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Analysis of the landscape change at River Basin scale based on SPOT and TM fusion remote sensing images: a case study of the Weigou River Basin on the Chinese Loess Plateau

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Abstract

Eco-environmental changes which generally manifest as the ecological landscape changes are mainly affected by natural and human factors. Through complex interaction, natural factors and human activities alter the landscape structure and decide the service function of regional ecosystem. With the development of geographical information system (GIS) and satellite remote sensing (RS) techniques, the researches on quantitative analysis of landscape changes have made great strides forward. In this paper, the landscape change dynamics in the Weigou River basin have been investigated by the combined use of high-resolution RS images and GIS techniques. The objectives are to determine the landscape transition rates among landscape types and to quantify changes of various landscape indexes using FRAGSTATS, one of the spatial pattern analysis programs for categorical maps. Under man–machine interactive interpretation method, all of the 10-m resolution SPOT + TM images are classified into six primary types (farmland, forest, grassland, water, construction area and desert) and 12 sub-types based on the interpretation key which was established based on 1947 filed pictures in the Weigou River basin. A field check on the data accuracy shows that the total interpretation accuracy approaches 97.53%. Significant land-use change has taken place in the Weigou River basin over the six years from 1998 to 2004 due to rehabilitation measures. The results show that there has been a notable decrease in farmland mainly due to conversion to forest and grassland, the landscape heterogeneity and evenness has increased, and there is a greater connectivity. The dominance of farmland patch has decreased. And hence the ecological environment has started to develop in a reversing direction. The study of the integration of high-resolution RS images and GIS technique is an effective approach to analyze the landscape changes at river basin scale.

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Abbreviations

ha:

Hectares

km:

Kilometer

GIS:

Geographical information system

RS:

Remote sensing

HRV:

High resolution visible

TM:

Thematic mapper

FRAGSTATS:

Spatial pattern analysis program for categorical maps

CA:

Class area

PLAND:

Percentage of landscape

NP:

Number of patches

LPI:

Largest patch index

MPS:

Mean patch size

AWMSI:

Area-weighted mean shape index

AWMPFD:

Area-weighted mean patch fractal dimension

MPI:

Mean proximity index

MNN:

Mean nearest-neighbor distance

IJI:

Interspersion and juxtaposition index

CONTAG:

Contagion index

SHDI:

Shannon’s diversity index

SHEI:

Shannon’s evenness index

RUSLE:

Revised universal soil loss equation

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Acknowledgments

This paper is supported by the National Natural Science Foundation of China (Grant Nos. 40671061). The authors would like to thank Li Xiaoying, Liu Zaiwen, You Zhiyuan, Yang Shihu and other members in the research group.

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Authors and Affiliations

  1. College of Resource and Environmental Science, Lanzhou University, Lanzhou, 730000, China

    Dong Xiaofeng & Liu Lichen

  2. Cold and Arid Regional Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, 730000, China

    Wang Jianhua

  3. School of Agricultural and Forestry Economics, Lanzhou Commercial College, Lanzhou, 730020, China

    Shi Jin

  4. Development and Application Research Center of GIS, Northwest Normal University, Lanzhou, 730070, China

    Pan Jinghu

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  1. Dong Xiaofeng
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  2. Liu Lichen
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  4. Shi Jin
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Correspondence to Liu Lichen.

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Xiaofeng, D., Lichen, L., Jianhua, W. et al. Analysis of the landscape change at River Basin scale based on SPOT and TM fusion remote sensing images: a case study of the Weigou River Basin on the Chinese Loess Plateau. Int J Earth Sci (Geol Rundsch) 98, 651–664 (2009). https://doi.org/10.1007/s00531-007-0271-2

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