Locally adaptive unmixing method for lake-water area extractionbased on MODIS 250 m bands

International Journal of Applied Earth Observation and Geoinformation

Volumn 33, Issue 1, 2014, Pages 109-118

  Ma, Baodong ^a   Wu, Lixin ^a,b   Zhang, Xuanxuan ^a   Li, Xingchun ^a   Liu, Ying ^c   Wang, Shenglei ^a  

^a NORTHEASTERN UNIVERSITY   (China)

^b CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

^c XI'AN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

250 m MODIS data; Lake water area; Locally adaptive unmixing; Near infrared; Satellite image

Indexed keywords

IMAGE ANALYSIS; LAKE; LAKE WATER; MODIS; PATTERN RECOGNITION; REMOTE SENSING; SATELLITE IMAGERY;

EID: 84904761562     PISSN: 15698432     EISSN: 1872826X     Source Type: Journal    
DOI: 10.1016/j.jag.2014.05.002     Document Type: Article

References (35)

1. Canham, It, Schlamm, A., Ziemann, A., Basener, B., Messinger, D., 2011. Spatially adaptive hyperspectral unmixing. IEEE Trans. Geosc. Remote Sens. 49 (11), 4248-426
2. Chipman, J.W., Lillesand, T.M., 2007. Satellite-based assessment of the dynamics of new lakes in southern Egypt. Int. J. Remote Sens. 28 (19), 4365-437
3. Dheeravath, V., Thenkabail, P.S., Chandrakantha, G., Noojipady, P., Reddy, G.P.O., Biradar, CM., Gumma, M.K., Velpuri, M., 2010. Irrigated areas of India derived using MODIS 500 m time series for the years 2001-2003. ISPRS J. Photogram. Remote Sens. 65 (1), 42-5
4. Ding, X., Li, X., 2011. Monitoring of the water-area variations of Lake Dongting in China with ENVISAT ASAR images. Int. J. Appl. Earth Observ. Geoinform. 13 (6), 894-90
5. Dominguez Gomez, J.A., Chuvieco Salinero, E., Sastre Merlin, A., 2009. Monitoring transparency in inland water bodies using multispectral images. Int. J. Remote Sens. 30 (6), 1567-158
6. Du, Z., Linghu, B., Ling, F., Li, W., Tian, W., Wang, H., Gui, Y., Sun, B., Zhang, X., 2012 Estimating surface water area changes using time-series Landsat data in the Qjngjiang River Basin, China. J. Appl. Remote Sens. 6 (1)
7. Ekercin, S., 2007. Coastline change assessment at the Aegean Sea Coasts in Turkey using multitemporal Landsat imagery. J. Coast. Res. 23 (3), 691-69
8. Feng, L., Hu, C, Chen, X., Cai, X., Tian, L., Gan, W., 2012. Assessment of inundation changes of Poyang Lake using MODIS observations between 2000 and 201 Remote Sens. Environ. 121, 80-9
9. Foody, G.M., Muslim, A.M., Atkinson, P.M., 2005. Super-resolution mapping of the waterline from remotely sensed data. Int. J. Remote Sens. 26 (24), 5381-539
10. Frazier, P.S., Page, K.J., 2000. Water body detection and delineation with Landsat TM data. Photogr. Eng. Remote Sens. 66 (12), 1461-146
11. Gens, R., 2010. Remote sensing of coastlines: detection, extraction and monitoring. Int. J. Remote Sens. 31 (7), 1819-183
12. Haas, E.M., Bartholome, E., Lambin, E.F., Vanacker, V., 2011. Remotely sensed surface water extent as an indicator of short-term changes in ecohydrological processes in sub-Saharan Western Africa. Remote Sens. Environ. 115 (12), 3436-344
13. Huang, S., Dahal, D., Young, C, Chander, G., Liu, S., 2011. Integration of Palmer Drought Severity Index and remote sensing data to simulate wetland water surface from 1910 to 2009 in Cottonwood Lake area, North Dakota. Remote Sens. Environ. 115 (12), 3377-338
14. Huang, Z.H., Xue, B., Yao, S.C., Pang, Y., 2008. Lake evolution and its implication for environmental changes in China during 1950-2000. J. Geogr. Sci. 18(2), 131-14
15. Ines, A.V.M., Honda, It, 2005. On quantifying agricultural and water management practices from low spatial resolution RS data using, genetic algorithms: a numerical study for mixed-pixel environment. Adv. Water Resour. 28 (8), 856-87
