Author:

Cheng-Liang Chang,

Jui-Chin Chang

Original Tittle:

Applications of Markov Model and Cellular Automata for Vegetation Recovery Simulation: A Case Study of Mount Jiou Jiou Area

Abstract:

The recovery of vegetation is the most significant landscape in the terrestrial globe. In recent years it has been changed rapidly due to human socio-economic growth and environmental impact. Therefore, many research methods have been applied so as to comprehend and forecast these dynamic changes.  This paper intends to apply some of theses methods and processes to quantify the change of vegetation recovery in Mount Jiou Jiou area. First of all, the graphic data of study area is collected by using the SPOT satellite images of four representative periods (Mar.1999, Oct.1999, Nov.2002 and Nov.2005).  Subsequently the vegetation types and their changes are examined through the Normalized Difference Vegetation Index (NDVI) analysis. Second, the Geographic Information System (GIS) technology is adopted to recognize the distributions of different vegetation types, characteristics of topography and their correlation. Finally, by combining the methods of Markov chains and Cellular automata this study models and simulates the spatio-temporal change of vegetation recovery. The results can be summarized as follow: (1) After 921 earthquake, 80% of vegetation on Mount Jiou Jiou area was destroyed seriously in 1999, therefore the index of NDVI was very low. After that, the vegetation is recovered gradually for recent years under stable weather conditions. (2) The healing situation of vegetation is intensely affected by geomorphologic factors, such as height, slope and aspect. (3).After comparing two models testing, the present study shows that CA-Markov model is more suitable for simulating the change trend of vegetation recovery.

Language:

Chinese

Publisher:

Journal of Geographical Research No.45, November 2006

Download (pdf):

Right Click and Save this link

Author:

1. CLAUDIA MARIA DE ALMEIDA
2. ANTONIO MIGUEL VIEIRA MONTEIRO
3. GILBERTO CAMARA
4. BRITALDO SILVEIRA
5. SOARES-FILHO
6. GUSTAVO COUTINHO CERQUEIRA
7. CASSIO LOPES PENNACHIN
8. MICHAEL BATTY

Abstract:

This paper is concerned with building up methodological guidelines for modelling urban land-use change through Geographical Information Systems, remote sensing imagery and Bayesian probabilistic methods. A medium-sized town in the west of Sa˜o Paulo State, Bauru, was adopted as a case study. Its urban structure was converted into a 100m6100m resolution grid and transition probabilities were calculated for each grid cell by means of the ‘weights of evidence’ statistical method and upon the basis of the information related to the technical infrastructure and socio-economic aspects of the town. The probabilities obtained from there fed a cellular automaton simulation model—DINAMICA—developed by the Centre for Remote Sensing of the Federal University of Minas Gerais (CSR-UFMG), based on stochastic transition algorithms. Different simulation outputs for the case study town in the period 1979–1988 were generated, and statistical validation tests were then conducted for the best results, employing a multiple resolution fitting procedure.  This modelling experiment revealed the plausibility of adopting Bayesian empirical methods based on the available knowledge of technical infrastructure and socio-economic status to simulate urban land-use change. It indicates their possible further applicability for generating forecasts of growth trends both for Brazilian cities and cities world-wide.

Publisher:

International Journal of Remote Sensing
Vol. 26, No. 4, 20 February 2005, 759–774

Download (PDF):

Right Click and Save this Link