Modeling walkability by remote sensing as latent walking speed extracted from multiple digital trail maps

IF 1.8 Q2 GEOGRAPHY
Ljiljana Šerić, Marina Tavra, I. Racetin, Antonia Ivanda
{"title":"Modeling walkability by remote sensing as latent walking speed extracted from multiple digital trail maps","authors":"Ljiljana Šerić, Marina Tavra, I. Racetin, Antonia Ivanda","doi":"10.5311/josis.2022.25.204","DOIUrl":null,"url":null,"abstract":"Coordinating and managing teams searching for missing persons in wilderness areas is challenging. Local terrain characteristics and environmental conditions strongly influence how searchers accomplish their search tasks. When making decisions, searchers consult various maps of the area. In this paper we proposed a methodology for mapping characteristics of the area that influence user behavior when walking the area, and define a walkability model of the terrain. We define walkability as a measure of how fast a person can walk through terrain. The observed walking speed depends on factors such as the fitness and motivation of a person walking through the terrain, as well as on assistive features and the configuration of the terrain. In our method, walkability is predicted only as a feature of terrain configuration. We used singular value decomposition (SVD) to transform datasets to extract latent features of the terrain and users from multiple Global Positioning System (GPS) trails. We define the walkability measure as a latent component of walking speed, which is a function of terrain features. Finally, we use a  polynomial regression algorithm to build a model for predicting terrain walkability based on remote sensing imagery from the Sentinel-2 mission. The application of the proposed model is demonstrated in the Kozjak mountain region in the Republic of Croatia.","PeriodicalId":45389,"journal":{"name":"Journal of Spatial Information Science","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2022-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Spatial Information Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5311/josis.2022.25.204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 1

Abstract

Coordinating and managing teams searching for missing persons in wilderness areas is challenging. Local terrain characteristics and environmental conditions strongly influence how searchers accomplish their search tasks. When making decisions, searchers consult various maps of the area. In this paper we proposed a methodology for mapping characteristics of the area that influence user behavior when walking the area, and define a walkability model of the terrain. We define walkability as a measure of how fast a person can walk through terrain. The observed walking speed depends on factors such as the fitness and motivation of a person walking through the terrain, as well as on assistive features and the configuration of the terrain. In our method, walkability is predicted only as a feature of terrain configuration. We used singular value decomposition (SVD) to transform datasets to extract latent features of the terrain and users from multiple Global Positioning System (GPS) trails. We define the walkability measure as a latent component of walking speed, which is a function of terrain features. Finally, we use a  polynomial regression algorithm to build a model for predicting terrain walkability based on remote sensing imagery from the Sentinel-2 mission. The application of the proposed model is demonstrated in the Kozjak mountain region in the Republic of Croatia.
从多个数字步道地图中提取潜在步行速度的遥感可步行性建模
协调和管理在荒野地区搜寻失踪人员的小组具有挑战性。当地地形特征和环境条件强烈影响搜索人员完成搜索任务的方式。在做出决定时,搜索人员会查阅该地区的各种地图。在本文中,我们提出了一种绘制影响用户在该区域行走时行为的区域特征的方法,并定义了地形的可行走性模型。我们将可步行性定义为一个人在地形中行走的速度。观察到的步行速度取决于一些因素,如一个人在地形中行走的健康度和动机,以及辅助功能和地形的配置。在我们的方法中,步行能力仅作为地形配置的一个特征进行预测。我们使用奇异值分解(SVD)对数据集进行变换,从多个全球定位系统(GPS)轨迹中提取地形和用户的潜在特征。我们将步行能力测量定义为步行速度的潜在组成部分,步行速度是地形特征的函数。最后,我们使用多项式回归算法,基于哨兵2号任务的遥感图像,建立了一个预测地形可步行性的模型。所提出的模型在克罗地亚共和国的Kozjak山区得到了应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
5.10
自引率
0.00%
发文量
5
审稿时长
9 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信