Nested hyper-rectangle learning model for remote sensing: Land cover classification
- Author
- LI CHEN1
[1] Department of Civil Engineering, Chung Hua University, Hsin Chu, 30067, Taiwan, Province of China - Source
Photogrammetric engineering and remote sensing. 2005, Vol 71, Num 3, pp 333-340, 8 p ; ref : 20 ref
- CODEN
- PERSDV
- ISSN
- 0099-1112
- Scientific domain
- Agronomy, agriculture, phytopathology; Ecology; Geology; Geophysics; Oceanography
- Publisher
- American Society for Photogrammetry and Remote Sensing, Bethesda, MD
- Publication country
- United States
- Document type
- Article
- Language
- English
- Keyword (fr)
- Apprentissage Caractéristique spectrale Classification supervisée Concept Couvert végétal Echantillon référence Ensemencement Espèce introduite Etude préalable Exemple Imagerie Modèle Modélisation Mémoire Nid Norme Nuage Occupation sol Poids Problème Procédure Profondeur Projectile SPOT Télédétection Taiwan Asie Extrême Orient
- Keyword (en)
- Learning Spectral data Supervised classification concepts Plant cover standard samples Seeding Introduced species Previous study Example imagery models Modeling Memory Nest Standards clouds land cover Weight Problem Procedure depth Projectile Spot remote sensing Taiwan Asia Far East
- Keyword (es)
- Aprendizaje Característica espectral Clasificación supervisada Cubierta vegetal Roca patrón Siembra Especie introducida Estudio previo Ejemplo Imaginería Modelo Modelización Memoria Nido Norma Nube Peso Problema Procedimiento Profundidad Proyectil Spot Detección a distancia Taiwan Asia Extremo Oriente
- Classification
- Pascal
- 001 Exact sciences and technology / 001E Earth, ocean, space / 001E01 Earth sciences / 001E01M Internal geophysics / 001E01M04 Applied geophysics
- Pascal
- 002 Biological and medical sciences / 002A Fundamental and applied biological sciences. Psychology / 002A14 Animal, plant and microbial ecology / 002A14A General aspects. Techniques / 002A14A03 Teledetection and vegetation maps
- Discipline
- Animal, vegetal and microbial ecology Earth sciences
- Origin
- Inist-CNRS
- Database
- PASCAL
- INIST identifier
- 16662728
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
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DOI
10.14358/PERS.71.3.333 
https://dx.doi.org/10.14358/PERS.71.3.333
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