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Spatio-Temporal data modeling in response to deforestation monitoring (a case study of small region in Riau Province, Indonesia)
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| 13.81 MB | Adobe PDF |
Autores
Resumo(s)
Indonesia with large amount of area covered by tropical forest faces a critical
problem of deforestation. A lot of forested areas were converted into other coverage
influenced by human activities. Therefore, deforestation monitoring and forest
prediction have to be done in order to manage the sustainability of forest. To monitor
deforestation, this research has analyzed the trend of forest cover in the study area by
combining NDVI differencing and image classification to describe the forest cover
change. In order to do that, Landsat images acquired in different time (1996, 2000,
and 2005) have been chosen as input. NDVI differencing has been conducted by
doing normalization of one image to another image initially. Subsequently, thresholds
to identify the change and no change have been carried out separately for decrease
and increase part. Apart from that, image classification was applied using supervised
classification. Eventually, land cover change detection has been performed by
combining NDVI differencing and image classification. It has been proved by the
research that forest in study area has decreased by 6% during 1996-2005.
In order to forecast future forest cover, three models were chosen to get the
best model for prediction. These models are Stochastic Markov Modal, Cellular
Automata Markov (CA_Markov) Model, and GEOMOD. To measure the best model
among them, Kappa index was employed to validate the simulation. As the result,
GEOMOD performed the highest Kappa. Therefore, GEOMOD was implemented to
model forest cover in 2015. The result of GEOMOD implementation revealed that
forest cover will be decreased by 12% during 2005-2015.
Descrição
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
Palavras-chave
Forest Deforestation Monitoring Prediction NDVI differencing Image Classification Landsat Normalization Supervised Classification Stochastic Markov Model CA_Markov Model GEOMOD Kappa index Validate