Research plan:

Well its just very earlier idea and plant and could be subject to change particularly on the study area but I hope not on the objectives, hopely:

Title: Remote sensing and Geographic Information systems for monitoring of forest condition and developing of forest fire hazard models.

Objectives of study:

1. To monitor forest condition, particularly on actual rate of deforestation, forest distribution, and ecological forest condition using remote sensing and geographic information system for the rehabilitation and management of tropical forest in Sasamba area of East Kalimantan province, Indonesia.

2. To develop land degradation models with emphasis on forest fire and soil erosion models which may result on land degradation hazard in East Kalimantan, Indonesia.

Background.

It is no doubt, that forest fire event in East Kalimantan since 1982 has been resulting on the destruction of forest, which may induce on accelerating soil erosion, land use/cover conflicts, and changes in ecological of tropical forest condition. All of these processes will bring to lead of Land degradation problem. However, type of research using remote sensing and Geographic information system (GIS) to monitor the forest condition and predicting model for land degradation hazard for input of the rehabilitation and management of tropical forest in East Kalimantan, is generally lacking. Therefore it is important to examine the possibility of remote sensing and GIS technique as a means for monitoring of forest condition and forest fire hazard.

Study area

Sasamba area in East Kalimantan province Indonesia will be selected for the study site. This area has long stories about forest fires and severe affected by last forest fire in 1997/1998. This area also is known as the most degraded area in East Kalimantan. However this area has been established by the Indonesian Government as one of the region of integrated of economical development (KAPET) in Eastern of Indonesia. Economical development of this area would be expected to accelerate the economical of the entire East Kalimantan province.

Methods

A multi temporal remote sensing data and digital elevation model (DEM) are will be used as the main data. The others variables will be derived from these two data corresponding to ecological forest condition, and forest fire hazard models. Six techniques change detections will be applied to evaluate the forest condition and identify burned areas are as follows: (1) spectral image differencing; (2) image rationing; (3) image regression; (4) change vector analysis; (5) vegetation index differencing, and (6) principle component analysis.

Integration of remote sensing and geographic information systems will be used to determine the ecological forest condition. Two type of forest will be selected, one as natural forest and the others as secondary forest. The ecological factors are then measures, particularly for determining of fuel type, biomass, ANPP and carbon lost.

The weight variable and statistical analysis (multi regression analysis) will be applied to develop forest fire hazard model. The GIS will be used to analysis the final model of forest fire hazard and ecological forest condition. The models are then will be assessed with the actual condition through ground check or using different remote sensing data.

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Expected result.

Through this study, it is expecting that the forest condition in East Kalimantan after several forest fires could be grasped, particularly on actual rate of deforestation, recently and prediction of ecological forest condition. Within this study also is expected that a model of land degradation in East Kalimantan can be mapped. Based on this land degradation map and forest condition recognition, it could be possible to determine the rehabilitation and management model of tropical rain forest in East Kalimantan.

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