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An Integrated GIS and Remote Sensing Approach for Monitoring Harvested Areas from Very High-Resolution, Low-Cost Satellite Images

1
Department of Forest Management, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences (CULS), Kamýcká 129, 165 21 Prague, Czech Republic
2
Department of Silviculture, Faculty of Forestry and Wood Sciences, Czech University of Life Sciences (CULS), Kamýcká 129, 165 21 Prague, Czech Republic
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(21), 2539; https://doi.org/10.3390/rs11212539
Received: 20 September 2019 / Revised: 20 October 2019 / Accepted: 27 October 2019 / Published: 29 October 2019
(This article belongs to the Special Issue Monitoring Forest Change with Remote Sensing)
Advanced monitoring and mapping of forest areas using the latest technological advances in satellite imagery is an alternative solution for sustainable forest management compared to conventional ground measurements. Remote sensing products have been a key source of information and cost-effective options for monitoring changes in harvested areas. Despite recent advances in satellite technology with a broad variety of spectral and temporal resolutions, monitoring the areal extent of harvested forest areas in managed forests is still a challenge, primarily due to the highly dynamic spatiotemporal patterns of logging activities. Our goal was to introduce a plot-based method for monitoring harvested forest areas from very high-resolution (VHR), low-cost satellite images. Our method encompassed two data categories, which included vegetation indices (VIs) and texture analysis (TA). Each group of data was used to model the amount of harvested volume both independently and in combination. Our results indicated that the composition of all spectral bands can improve the accuracy of all models of average volume by 23.52 RMSE reduction and total volume by 33.57 RMSE reduction. This method demonstrated that monitoring and extrapolation of the calculated relation and results from smaller forested areas could be applied as an automatic remote-based supervised monitoring method over larger forest areas. View Full-Text
Keywords: Pleiades’-HR 1A-1B; pre-harvest; post-harvest; random forest; spectral differences; texture analysis; modeling; plot-based analysis; geographic information systems; vegetation indices Pleiades’-HR 1A-1B; pre-harvest; post-harvest; random forest; spectral differences; texture analysis; modeling; plot-based analysis; geographic information systems; vegetation indices
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MDPI and ACS Style

Abdollahnejad, A.; Panagiotidis, D.; Bílek, L. An Integrated GIS and Remote Sensing Approach for Monitoring Harvested Areas from Very High-Resolution, Low-Cost Satellite Images. Remote Sens. 2019, 11, 2539.

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