Author: Gary M. SchaalPublisher:
ISBN:
Category : Land use
Languages : en
Pages : 14
Book Description
Ohio Land Use Land Cover Classification System. (4th Ed.).
Author: Gary M. SchaalPublisher:
ISBN:
Category : Land use
Languages : en
Pages : 14
Book Description
Ohio Land Use, Land Cover Classification System
Author: Gary M. SchaalPublisher:
ISBN:
Category : Land use
Languages : en
Pages : 20
Book Description
Land Use/land Cover Classification System
Author: Gary M. SchaalPublisher:
ISBN:
Category : Land use
Languages : en
Pages : 14
Book Description
"This publication summarizes the classification sytem used by the Ohio Department of Natural Resources (Division of Water, Remote Sensing Unit) in preparing land use/land cover maps"--Page 1.
A Land Use and Land Cover Classification System for Use with Remote Sensor Data
Author: James Richard AndersonPublisher:
ISBN:
Category : Land cover
Languages : en
Pages : 36
Book Description
An Inventory of Ohio's Land Use/land Cover as Seen by LANDSAT
Author: Gary M. SchaalPublisher:
ISBN:
Category : Land cover
Languages : en
Pages : 106
Book Description
An Object Oriented Approach to Land Cover Classification for State of Ohio
Author: Navendu ChaudharyPublisher:
ISBN: 9780549022954
Category :
Languages : en
Pages : 129
Book Description
The purpose of this research was to develop an object oriented approach to land cover analysis and evaluate this approach along with five other classifiers for accuracy in classifying Level II land-cover categories in Ohio. These methods consist of (1) USGS National Land Cover Data; (2) the spectral angle mapper; (3) the maximum likelihood classifier; (4) the maximum likelihood classifier with texture analysis; and (5) a recently introduced hybrid artificial neural network; The segmentation object-oriented processing (SOOP) classifier outperformed all others with an overall accuracy of 93.8% and Kappa of 0.93. SOOP was the only classifier to have by-class producer and user accuracies of 90% or higher for all categories. An artificial neural network (ANN) classifier had the second highest overall accuracy of 87.6% and Kappa of 0.85. The four remaining classifiers had overall accuracies less than 85%. The SOOP classifier has been applied to Landsat-7 data to perform a level II land-cover classification for the state of Ohio.
Standard Land Use Coding Manual
Author: United States. Urban Renewal AdministrationPublisher:
ISBN:
Category : Government publications
Languages : en
Pages : 132
Book Description
Land Use and Land Cover Classification System For Use With Remote Sensor Data
Author: Geological Survey (U.S.)Publisher:
ISBN:
Category :
Languages : en
Pages : 35
Book Description
Land Cover Classification System
Author: Antonio Di GregorioPublisher: Food & Agriculture Org.
ISBN: 9789251053270
Category : Business & Economics
Languages : en
Pages : 212
Book Description
"Based on the original software version 1 prepared by Antonio Di Gregorio and Louisa J.M. Jansen."
Land Use and Land Cover Classification Systems
Author: James R. AndersonPublisher:
ISBN:
Category : Land use
Languages : en
Pages : 0
Book Description