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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.

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