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

Gudmann et al., 2022 - Google Patents

Pixel and object-based land cover mapping and change detection from 1986 to 2020 for Hungary using histogram-based gradient boosting classification tree classifier

Gudmann et al., 2022

View PDF
Document ID
1868749640080630987
Author
Gudmann A
Mucsi L
Publication year
Publication venue
Geographica Pannonica

External Links

Snippet

The large-scale pixel-based land use/land cover classification is a challenging task, which depends on many circumstances. This study aims to create LULC maps with the nomenclature of Coordination of Information on the Environment (CORINE) Land Cover …
Continue reading at aseestant.ceon.rs (PDF) (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
    • 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
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • 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
    • 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
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • 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
    • G06F17/30241Information retrieval; Database structures therefor; File system structures therefor in geographical information databases
    • 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
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05Geographic models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
    • G06T11/20Drawing from basic elements, e.g. lines or circles
    • G06T11/206Drawing of charts or graphs

Similar Documents

Publication Publication Date Title
Chatziantoniou et al. Co-Orbital Sentinel 1 and 2 for LULC mapping with emphasis on wetlands in a mediterranean setting based on machine learning
Bragagnolo et al. Convolutional neural networks applied to semantic segmentation of landslide scars
Zhu et al. Optimizing selection of training and auxiliary data for operational land cover classification for the LCMAP initiative
Pham et al. Biomass estimation of Sonneratia caseolaris (l.) Engler at a coastal area of Hai Phong city (Vietnam) using ALOS-2 PALSAR imagery and GIS-based multi-layer perceptron neural networks
Kavzoglu Increasing the accuracy of neural network classification using refined training data
Jia et al. Evaluating the effectiveness of conservation on mangroves: A remote sensing-based comparison for two adjacent protected areas in Shenzhen and Hong Kong, China
Tehrani et al. Multi-regional landslide detection using combined unsupervised and supervised machine learning
Ghaffarian et al. Post-disaster recovery monitoring with google earth engine
Tsai et al. Analysis of topographic and vegetative factors with data mining for landslide verification
Geiß et al. Joint use of remote sensing data and volunteered geographic information for exposure estimation: evidence from Valparaíso, Chile
Seoane et al. Are existing vegetation maps adequate to predict bird distributions?
Kantarcioglu et al. Artificial neural networks for assessing forest fire susceptibility in Türkiye
Xia et al. Land resource use classification using deep learning in ecological remote sensing images
Nguyen Land cover change detection in northwestern Vietnam using Landsat images and Google Earth Engine
Gudmann et al. Pixel and object-based land cover mapping and change detection from 1986 to 2020 for Hungary using histogram-based gradient boosting classification tree classifier
Asiyabi et al. Earth observation semantic data mining: Latent dirichlet allocation-based approach
Chang et al. Discrete rough set analysis of two different soil-behavior-induced landslides in National Shei-Pa Park, Taiwan
Kranz et al. Earth observation based multi-scale assessment of logging activities in the Democratic Republic of the Congo
Coladello et al. Macrophytes’ abundance changes in eutrophicated tropical reservoirs exemplified by Salto Grande (Brazil): Trends and temporal analysis exploiting Landsat remotely sensed data
Stomberg et al. Exploring wilderness characteristics using explainable machine learning in satellite imagery
Boston et al. U-Net Convolutional Neural Network for Mapping Natural Vegetation and Forest Types from Landsat Imagery in Southeastern Australia
Sampedro et al. Remote sensing of invasive species in the Galapagos Islands: comparison of pixel-based, principal component, and object-oriented image classification approaches
Amarsaikhan Advanced classification of optical and SAR images for urban land cover mapping
Feng et al. Potential of Sample Migration and Explainable Machine Learning Model for Monitoring Spatiotemporal Changes of Wetland Plant Communities
Bell et al. Data-informed sampling and mapping: an approach to ensure plot-based classifications locate, classify and map rare and restricted vegetation types