Combined multi-temporal optical and radar parameters for estimating LAI and biomass in winter wheat using HJ and RADARSAR-2 data

Remote Sensing

Volumn 7, Issue 10, 2015, Pages 13251-13272

  Jin, Xiuliang ^a,b,c   Yang, Guijun ^a,b,d   Xu, Xingang ^a,b,e   Yang, Hao ^a,b   Feng, Haikuan ^a,b   Li, Zhenhai ^a,b   Shen, Jiaxiao ^a,b   Zhao, Chunjiang ^a,b,d,e   Lan, Yubin ^f  

^a INSTITUTE OF PLANT AND ENVIRONMENT PROTECTION   (China)

^b NATIONAL ENGINEERING RESEARCH CENTER FOR INFORMATION TECHNOLOGY IN AGRICULTURE   (China)

^c NORTHEAST INSTITUTE OF GEOGRAPHY AND AGRICULTURAL ECOLOGY   (China)

^d AGRO ENVIRONMENTAL PROTECTION INSTITUTE   (China)

^e Beijing Engineering Research Center of Agricultural Internet of Things   (China)

^f SOUTH CHINA AGRICULTURAL UNIVERSITY   (China)

Author keywords

Biomass; LAI; Optical spectral vegetation indices; Radar polarimetric parameters; Winter wheat

Indexed keywords

CROPS; EIGENVALUES AND EIGENFUNCTIONS; ESTIMATION; LEAST SQUARES APPROXIMATIONS; PARAMETER ESTIMATION; PLANTS (BOTANY); POLARIMETERS; RADAR; REGRESSION ANALYSIS; REMOTE SENSING; VEGETATION;

EARTH OBSERVATION SATELLITES; EIGENVALUE RELATIVE DIFFERENCES; LAI; MULTISOURCE REMOTE SENSING DATA; PARTIAL LEAST SQUARES REGRESSIONS (PLSR); POLARIMETRIC PARAMETERS; SPECTRAL VEGETATION INDICES; WINTER WHEAT;

BIOMASS;

EID: 84945901876     PISSN: None     EISSN: 20724292     Source Type: Journal    
DOI: 10.3390/rs71013251     Document Type: Article

References (59)

