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

Backoulou et al., 2018 - Google Patents

Detecting change in a sorghum field infested by sugarcane aphid1

Backoulou et al., 2018

Document ID
3191380339690947997
Author
Backoulou G
Elliott N
Giles K
Brewer M
Starek M
Publication year
Publication venue
Southwestern Entomologist

External Links

Snippet

The sugarcane aphid, Melanaphis sacchari (Zehntner), is a destructive insect pest of sorghum, Sorghum bicolor (L.) Moench. Outbreaks of sugarcane aphids were reported in commercial sorghum fields in Kansas, Louisiana, Mississippi, Oklahoma, and Texas …
Continue reading at bioone.org (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
    • G06K9/36Image 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
    • 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

Similar Documents

Publication Publication Date Title
Stanton et al. Unmanned aircraft system-derived crop height and normalized difference vegetation index metrics for sorghum yield and aphid stress assessment
Jorge et al. Detection of irrigation inhomogeneities in an olive grove using the NDRE vegetation index obtained from UAV images
Lamb et al. Pa—precision agriculture: Remote-sensing and mapping of weeds in crops
US7715013B2 (en) Optical system for plant characterization
Lambert et al. Evaluating the potential of Unmanned Aerial Systems for mapping weeds at field scales: a case study with Alopecurus myosuroides
Yang et al. Comparison of QuickBird satellite imagery and airborne imagery for mapping grain sorghum yield patterns
US20140039967A1 (en) Method of predicting crop yield loss due to n-deficiency
Sharifi Estimation of biophysical parameters in wheat crops in Golestan province using ultra-high resolution images
US9508007B2 (en) Method of predicting crop yield loss due to N-deficiency
Backoulou et al. Processed multispectral imagery differentiates wheat crop stress caused by greenbug from other causes
Mirik et al. High spectral and spatial resolution hyperspectral imagery for quantifying Russian wheat aphid infestation in wheat using the constrained energy minimization classifier
Backoulou et al. Using multispectral imagery to map spatially variable sugarcane aphid1 infestations in sorghum
Sadeghi et al. Forest losses and gains in Kurdistan province, western Iran: Where do we stand?
Yang et al. Mapping three invasive weeds using airborne hyperspectral imagery
Backoulou et al. Detecting change in a sorghum field infested by sugarcane aphid1
Apan et al. Spectral discrimination and separability analysis of agricultural crops and soil attributes using ASTER imagery
Aasen et al. Spectral and 3D nonspectral approaches to crop trait estimation using ground and UAV sensing
Backoulou et al. Differentiating stress to wheat fields induced by Diuraphis noxia from other stress causing factors
Backoulou et al. Using Multispectral Imagery to Compare the Spatial Pattern of Injury to Wheat Caused by Russian Wheat Aphid1 and Greenbug1
Singh et al. A wavelet-based approach for monitoring plantation crops (tea: Camellia sinensis) in North East India
Tian Sensor-based precision chemical application systems
Hunt Jr et al. Insect detection and nitrogen management for irrigated potatoes using remote sensing from small unmanned aircraft systems
Pena et al. Use of satellite-derived hyperspectral indices to identify stress symptoms in an Austrocedrus chilensis forest infested by the aphid Cinara cupressi
Yang et al. Evaluating airborne hyperspectral imagery for mapping saltcedar infestations in west Texas
Bilotta et al. UAV for precision agriculture in vineyards: a case study in Calabria