16. Ji, L., Zhang, L, Wylie, B., 2009. Analysis of dynamic thresholds for the normalized difference water index. Photogr. Eng. Remote Sens. 75 (11), 1307-131
17. Kabbara, N., Benkhelil, J., Awad, M., Barale, V., 2008. Monitoring water quality in the coastal area of Tripoli (Lebanon) using high-resolution satellite data. ISPRS J. Photogram. Rem. Sens. 63 (5), 488-49
18. Keith, D.J., Milstead, B., Walker, H., Snook, H., Szykman.J., Wusk, M., Kagey, L., Howell, C, Mellanson, C, Drueke, C, 2012. Trophic status, ecological condition, and cyanobacteria risk of New England lakes and ponds based on aircraft remote sensing,. J. Appl. Remote Sens. 6(1).
19. Keshava, N., 2003. A survey of spectral unmixing algorithms. Lincoln Lab. J. 14 (1), 55-7
20. Lee, H., Durand, M., Jung, H.C., Alsdorf, D., Shum, C.It, Sheng, Y., 2010. Characterization of surface water storage changes in Arctic lakes using simulated SWOT measurements. Int. J. Remote Sens. 31 (14), 3931-395
21. Liu, H., Jezek, ItC, 2004. Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods. Int. J. Remote Sens. 25 (5), 937-95
22. Maiti, S., Bhattacharya, A.It, 2009. Shoreline change analysis and its application to prediction: a remote sensing and statistics based approach. Mar. Geol. 257 (1-4), 11-2
23. McCuIIough, I.M., Loftin, C.S., Sader, S.A., 2012. Combining lake and watershed characteristics with Landsat TM data for remote estimation of regional lake clarity. Remote Sens. Environ. 123,109-11
24. Miller, H.J., 2004. Tobler's first law and spatial analysis. Ann. Assoc. Am. Geogr. 94 (2), 284-28
25. M-Muslim, A.M., Foody, G.M., Atkinson, P.M., 2007. Shoreline mapping from coarsespatial resolution remote sensing imagery of Seberang Takir, Malaysia. J. Coast. Res. 23 (6), 1399-140
26. Oyama, Y., Matsushita, B., Fukushima, T., Matsushige, It, Imai, A., 2009. Application of spectral decomposition algorithm for mapping water quality in a turbid lake (Lake Kasumigaura, Japan) from Landsat TM data. ISPRS J. Photogram. Remote Sens. 64(1), 73-8
27. Pardo-Pascual, J.E., Almonacid-Caballer, J., Ruiz, LA., Palomar-Vazquez, J., 201 Automatic extraction of shorelines from Landsat TM and ETM+ multi-temporal images with subpixel precision. Remote Sens. Environ. 123,1-1
28. Rogge, D.M., Rivard, B., Zhang, J., Sanchez, A., Harris, J., Feng, J., 2007. Integration of spatial-spectral information for the improved extraction of endmembers. Remote Sens. Environ. 110 (3), 287-30
29. Schroeter, L., Glaesser, C, 2011. Analyses and monitoring of lignite mining lakes in Eastern Germany with spectral signatures of Landsat TM satellite data. Int. J. Coal Geol. 86(1), 27-3
30. Singh, A., Seitz, F., Schwatke, C, 2012. Inter-annual water storage changes in the Aral Sea from multi-mission satellite altimetry, optical remote sensing, and GRACE satellite gravimetry. Remote Sens. Environ. 123,187-19
31. Song, It, Wang, Z., Blackwell, J., Zhang, B., Li, F., Zhang, Y.Jiang, G., 2011. Waterquality monitoring using Landsat Themate Mapper data with empirical algorithms in Chagan Lake, China. J. Appl. Remote Sens. 5 (1).
32. Van der Meer, F.D., Jia, X., 2012. CoIIinearity and orthogonality of endmembers in linear spectral unmixing. Int. J. Appl. Earth Observ. Geoinform. 18,491-50
33. Vikhamar, D., Solberg, R., 2003. Snow-cover mapping in forests by constrained linear spectral unmixing of MODIS data. Remote Sens. Environ. 88 (3), 309-32
34. Wang, M., Shi, W., Tang, J., 2011. Water property monitoring and assessment for China's inland Lake Taihu from MODIS-Aqua measurements. Remote Sens. Environ. 115 (3), 841-85
35. Zheng, M.P., Qj, W., Jiang, X.F., Zhao, Y.Y., Li, M.H., 2004. Trend of salt lake changes in the background of global warming and tactics for adaptation to the changes. Acta Geol. Sin. Engl. Ed. 78 (3), 795-80