Land use/cover change in mining areas using multi-source remotely sensed imagery

Peijun Du; Huapeng Zhang; Pei Liu; Kun Tan; Zuoxia Yin

doi:10.1109/MULTITEMP.2007.4293074

Land use/cover change in mining areas using multi-source remotely sensed imagery

Peijun Du^*
, Huapeng Zhang
, Pei Liu
, Kun Tan
, Zuoxia Yin

^*Corresponding author for this work

China University of Mining and Technology
University of Nottingham

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

This paper assessed the advantages of monitoring and analyzing Land Use/Cover Change (LUCC) in mining areas via multi-source remotely sensed data. Comparing with the traditional and object-oriented classification methods, the support vector machine classifier is used to land cover classification based on Landsat TM/ETM+ and ASTER data. The landscape pattern indices on patch/class and landscape metrics are chosen to analyze and assess LUCC in mining areas and the land cover changes are derived. Finally, a framework of integrating multi-source and multi-temporal RS information for LUCC in mining areas is proposed.

Original language	English
Title of host publication	Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images
DOIs	https://doi.org/10.1109/MULTITEMP.2007.4293074
State	Published - 2007
Externally published	Yes
Event	2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, MultiTemp 2007 - Leuven, Belgium Duration: 18 Jul 2007 → 20 Jul 2007

Publication series

Name	Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images

Conference

Conference	2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, MultiTemp 2007
Country/Territory	Belgium
City	Leuven
Period	18/07/07 → 20/07/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 15 Life on Land

Keywords

Change vector analysis
Classification
Land Use/Cover Change (LUCC)
Landscape pattern index
Mining areas

Access to Document

10.1109/MULTITEMP.2007.4293074

Cite this

Du, P., Zhang, H., Liu, P., Tan, K., & Yin, Z. (2007). Land use/cover change in mining areas using multi-source remotely sensed imagery. In Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images Article 4293074 (Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images). https://doi.org/10.1109/MULTITEMP.2007.4293074

Du, Peijun ; Zhang, Huapeng ; Liu, Pei et al. / Land use/cover change in mining areas using multi-source remotely sensed imagery. Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images. 2007. (Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images).

@inproceedings{05ba2e37da2644308a5766a550a558cf,

title = "Land use/cover change in mining areas using multi-source remotely sensed imagery",

abstract = "This paper assessed the advantages of monitoring and analyzing Land Use/Cover Change (LUCC) in mining areas via multi-source remotely sensed data. Comparing with the traditional and object-oriented classification methods, the support vector machine classifier is used to land cover classification based on Landsat TM/ETM+ and ASTER data. The landscape pattern indices on patch/class and landscape metrics are chosen to analyze and assess LUCC in mining areas and the land cover changes are derived. Finally, a framework of integrating multi-source and multi-temporal RS information for LUCC in mining areas is proposed.",

keywords = "Change vector analysis, Classification, Land Use/Cover Change (LUCC), Landscape pattern index, Mining areas",

author = "Peijun Du and Huapeng Zhang and Pei Liu and Kun Tan and Zuoxia Yin",

year = "2007",

doi = "10.1109/MULTITEMP.2007.4293074",

language = "英语",

isbn = "1424408466",

series = "Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images",

booktitle = "Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images",

note = "2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, MultiTemp 2007 ; Conference date: 18-07-2007 Through 20-07-2007",

}

Du, P, Zhang, H, Liu, P, Tan, K & Yin, Z 2007, Land use/cover change in mining areas using multi-source remotely sensed imagery. in Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images., 4293074, Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, MultiTemp 2007, Leuven, Belgium, 18/07/07. https://doi.org/10.1109/MULTITEMP.2007.4293074

Land use/cover change in mining areas using multi-source remotely sensed imagery. / Du, Peijun; Zhang, Huapeng; Liu, Pei et al.
Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images. 2007. 4293074 (Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Land use/cover change in mining areas using multi-source remotely sensed imagery

AU - Du, Peijun

AU - Zhang, Huapeng

AU - Liu, Pei

AU - Tan, Kun

AU - Yin, Zuoxia

PY - 2007

Y1 - 2007

N2 - This paper assessed the advantages of monitoring and analyzing Land Use/Cover Change (LUCC) in mining areas via multi-source remotely sensed data. Comparing with the traditional and object-oriented classification methods, the support vector machine classifier is used to land cover classification based on Landsat TM/ETM+ and ASTER data. The landscape pattern indices on patch/class and landscape metrics are chosen to analyze and assess LUCC in mining areas and the land cover changes are derived. Finally, a framework of integrating multi-source and multi-temporal RS information for LUCC in mining areas is proposed.

AB - This paper assessed the advantages of monitoring and analyzing Land Use/Cover Change (LUCC) in mining areas via multi-source remotely sensed data. Comparing with the traditional and object-oriented classification methods, the support vector machine classifier is used to land cover classification based on Landsat TM/ETM+ and ASTER data. The landscape pattern indices on patch/class and landscape metrics are chosen to analyze and assess LUCC in mining areas and the land cover changes are derived. Finally, a framework of integrating multi-source and multi-temporal RS information for LUCC in mining areas is proposed.

KW - Change vector analysis

KW - Classification

KW - Land Use/Cover Change (LUCC)

KW - Landscape pattern index

KW - Mining areas

UR - https://www.scopus.com/pages/publications/47249159045

U2 - 10.1109/MULTITEMP.2007.4293074

DO - 10.1109/MULTITEMP.2007.4293074

M3 - 会议稿件

AN - SCOPUS:47249159045

SN - 1424408466

SN - 9781424408467

T3 - Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images

BT - Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images

T2 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, MultiTemp 2007

Y2 - 18 July 2007 through 20 July 2007

ER -

Du P, Zhang H, Liu P, Tan K, Yin Z. Land use/cover change in mining areas using multi-source remotely sensed imagery. In Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images. 2007. 4293074. (Proceedings of MultiTemp 2007 - 2007 International Workshop on the Analysis of Multi-Temporal Remote Sensing Images). doi: 10.1109/MULTITEMP.2007.4293074

Land use/cover change in mining areas using multi-source remotely sensed imagery

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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