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

Hais et al., 2016 - Google Patents

Landsat imagery spectral trajectories—important variables for spatially predicting the risks of bark beetle disturbance

Hais et al., 2016

View HTML
Document ID
9531736122263519401
Author
Hais M
Wild J
Berec L
Brůna J
Kennedy R
Braaten J
Brož Z
Publication year
Publication venue
Remote Sensing

External Links

Snippet

Tree mortality caused by bark beetle infestation has significant effects on the ecology and value of both natural and commercial forests. Therefore, prediction of bark beetle infestations is critical in forest management. Existing predictive models, however, rarely …
Continue reading at www.mdpi.com (HTML) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30286Information retrieval; Database structures therefor; File system structures therefor in structured data stores
    • G06F17/30587Details of specialised database models
    • 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
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • G06Q10/063Operations research or analysis
    • 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
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/01Social networking
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/18Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/20Handling natural language data
    • 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
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • 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
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism
    • G06Q50/10Services
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications

Similar Documents

Publication Publication Date Title
Hais et al. Landsat imagery spectral trajectories—important variables for spatially predicting the risks of bark beetle disturbance
Shimizu et al. Detecting forest changes using dense Landsat 8 and Sentinel-1 time series data in tropical seasonal forests
Janiec et al. A comparison of two machine learning classification methods for remote sensing predictive modeling of the forest fire in the North-Eastern Siberia
Benson et al. Mangrove carbon stocks and ecosystem cover dynamics in southwest Madagascar and the implications for local management
Dorais et al. Strategies for incorporating high-resolution google earth databases to guide and validate classifications: Understanding deforestation in Borneo
Li et al. Estimating soil moisture with Landsat data and its application in extracting the spatial distribution of winter flooded paddies
Ndalila et al. Geographic patterns of fire severity following an extreme eucalyptus forest fire in southern Australia: 2013 Forcett-Dunalley fire
Sterk et al. Desertification–scientific versus political realities
Zhao et al. Long-term post-disturbance forest recovery in the greater Yellowstone ecosystem analyzed using Landsat time series stack
Chu et al. Effects of burn severity and environmental conditions on post-fire regeneration in Siberian larch forest
Liang et al. Mapping mountain pine beetle mortality through growth trend analysis of time-series Landsat data
Qiu et al. Quantifying forest fire and post-fire vegetation recovery in the daxin’anling area of northeastern China using landsat time-series data and machine learning
Mezei et al. Potential solar radiation as a driver for bark beetle infestation on a landscape scale
Ghulam et al. Remote sensing based spatial statistics to document tropical rainforest transition pathways
Guo et al. Spatial modelling of fire drivers in urban-forest ecosystems in China
Dutra Silva et al. Limitations of species distribution models based on available climate change data: a case study in the Azorean forest
Biswas et al. A multi sensor approach to forest type mapping for advancing monitoring of sustainable development goals (SDG) in Myanmar
Abdi Climate-triggered insect defoliators and forest fires using multitemporal Landsat and TerraClimate data in NE Iran: An application of GEOBIA TreeNet and panel data analysis
Nguyen et al. A comparison of imputation approaches for estimating forest biomass using Landsat time-series and inventory data
Venkatappa et al. Applications of the google earth engine and phenology-based threshold classification method for mapping forest cover and carbon stock changes in Siem Reap province, Cambodia
White et al. Landscape dynamics on the island of La Gonave, Haiti, 1990–2010
Krejci et al. Application of GIS to empirical windthrow risk model in mountain forested landscapes
Shevade et al. Expansion of industrial plantations continues to threaten Malayan tiger habitat
Vozmishcheva et al. Strong disturbance impact of tropical cyclone Lionrock (2016) on Korean pine-broadleaved forest in the Middle Sikhote-Alin Mountain Range, Russian far east
Coates et al. Susceptibility of trees to windthrow storm damage in partially harvested complex-structured multi-species forests