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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bianchi, F. Catani, F. Moretti, S. Dessena, M.A. |
| Copyright Year | 2000 |
| Description | Author affiliation: Dept. of Earth Sci., Firenze Univ., Italy (Bianchi, F.) |
| Abstract | The Mulargia river basin is located in central Sardinia (Italy) and is characterized by the presence of geomorphologically active processes and human activities whose overall effect results in a environmental impact on superficial water quality, in the framework of a drought-prone region. On this subject, a large multidisciplinary project is in progress in which the elaboration of remotely sensed images constitutes an important part, allowing the seasonal land-use evolution to be understood. The presence and movement of organic materials may also be studied. These data have been combined with those derived from ground truth and ground survey campaigns concerning geology and geomorphology. Furthermore, rainfall simulations have been carried out in order to evaluate the principal parameters involved in the soil erosion processes. On these data an hydrologic model has been applied based on a DTM of the whole area, providing information on the spatial prevalence of the different erosion processes. Then, in order to reasonably assess the vegetation cover effect on landscape evolution, a set of classified data concerning the latter have been extracted from Landsat TM imagery and subsequently fed into the model. Results show a clear improvement in the model forecasting concerning soil erosion hazardous areas. |
| Starting Page | 2008 |
| Ending Page | 2010 |
| File Size | 397009 |
| Page Count | 3 |
| File Format | |
| ISBN | 0780363590 |
| DOI | 10.1109/IGARSS.2000.858247 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2000-07-24 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Remote sensing Soil Rivers Humans Organic materials Geology Vegetation mapping Data mining Satellites Predictive models |
| Content Type | Text |
| Resource Type | Article |
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