Review article

A Review of Satellite Missions and Forest Cover Classification Methods Using High Resolution Satellite Imagery

Martina Deur orcid.org/0000-0002-3917-4337 ; Zavod za prostorno uređenje Šibensko-kninske županije, Šibenik, Hrvatska
Mateo Gašparović orcid.org/0000-0003-2345-7882 ; Faculty of Geodesy, University of Zagreb, Zagreb, Croatia
Ivan Balenović orcid.org/0000-0001-7422-753X ; Croatian Forest Research Institute, Zagreb, Croatia

Abstract

Advances in remote sensing technologies enables increasing achievements in the field of tree species classification. In recent years, significant technological progress and improvements in the characteristics of optical sensors have been made, thus enabling improved resolution of details on satellite imagery (spatial, spectral and radiometric resolution). The increase in spatial resolution had a significant impact on the development of remote sensing techniques and methods. A new generation of very high resolution satellite imagery enables research at local and regional levels and represent a important source of forestry information. The aim of this paper is to provide an overview of global high and very high resolution satellite missions, as well as analysis and processing methodology in forest cover classification. In combination with machine learning algorithms, the application of high and very high resolution satellite imageries reduces the need for labor-intensive and time-consuming traditional field methods while increasing the quantitative and qualitative value of the information obtained in forestry.

Keywords

remote sensing; high resolution satellite imagery; forest cover classification

Hrčak ID:

261116

URI

https://hrcak.srce.hr/261116

Publication date:

27.6.2021.

Article data in other languages: croatian

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