Remote sensing and Markov model analysis on forest change in hun watershed

Dianzhong Wang; Zhanqing Hao; Wenquan Han; Sun Guoqing

doi:10.1109/IGARSS.2006.793

Remote sensing and Markov model analysis on forest change in hun watershed

Dianzhong Wang
, Zhanqing Hao
, Wenquan Han
, Sun Guoqing

CAS - Shenyang Institute of Applied Ecology
University of Chinese Academy of Sciences
Beijing Normal University
Nanjing University

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

Abstract

In this paper, remote sensing analysis was integrated with stochastic theory to evaluate the magnitude, the pattern, and the mode of forest changes in a forested watershed. We visually interpreted three scenes of Landsat TM Images obtained In 1986, 1992, and 2001 into nine categories of forest landscape maps. We thus combined Markov models and remote sensing and studied the changes of two time spans, 1986-1992 and 1992-2001. We found that broadleaved forest and larch plantation were the largest two categories. Each dominated the forest change of one span. And we found the change modes were different despite of the similar increase rate of total forest. This study demonstrated that remote sensing analysis with Markov modeling could effectively monitor and analyze the characteristics of forest change even in the presence of different anthropogenic influences.

Original language	English
Title of host publication	2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
Pages	3090-3092
Number of pages	3
DOIs	https://doi.org/10.1109/IGARSS.2006.793
State	Published - 2006
Externally published	Yes
Event	2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS - Denver, CO, United States Duration: 31 Jul 2006 → 4 Aug 2006

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference	2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
Country/Territory	United States
City	Denver, CO
Period	31/07/06 → 4/08/06

Keywords

Markov model
Remote sensing analysis
Transition probability

Access to Document

10.1109/IGARSS.2006.793

Cite this

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title = "Remote sensing and Markov model analysis on forest change in hun watershed",

abstract = "In this paper, remote sensing analysis was integrated with stochastic theory to evaluate the magnitude, the pattern, and the mode of forest changes in a forested watershed. We visually interpreted three scenes of Landsat TM Images obtained In 1986, 1992, and 2001 into nine categories of forest landscape maps. We thus combined Markov models and remote sensing and studied the changes of two time spans, 1986-1992 and 1992-2001. We found that broadleaved forest and larch plantation were the largest two categories. Each dominated the forest change of one span. And we found the change modes were different despite of the similar increase rate of total forest. This study demonstrated that remote sensing analysis with Markov modeling could effectively monitor and analyze the characteristics of forest change even in the presence of different anthropogenic influences.",

keywords = "Markov model, Remote sensing analysis, Transition probability",

author = "Dianzhong Wang and Zhanqing Hao and Wenquan Han and Sun Guoqing",

year = "2006",

doi = "10.1109/IGARSS.2006.793",

language = "英语",

isbn = "0780395107",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

pages = "3090--3092",

booktitle = "2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS",

note = "2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS ; Conference date: 31-07-2006 Through 04-08-2006",

}

Wang, D, Hao, Z, Han, W & Guoqing, S 2006, Remote sensing and Markov model analysis on forest change in hun watershed. in 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS., 4241941, International Geoscience and Remote Sensing Symposium (IGARSS), pp. 3090-3092, 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS, Denver, CO, United States, 31/07/06. https://doi.org/10.1109/IGARSS.2006.793

Remote sensing and Markov model analysis on forest change in hun watershed. / Wang, Dianzhong; Hao, Zhanqing; Han, Wenquan et al.
2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS. 2006. p. 3090-3092 4241941 (International Geoscience and Remote Sensing Symposium (IGARSS)).

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

TY - GEN

T1 - Remote sensing and Markov model analysis on forest change in hun watershed

AU - Wang, Dianzhong

AU - Hao, Zhanqing

AU - Han, Wenquan

AU - Guoqing, Sun

PY - 2006

Y1 - 2006

N2 - In this paper, remote sensing analysis was integrated with stochastic theory to evaluate the magnitude, the pattern, and the mode of forest changes in a forested watershed. We visually interpreted three scenes of Landsat TM Images obtained In 1986, 1992, and 2001 into nine categories of forest landscape maps. We thus combined Markov models and remote sensing and studied the changes of two time spans, 1986-1992 and 1992-2001. We found that broadleaved forest and larch plantation were the largest two categories. Each dominated the forest change of one span. And we found the change modes were different despite of the similar increase rate of total forest. This study demonstrated that remote sensing analysis with Markov modeling could effectively monitor and analyze the characteristics of forest change even in the presence of different anthropogenic influences.

AB - In this paper, remote sensing analysis was integrated with stochastic theory to evaluate the magnitude, the pattern, and the mode of forest changes in a forested watershed. We visually interpreted three scenes of Landsat TM Images obtained In 1986, 1992, and 2001 into nine categories of forest landscape maps. We thus combined Markov models and remote sensing and studied the changes of two time spans, 1986-1992 and 1992-2001. We found that broadleaved forest and larch plantation were the largest two categories. Each dominated the forest change of one span. And we found the change modes were different despite of the similar increase rate of total forest. This study demonstrated that remote sensing analysis with Markov modeling could effectively monitor and analyze the characteristics of forest change even in the presence of different anthropogenic influences.

KW - Markov model

KW - Remote sensing analysis

KW - Transition probability

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DO - 10.1109/IGARSS.2006.793

M3 - 会议稿件

AN - SCOPUS:34948890611

SN - 0780395107

SN - 9780780395107

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 3090

EP - 3092

BT - 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS

T2 - 2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS

Y2 - 31 July 2006 through 4 August 2006

ER -

Remote sensing and Markov model analysis on forest change in hun watershed

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Keywords

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