Search for dissertations about: "optical remote sensing"

Showing result 6 - 10 of 74 swedish dissertations containing the words optical remote sensing.

  1. 6. Multispectral Remote Sensing and Deep Learning for Wildfire Detection

    Author : Xikun Hu; Yifang Ban; Ioannis Gitas; KTH; []
    Keywords : 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;

    Abstract : 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). READ MORE

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

    Author : Xikun Hu; Yifang Ban; Martin Wooster; KTH; []
    Keywords : 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;

    Abstract : 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. READ MORE

  3. 8. Satellite Monitoring of Urbanization and Indicator-based Assessment of Environmental Impact

    Author : Dorothy Furberg; Yifang Ban; Xiaojun Yang; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Urbanization; remote sensing; land-cover classification; landscape metrics; environmental indicators; environmental impact; ecosystem services; green infrastructure; habitat network analysis; Greater Toronto Area; Stockholm; Shanghai; urbanisering; fjärranalys; marktäckeklassificering; landskapsnyckeltal; miljöindikatorer; miljöpåverkan; ekosystemtjänster; grön infrastruktur; habitat nätverksanalys; Greater Toronto Area; Stockholm; Shanghai; Geodesy and Geoinformatics; Geodesi och geoinformatik; Geoinformatik; Geoinformatics;

    Abstract : As of 2018, 55% of the world population resides in urban areas. This proportion is projected to increase to 68% by 2050 (United Nations 2018). The Stockholm region is no exception to this urbanizing trend: the population of Stockholm City has risen by 28% since the year 2000. READ MORE

  4. 9. Supervised and Unsupervised Deep Learning Models for Flood Detection

    Author : Ritu Yadav; Yifang Ban; Andrea Nascetti; Nicolas Audebert; KTH; []
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Floods; Remote Sensing; Sentinel-1 SAR; Segmentation; Change Detection; DEM; Data Fusion; Time Series; Deep Learning; Unsupervised Learning; Contrastive Learning; Self-Attention; Convolutional LSTM; Variational AutoEncoder VAE ; Geoinformatik; Geoinformatics;

    Abstract : Human civilization has an increasingly powerful influence on the earthsystem. Affected by climate change and land-use change, floods are occurringacross the globe and are expected to increase in the coming years. Currentsituations urge more focus on efficient monitoring of floods and detecting impactedareas. READ MORE

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

    Author : Yu Zhao; Yifang Ban; Andrea Nascetti; Josephine Sullivan; Cartalis Constantinos; KTH; []
    Keywords : 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;

    Abstract : 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. READ MORE