Earth Observation Data Mining: A Use Case for Forest Monitoring
| Autor: | Anna Pulak-Siwiec, Bartosz Kulawik, Corneliu Octavian Dumitru, Jose Lorenzo, Gottfried Schwarz, Mihai Datcu |
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| Rok vydání: | 2019 |
| Předmět: |
Synthetic aperture radar
Earth observation Multispectral data Computer science 0211 other engineering and technologies Copernicus data forest monitoring 02 engineering and technology Land cover 021001 nanoscience & nanotechnology computer.software_genre Data set Identification (information) Satellite Data mining 0210 nano-technology Focus (optics) computer EO Data Science 021101 geological & geomatics engineering |
| Zdroj: | IGARSS |
| DOI: | 10.1109/igarss.2019.8899135 |
| Popis: | The increased number of free and open satellite images has led to new applications of these data. Among them is the systematic classification of land cover/use types based on patterns of settlements or agriculture recorded by satellite imagers, in particular, the identification and quantification of temporal changes. In this paper, we will present guidelines and practical examples of how to obtain reliable image patch classification results based on data mining techniques for detecting possible changes that can appear within a data set. Here, we will focus on a scenario, namely forest monitoring using Earth observation Synthetic Aperture Radar data acquired by Sentinel-1, and multispectral data acquired by Sentinel-2. |
| Databáze: | OpenAIRE |
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