| DC Field | Value | Language |
|---|
| dc.contributor.author | Shepeliev, Oleksandr | |
| dc.contributor.author | Bilova, Mariia | |
| dc.coverage.temporal | 23-24 April 2020, Lviv, Ukraine | |
| dc.date.accessioned | 2020-06-12T11:09:47Z | - |
| dc.date.available | 2020-06-12T11:09:47Z | - |
| dc.date.created | 2020-04-23 | |
| dc.date.issued | 2020-04-23 | |
| dc.identifier.citation | Shepeliev O. State Estimation of Forest condition in the Event of Fire, Based on Satellite Image Processing / Oleksandr Shepeliev, Mariia Bilova // Computational linguistics and intelligent systems : proceedings of the 4nd International conference, 23-24 April 2020, Lviv, Ukraine. — Lviv : Lviv Politechnic Publishing House, 2020. — Vol 2 : Proceedings of the 4nd International conference, COLINS 2020. Workshop, Lviv, Ukraine April 23-24, 2020. — P. 228–229. — (Intelligent Systems). | |
| dc.identifier.issn | 2523-4013 | |
| dc.identifier.uri | https://ena.lpnu.ua/handle/ntb/52139 | - |
| dc.description.abstract | The relevancy of the work connected with the need to improve existing software designed to assess the condition of the forest in the event of a fire.
The task of responding quickly and assessing the state of forests in recent years
has become a very important factor, since the economic and environmental impacts of forests can cause irreparable damage to the state and the planet. Geoinformation systems (GIS) can be used to achieve this goal.
Most Earth observation applications involve converting multi-channel image
data into thematic maps using classification procedures. This research is an attempt to automate the process of extracting feature boundaries from satellite
imagery. | |
| dc.format.extent | 228-229 | |
| dc.language.iso | en | |
| dc.publisher | Видавництво Львівської політехніки | |
| dc.publisher | Lviv Politechnic Publishing House | |
| dc.relation.ispartof | Computational linguistics and intelligent systems : proceedings of the 4nd International conference (2), 2020 | |
| dc.subject | Computer vision | |
| dc.subject | GIS | |
| dc.subject | Feature | |
| dc.subject | Extraction | |
| dc.subject | Imagery | |
| dc.subject | Segmentation | |
| dc.title | State Estimation of Forest condition in the Event of Fire, Based on Satellite Image Processing | |
| dc.type | Article | |
| dc.rights.holder | © Національний університет “Львівська політехніка”, 2020 | |
| dc.contributor.affiliation | National Technical University «Kharkiv Polytechnic Institute» | |
| dc.format.pages | 2 | |
| dc.identifier.citationen | Shepeliev O. State Estimation of Forest condition in the Event of Fire, Based on Satellite Image Processing / Oleksandr Shepeliev, Mariia Bilova // Computational linguistics and intelligent systems : proceedings of the 4nd International conference, 23-24 April 2020, Lviv, Ukraine. — Lviv : Lviv Politechnic Publishing House, 2020. — Vol 2 : Proceedings of the 4nd International conference, COLINS 2020. Workshop, Lviv, Ukraine April 23-24, 2020. — P. 228–229. — (Intelligent Systems). | |
| dc.relation.references | 1. Bausys, R.; Kazakeviciute-Januskeviciene, G.; Cavallaro, F.; Usovaite, A. Algorithm Selection for Edge Detection in Satellite Images by Neutrosophic WASPAS Method. Sustainability 2020, 12, 548. | |
| dc.relation.references | 2. Mohammad D. Hossain, Dongmei Chen, Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective, ISPRS Journal of Photogrammetry and Remote Sensing,Volume 150,2019,Pages 115-134,ISSN 0924-2716. | |
| dc.relation.references | 3. Comaniciu, D. and Meer, P., 1997. Robust analysis of feature spaces: colorimage segmentation. In: Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR ‘97), IEEE Computer Society, Washington, DC, USA, pp.750–755. | |
| dc.relation.references | 4. Gold, C. M., 1999. Crust and anti-crust: A one-step boundary and skeleton extraction algorithm. In: Symposium on Computational Geometry, ACM Press, New York, NY, USA, pp. 189–196. | |
| dc.relation.referencesen | 1. Bausys, R.; Kazakeviciute-Januskeviciene, G.; Cavallaro, F.; Usovaite, A. Algorithm Selection for Edge Detection in Satellite Images by Neutrosophic WASPAS Method. Sustainability 2020, 12, 548. | |
| dc.relation.referencesen | 2. Mohammad D. Hossain, Dongmei Chen, Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective, ISPRS Journal of Photogrammetry and Remote Sensing,Volume 150,2019,Pages 115-134,ISSN 0924-2716. | |
| dc.relation.referencesen | 3. Comaniciu, D. and Meer, P., 1997. Robust analysis of feature spaces: colorimage segmentation. In: Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR ‘97), IEEE Computer Society, Washington, DC, USA, pp.750–755. | |
| dc.relation.referencesen | 4. Gold, C. M., 1999. Crust and anti-crust: A one-step boundary and skeleton extraction algorithm. In: Symposium on Computational Geometry, ACM Press, New York, NY, USA, pp. 189–196. | |
| dc.citation.spage | 228 | |
| dc.citation.epage | 229 | |
| dc.coverage.placename | Львів | |
| dc.coverage.placename | Lviv | |
| Appears in Collections: | Computational linguistics and intelligent systems. – 2020 р.
|
