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- W184339750 abstract "Based on a spectral-domain prior knowledge-based classification system, recently presented in remote sensing literature, an original spectral rule-based per-pixel classifier, called SOIL MAPPER®, has been developed and commercialized by MEEO S.r.l. The SOIL MAPPER® classifier consists of a modular hierarchical data processing structure. As input, it requires a multi-spectral remote sensing image, whose spectral channels range from visible to thermal infrared wavelengths, radiometrically calibrated into top-of-atmosphere reflectance and at-satellite temperature. As output, it provides a preliminary classification map consisting of a set of kernel (i.e., reliable) semantic labels equivalent to colour-based semi-concepts. The symbolic meaning of semi-concepts is either equal or inferior (not superior) to that of concepts (object models) constituting the so-called world model (e.g., concepts equivalent to land cover classes in the USGS classification scheme). In operational terms, the degree of novelty of SOIL MAPPER® is relevant. It is fully automated, computationally efficient and easy to modify, augment, or scale to different sensors' spectral properties. Second-level application-specific processing systems (e.g., fire detection, flood detection, land cover change detection, etc.), which incorporate the “stratified” or “layered” approach, can be developed in cascade to the general-purpose SOIL MAPPER® first-stage.KeywordsLand CoverLand UseMulti-Spectral ImageRemote SensingSOIL MAPPER® Spectral Rule-Based Preliminary Classification" @default.
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- W184339750 date "2009-01-01" @default.
- W184339750 modified "2023-09-26" @default.
- W184339750 title "Soil Mapper® Multi-Sensor and Multi-Temporal Applications for Semantic-Based Image Information Mining" @default.
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- W184339750 doi "https://doi.org/10.1007/978-90-481-2899-0_13" @default.
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