A generic procedure for automatically segmenting landforms into landform elements using DEMs, heuristic rules and fuzzy logic

By R. MacMillan, W. W. Pettapiece, S. Nolan, T. Goddard. Fuzzy Sets Syst., 2000

338 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering, Soil Science

View Paper: https://www.semanticscholar.org/paper/1582e301d31a05c118532d964b0c6b3d06885217

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Thomas Scholten
2. A-Xing Zhu
3. Lucian Dragut
4. Thorsten Behrens
5. Thomas Blaschke
6. Yones Khaledian
7. Bradley A. Miller

In Environmental Engineering

1. Thomas Scholten
2. Andy Nelson
3. A-Xing Zhu
4. K. Schmidt
5. C. Qin
6. Lucian Dragut
7. Andrew Jarvis
8. Baharin bin Ahmad

In Soil Science

1. Thomas Scholten
2. A-Xing Zhu
3. C. Qin
4. Lucian Dragut
5. Thomas Blaschke

Citations in the corpus

• Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio, logistic regression, and fuzzy logic methods at the central Zab basin, Iran (2015, methodology): “There are two basic methods for building fuzzy membership functions: the fuzzy k-means clustering (Burrough et al. 1998, 2000; Gorsevski et al. 2005) and the fuzzy semantic import (SI) model (Burrough et al. 1998; MacMillan et al. 2000; Gorsevski et al. 2006).”
• Mapping soil organic matter in small low-relief catchments using fuzzy slope position information (2012, methodology): “The quantification of the spatial gradation of slope positions (referred to as fuzzy slope position hereafter) is assumed to be important in digital soil mapping and other terrain-related geographical or ecological modeling at fine scale (MacMillan et al., 2000; Schmidt and Hewitt, 2004).”
• Multi-scale digital terrain analysis and feature selection for digital soil mapping (2010, methodology): “Finally, the streamline DEM is subtracted from the original DEM, resulting in a grid containing local elevation (e.g., MacMillan et al., 2000; Behrens, 2003).”
• An evaluation of void‐filling interpolation methods for SRTM data (2007, background): “…SRTM data are a considerable problem for many uses and applications, including hydrological modelling, terrain indices, land surface characterisation, digital soil mapping and many other geomorphometric models, and thus these voids need to be filled to create a seamless DEM (MacMillan et al. 2000).”
• Automated classification of landform elements using object-based image analysis (2006, methodology): “This has been observed in other studies (Friedrich, 1996; MacMillan et al., 2000; Romstad, 2001; Wielemaker et al., 2001).”
• The Effect of DEM Raster Resolution on First Order, Second Order and Compound Terrain Derivatives (2004, background): “…one or several terrain variables and indices, a catchment area can be characterized in terms of geomorphology (e.g. Jenson and Domingue 1988, Moore et al. 1993), stream network patterns (e.g. Tarboton et al. 1991, Band 1993) or landform classification (Blaszcynski 1997, Macmillan et al. 2000).”