A Robust Built-Up Area Presence Index by Anisotropic Rotation-Invariant Textural Measure
By Martino Pesaresi, A. Gerhardinger, François Kayitakire. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2008
323 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Media Technology
View Paper: https://www.semanticscholar.org/paper/64fdd711ce8f46d13898ef4bedd78ed6d39c3493
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Media Technology
- Liangpei Zhang
- Xin Huang
- Monika Kuffer
- Karin Pfeffer
- Richard Sliuzas
- Martino Pesaresi
- Lionel Gueguen
- Bo Du
Citations in the corpus
- Morphological Building/Shadow Index for Building Extraction From High-Resolution Imagery Over Urban Areas (2012, methodology): “To this aim, some researchers proposed automated approaches for building detection from high-resolution data, such as the procedure for the calculation of a texture-derived built-up presence index (PanTex) [7].”
- Object-oriented mapping of landslides using Random Forests (2011, unknown): “Rotation-invariance of a GLCM derivative can be achieved by calculating its mean or minimum value among all four directions (e.g. Pesaresi et al., 2008), or by summing up the four directional GLCMs (GLCMall dir.) before the calculation of the derivative.”
- A Global Human Settlement Layer From Optical HR/VHR RS Data: Concept and First Results (2013, methodology): “The capacity to discriminate built-up (BU) from non-built-up (NBU) areas of the PANTEX features was previously assessed in a number of experiments including multi-temporal SPOT panchromatic data [23], [27], and a set of 56 globally-representative VHR optical scenes representing large cities [12].”
- An SVM Ensemble Approach Combining Spectral, Structural, and Semantic Features for the Classification of High-Resolution Remotely Sensed Imagery (2013, background): “However, it should be recognized that although various spatial features are currently available for high-resolution image processing, such as morphological features [6]–[10], [12], structural feature set [29], PSI [13], wavelet-based texture [30], object-based features [32], and GLCM [4], [33], it i”
- Slums from Space - 15 Years of Slum Mapping Using Remote Sensing (2016, background): “, [62,170,171]), which is also the basis for the “anisotropic rotation-invariant built-up presence index” (Pantex) [172].”