{"title":"VAST 2017迷你挑战赛的时空分析","authors":"Chris Muller, Kevin McGurgan, Stephanie Kane","doi":"10.1109/VAST.2017.8585475","DOIUrl":null,"url":null,"abstract":"This paper summarizes the approach and tools used by our team to analyze the dataset for Mini-Challenge 1 of the 2017 VAST Challenge. The goal of the mini-challenge was to find patterns of traffic activity within the park that may be associated with declining numbers of nesting bird pairs. We developed a custom, web-based application using Python and JavaScript to visualize and analyze the data to solve the mini-challenge.","PeriodicalId":149607,"journal":{"name":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Temporal and Spatial Analysis of VAST 2017’s Mini-Challenge 1\",\"authors\":\"Chris Muller, Kevin McGurgan, Stephanie Kane\",\"doi\":\"10.1109/VAST.2017.8585475\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper summarizes the approach and tools used by our team to analyze the dataset for Mini-Challenge 1 of the 2017 VAST Challenge. The goal of the mini-challenge was to find patterns of traffic activity within the park that may be associated with declining numbers of nesting bird pairs. We developed a custom, web-based application using Python and JavaScript to visualize and analyze the data to solve the mini-challenge.\",\"PeriodicalId\":149607,\"journal\":{\"name\":\"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VAST.2017.8585475\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Conference on Visual Analytics Science and Technology (VAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VAST.2017.8585475","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Temporal and Spatial Analysis of VAST 2017’s Mini-Challenge 1
This paper summarizes the approach and tools used by our team to analyze the dataset for Mini-Challenge 1 of the 2017 VAST Challenge. The goal of the mini-challenge was to find patterns of traffic activity within the park that may be associated with declining numbers of nesting bird pairs. We developed a custom, web-based application using Python and JavaScript to visualize and analyze the data to solve the mini-challenge.