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Terrain segmentation and classification using SRTM data

Domenii publicaţii > Ştiinţele pământului şi planetare + Tipuri publicaţii > Capitol de carte

Autori: Drãguţ, L. and Blaschke, T.

Editorial: Zhou, Q., Lees, B. and Tang, G., Springer, Advances in Digital Terrain Analysis, p.141-158, 2008.


The main objective of this chapter is to segment and classify Shuttle Radar
Topography Mission (SRTM) data into specific landforms. Based on the
results of previous research (Dragut and Blaschke 2006), a classification
system of landform elements was improved and adapted for SRTM 3 arc
second data. Terrain derivatives such as elevation, slope gradient, slope
aspect, profile curvature, and plane curvatures were classified in a multiresolution
object-oriented approach comprising four different scale levels.
We carried out object-based image analysis, using a software program
called eCognition Professional 4.0, to segment terrain derivatives into relatively
homogeneous objects, which were further classified using fuzzy
logic rule sets. Special emphasis was put on the accuracy assessment of the
results as well as on the transferability of the procedure between study areas.
We classified two SRTM datasets comprising a rolling hill landscape,
which covers small areas of the states of Arkansas, Missouri and Oklahoma,
USA, and a high mountain area of 50 square km around Hochkalter
Peak, Berchtesgaden National Park, Germany. Results were visually compared
and accuracy assessments using fuzzy classification options and an
error matrix were performed. The classification system proved to be transferable
between hilly and high mountain areas, its outcomes being satisfactorily

Cuvinte cheie: terrain segmentation, SRTM, accuracy assessment, fuzzy logic, geomorphometry