[go: up one dir, main page]

Snow, 2016 - Google Patents

The truth about drones in precision agriculture

Snow, 2016

View PDF
Document ID
5791072404101431246
Author
Snow C
Publication year
Publication venue
Skylogic Research1

External Links

Snippet

Over the past few years, the press has emphasized how much unmanned aerial systems (UAS) will be used to improve farming. From Australia, to Canada, to France, to England, and the US, the assumption is that drones provide cost savings for inputs—and in particular …
Continue reading at lawtaxprof.com (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G06K9/0063—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas
    • G06K9/00657—Recognising patterns in remote scenes, e.g. aerial images, vegetation versus urban areas of vegetation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10032—Satellite or aerial image; Remote sensing
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01M—CATCHING OR TRAPPING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
    • A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
    • A01M7/0089—Regulating or controlling systems

Similar Documents

Publication Publication Date Title
Zhang et al. High-resolution satellite imagery applications in crop phenotyping: An overview
Duan et al. Comparison of ground cover estimates from experiment plots in cotton, sorghum and sugarcane based on images and ortho-mosaics captured by UAV
Balafoutis et al. Smart farming technologies–description, taxonomy and economic impact
Zhang et al. The application of small unmanned aerial systems for precision agriculture: a review
Jiménez-Brenes et al. Quantifying pruning impacts on olive tree architecture and annual canopy growth by using UAV-based 3D modelling
Widjaja Putra et al. Enhanced broadband greenness in assessing Chlorophyll a and b, Carotenoid, and Nitrogen in Robusta coffee plantations using a digital camera
Caturegli et al. Unmanned aerial vehicle to estimate nitrogen status of turfgrasses
Abdullahi et al. Technology impact on agricultural productivity: A review of precision agriculture using unmanned aerial vehicles
Kalisperakis et al. Leaf area index estimation in vineyards from UAV hyperspectral data, 2D image mosaics and 3D canopy surface models
Samseemoung et al. Application of low altitude remote sensing (LARS) platform for monitoring crop growth and weed infestation in a soybean plantation
US20040034450A1 (en) Method and apparatus for spatially variable rate application of agricultural chemicals based on remotely sensed vegetation data
Negash et al. Emerging UAV applications in agriculture
Mozgeris et al. Imaging from manned ultra-light and unmanned aerial vehicles for estimating properties of spring wheat
Rains et al. Precision farming: An introduction
Elango et al. Precision agriculture: a novel approach on AI-driven farming
Montilla et al. Precision agriculture for rice crops with an emphasis in low health index areas
Snow The truth about drones in precision agriculture
Wang et al. Implementation of drone system in survey for tomato chlorotic spot virus
Ghosh A Study to Determine Yield for Crop Insurance using Precision Agriculture on an Aerial Platform
Papadopoulos et al. Spatio-temporal monitoring of cotton cultivation using ground-based and airborne multispectral sensors in GIS environment
Barwicki et al. Monitoring of typical field work in different soil conditions using remote sensing–a literature review and some concepts for the future
Johannsen et al. Applying remote sensing technology to precision farming
Kaivosoja et al. Applying Different Remote Sensing Data to Determine Relative Biomass Estimations of Cereals for Precision Fertilization Task Generation.
Kasimati et al. Unmanned aerial systems applications in orchards and vineyards
Jia et al. In-Season Maize Nitrogen Status Diagnosis at Field Scale from Uav Hyperspectral Images