Threshold model for detecting transparent plastic-mulched landcover using moderate-resolution imaging spectroradiometer time series data: A case study in southern Xinjiang, China

Journal of Applied Remote Sensing

Volumn 9, Issue 1, 2015, Pages

  Lu, Lizhen ^a   Hang, Danwei ^a   Di, Liping ^b  

^a ZHEJIANG UNIVERSITY   (China)

^b GEORGE MASON UNIVERSITY   (United States)

Author keywords

moderate resolution imaging spectroradiometer time series data; plastic mulched landcover; southern Xinjiang; temporal spectral features selection; threshold model

Indexed keywords

BIODIVERSITY; MAPPING; MAXIMUM LIKELIHOOD; SPECTROMETERS; SURFACE MEASUREMENT; TIME SERIES;

LAND COVER; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER TIME SERIES; SPECTRAL FEATURE; THRESHOLD MODEL; XINJIANG;

RADIOMETERS;

EID: 84926166350     PISSN: None     EISSN: 19313195     Source Type: Journal    
DOI: 10.1117/1.JRS.9.097094     Document Type: Article

References (42)

1. P. Dubois, Plastics in Agriculture, p. 176, Applied Science Publishers, London, England (1978).
2. W. J. Lamont, "What are the components of a plasticulture vegetable system?," HortTechnology 6(3), 150-154 (1996).
3. M. Orzolek, "The plastic advantage," Resource 13-14 (1999).
4. T. Takakura and W. Fang, Climate Under Cover, 2nd ed., p. 190, Kluwer Academic Publishers, Dordrecht (2002).
5. L. Lu, L. Di, and Y. Ye, "A decision-tree classifier for extracting transparent plastic-mulched landcover from Landsat-5 TM images," IEEE J. Sel. Topics Appl. Earth Obs. Remote Sens. 7(11), 4548-4558 (2014).
6. MA/PRC, China Agriculture Statistical Report 2012, China Agriculture Press, Beijing, China (November 2012).
7. G. Zhou, "Analysis of situations of China agro-film industry (2010) and countermeasures for its development," China Plast. 24(8), 9-12 (2010).
8. P. Picuno, A. Tortora, and R. L. Capobianco, "Analysis of plasticulture landscapes in Southern Italy through remote sensing and solid modelling techniques," Landsc. Urban Plan. 100(1-2), 45-56 (2011).
9. N. Levin et al., "Remote sensing as a tool for monitoring plasticulture in agricultural landscapes," Int. J. Remote Sens. 28(1), 183-202 (2007).
10. F. Agüera and J. G. Liu, "Automatic greenhouse delineation from QuickBird and Ikonos satellite images," Comput. Electron. Agric. 66(2), 191-200 (2009).
11. E. Espí et al., "Plastic films for agricultural applications," J. Plast. Film Sheeting 22(2), 85-102 (2006).
12. F. Agüera, F. J. Aguilar, and M. A. Aguilar, "Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses," ISPRS 63(6), 635-646 (2008).
13. E. Tarantino and B. Figorito, "Mapping rural areas with widespread plastic covered vineyards using true color aerial data," Remote Sens. 4(12), 1913-1928 (2012).
14. F. Carvajal et al., "Greenhouses detection using an artificial neural network with a very high resolution satellite image," in Proc. ISPRS Technical Commission II Symp., pp. 37-42, ISPRS, Vienna, Austria (2006).
15. J. D. Colby and P. L. Keating, "Land cover classification using Landsat TM imagery in the tropical islands: the influence of anisotropic reflectance," Int. J. Remote Sens. 19, 1479-1500 (1998).
16. H. Thunnissen and A. D. Wit, "The national land cover database of the Netherlands," Int. Arch. Photogramm. Remote Sens. 33, 223-230 (2000).
17. F. Jacob et al., "Comparison of land surface emissivity and radiometric temperature derived from MODIS and ASTER sensors," Remote Sens. Environ. 90(2), 137-152 (2004).
18. J. Li, "Economic analysis of agro-film pollution in Xinjiang region," Bord. Econ. Culture 1(1), 16-17 (2008).
19. Y. Li et al., "Spatio-temporal pattern dynamic of cotton plantation in Xinjiang and its driving forces," J. Desert Res. 31(2), 476-484 (2011).
