Morphometric and Landscape Feature Analysis with Artificial Neural Networks and SRTM data : Applications in Humid and Arid Environments
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Summary
This thesis presents a semi-automatic method to analyze morphometric features and landscape elements based on Self Organizing Map as an unsupervised Artificial Neural Network algorithm in two steps.
- Type
- article
- Published
- 2008-01-01
- Cited by
- 2
- References
- 117
- Access
- Open access
- OpenAlex
- https://openalex.org/W134296195
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:14531073
Keywords
Arid, Shuttle Radar Topography Mission, Artificial neural network, Feature (linguistics), Artificial intelligence
References
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- Visual Explorations in Finance with Self-Organizing Maps
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- Distribution of landslides in the Upper Tiber River basin, central Italy
- Comparing feature extraction techniques for urban land‐use classification
- Scale matters–A multi-resolution study of the determinants of patterned ground activity in subarctic Finland
- Effect of Contour Intervals and Grid Cell Size on the Accuracy of DEMs and Slope Derivatives
- Evolution of the yardangs at Rogers Lake, California
- Cross-border comparison of land cover and landscape pattern in Eastern Europe using a hybrid classification technique
- Fuzzy and isodata classification of landform elements from digital terrain data in Pleasant Valley, Wisconsin
- Segmentation of physiographic features from the global digital elevation model/GTOPO30
- The shuttle radar topography mission—a new class of digital elevation models acquired by spaceborne radar
- Computer-assisted discrimination of morphological units on north-central Crete (Greece) by applying multivariate statistics to local relief gradients
- Contribution of Landsat ETM+ thermal band to land cover classification using SMAP and ML algorithms (case study: Eastern Carpathians)
- Assessing effects of digital elevation model resolutions on soil-landscape correlations in a hilly area
- Artificial neural networks as a tool in ecological modelling, an introduction
- An overview of scale, pattern, process relationships in geomorphology: a remote sensing and GIS perspective
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