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Scale Issues Related to the Accuracy Assessment of Land Use/Land Cover Maps Produced Using Multi-Resolution Data: Comments on “The Improvement of Land Cover Classification by Thermal Remote Sensing”. Remote Sens. 2015, 7(7), 8368–8390
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Remote Sens. 2015, 7(10), 13440-13447; doi:10.3390/rs71013440

Response to Johnson B.A. Scale Issues Related to the Accuracy Assessment of Land Use/Land Cover Maps Produced Using Multi-Resolution Data: Comments on “The Improvement of Land Cover Classification by Thermal Remote Sensing”. Remote Sens. 2015, 7, 8368–8390

1
Department of Geography, Ludwig Maximilian University of Munich, Munich 80333, Germany
2
Institute for Water Management, Hydrology and Hydraulic Engineering (IWHW), University of Natural Resources and Life Sciences, Vienna 1180, Austria
*
Author to whom correspondence should be addressed.
Academic Editors: Ruiliang Pu and Prasad S. Thenkabail
Received: 24 August 2015 / Revised: 23 September 2015 / Accepted: 10 October 2015 / Published: 15 October 2015
View Full-Text   |   Download PDF [319 KB, uploaded 15 October 2015]   |  

Abstract

Following the suggestion made by Johnson (Johnson B.A., 2015), a polygon-based cross validation (CV) method is compared to the pixel-based CV method to classify different levels of land cover categories using a single-date Landsat 8 image and time series of Landsat TM images. Also, different variants of band combinations, with and without the thermal bands, were considered. The results demonstrate that the inclusion of thermal information into the classification process will improve the classification performance, as was already shown in our original study (Sun and Schulz, 2015). However, it is also demonstrated that the polygon-based CV method produced lower overall accuracy values when compared to the pixel-based CV method. This confirms the argument made by Johnson that a correlation of calibration and validation data due to random sampling of multi-scale data will overestimate the performance of the classifier, and independent polygon-based CV methods have to be applied instead. View Full-Text
Keywords: thermal remote sensing; land cover classification; polygon-based cross validation; multi-resolution images; Landsat 8 image; calibration/validation data correlation thermal remote sensing; land cover classification; polygon-based cross validation; multi-resolution images; Landsat 8 image; calibration/validation data correlation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Sun, L.; Schulz, K. Response to Johnson B.A. Scale Issues Related to the Accuracy Assessment of Land Use/Land Cover Maps Produced Using Multi-Resolution Data: Comments on “The Improvement of Land Cover Classification by Thermal Remote Sensing”. Remote Sens. 2015, 7, 8368–8390. Remote Sens. 2015, 7, 13440-13447.

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