1. Darvishzadeh, R.; Skidmore, A.; Schlerf, M.; Atzberger, C. Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland. Remote Sens. Environ. 2008, 112, 2592-2604.
2. Scharf, P.C.; Lory, J.A. Calibrating corn color from aerial photographs to predict side-dress nitrogen need. Agron. J. 2002, 94, 397-404.
3. Bastiaanssen, W.G.M.; Molden, D.J.; Makin, I.W. Remote sensing for irrigated agriculture examples from research and possible applications. Agr. Water Manage. 2000, 46, 137-155.
4. Hunsaker, D.J.; Barnes, E.M.; Clarke, T.R.; Fitzgerald, G.J.; Pinter, P.J. Cotton irrigation scheduling using remotely sensed and FAO-56 basal crop coefficients. Trans. ASAE 2005, 48, 1395-1407.
5. Luedeling, E.; Hale, A.; Zhang, M.; Bentley, W.J.; Dharmasri, L.C. Remote sensing of spider mite damage in California peach orchards. Int. J. Appl. Earth Obs. 2009, 11, 244-255.
6. Mahlein, A.K.; Oerke, E.C.; Steiner, U.; Dehne, H.W. Recent advances in sensing plant diseases for precision crop protection. Eur. J. Plant. Pathol. 2012, 133, 197-209.
7. Groten, S.M.E. NDVI-crop monitoring and early yield assessment of Burkina Faso. Int. J. Remote Sens. 1993, 14, 1495-1515.
8. Mkhabela, M.S.; Bullock, P.; Raj, S.; Wang, S.; Yang, Y. Crop yield forecasting on the Canadian Prairies using MODIS NDVI data. Agr. Forest Meteorol. 2011, 151, 385-393.
9. Dente, L.; Satalino, G.; Mattia, F.; Rinaldi, M. Assimilation of leaf area index derived from ASAR and MERIS data into CERES-wheat model to map wheat yield. Remote Sens. Environ. 2008, 112, 1395-1407.
10. Bala, S.K.; Islam, A.S. Correlation between potato yield and MODIS-derived vegetation indices. Int. J. Remote Sens. 2009, 30, 2491-2507.
11. Li, X.C.; Zhang, Y.J.; Luo, J.H., Jin, X.L.; Xu, Y.; Yang, W.Z. Quantification winter wheat LAI with HJ-1CCD image features over multiple growing seasons. Int. J. Appl. Earth Obs. 2015, 44, 104-112.
12. Koppe, W.; Gnyp, M.L.; Hennig, S.D.; Li, Fei.; Miao, Y.X.; Chen, X.P., Jia, L.L.; Bareth, G. Multi-temporal hyperspectral and radar remote sensing for estimating winter wheat biomass in the North China Plain. Photogramm. Fernerkund. Geoinf. 2012, 2012, 281-298.
13. Chen, P.; Tremblay, N.; Wang, J.; Vigneaulta, P. New index for crop canopy fresh biomass estimation. Spectrosc. Spect. Anal. 2010, 30, 512-517.
14. Liu, J.; Pattey, E.; Miller, J.R.; McNairn, H.; Smith, A.; Hu, B. Estimating crop stresses, aboveground dry biomass and yield of corn using multi-temporal optical data combined with a radiation use efficiency model. Remote Sens. Environ. 2010, 114, 1167-1177.
15. Liu, J.; Pattey, E.; Jégo, J.R.G. Assessment of vegetation indices for regional crop green LAI estimation from Landsat images over multiple growing seasons. Remote Sens. Environ. 2012, 123, 347-358.
16. Nguy-Robertson, A.; Gitelson, A.; Peng, Y.; Vina, A.; Arkebauer, T.; Rundquist, D. Green leaf area index estimation in maize and soybean: Combining vegetation indices to achieve maximal sensitivity. Agron. J. 2012, 104, 1336-1347.
17. Jin, X.L.; Diao, W.Y.; Xiao, C.H.; Wang, F.Y.; Chen, B.; Wang, K.R.; Li, S.K. Estimation of wheat agronomic parameters using new spectral indices. PLoS ONE 2013, 8, doi:10.1371/journal.pone.0072736.
18. Haboudane, D.; Miller, J.R.; Pattey, E.; Zarco-Tejada, P.J.; Strachan, I.B. Hyper-spectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture. Remote Sens. Environ. 2004, 90, 337-352.
19. Liu, J.; Pattey, E.; Shang, J.; Admira, S.; Jégo, G.; McNairn, H.; Smith, A.; Hu, B.; Zhang, F.; Freementle, J. Quantifying crop biomass accumulation using multi-temporal optical remote sensing observations. In Proceedings of the 30th Canadian Symposium on Remote Sensing, Lethbridge, AB, Canada, 22-25 June 2009.
