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Proceedings Paper

Web-GIS platform for forest fire danger prediction in Ukraine: prospects of RS technologies
Author(s): N. V. Baranovskiy; M. V. Zharikova
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Paper Abstract

There are many different statistical and empirical methods of forest fire danger use at present time. All systems have not physical basis. Last decade deterministic-probabilistic method is rapidly developed in Tomsk Polytechnic University. Forest sites classification is one way to estimate forest fire danger. We used this method in present work. Forest fire danger estimation depends on forest vegetation condition, forest fire retrospective, precipitation and air temperature. In fact, we use modified Nesterov Criterion. Lightning activity is under consideration as a high temperature source in present work. We use Web-GIS platform for program realization of this method. The program realization of the fire danger assessment system is the Web-oriented geoinformation system developed by the Django platform in the programming language Python. The GeoDjango framework was used for realization of cartographic functions. We suggest using of Terra/Aqua MODIS products for hot spot monitoring. Typical territory for forest fire danger estimation is Proletarskoe forestry of Kherson region (Ukraine).

Paper Details

Date Published: 19 October 2016
PDF: 6 pages
Proc. SPIE 10001, Remote Sensing of Clouds and the Atmosphere XXI, 100010Y (19 October 2016); doi: 10.1117/12.2241670
Show Author Affiliations
N. V. Baranovskiy, Tomsk Polytechnic Univ. (Russian Federation)
M. V. Zharikova, Kherson National Technical Univ. (Ukraine)

Published in SPIE Proceedings Vol. 10001:
Remote Sensing of Clouds and the Atmosphere XXI
Adolfo Comerón; Evgueni I. Kassianov; Klaus Schäfer, Editor(s)

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