Midlands State University Library

Automatic drainage pattern recognition in river networks (Record no. 160715)

MARC details
000 -LEADER
fixed length control field 01739nam a22002417a 4500
003 - CONTROL NUMBER IDENTIFIER
control field ZW-GwMSU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20221207123044.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 221207b |||||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Original cataloging agency MSU
Transcribing agency MSU
Description conventions rda
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Zhang, Ling
Relator term author
245 10 - TITLE STATEMENT
Title Automatic drainage pattern recognition in river networks
Statement of responsibility, etc. created by Ling Zhang & Eric Guilbert
264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Hong Kong:
Name of producer, publisher, distributor, manufacturer Taylor and Francis ,
Date of production, publication, distribution, manufacture, or copyright notice 2013.
336 ## - CONTENT TYPE
Source rdacontent
Content type term text
Content type code txt
337 ## - MEDIA TYPE
Source rdamedia
Media type term unmediated
Media type code n
338 ## - CARRIER TYPE
Source rdacarrier
Carrier type term volume
Carrier type code nc
440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE
Volume/sequential designation Volume , number ,
520 ## - SUMMARY, ETC.
Summary, etc. In both geographic information system and terrain analysis, drainage systems are important components. Owing to local topography and subsurface geology, a drainage system achieves a particular drainage pattern based on the form and texture of its network of stream channels and tributaries. Although research has been done on the description of drainage patterns in geography and hydrology, automatic drainage pattern recognition in river networks is not well developed. This article introduces a new method for automatic classification of drainage systems in different patterns. The method applies to river networks, and the terrain model is not required in the process. A series of geometric indicators describing each pattern are introduced. Network classification is based on fuzzy set theory. For each pattern, the level of membership of the network is given by the different indicator values. The method was implemented, and the experimental results are presented and discussed.<br/><br/><br/><br/>
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element river network
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element drainage pattern
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element terrain analysis
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1080/13658816.2013.802794
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Journal Article
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Shelving location Date acquired Serial Enumeration / chronology Total Checkouts Full call number Date last seen Copy number Price effective from Koha item type Public note
    Library of Congress Classification     Main Library Main Library - Special Collections 14/01/2014 Vol 27, Nos 11-12 pages 2319-2342   G70.2 INT 07/12/2022 SP17880 07/12/2022 Journal Article For in-house use only