AUTOMATIC WATER SURFACE EXTRACTION ALGORITHM FOR LANDSAT7-ETM+ SATELLITE IMAGE OVER COASTAL AND INLAND WATERS

Dinh Ngoc Dat; Pham Van Bach Ngoc; Huynh Xuan Quang; Mai Thi Hong Nguyen; Doan Minh Chung; Bui Trung Thanh

Dinh Ngoc Dat Institute of Space Technology, Vietnam Academy of Science and Technology, Cau Giay, Hanoi
Pham Van Bach Ngoc Institute of Space Technology, Vietnam Academy of Science and Technology, Cau Giay, Hanoi
Huynh Xuan Quang Institute of Space Technology, Vietnam Academy of Science and Technology, Cau Giay, Hanoi
Mai Thi Hong Nguyen Institute of Space Technology, Vietnam Academy of Science and Technology, Cau Giay, Hanoi
Doan Minh Chung Institute of Space Technology, Vietnam Academy of Science and Technology, Cau Giay, Hanoi
Bui Trung Thanh Hung Yen University of Technology and Education

Keywords: WiPE algorithm, Landsat-7/ETM satellite imagery, phân tích hình dạng quang phổ

Abstract

Identifying pixels on the water surface natural water is an important step before applying a specific algorithm to calculate water environment parameters from satellite imagery. A mistake can occur when detecting clouds on turbid water (due to glare) and detecting their shadows on any surface water. Some algorithms exist but their performance is unsatisfactory, especially on turbid waters where cloudless pixels are sometimes classified as clouds or earth, resulting in data loss. This is especially important for the satellite image sensing have high resolution, such as the observations made by the sensor ETM + on Landsat-7, OLI on Landsat-8 or MSI on Sentinel- 2. In this study, we develop a two-step algorithm to extract water pixels (called LS7WiPE) for the Landsat-7 / ETM + sensor based on our experience from the WiPE algorithm for OLI and MSI sensors (Dat et al., 2019).

References

Pahlevan N., Schott J. R.. Leveraging EO-1 to evaluate capability of new generation of Landsat sensors for coastal/inland water studies. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2013, Vol. 6, pp. 360-374.

Vanhellemont Q., Ruddick K.. Turbid wakes associated with offshore wind turbines observed with Landsat 8. Remote Sensing of Environment, 2014, Vol. 145, pp. 105-115.

Concha J. A. and J. R. Schott. Retrieval of color producing agents in Case 2 waters using Landsat 8. Remote sensing of Environment, 2016, 185, pp. 95-107.

Kutser Tiit, Pascual Gema Casal, Barbosa Claudio, Paavel Birgot, Ferreira Renato, Carvalho Lino, Toming Kaire. Mapping inland water carbon content with Landsat 8 data. International Journal of Remote Sensing, 2016, 37, pp.13-2950.

Lymburner, L., Elizabeth Botha, Erin Hestir, Janet Anstee, Stephen Sagar, Arnold Dekker, Tim Malthus. Landsat 8: Providing continuity and increased precision for measuring multi-decadal time series of total suspended matter. Remote Sensing of Environment, 2016, Vol. 185, pp. 108-118.

Lee Z-P, Shaoling Shang, Lin Qi, Jing Yan, Gong Lin. A semi-analytical scheme to estimate Secchi-disk depth from Landsat-8 measurements. Remote Sensing of Environment, 2016, Vol. 177, pp. 101-106.

Urbanski J-A, Agnieszka Wochna, Iwona Bubak, Waldemar Grzybowski, Katarzyna Lukawska-Matuszewska, Magda Łącka, Sylwia Śliwińska, Bożena Wojtasiewicz, Marek Zajączkowski. Application of Landsat 8 imagery to regional-scale assessment of lake water quality. International Journal of Applied Earth Observation and Geoinformation, 2016, Vol. 51, pp. 28-36.

Slonecker E. T., Daniel K. J., Brian A. P. The new Landsat 8 potential for remote sensing of colored dissolved organic matter (CDOM). Marine Pollution Bulletin, 2016, Vol. 107, pp. 518-527.

Li Y., Yunlin Zhang, Kun Shi, Yongqiang Zhou, Yibo Zhang, Xiaohan Liu, Yulong Guo. Spatiotemporal dynamics of chlorophyll-a in a large reservoir as derived from Landsat 8 OLI data: understanding its driving and restrictive factors. Environmental Science and Pollution Research, 2017, ISSN 0944-1344.

S.K. McFeeters. The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 1996, Vol. 17, pp. 1425-1432.

McFeeters, S.K., Using the normalized diff erence water index (NDWI) within a geographic information system to detect swimming pools for mosquito abatement: a practical approach. Remote Sens., 2013, 5, pp. 3544–3561.

Vermote, E.F., Saleous, N.Z., Operational atmospheric correction of MODIS visible to middle infrared land surface data in the case of an infi nite Lambertian target. In: Qu, J.J. (Ed.), Earth Science Satellite Remote Sensing, Science and Instruments, 2006, vol. 1, Tsinghua Univ. Press, Beijing, pp. 123–153.

Jawak, S.D., Kulkarni, K., Luis, A.J., A review on extraction of lakes from remotely sensed optical satellite data with a special focus on cryospheric lakes. Adv. Remote Sens, 2015, 4, pp. 196–213.

Xue, H., Modifi cation of normalized diff erence water index (NDWI) to enhance open water features in remotely sensed imagery. Int. J. Remote Sens, 2006, 27 (14), pp. 3025–3033.

Zhu Z., Woodcock C. E. Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment. 2012, Vol. 118, pp. 83-94.

Zhu Z., Wang S., Woodcock C. E., Improvement and expansion of the Fmask algorithm: cloud, cloud shadow, and snow detection for Landsats 4-7, 8, and Sentinel-2 images. Remote Sensing of Environment, 2015, Vol. 159, pp. 269-277.

Nordkvist K., Loisel H., Gaurier L. D. Cloud masking of SeaWiFS images over coastal waters using spectral variability. Optics Express, 2009, Vol. 17, pp. 12246-12258.

Gordon, H. R. Atmospheric correction of ocean color imagery in the Earth Observing System era. Journal of Geophysical Research, 1997, 102, pp. 17081-17106.

Wang M., and S. W. Bailey. Correction of sun glint contamination on the SeaWiFS ocean and atmosphere-products. Applied Optics, 2001, 40, pp. 4790-4798.

Gordon H. R., Brown J. W., Evans R. H. Exact Rayleigh scattering calculations for use with the Nimbus-7 coastal zone color scanner. Applied Optics, 1988, Vol. 27, pp. 862-871.

Wang M., Michael D. King. Correction of Rayleigh scattering effects in cloud optical thickness retrievals. Journal of Geophysical Research, 1997, Vol. 102, pp. 25915-25926.