Title :
DEM and image based loess slope segmentation
Author_Institution :
Key Lab. of Virtual Geographic Environ. (Minist. of Educ.), Nanjing Normal Univ., Nanjing, China
Abstract :
An integrated method combining digital terrain analysis (DTA) and object-oriented image analysis is used to classified loess slope into six types according to surface shape. Firstly, several data layers are extracted from Digital Elevation Models (DEM). Secondly, the data layers are combined into a multi-band image. Thirdly, object-based image analysis is use for slope segmentation and classification based on the multi-band image. It is proved that the methodology is effective, and useful in geomorphological research. Then, to quantitatively depict the classification result, several landscape indices are tested. Results show that these indices can properly describe the size, shape, aggregated degree, connectivity degree of each slope patch. Our study also provides a potential way to quantitative research of loess landform from the landscape ecology point of view.
Keywords :
digital elevation models; geomorphology; geophysical image processing; image classification; image segmentation; terrain mapping; DEM; digital elevation models; digital terrain analysis; geomorphology; image based loess slope segmentation; landscape ecology; landscape index; loess landform; loess slope classification; multiband image; object-based image analysis; object-oriented image analysis; surface shape; Environmental factors; Image analysis; Image color analysis; Image segmentation; Indexes; Neodymium; Shape; digital terrain analysis; image segmentation; loess slope;
Conference_Titel :
Image and Signal Processing (CISP), 2010 3rd International Congress on
Conference_Location :
Yantai
Print_ISBN :
978-1-4244-6513-2
DOI :
10.1109/CISP.2010.5646918