Geoinformation system for prediction of forest fire danger caused by solar radiation using remote sensing data

Nikolay V. Baranovskiy; Elena P. Yankovich

doi:10.1117/12.2193864

20 October 2015 Geoinformation system for prediction of forest fire danger caused by solar radiation using remote sensing data

Nikolay V. Baranovskiy, Elena P. Yankovich

Author Affiliations +

Proceedings Volume 9640, Remote Sensing of Clouds and the Atmosphere XX; 96400Z (2015) https://doi.org/10.1117/12.2193864
Event: SPIE Remote Sensing, 2015, Toulouse, France

Abstract

This article reviews the project of subsystem that reflects the Earth remote sensing data from the space in order to monitor the forest fire danger, caused by the focused solar radiation effect. This subsystem is based on the use of sensing data from the MODIS instrument aboard the Terra satellite. We consider the Timiryazevsky Forestry of Tomsk region to be a typical territory of the boreal forest zone. To estimate the forest fire danger level, we use an original method to classify the forest areas according to their characteristics (the ground mensuration data) and the main meteorological parameters, namely, the cloud cover on this territory, obtained from the MODIS satellite data.

Citation Download Citation

Nikolay V. Baranovskiy and Elena P. Yankovich "Geoinformation system for prediction of forest fire danger caused by solar radiation using remote sensing data", Proc. SPIE 9640, Remote Sensing of Clouds and the Atmosphere XX, 96400Z (20 October 2015); https://doi.org/10.1117/12.2193864

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available