- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
SPATIAL INTERPOLATION AS A TOOL FOR SPECTRAL UNMIXING OF REMOTELY SENSED IMAGES ; volume:XXXIX-B7 ; year:2012 ; pages:209-212
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XXXIX-B7 (2012), 209-212
- Creator
-
Xi, L.
Xiaoling, C.
- DOI
-
10.5194/isprsarchives-XXXIX-B7-209-2012
- URN
-
urn:nbn:de:101:1-2017121141491
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:39 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Xi, L.
- Xiaoling, C.
Other Objects (12)
Forest biodiversity monitoring based on remotely sensed spectral diversity — a review
SALIENCY-GUIDED CHANGE DETECTION OF REMOTELY SENSED IMAGES USING RANDOM FOREST
Combining remotely sensed data using aggregation algorithms
Unsupervised classification of saturated areas using a time series of remotely sensed images
OPTIMIZATION OF THE SPARSE REPRESENTATION PARAMETERS FOR THE FUSION OF REMOTELY SENSED SATELLITE IMAGES
Noise Filtering of Remotely Sensed Images using Iterative Thresholding of Wavelet and Curvelet Transforms
Remotely-sensed productivity clusters capture global biodiversity patterns
Simulation of remotely sensed rainfall fields using copulas
Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images
Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices
Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices
Combining remotely sensed spectral data and digital surface models for fine-scale modelling of mire ecosystems
Forest biodiversity monitoring based on remotely sensed spectral diversity — a review
SALIENCY-GUIDED CHANGE DETECTION OF REMOTELY SENSED IMAGES USING RANDOM FOREST
Combining remotely sensed data using aggregation algorithms
Unsupervised classification of saturated areas using a time series of remotely sensed images
OPTIMIZATION OF THE SPARSE REPRESENTATION PARAMETERS FOR THE FUSION OF REMOTELY SENSED SATELLITE IMAGES
Noise Filtering of Remotely Sensed Images using Iterative Thresholding of Wavelet and Curvelet Transforms
Remotely-sensed productivity clusters capture global biodiversity patterns
Simulation of remotely sensed rainfall fields using copulas
Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images
Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices
Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices
Combining remotely sensed spectral data and digital surface models for fine-scale modelling of mire ecosystems
Forest biodiversity monitoring based on remotely sensed spectral diversity — a review
SALIENCY-GUIDED CHANGE DETECTION OF REMOTELY SENSED IMAGES USING RANDOM FOREST
Combining remotely sensed data using aggregation algorithms
Unsupervised classification of saturated areas using a time series of remotely sensed images
OPTIMIZATION OF THE SPARSE REPRESENTATION PARAMETERS FOR THE FUSION OF REMOTELY SENSED SATELLITE IMAGES
Noise Filtering of Remotely Sensed Images using Iterative Thresholding of Wavelet and Curvelet Transforms
Remotely-sensed productivity clusters capture global biodiversity patterns
Simulation of remotely sensed rainfall fields using copulas
Using heterogeneous computing and edge computing to accelerate anomaly detection in remotely sensed multispectral images
Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices
Improving data-oriented light use efficiency models of gross primary productivity with remotely sensed spectral indices