Next Article in Journal
Long-Term Changes of the Wildland–Urban Interface in the Polish Carpathians
Next Article in Special Issue
Use of DEMs Derived from TLS and HRSI Data for Landslide Feature Recognition
Previous Article in Journal
A Novel Approach for Identifying Urban Built-Up Area Boundaries Using High-Resolution Remote-Sensing Data Based on the Scale Effect
Previous Article in Special Issue
Roughness Spectra Derived from Multi-Scale LiDAR Point Clouds of a Gravel Surface: A Comparison and Sensitivity Analysis
Open AccessArticle

Saddle Position-Based Method for Extraction of Depressions in Fengcong Areas by Using Digital Elevation Models

by 1,2,3, 1,3,4, 1,3 and 1,3,4,*
Key laboratory of Virtual Geographic Environment, Ministry of Education, Nanjing Normal University, Nanjing 210023, China
School of Geographic Sciences, Xinyang Normal University, Xinyang 464000, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Nanjing 210023, China
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(4), 136;
Received: 7 March 2018 / Revised: 26 March 2018 / Accepted: 26 March 2018 / Published: 1 April 2018
(This article belongs to the Special Issue Leading Progress in Digital Terrain Analysis and Modeling)
A karst depression is an important sign of the development stage of karst landforms. The morphological characteristics of depressions can help reflect the development and evolution process of such landforms. The accurate identification and extraction of depressions in Fengcong areas are the basis of this research on karst depressions. Previous studies on Fengcong depressions were primarily based on manual surveys, remote sensing image interpretation, and manual map plotting or GIS-based techniques. The extracted landform units of Fengcong depressions in these studies were not accurate and even inauthentic in certain cases. Thus, this work proposes a method for extracting Fengcong depressions in karst areas which is based on terrain saddle points and uses digital elevation models (DEMs). First, the surface morphology of the Fengcong karst area is analyzed. Second, saddles are detected from the intersection points, and spatial trend surfaces are generated by interpolating the elevations of these saddle points. The interface between pinnacles and depressions can be determined by the trend surface. We applied the method in a case Fengcong area of the Lijiang River in Guilin, China. Results showed that the proposed method successfully divided the positive terrain form of pinnacles and the negative terrain form of the depressions in the Fengcong karst area. A total of 188 surface depressions were extracted, whose average area was 0.14 km2 and polygonal depression density was 2.5 km2. Results also showed that most of the depressions were stable in terms of the morphological features of area and depth. A total of 94% of the depth measured less than 60 m, and the area was less than 0.5 km2. This proposed method can accurately determine the boundary of depressions and provide an important reference for quantitative research on the Fengcong depression terrain in karst landforms. View Full-Text
Keywords: Fengcong depression; saddle; karst; DEMs Fengcong depression; saddle; karst; DEMs
Show Figures

Figure 1

MDPI and ACS Style

Yang, X.; Tang, G.; Meng, X.; Xiong, L. Saddle Position-Based Method for Extraction of Depressions in Fengcong Areas by Using Digital Elevation Models. ISPRS Int. J. Geo-Inf. 2018, 7, 136.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map

Back to TopTop