NDLI: Multivariate analysis of airborne remote sensing and topographic features for corn yield spatial pattern discrimination

Content Provider	IEEE Xplore Digital Library
Author	Serele, C.Z. Gwyn, Q.H.J. Boisvert, J.B. Pattey, E. Brazeau, S. McLaughlin, N. Daoust, G.
Copyright Year	2000
Description	Author affiliation: Centre d'Appl. et de Recherches en Teledetection, Sherbrooke Univ., Que., Canada (Serele, C.Z.)
Abstract	Multivariate discriminant analysis (MDA) was applied to airborne remotely sensed and topographic data to select the best indicators of corn yield spatial variability. In the MDA models, elevation, slope and texture indices (contrast and second angular moment) contribute most to the discrimination of corn yield classes. The classification of yield based on the MDA results in yield classes that are well sorted in a proportion of 99% low and 71% medium yield pixels, while high yield pixels were correctly classified in 88% of the cases. The overall classification rate of 86% demonstrates that, on the basis of MDA, using texture indices and topographic data and, to a lesser extent vegetation indices, the authors can discriminate corn yield spatial patterns.
Starting Page	381
Ending Page	383
File Size	305417
Page Count	3
File Format	PDF
ISBN	0780363590
DOI	10.1109/IGARSS.2000.860526
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-24
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Remote sensing Vegetation mapping Soil Crops Agriculture Spatial resolution Atmospheric modeling Physics Chemicals Environmental management
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Airborne remote sensing to support precision farming

Corn yield prediction with artificial neural network trained using airborne remote sensing and topographic data

Estimating Biophysical Variables at 250 M with Reconstructed EOS/MODIS Time Series to Monitor Fragmented Landscapes

Precision agriculture using hyperspectral remote sensing and GIS

Agroclimatic zoning of Kazakhstan territory using remote sensing data

The spatial scaling effects study of NPP using airborne and field data based on BEPS

An Airborne Microwave Radiometer System for Soil Moisture Mapping

Net primary productivity distribution in China from a process model driven by remote sensing

Use of airborne hyperspectral image data to assess winter wheat yield

Multivariate analysis of airborne remote sensing and topographic features for corn yield spatial pattern discrimination

Similar Documents

Airborne remote sensing to support precision farming

Corn yield prediction with artificial neural network trained using airborne remote sensing and topographic data

Estimating Biophysical Variables at 250 M with Reconstructed EOS/MODIS Time Series to Monitor Fragmented Landscapes

Precision agriculture using hyperspectral remote sensing and GIS

Agroclimatic zoning of Kazakhstan territory using remote sensing data

The spatial scaling effects study of NPP using airborne and field data based on BEPS

An Airborne Microwave Radiometer System for Soil Moisture Mapping

Net primary productivity distribution in China from a process model driven by remote sensing

Use of airborne hyperspectral image data to assess winter wheat yield

Multivariate analysis of airborne remote sensing and topographic features for corn yield spatial pattern discrimination