Sökning: "Remote source"

Visar resultat 1 - 5 av 97 avhandlingar innehållade orden Remote source.

  1. 1. Studies of Volcanic Plumes with Spectroscopic Remote Sensing Techniques

    Författare :Santiago Arellano; Chalmers tekniska högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Remote Sensing; FTIR; DOAS; Volcanic gas emissions;

    Sammanfattning : Volcanism is a widespread phenomenon on Earth and other planetary bodies. Terrestrial volcanoes are shallow manifestations of deep and complex mechanisms of heat and mass transport and play an important role in the formation and change of the atmosphere and the natural landscape. LÄS MER

  3. 2. Optical remote sensing of industrial gas emission fluxes

    Författare :John Johansson; Chalmers tekniska högskola; []
    Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; optical remote sensing; DOAS; gas emission; absorption spectroscopy; VOC; flux measurement; solar occultation; FTIR; formaldehyde;

    Sammanfattning : Mobile optical remote sensing techniques offer promising possibilities to quantify and geographically attribute local industrial gaseous emissions to the atmosphere. Studies have repeatedly shown that such emissions are often poorly understood, underestimated, and thereby not properly accounted for in emission inventories and regional atmospheric chemistry models, especially for emissions of VOCs. LÄS MER

  4. 3. 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

  5. 4. 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

  7. 5. Supervised and Unsupervised Deep Learning Models for Flood Detection

    Författare :Ritu Yadav; Yifang Ban; Andrea Nascetti; Nicolas Audebert; KTH; []
    Nyckelord :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;

    Sammanfattning : 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. LÄS MER