20. Vina, A.; Gitelson, A.A.; Nguy-Robertson, A.L.; Peng, Y. Comparison of different vegetation indices for the remote assessment of green leaf area index of crops. Remote Sens. Environ. 2011, 115, 3468-3478.
21. Ramoelo, A.; Skidmore, A.K.; Cho, M.A.; Schlerf, M.; Mathieu, R.; Heitkönig, I.M.A. Regional estimation of savanna grass nitrogen using the red-edge band of the spaceborne RapidEye sensor. Int. J. Appl. Earth Obs. 2012, 19, 151-162.
22. Tang, S.; Chen, J.M.; Zhu, Q.; Li, X.; Chen, M.; Sun, R.; Zhou, Y.; Deng, F.; Xie, D. LAI inversion algorithm based on directional reflectance kernels. J. Environ. Manage. 2007, 85, 638-648.
23. Ulaby, F.; Moore, R.; Fung, A. Microwave Remote Sensing: From Theory to Applications; Artech House Publishers: Norwood, MA, USA, 1986.
24. Gao, S.; Niu, Z.; Huang, N.; Hou, X.H. Estimating the leaf area index, height and biomass of maize using HJ-1 and RADARSAT-2. Int. J. Appl. Earth Obs. 2013, 24, 1-8.
25. eoPortal Directory. Satellite Missions Database. Available online: https://directory.eoportal.org/web/eoportal/satellite-missions (accessed on 21 August 2015).
26. Global Monitoring for Environment and Security (GMES)-Observing the Earth. Synthetic Aperture Radar Missions. Available online: http://www.esa.int/Our_Activities/Observing_the_Earth/GMES/SAR_missions (accessed on 21 August 2015).
27. Capodici, F.; D'Urso, G.; Maltese, A. Investigating the Relationship between X-Band SAR Data from COSMO-SkyMed Satellite and NDVI for LAI Detection. Remote Sens. 2013, 5, 1389-1404.
28. Cutler, M.E.J.; Boyd, D.S.; Foody, G.M.; Vetrivel, A. Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions. ISPRS J. Photogramm. Remote Sens. 2012, 70, 66-77.
29. Imhoff, M.L. Radar backscatter and biomass saturation: Ramifications for global biomass inventory. IEEE Trans. Geosci. Remote Sens. 1995, 33, 511-518.
30. Lu, D. The potential and challenge of remote sensing-based biomass estimation. Int. J. Remote Sens. 2006, 27, 1297-1328.
31. Rauste, Y. Multi-temporal JERS SAR data in boreal forest mapping. Remote Sens. Environ. 2005, 97, 263-275.
32. Castel, T.; Guerra, F.; Caraglio, Y.; Houllier, F. Retrieval biomass of a large Venezuelan pine plantation using JERS-1 SAR data-Analysis of forest structure impact on radar signature. Remote Sens. Environ. 2002, 79, 30-41.
33. Lucas, R.M.; Cronin, N.; Lee, A.; Moghaddam, M.; Witte, C.; Tickle, P. Empirical relationships between AIRSAR backscatter and LiDAR-derived forest biomass, Queensland, Australia. Remote Sens. Environ. 2006, 100, 407-425.
34. Lucas, R.M.; Cronin, N.; Moghaddam, M.; Lee, A.; Armston, J.; Bunting, P.; Witte, C. Integration of radar and Landsat-derived foliage projected cover for woody regrowth mapping, Queensland, Australia. Remote Sens. Environ. 2006, 100, 388-406.
35. Clevers, J.G.P.W.; Vanleeuwen, H.J.C. Combined use of optical and microwave remote sensing data for crop growth monitoring. Remote Sens. Environ. 1996, 56, 42-51.
36. Manninen, T.; Smolander, H.; Voipio, P.; Stenberg, P.; Rautiainen, M.; Ahola, H. Boreal forest LAI retrieval using both optical and microwave data of ENVISAT. In Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium, Seoul, Korea, 25-29 July 2005.
37. Kar, G.; Verma, H.N.; Singh, R. Effect of winter crop and supplementary irrigation on crop yield, water use efficiency and profitability in rainfed rice based on cropping system of eastern India. Agr. Water Manage. 2006, 79, 280-292.
