Sökning: "Geoinformatik"

Visar resultat 1 - 5 av 57 avhandlingar innehållade ordet Geoinformatik.

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

   Författare :Dorothy Furberg; Yifang Ban; Xiaojun Yang; KTH; []
   Nyckelord :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;

   Sammanfattning : 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. LÄS MER

3. 2. Population Displacement Estimation During Disasters Using Mobile Phone Data

   Författare :Silvino Pedro Cumbane; Yifang Ban; Gyözö Gidofalvi; Zeferino Saugene; John Östh; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Geoinformatics; Geoinformatik;

   Sammanfattning : Natural disasters result in devastating losses in human life, environmental assets, and personal-, regional-, and national economies. The availability of different big data such as satellite images, Global Positioning System (GPS)traces, mobile Call Detail Records (CDR), social media posts, etc. LÄS MER

4. 3. Multi-Modal Deep Learning with Sentinel-1 and Sentinel-2 Data for Urban Mapping and Change Detection

   Författare :Sebastian Hafner; Yifang Ban; Paolo Gamba; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; NATURVETENSKAP; NATURAL SCIENCES; Geoinformatics; Geoinformatik;

   Sammanfattning : Driven by the rapid growth in population, urbanization is progressing at an unprecedented rate in many places around the world. Earth observation has become an invaluable tool to monitor urbanization on a global scale by either mapping the extent of cities or detecting newly constructed urban areas within and around cities. 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. 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