Abstract

Land use/land cover change (LUCC) is the most direct driving force of landscape pattern change. The Zoige Plateau is a natural ecosystem with the largest high-altitude swamp wetland in China and its land use pattern has undergone great changes in recent years, but how the changes of each land use type affect the landscape pattern is uncertain. Here, we used the object-oriented method to extract land use information in 2015. Then, combined with land use data, the land use change characteristics from 2000 to 2015 were analyzed. We used the correlation analysis method to analyze the effects of land use changes on landscape pattern systematically. Three key conclusions were reached. (1) Land use information for the Zoige Plateau could be extracted with high accuracy by combining the object-oriented method and support vector machine (SVM). The overall accuracy was 93.2% and the Kappa coefficient was 0.889. (2) The comprehensive dynamic degree of land use was the highest from 2010 to 2015. From 2000 to 2015, the wetland area decreased the fastest because 57.05% of the wetlands were transferred out. Construction land increased the fastest, and the transferred in area from grassland and farmland were the main reason. (3) The effects of unused land, farmland, and construction land on the overall landscape pattern were stronger than that of the other types, among which farmland had the most significant impact (with a correlation coefficient of 0.959, p < 0.001). The change of unused land was the most highly significant factor associated with the landscape area pattern, and both the water body and unused land showed strong correlations with landscape shape pattern change. This suggested that the effects of land use types occupying a relatively small area on the landscape pattern were intensified. This study will provide guidance for the environmental management of local land resources and other natural ecosystem areas.

Highlights

  • Land use and land cover change (LUCC) is a basic parameter to quantify changes in the natural environment and to measure the impact of human activity [1,2,3,4]

  • With respect to individual classes, except that the user’s accuracy of water body obtained by K-nearest neighbor (KNN) method was greater than the result of support vector machine (SVM) method, all other SVM classification results were better than KNN

  • Our study showed that it was feasible to extract land use information in the Zoige Plateau by combining the object-oriented method and SVM

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Summary

Introduction

Land use and land cover change (LUCC) is a basic parameter to quantify changes in the natural environment and to measure the impact of human activity [1,2,3,4]. As one of the decisive factors affecting the global ecosystem and the most direct manifestation of global change [5,6,7], LUCC has always been an important concern in global climate change and global environmental change research [7,8,9]. The rapid development of new satellite sensors and automatic techniques for classification has enabled researchers to expand the scale of studies from local surveys to macroscopic regional and global monitoring [8,14,15]. Pixel-based and object-based techniques are the two main approaches generally used for classification. Object-based classification is generally better than that based on pixels, especially for high resolution images [18]. Object-oriented analysis (OOA), referred to as object-based image analysis (OBIA), is becoming a popular research direction, and good results have already been achieved [17,18,19]

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