[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Weirather et al., 2018 - Google Patents

Automated Delineation Of Wildfire Areas Using Sentinel-2 Satellite Imagery

Weirather et al., 2018

Document ID
4677151889127659349
Author
Weirather M
Zeug G
Schneider T
Publication year
Publication venue
GI_Forum 2018

External Links

Snippet

Climate change will bring many changes to the world. For example, the frequency and severity of natural hazards and related disasters are expected to increase globally. Wildfires already affect thousands of people every year and cause billions of Euros' worth of damage …
Continue reading at hw.oeaw.ac.at (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • G06K9/00657Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10032Satellite or aerial image; Remote sensing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20Image acquisition
    • G06K9/2018Identifying/ignoring parts by sensing at different wavelengths
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30181Earth observation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/08Insurance, e.g. risk analysis or pensions
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation

Similar Documents

Publication Publication Date Title
Mondejar et al. Near infrared band of Landsat 8 as water index: a case study around Cordova and Lapu-Lapu City, Cebu, Philippines
Argañaraz et al. Assessing wildfire exposure in the Wildland-Urban Interface area of the mountains of central Argentina
Thomas et al. Validation of North American forest disturbance dynamics derived from Landsat time series stacks
Fraser et al. A method for detecting large-scale forest cover change using coarse spatial resolution imagery
Xin et al. Toward near real-time monitoring of forest disturbance by fusion of MODIS and Landsat data
CN102542248B (en) Automatic detection of fires on earth's surface and of atmospheric phenomena such as clouds, veils, fog or the like, by means of a satellite system
Zhang et al. Monthly burned area and forest fire carbon emission estimates for the Russian Federation from SPOT VGT
Souza Jr et al. Combining spectral and spatial information to map canopy damage from selective logging and forest fires
Shimada et al. New global forest/non-forest maps from ALOS PALSAR data (2007–2010)
US20160048925A1 (en) Method of determining structural damage using positive and negative tree proximity factors
Lizundia-Loiola et al. Global burned area mapping from Sentinel-3 Synergy and VIIRS active fires
Koltunov et al. On timeliness and accuracy of wildfire detection by the GOES WF-ABBA algorithm over California during the 2006 fire season
Fensholt et al. Analysing the advantages of high temporal resolution geostationary MSG SEVIRI data compared to Polar Operational Environmental Satellite data for land surface monitoring in Africa
Reimer et al. Advancing reference emission levels in subnational and national REDD+ initiatives: a CLASlite approach
Pu et al. A dynamic algorithm for wildfire mapping with NOAA/AVHRR data
Kuhnell et al. Mapping woody vegetation cover over the state of Queensland using Landsat TM imagery
He et al. Enhancement of a fire detection algorithm by eliminating solar reflection in the mid-IR band: Application to AVHRR data
Farhadi et al. Badi: a novel burned area detection index for sentinel-2 imagery using google earth engine platform
Zidane et al. An improved algorithm for mapping burnt areas in the Mediterranean forest landscape of Morocco
Chung et al. Wildfire damage assessment using multi-temporal Sentinel-2 data
Gülci et al. Mapping wildfires using Sentinel 2 MSI and Landsat 8 imagery: spatial data generation for forestry
Hamilton et al. Spectroscopic analysis for mapping wildland fire effects from remotely sensed imagery
Weirather et al. Automated Delineation Of Wildfire Areas Using Sentinel-2 Satellite Imagery
Lee et al. Detection of wildfire-damaged areas using kompsat-3 image: A case of the 2019 unbong mountain fire in busan, South Korea
CN111563472A (en) Method and device for rapidly extracting tobacco plume forest land burned area