Sökning: "aktiv branddetektering"

Hittade 3 avhandlingar innehållade orden aktiv branddetektering.

1. 1. Deep Learning for Active Fire Detection Using Multi-Source Satellite Image Time Series

   Författare :Yu Zhao; Yifang Ban; Andrea Nascetti; Josephine Sullivan; Cartalis Constantinos; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Wildfire; Remote Sensing; Active Fire Detection; GOES-R ABI; Suomi-NPP VIIRS; Image Segmentation; Deep Learning; Gated Recurrent Units GRU ; Transformer.; Vilda Bränder; Fjärranalys; Aktiv Branddetektering; GOES- R ABI; Suomi-NPP VIIRS; Bildsegmentering; Djupinlärning; Gated Recurrent Units GRU ; Transformer; Geoinformatik; Geoinformatics;

   Sammanfattning : In recent years, climate change and human activities have caused increas- ing numbers of wildfires. Earth observation data with various spatial and temporal resolutions have shown great potential in detecting and monitoring wildfires. LÄS MER

3. 2. Multispectral Remote Sensing and Deep Learning for Wildfire Detection

   Författare :Xikun Hu; Yifang Ban; Ioannis Gitas; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; active fire detection; biome; multi-criteria; Sentinel-2; Landsat-8; burned area mapping; deep learning; semantic segmentation; machine learning.; aktiv branddetektering; biom; multikriterietillvägagångssätt; Sentinel-2; Landsat-8; kartläggning av bränt område; djupinlärning; semantisk segmentering; maskininlärningsmetoderna; Geoinformatik; Geoinformatics;

   Sammanfattning : Remote sensing data has great potential for wildfire detection and monitoring with enhanced spatial resolution and temporal coverage. Earth Observation satellites have been employed to systematically monitor fire activity over large regions in two ways: (i) to detect the location of actively burning spots (during the fire event), and (ii) to map the spatial extent of the burned scars (during or after the event). LÄS MER

4. 3. Large-Scale Multi-Source Satellite Data for Wildfire Detection and Assessment Using Deep Learning

   Författare :Xikun Hu; Yifang Ban; Martin Wooster; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Wildfire; Remote Sensing; Active Fire Detection; Burned Area Mapping; Burn Severity Assessment; Sentinel-2; Landsat; Sentinel-1; Deep Learning; Semantic Segmentation; Image Translation; Skogsbrand; fjärranalys; aktiv branddetektering; kartläggning av bränt område; bedömning av brännskador; Sentinel-2; Landsat; Sentinel-1; djupinlärning; semantisk segmentering; bildöversättning.; Geoinformatik; Geoinformatics;

   Sammanfattning : Earth Observation (EO) satellites have great potential in wildfire detection and assessment at fine spatial, temporal, and spectral resolutions. For a long time, satellite data have been employed to systematically monitor wildfire dynamics and assess wildfire impacts, including (i) to detect the location of actively burning spots, (ii) to map the spatial extent of the burn scars, (iii) to assess the wildfire damage levels. LÄS MER