20. J. Knorn et al., "Land cover mapping of large areas using chain classification of neighboring Landsat satellite images," Remote Sens. Environ. 113(5), 957-964 (2009).
21. A. B. Salberg, "Land cover classification of cloud-contaminated multitemporal high-resolution images," IEEE Trans. Geosci. Remote Sens. 49(1), 377-387 (2011).
22. A. R. S. Marçal et al., "Land cover update by supervised classification of segmented ASTER images," Int. J. Remote Sens. 26(7), 1347-1362 (2005).
23. A. Schneider, M. A. Friedl, and D. Potere, "Mapping global urban areas using MODIS 500-m data: new methods and datasets based on 'urban ecoregions'," Remote Sens. Environ. 114(8), 1733-1746 (2010).
24. J. Munoz-Marf, L. Bruzzone, and G. Camps-Vails, "A support vector domain description approach to supervised classification of remote sensing images," IEEE Trans. Geosci. Remote Sens. 45(8), 2683-2692 (2007).
25. J. Byeungwoo and D. A. Landgrebe, "Partially supervised classification using weighted unsupervised clustering," IEEE Trans. Geosci. Remote Sens. 37(2), 1073-1079 (1999).
26. L. M. Manevitz and M. Yousef, "One-class SVMs for document classification," J. Mach. Learn. Res. 2, 139-154 (2001).
27. C. Sanchez-Hernandez, D. S. Boyd, and G. M. Foody, "One-class classification for mapping a specific land-cover class: SVDD classification of fenland," IEEE Trans. Geosci. Remote Sens. 45(4), 1061-1073 (2007).
28. G. M. Foody et al., "Training set size requirements for the classification of a specific class," Remote Sens. Environ. 104(1), 1-14 (2006).
29. W. K. Li, Q. H. Guo, and C. Elkan, "A positive and unlabeled learning algorithm for oneclass classification of remote-sensing data," IEEE Trans. Geosci. Remote Sens. 49(2), 717-725 (2011).
30. C. B. Schaaf et al., "First operational BRDF, albedo and nadir reflectance products from MODIS," Remote Sens. Environ. 83(1-2), 135-148 (2002).
31. W. L. Stefanov and M. Netzband, "Assessment of ASTER land cover and MODIS NDVI data at multiple scales for ecological characterization of an arid urban center," Remote Sens. Environ. 99(1-2), 31-43 (2005).
32. G. Yang et al., "Responses of cotton growth, yield, and biomass to nitrogen split application ratio," Eur. J. Agron. 35(3), 164-170 (2011).
33. LSSJCX/CMA, "Kashgar precipitation figure in March 2006," (March 2006), http://search.weather.com.cn/index.php?y=2006&m=03&id=51709&type1=d&type2=p&last=010000 MON01&tag=HCDV-PAMS-EE0-A&td=2006/ (December 2014).
34. L. B. Zhao et al., "A preliminary study on the best temporal period for remote sensing to identify the cotton crops in southern and eastern Xinjiang," China Cotton 36(6), 11-14 (2008). (in Chinese)
35. L. Di, "GeoBrain-a web services based geospatial knowledge building system," presented at Proc. of NASA Earth Science Technology Conf., Greenbelt, Maryland, pp. 22-24 (2004).
36. C. J. Tucker, "Red and photographic infrared linear combinations for monitoring vegetation," Remote Sens. Environ. 8(2), 127-150 (1979).
37. CNIC, "GSCloud," 2010, http://www.gscloud.cn/ (December 2014).
38. USGS, "USGS earthexplorer," http://earthexplorer.usgs.gov/ (November 2014).
39. J. Sun et al., "Automatic remotely sensed image classification in a grid environment based on the maximum likelihood method," MComM 58(3-4), 573-581 (2013).
40. J. Cohen, "A coefficient of agreement for nominal scales," Educ. Psychol. Meas. 20, 37-46 (1960).
41. Y. Chen et al., "An evaluation of MODIS daily and 8-day composite products for floodplain and wetland inundation mapping," Wetlands 33(5), 823-835 (2013).
42. C. Huang, Y. Chen, and J. Wu, "Mapping spatio-temporal flood inundation dynamics at large river basin scale using time-series flow data and MODIS imagery," Int. J. Appl. Earth Obs. Geoinf. 26, 350-362 (2014).