38. Dettwiler, M. Radarsat-2 Product Format Definition; Macdonald, Dettwiler and Associates Ltd.: Richmond, BC, Canada, 2008.
39. Koppe, W.; Gnyp, M.L.; Hütt, C.; Yao, Y.; Miao, Y.; Chen, X.; Bareth, G. Rice monitoring with multi-temporal and dual-polarimetric TerraSAR-X data. Int. J. Appl. Earth Obs. 2013, 21, 568-576.
40. Johnstone, I.M.; Raimondo, M. Periodic boxcar deconvolution and diophantine approximation. Ann. Stat. 2004, 32, 1781-1804.
41. Lee, J.S.; Pottier, E. Polarimetric Radar Imaging: From Basics to Applications; CRC Press: New York, NY, USA, 2009.
42. Sheng, Y.; Alsdorf, D.E. Automated georeferencing and orthorectification of Amazon basin-wide SAR mosaics using SRTM DEM data. IEEE Trans. Geosci. Remote Sens. 2005, 43, 1929-1940.
43. Gens, R.; Pottier, E.; Atwood, D.K. Geocoding of polarimetric processing results: Alternative processing strategies. Remote Sens. Lett. 2013, 4, 39-45.
44. Cloude, S.R. Polarisation: Applications in Remote Sensing; Oxford University Press: Oxford, UK, 2009.
45. Freeman, A.; Durden, S.L. A three-component scattering model for polarimetric SAR data. IEEE Trans. Geosci. Remote Sens. 1998, 36, 963-973.
46. Cloude, S.R.; Pottier, E. An entropy based classification scheme for land applications of polarimetric SAR. IEEE Trans. Geosci. Remote Sens. 1997, 35, 68-78.
47. Allain, S.; Ferro-Famil L.; Pottier, E. A polarimetric classification from POLSAR data using SERD/DERD parameters. In Proceedings of the 6th European Conference on Synthetic Aperture Radar, Dresden, Germany, 16-18 May 2006.
48. Kim, Y.; van Zyl, J.J. Comparison of forest estimation techniques using SAR data. In Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, Vancouver, BC, Canada, 24-29 July 2011; pp. 1395-1397.
49. Birth, G.S.; McVey, G. Measuring the color of growing turf with a reflectance spectroradiometer. Agron. J. 1968, 60, 640-643.
50. Rouse, J.W., Jr.; Haas, R.H.; Schell, J.A.; Deering, D.W.; Harlan, J.C. Monitoring the Vernal Advancement of Retrogradation (Green Wave Effect) of Natural Vegetation; Texas A & M University: Greenbelt, MD, USA, 1974.
51. Huete, A.R. A soil-adjusted vegetation index (SAVI). Remote Sens. Environ. 1988, 25, 295-309.
52. Rondeaux, G.; Steven, M.; Baret, F. Optimization of soil-adjusted vegetation indices. Remote Sens. Environ. 1996, 55, 95-107.
53. Liu, H.Q.; Huete, A.R. A feedback based modification of the NDVI to minimize canopy background and atmospheric noise. IEEE Trans. Geosci. Remote Sens. 1995, 33, 457-465.
54. Jin, X.L.; Wang, K.R.; Xiao, C.H.; Diao, W.Y.; Wang, F.Y.; Chen, B.; Li, S.K. Comparison of two methods for estimation of leaf total chlorophyll content using remote sensing in wheat. Field Crop. Res. 2012, 135, 24-29.
55. Jin, X.L.; Xu, X.G.; Song, X.Y.; Li, Z.H.; Wang, J.H.; Guo, W.S. Estimation of leaf water content in winter wheat using grey relational analysis-Partial least squares modeling with hyperspectral data. Agron. J. 2013, 105, 1385-1392.
56. Wang, B.S. Field-Experiment and Statistic-Method; China Agriculture Press: Beijing, China, 2002.
57. Koay, J.Y.; Tan, C.P.; Lim, K.S.; Bin Abu Bakar, S.B.; Ewe, H.T.; Chuah, H.T.; Kong, J.A. Paddy fields as electrically dense media: Theoretical modeling and measurement comparisons. IEEE Trans. Geosci. Remote Sens. 2007, 45, 2837-2849.
58. Karam, M.; Fung, A.; Lang R.; Chauhan, N. A microwave scattering model for layered vegetation. IEEE Trans. Geosci. Remote Sens. 1992, 30, 767-784.
59. Fourty, T.; Baret, F. Vegetation water and dry matter contents estimated from top-of-the-atmosphere reflectance data: A simulation. Remote Sens. Environ. 1997, 61, 34-45.