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Assessment of the impact of Landsat 7 Scan Line Corrector data gaps on Sungai Pulai Estuary seagrass mapping

Hossain, Mohammad Shawkat and Bujang, Japar Sidik and Zakaria, Muta Harah and Hashim, Mazlan (2015) Assessment of the impact of Landsat 7 Scan Line Corrector data gaps on Sungai Pulai Estuary seagrass mapping. Applied Geomatics, 7 (3). pp. 189-202. ISSN 1866-7511

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Official URL: http://dx.doi.org/10.1007/s12518-015-0162-3

Abstract

The data gaps in the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) Scan Line Corrector (SLC)-off imagery as a result of SLC failure are well recognized. The degradation introduced by their use in scientific applications is concerning to Landsat users. SLC-off data gaps cause problems in many applications of ETM+ images, but no literature reported the problem in seagrass mapping. To investigate the impact of SLC-off data loss on the seagrass information extraction, two types of data were compared: (a) data with interpolation after the SLC anomaly, termed the “Interpolation ON (ION)”, and (b) the data without interpolation, termed the “Interpolation OFF (IOFF)” image, for the Sungai Pulai estuary seagrass meadows of Malaysia. Additionally, the random shifting of SLC-off stripes was tested by swipe analysis of SLC-off image pairs. Overall, the SLC-off scene analysis suggests that a gradual increase of data gaps from the central part toward the edge may cause a cumulative error of 2 % based on an object’s distance from the nadir path. The random shifting of SLC-off stripes may be completely invisible if a single SLC-off stripe passes over a targeted small seagrass meadow such as the Tanjung Adang Laut shoal, which has a spatial extent of 11.07 ha. The data gaps eventually lead to misinterpretations and produce erroneous seagrass distribution maps. The co-existence of SLC-off stripes and their random shifting phenomenon have caused non-overlapping regions between SLC-off scenes acquired on different dates. Future research should develop suitable methods for gap-filling and resolve aquatic remote sensing mapping issues by using knowledge from the present research.

Item Type:Article
Uncontrolled Keywords:aquatic remote sensing, data gap, etm+ slc-off, landsat, seagrass mapping, sungai pulai estuary
Subjects:A General Works
ID Code:57918
Deposited By: Haliza Zainal
Deposited On:04 Dec 2016 12:07
Last Modified:12 Apr 2017 09:34

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