Abstract
Exploring how human activity impacts land use/cover change (LUCC) is a hot research topic in the field of geography and sustainability management. Researchers have primarily used socioeconomic variables to measure human activity. However, the human activity indexes mainly based on socioeconomic variables have a spatial resolution that is coarser than traditional LUCC datasets, which hinders a deep and comprehensive analysis. In view of these problems, we selected China’s Lijiang River Basin as our study area and proposed the use of GPS trajectory data for analyzing the impact of human activity on LUCC from two perspectives: (1) Type of population: we used the kernel density estimation method to extract the spatial distribution of activity intensity of local residents and tourists, investigated their correlation with the LUCC result, and found these two populations have different impacts on each land cover; (2) Flow of population: we used the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and a network analysis method to build a flow network of population from raw trajectories, conducted regression analysis with LUCC, and found that the flow of population is an important factor driving LUCC and is sometimes a more important factor than the static distribution of the population. Experimental results validated that the proposed method can be used to uncover the impact mechanism of human activity on LUCC at fine-grained scales and provide more accurate planning and instructions for sustainability management.
Highlights
Since the Industrial Revolution in 1760s, human activity has brought significant changes to Earth’s natural environment with the improvement of engineering tools
By comparing classification results and validation datasets, the classification accuracies for the years 2009 and 2013 are 79.81% and 82.69%, respectively. This is usually acceptable in land cover change research
In order to fill this gap, we selected the Lijiang River Basin as a study area, introduced the emerging participatory sensing technology, and analyzed the impact of human activity on land use/cover changes (LUCC) from the perspectives of flow and type of population: (1) we used the kernel density estimation to extract the spatial distribution of activity intensity of local people and tourists from GPS trajectory data, and overlaid human activity on LUCC to explore the correlation characteristics between the two types of populations and each land cover; (2) we used the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm and a network analysis method to build a flow network of population from raw trajectories, and conducted regression analysis to explore the influence of the flow of population on the change of each land cover
Summary
Since the Industrial Revolution in 1760s, human activity has brought significant changes to Earth’s natural environment with the improvement of engineering tools. An apparent phenomenon among these is the change of land cover [1]. According to some estimates [2,3], the majority of the terrestrial biosphere was transformed to agricultural and settled anthromes by 2000. During the period from 1880 to 1980, logging resulted in a 47% decline of forest/woodland in tropical Asia [4]. Human-induced land use/cover changes (LUCC), in turn, affect human survival and development, which has raised widespread concerns in human society. We mean all undertakings by humans for survival and improvement of living standards including land reclamation, grazing, water resource use and development, engineering construction, ecological system management, etc. We mean all undertakings by humans for survival and improvement of living standards including land reclamation, grazing, water resource use and development, engineering construction, ecological system management, etc. [5]
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