{"title":"GPGPU加速环境和运动数据集","authors":"Daniel Bird, S. Laycock","doi":"10.1145/3306214.3338584","DOIUrl":null,"url":null,"abstract":"Due to the increased availability and accuracy of GPS sensors, the field of movement ecology has been able to benefit from larger datasets of movement data. As miniaturisation and the efficiency of electronic components have improved, additional sensors have been coupled with GPS tracking to enable features related to the animal's state at a given position to be recorded. This capability is especially relevant to understand how environmental conditions may affect movement.","PeriodicalId":216038,"journal":{"name":"ACM SIGGRAPH 2019 Posters","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"GPGPU acceleration of environmental and movement datasets\",\"authors\":\"Daniel Bird, S. Laycock\",\"doi\":\"10.1145/3306214.3338584\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the increased availability and accuracy of GPS sensors, the field of movement ecology has been able to benefit from larger datasets of movement data. As miniaturisation and the efficiency of electronic components have improved, additional sensors have been coupled with GPS tracking to enable features related to the animal's state at a given position to be recorded. This capability is especially relevant to understand how environmental conditions may affect movement.\",\"PeriodicalId\":216038,\"journal\":{\"name\":\"ACM SIGGRAPH 2019 Posters\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM SIGGRAPH 2019 Posters\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3306214.3338584\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM SIGGRAPH 2019 Posters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3306214.3338584","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GPGPU acceleration of environmental and movement datasets
Due to the increased availability and accuracy of GPS sensors, the field of movement ecology has been able to benefit from larger datasets of movement data. As miniaturisation and the efficiency of electronic components have improved, additional sensors have been coupled with GPS tracking to enable features related to the animal's state at a given position to be recorded. This capability is especially relevant to understand how environmental conditions may affect movement.