A Novel Index Designed for Feature Information of Runoff Nodes Based on DEM
Hu Zu · 2015
Runoff nodes, which could be captured from every watershed on earth, are one type of the real geographical entities within the river-network. Generally, runoff nodes often locate at sites where lower grade of runoffs merging themselves into a more advanced trunk stream. It is clear that runoff nodes carry a lot of hydraulic and landform information. Although many reports have documents related to runoff nodes, the quantitative measuring researches, that concerning the geographical information of runoff nodes and taking advantages of valid theories or methods, are still rare. This may prevent people from further understanding the existence of runoff nodes in nature. Aimed to solve the aforementioned issue, this paper employs the Theory of Rough Sets(TRS) to develop a new landscape metric for perfectly characterizing the geographical features of runoff nodes. Firstly, according to current knowledge about runoff nodes, this paper extracts the potential information carried by runoff nodes. Secondly, this paper reviews some typical valid methods on how to extract runoff nodes from Digital Elevation Models(DEM). Thirdly, this paper presents the feature information index of runoff nodes(FIIRN) and illustrates the relevant computing procedures. Based on these researches and preparations, this paper carries out a case study of FIIRN for seven special regions from the Loess Plateau of China(which well represents the typical loess landscapes existed in the world). The experimental materials of DEM data are predominantly characterized with 5 meters of resolution. With the help of Arc GIS 10.1 software, this paper extracts all runoff nodes from the experimental sample regions according to their geometric features in the runoff network. Then, this paper computes the values of FIIRN using Excel 2003 and MATLAB 7.7. Surprisingly, the results show that FIIRN can effectively map the complete geographical information of a given watershed unit. Therefore, as we concluded in this paper, that FIIRN can play a valuable role for mining the information from watershed units in future. In fact,FIIRN should be considered as an optimal parameter for analyzing the morphological patterns of watershed units.