SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA

SAMPLING METHOD ANALYSIS AND QUALITY EVALUATION STRATEGY FOR REMOTE SENSING BIG DATA

Under the background of the increasingly unified management of natural resources, remote sensing big-data will become the main data source to support a number of major projects. How to sample the natural resources results efficiently and reliably in the process of quality evaluation is always a rese...

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Bibliographic Details
Published in:International archives of the photogrammetry, remote sensing and spatial information sciences. Vol. XLII-3/W10; pp. 11 - 16
Main Authors: Dang, Y., Zhang, J. X., Zhang, P. C., Luo, F. J., Bai, J.
Format: Journal Article Conference Proceeding
Language:English
Published: Gottingen Copernicus GmbH 07-02-2020
Copernicus Publications
Subjects:
Algorithms
Data
Detection
Evaluation
Natural resource management
Natural resources
Optimization
Quality assessment
Remote sensing
Resource management
Theoretical analysis
Online Access:Get full text
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Summary:Under the background of the increasingly unified management of natural resources, remote sensing big-data will become the main data source to support a number of major projects. How to sample the natural resources results efficiently and reliably in the process of quality evaluation is always a research hotspot when it comes to the natural resources results involving remote sensing big-data. A sequential quality evaluation model based on root mean square error (RMSprop) optimization algorithm is constructed by theoretical analysis with an numerical experiments to validate the effectiveness of this method.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLII-3-W10-11-2020