Land Use and Land Cover Mapping in Europe : Practices & Trends /
Autor Corporativo: | |
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Otros Autores: | , |
Formato: | eBook |
Lenguaje: | English |
Publicado: |
Dordrecht :
Springer Netherlands : Imprint: Springer,
2014.
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Edición: | 1st ed. 2014. |
Colección: | Remote Sensing and Digital Image Processing,
18 |
Materias: |
Tabla de Contenidos:
- Remote Sensing in support of the geo-information in Europe
- Global land cover mapping: Current status and future trends
- The users’ role in the current European land monitoring context
- Towards an European land cover monitoring service and high-resolution layers
- CORINE Land Cover and land cover change products
- European Area Frame Sampling based on Very High Resolution image
- European forest monitoring approaches
- The European Urban Atlas
- A review of modern approaches to classification of remote sensing data
- Recent advances in remote sensing change detection – a review
- Synergies from SAR-optical data fusion for LULC mapping
- Application of object-oriented method for classification of VHR satellite images using rule-based approach and texture measures
- Remote sensing of vegetation for nature conservation
- Modeling urban sprawl
- Land Information System Austria (LISA)
- Digital Land Cover Model for Germany DLM DE – The “German Way”
- Land Use & land cover mapping in Europe: Examples from the UK
- Operational land cover and land use mapping in the Netherlands
- The use of the Land-Cover Classification System in Eastern European countries: experiences, lessons learnt and the way forward
- Differentiation of Crop Types and Grassland by Multi-Scale Analysis of Seasonal Satellite Data
- Enhancing remotely sensed low resolution vegetation data for assessing Mediterranean areas prone to land degradation
- Beyond NDVI: Extraction of biophysical variables from remote sensing imagery
- Land transformation processes in NE China: Tracking trade-offs in ecosystem services across several decades with Landsat-TM/ETM+ time series
- Carbon stock estimation of tropical forests on Borneo, Indonesia, for REDD+.