OUTLIER DETECTION AND RECONSTRUCTION OF LOST LAND SURFACE TEMPERATURE DATA IN REMOTE SENSING
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Author : Muhammad Yasir Adnan, Prof Yong Xue, Richard Self
Affiliation : University of Derby
Country : United Kingdom
Category : Data Mining
Volume, Issue, Month, Year : 12, 13, July, 2022
Abstract :
In quantitative remote sensing, missing values classified as outliers occur frequently. This is due
to technical constraints and the impact of weather on the efficiency of instruments to collect
data. In order to deal with these missing values, we offer an Outlier-Search-and-Replace (OSR)
algorithm that uses spatial and temporal information for the detection and reconstruction of
missing data. The algorithm searches for outlier in the data and reconstruct by finding the best
possible match in spatial locations.
Keyword : Remote Sensing, Missing Data Reconstruction, Outlier, MODIS, Land Surface Temperature
URL : https://aircconline.com/csit/papers/vol12/csit121317.pdf
User Name : yasir010
Posted 14-09-2022 on 00:19:52 AEDT
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