Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China
The interaction between human activity and landscape pattern has been a hot research topic during the last few decades. However, scholars used to measure human activity by social, economic and humanistic indexes. These indexes cannot directly reflect human activity and are not suitable for fine-grai...
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doaj-0ed2a5453a0543e69b79f6818e9f33512020-11-24T21:07:34ZengMDPI AGISPRS International Journal of Geo-Information2220-99642016-06-015710410.3390/ijgi5070104ijgi5070104Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, ChinaJun Li0Yuan Zhang1Xiang Wang2Qiming Qin3Zhuangzhuang Wei4Jingze Li5College of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, ChinaInstitute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, ChinaInstitute of Remote Sensing and Geographic Information Systems, Peking University, Beijing 100871, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, ChinaCollege of Geoscience and Surveying Engineering, China University of Mining and Technology, Beijing 100083, ChinaThe interaction between human activity and landscape pattern has been a hot research topic during the last few decades. However, scholars used to measure human activity by social, economic and humanistic indexes. These indexes cannot directly reflect human activity and are not suitable for fine-grained analysis due to the coarse spatial resolution. In view of the above problems, this paper proposes a method that obtains the intensity of human activity from GPS trajectory data, collects landscape information from remote sensing images and further analyzes the interaction between human activity and landscape pattern at a fine-grained scale. The Lijiang River Basin is selected as the study area. Experimental results show that human activity and landscape pattern interact synergistically in this area. Built-up land and water boost human activity, while woodland restrains human activity. The effect of human activity on landscape pattern differs by the land cover category. Overall, human activities make natural land, such as woodland and water, scattered and fragmented, but cause man-built land, such as built-up land and farmland, clustered and regular. Nevertheless, human activities inside and outside urban areas are the opposite. The research findings in this paper are helpful for designing and implementing sustainable management plans.http://www.mdpi.com/2220-9964/5/7/104remote sensinglandscape patterntrajectory datahuman activityinteraction analysis |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jun Li Yuan Zhang Xiang Wang Qiming Qin Zhuangzhuang Wei Jingze Li |
spellingShingle |
Jun Li Yuan Zhang Xiang Wang Qiming Qin Zhuangzhuang Wei Jingze Li Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China ISPRS International Journal of Geo-Information remote sensing landscape pattern trajectory data human activity interaction analysis |
author_facet |
Jun Li Yuan Zhang Xiang Wang Qiming Qin Zhuangzhuang Wei Jingze Li |
author_sort |
Jun Li |
title |
Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China |
title_short |
Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China |
title_full |
Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China |
title_fullStr |
Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China |
title_full_unstemmed |
Application of GPS Trajectory Data for Investigating the Interaction between Human Activity and Landscape Pattern: A Case Study of the Lijiang River Basin, China |
title_sort |
application of gps trajectory data for investigating the interaction between human activity and landscape pattern: a case study of the lijiang river basin, china |
publisher |
MDPI AG |
series |
ISPRS International Journal of Geo-Information |
issn |
2220-9964 |
publishDate |
2016-06-01 |
description |
The interaction between human activity and landscape pattern has been a hot research topic during the last few decades. However, scholars used to measure human activity by social, economic and humanistic indexes. These indexes cannot directly reflect human activity and are not suitable for fine-grained analysis due to the coarse spatial resolution. In view of the above problems, this paper proposes a method that obtains the intensity of human activity from GPS trajectory data, collects landscape information from remote sensing images and further analyzes the interaction between human activity and landscape pattern at a fine-grained scale. The Lijiang River Basin is selected as the study area. Experimental results show that human activity and landscape pattern interact synergistically in this area. Built-up land and water boost human activity, while woodland restrains human activity. The effect of human activity on landscape pattern differs by the land cover category. Overall, human activities make natural land, such as woodland and water, scattered and fragmented, but cause man-built land, such as built-up land and farmland, clustered and regular. Nevertheless, human activities inside and outside urban areas are the opposite. The research findings in this paper are helpful for designing and implementing sustainable management plans. |
topic |
remote sensing landscape pattern trajectory data human activity interaction analysis |
url |
http://www.mdpi.com/2220-9964/5/7/104 |
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