Nothing Special   »   [go: up one dir, main page]

Lambert et al., 2018 - Google Patents

Evaluating the potential of Unmanned Aerial Systems for mapping weeds at field scales: a case study with Alopecurus myosuroides

Lambert et al., 2018

View PDF
Document ID
11990590841460481234
Author
Lambert J
Hicks H
Childs D
Freckleton R
Publication year
Publication venue
Weed research

External Links

Snippet

Mapping weed densities within crops has conventionally been achieved either by detailed ecological monitoring or by field walking, both of which are time‐consuming and expensive. Recent advances have resulted in increased interest in using Unmanned Aerial Systems …
Continue reading at onlinelibrary.wiley.com (PDF) (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
    • 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
    • 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
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination

Similar Documents

Publication Publication Date Title
Lambert et al. Evaluating the potential of Unmanned Aerial Systems for mapping weeds at field scales: a case study with Alopecurus myosuroides
Borra‐Serrano et al. Canopy height measurements and non‐destructive biomass estimation of Lolium perenne swards using UAV imagery
Vuolo et al. How much does multi-temporal Sentinel-2 data improve crop type classification?
Lussem et al. Estimating biomass in temperate grassland with high resolution canopy surface models from UAV-based RGB images and vegetation indices
Chauhan et al. Remote sensing-based crop lodging assessment: Current status and perspectives
Louargant et al. Weed detection by UAV: Simulation of the impact of spectral mixing in multispectral images
Kussul et al. Crop inventory at regional scale in Ukraine: developing in season and end of season crop maps with multi-temporal optical and SAR satellite imagery
Barbosa et al. RGB vegetation indices applied to grass monitoring: A qualitative analysis
Rossi et al. Spatial resolution, spectral metrics and biomass are key aspects in estimating plant species richness from spectral diversity in species‐rich grasslands
Forsmoo et al. Drone‐based structure‐from‐motion photogrammetry captures grassland sward height variability
US7715013B2 (en) Optical system for plant characterization
Waite et al. A view from above: Unmanned aerial vehicles (UAV s) provide a new tool for assessing liana infestation in tropical forest canopies
Jiménez-Brenes et al. Automatic UAV-based detection of Cynodon dactylon for site-specific vineyard management
Mertens et al. Spatial modelling of deforestation in southern Cameroon: spatial disaggregation of diverse deforestation processes
de Castro et al. Broad-scale cruciferous weed patch classification in winter wheat using QuickBird imagery for in-season site-specific control
Rossi et al. From local to regional: Functional diversity in differently managed alpine grasslands
Huo et al. Assessing the detectability of European spruce bark beetle green attack in multispectral drone images with high spatial-and temporal resolutions
CN102265287A (en) Method and apparatus for monitoring tree growth
Preston et al. Enumerating white‐tailed deer using unmanned aerial vehicles
Anderegg et al. On-farm evaluation of UAV-based aerial imagery for season-long weed monitoring under contrasting management and pedoclimatic conditions in wheat
Herbei et al. Processing and Use of Satellite Images in Order to Extract Useful Information in Precision Agriculture.
Rasmussen et al. Pre-harvest weed mapping of Cirsium arvense L. based on free satellite imagery–The importance of weed aggregation and image resolution
Borra-Serrano et al. Towards an objective evaluation of persistency of Lolium perenne swards using UAV imagery
Jackson et al. Season, classifier, and spatial resolution impact honey mesquite and yellow bluestem detection using an unmanned aerial system
Dammer et al. Combined UAV‐and tractor‐based stripe rust monitoring in winter wheat under field conditions