\":14162,\"journal\":{\"name\":\"International Journal of Geographical Information Science\",\"volume\":\"39 1\",\"pages\":\"\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-07-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Geographical Information Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/13658816.2024.2376325\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Geographical Information Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/13658816.2024.2376325","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Spatial ensemble learning for predicting the potential geographical distribution of invasive species
Understanding the geographical distribution of invasive species is beneficial for preventing and controlling biological invasions. A global model is often constructed with existing species distribu...
期刊介绍：
International Journal of Geographical Information Science provides a forum for the exchange of original ideas, approaches, methods and experiences in the rapidly growing field of geographical information science (GIScience). It is intended to interest those who research fundamental and computational issues of geographic information, as well as issues related to the design, implementation and use of geographical information for monitoring, prediction and decision making. Published research covers innovations in GIScience and novel applications of GIScience in natural resources, social systems and the built environment, as well as relevant developments in computer science, cartography, surveying, geography and engineering in both developed and developing countries.
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