{"title":"远足时间公式:回顾","authors":"Erich Prisner, Peter Sui","doi":"10.1080/15230406.2023.2197625","DOIUrl":null,"url":null,"abstract":"ABSTRACT Hiking-time formulas attempt to predict the time required for a hike based on available data. Most known hiking-time formulas can be classified into either pace-based, requiring the elevation profile as input, or formulas having horizontal distance , cumulative elevation gain and loss as input. In the first part of the paper, we discuss some known formulas, give a list of desirable features of such pace-based functions, discuss advantages and disadvantages of the two approaches and the connection between them. It turns out that only linear functions with input and have uniquely identifiable pace-based function counterparts. Then. we demonstrate how such simple linear functions with input and can be constructed for individuals provided enough hiking data are available, using a case study of four hikers. We also include simple adjustments for the formulas based on the elevation of start and end point of the hike. Although no statistically valid conclusions can be drawn from such a small nonrandom sample, the results still give some insight into practical questions for hikers.","PeriodicalId":47562,"journal":{"name":"Cartography and Geographic Information Science","volume":"50 1","pages":"421 - 432"},"PeriodicalIF":2.6000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hiking-time formulas: a review\",\"authors\":\"Erich Prisner, Peter Sui\",\"doi\":\"10.1080/15230406.2023.2197625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Hiking-time formulas attempt to predict the time required for a hike based on available data. Most known hiking-time formulas can be classified into either pace-based, requiring the elevation profile as input, or formulas having horizontal distance , cumulative elevation gain and loss as input. In the first part of the paper, we discuss some known formulas, give a list of desirable features of such pace-based functions, discuss advantages and disadvantages of the two approaches and the connection between them. It turns out that only linear functions with input and have uniquely identifiable pace-based function counterparts. Then. we demonstrate how such simple linear functions with input and can be constructed for individuals provided enough hiking data are available, using a case study of four hikers. We also include simple adjustments for the formulas based on the elevation of start and end point of the hike. Although no statistically valid conclusions can be drawn from such a small nonrandom sample, the results still give some insight into practical questions for hikers.\",\"PeriodicalId\":47562,\"journal\":{\"name\":\"Cartography and Geographic Information Science\",\"volume\":\"50 1\",\"pages\":\"421 - 432\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2023-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Cartography and Geographic Information Science\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1080/15230406.2023.2197625\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"GEOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cartography and Geographic Information Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/15230406.2023.2197625","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GEOGRAPHY","Score":null,"Total":0}
ABSTRACT Hiking-time formulas attempt to predict the time required for a hike based on available data. Most known hiking-time formulas can be classified into either pace-based, requiring the elevation profile as input, or formulas having horizontal distance , cumulative elevation gain and loss as input. In the first part of the paper, we discuss some known formulas, give a list of desirable features of such pace-based functions, discuss advantages and disadvantages of the two approaches and the connection between them. It turns out that only linear functions with input and have uniquely identifiable pace-based function counterparts. Then. we demonstrate how such simple linear functions with input and can be constructed for individuals provided enough hiking data are available, using a case study of four hikers. We also include simple adjustments for the formulas based on the elevation of start and end point of the hike. Although no statistically valid conclusions can be drawn from such a small nonrandom sample, the results still give some insight into practical questions for hikers.
期刊介绍:
Cartography and Geographic Information Science (CaGIS) is the official publication of the Cartography and Geographic Information Society (CaGIS), a member organization of the American Congress on Surveying and Mapping (ACSM). The Cartography and Geographic Information Society supports research, education, and practices that improve the understanding, creation, analysis, and use of maps and geographic information. The society serves as a forum for the exchange of original concepts, techniques, approaches, and experiences by those who design, implement, and use geospatial technologies through the publication of authoritative articles and international papers.