Classification of Space Images for Forest State Identification Within the Siberia Region: Part 1

Sakhatsky, A.I., Khodorovsky, A.Ya., Bujanova, I.J., & McCallum, I. ORCID: https://orcid.org/0000-0002-5812-9988 (2002). Classification of Space Images for Forest State Identification Within the Siberia Region: Part 1. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-02-029

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Abstract

This paper describes the initial stages of a multi-phase collaborative effort underway between IIASA's Forestry Project and the Center of Aerospace Research of the Earth (CASRE). The main goal of this effort is to develop a procedure for the retrieval of forest inventory information across Siberia, Russia. Due to the great size of the area, satellite data may play an important role. We are currently investigating the application of a multi-sensor approach, whereby a combination of high and low resolution sensors is used to achieve results.

Initial efforts have focused on the classification of high-resolution Landsat images with the aid of GIS ground-truth data. In addition, a brief analysis was made of SPOT Vegetation data over the study site. The interaction between the detailed GIS data, the high-resolution Landsat data, and the course resolution SPOT Vegetation data was explored. It appears difficult at present to merge these various datasets in a meaningful way. It will be necessary to incorporate other sensors, possibly those of a moderate resolution in order to tackle the problem. One additional area of investigation begun here was the possible identification of different types of disturbances, in particular, damage from pests. At this stage, it appears that the interpretation of a classified Landsat image after threshholding allows for the identification of forests affected by the Siberian moth.

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