Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
A texture thesaurus for browsing large aerial photographs
Journal of the American Society for Information Science - Special topic issue: artificial intelligence techniques for emerging information systems applications
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Neuro-Dynamic Programming
Texture classification using wavelet transform
Pattern Recognition Letters
Textural Features for Image Database Retrieval
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
The steerable pyramid: a flexible architecture for multi-scale derivative computation
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 3)-Volume 3 - Volume 3
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Automated mapping of land cover using black and white aerial photographs, as an alternative method to traditional photo-interpretation, requires using methods other than spectral analysis classification. To this end, textural measurements have been shown to be useful indicators of land cover. In this work, a neural network model is proposed and tested to map historical land use/land cover (LUC) from very detailed panchromatic aerial photographs (5 m resolution) using textural measurements. The method is used to identify different land use and management types (e.g. traditional versus mechanized vineyard systems). These have been tested with known ground reference data. The results show the potential of the methodology to obtain automatic, historic, and very detailed cartography information from a complex landscape such as the mountainous and Mediterranean region to which it is applied here, and the advantages that this method has over traditional methods.