<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Zeng, Chuiqing</style></author><author><style face="normal" font="default" size="100%">Bird, Stephen</style></author><author><style face="normal" font="default" size="100%">Luce, James</style></author><author><style face="normal" font="default" size="100%">Wang, Jinfei</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Natural-Rule-Based-Connection (NRBC) method for river network extraction from high-resolution imagery</style></title><secondary-title><style face="normal" font="default" size="100%">Remote Sensing</style></secondary-title><short-title><style face="normal" font="default" size="100%">Remote Sensing</style></short-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">center line</style></keyword><keyword><style  face="normal" font="default" size="100%">feature detection</style></keyword><keyword><style  face="normal" font="default" size="100%">river</style></keyword><keyword><style  face="normal" font="default" size="100%">segment connection</style></keyword><keyword><style  face="normal" font="default" size="100%">water body</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2015</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2015</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.mdpi.com/2072-4292/7/10/14055/htm</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">7</style></volume><pages><style face="normal" font="default" size="100%">23 pages </style></pages><language><style face="normal" font="default" size="100%">eng </style></language><abstract><style face="normal" font="default" size="100%">This study proposed a natural-rule-based-connection (NRBC) method to connect river segments after water body detection from remotely sensed imagery. A complete river network is important for many hydrological applications. While water body detection methods using remote sensing are well-developed, less attention has been paid to connect discontinuous river segments and form a complete river network. This study designed an automated NRBC method to extract a complete river network by connecting river segments at polygon level. With the assistance of an image pyramid, neighbouring river segments are connected based on four criteria: gap width (Tg), river direction consistency (Tθ), river width consistency (Tw), and minimum river segment length (Tl). The sensitivity of these four criteria were tested, analyzed, and proper criteria values were suggested using image scenes from two diverse river cases. The comparison of NRBC and the alternative morphological method demonstrated NRBC’s advantage of natural rule based selective connection. We refined a river centerline extraction method and show how it outperformed three other existing centerline extraction methods on the test sites. The extracted river polygons and centerlines have a multitude of end uses including rapidly mapping flood extents, monitoring surface water supply, and the provision of validation data for simulation models required for water quantity, quality and aquatic biota assessments. The code for the NRBC is available on GitHub.</style></abstract><issue><style face="normal" font="default" size="100%">10</style></issue><custom2><style face="normal" font="default" size="100%">Athabasca River</style></custom2><custom3><style face="normal" font="default" size="100%">http://www.worldcat.org/oclc/5919145975</style></custom3></record></records></xml>