Web-GIS platform for forest fire danger prediction in Ukraine: prospects of RS technologies; Proceedings of SPIE; Vol. 10001 : Remote Sensing of Clouds and the Atmosphere XXI
| Parent link: | Proceedings of SPIE Vol. 10001 : Remote Sensing of Clouds and the Atmosphere XXI.— 2016.— [100010Y, 6 p.] |
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| Résumé: | Title screen 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). Режим доступа: по договору с организацией-держателем ресурса |
| Langue: | anglais |
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2016
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| Collection: | Poster Session |
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| Accès en ligne: | http://dx.doi.org/10.1117/12.2241670 |
| Format: | Électronique Chapitre de livre |
| KOHA link: | https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=654196 |