Regional crop monitoring and discrimination based on simulated ENVISAT ASAR wide swath mode images

The current paper investigates the potential contribution of ENVISAT wide swath (WS) images for discrimination and monitoring of crops at a regional scale. The study was based on synthetic aperture radar (SAR) images acquired throughout an entire growing season. Advanced synthetic aperture radar sensor (ASAR) images in both narrow swath (NS) and WS modes were simulated based on 15 European Remote Sensing (ERS) satellite images recorded over Belgium. Unlike ‘real’ ASAR imagery, this exercise provided a consistent data set (i.e. same incidence angle, same acquisition date, same acquisition hour) to study the impact of spatial resolution on the SAR signal information content. A quantitative approach using 787 parcels of medium field size and various data combinations assessed monitoring and discrimination capabilities for six crop types: wheat, barley, grasses, sugar beet, maize and potato. The spatial resolution impact of the ASAR sensor was discussed with respect to the field size by comparing the results obtained from NS (30 m) and WS (150 m) mode images. WS temporal profiles were able to discriminate the various crops of interest and were representative of the crop development observed in the region. Furthermore, parcel‐based unsupervised classifications successfully discriminated between grass, wheat, barley and other crops of large parcels (success rate of 83%). Dedicated interpretation schemes were developed in order to discriminate between cereal crops.

[1]  D. Legates,et al.  Crop identification using harmonic analysis of time-series AVHRR NDVI data , 2002 .

[2]  Pierre-Louis Frison,et al.  Use of ERS-1 wind scatterometer data over land surfaces , 1996, IEEE Trans. Geosci. Remote. Sens..

[4]  Maurice Borgeaud,et al.  A study of vegetation cover effects on ERS scatterometer data , 1999, IEEE Trans. Geosci. Remote. Sens..

[5]  D. Stevens,et al.  A processing algorithm for the ENVISAT alternating polarization mode single look complex product , 1997, IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development.

[6]  S. Quegan,et al.  RELATING ERS SCATTEROMETER DATA TO GLOBAL VEGETATION MODELS , 2000 .

[7]  Sushma Panigrahy,et al.  A processing and software system for rice crop inventory using multi-date RADARSAT ScanSAR data , 2000 .

[8]  P. Mather,et al.  Crop discrimination using multi-temporal SAR imagery , 1999 .

[9]  C.C. Schmullius,et al.  Monitoring Siberian forests and agriculture with the ERS-1 Windscatterometer , 1997, IEEE Trans. Geosci. Remote. Sens..

[10]  Claudio Prati,et al.  ScanSAR focusing and interferometry , 1996, IEEE Trans. Geosci. Remote. Sens..

[11]  Sushma Panigrahy,et al.  Evaluation of RADARSAT Standard Beam data for identification of potato and rice crops in India , 1999 .

[12]  C. Vignolles,et al.  A methodology for a combined use of normalised difference vegetation index and CORINE land cover data for crop yield monitoring and forecasting. A case study on Spain , 2001 .

[13]  D. Michelson.  Comparison of Algorithms for Classifying Swedish Landcover Using Landsat TM and ERS-1 SAR Data , 2000 .

[14]  James H. Lambert,et al.  A Methodology for , 2000 .

[15]  D. Capstick,et al.  The effects of speckle reduction on classification of ERS SAR data , 2001 .

[17]  Dirk H. Hoekman,et al.  Determining land-surface parameters from the ERS wind scatterometer , 2000, IEEE Trans. Geosci. Remote. Sens..

[18]  Yifang Ban,et al.  Orbital effects on ERS-1 SAR temporal backscatter profiles of agricultural crops , 1997 .

[19]  F. Kogan,et al.  Drought Monitoring and Corn Yield Estimation in Southern Africa from AVHRR Data , 1998 .

[20]  Yifang Ban,et al.  Multitemporal ERS-1 SAR data for crop classification : A sequential-masking approach , 1999 .

[21]  U. Wegmuller,et al.  Radiometric calibration of airborne SAR imagery , 1994, Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium.

[22]  S. Le Hegarat-Mascle,et al.  Land cover discrimination from multitemporal ERS images and multispectral Landsat images: A study case in an agricultural area in France , 2000 .

[23]  A. Lopes,et al.  Preliminary analysis of ERS-1 wind scatterometer data over land surfaces , 1995 .

[24]  Eric Mougin,et al.  Monitoring global vegetation dynamics with ERS-1 wind scatterometer data , 1996 .

[25]  Maurice Borgeaud,et al.  Interpreting ERS SAR signatures of agricultural crops in Flevoland, 1993-1996 , 2000, IEEE Trans. Geosci. Remote. Sens..

[26]  C. G. J. Schotten,et al.  Assessment of the capabilities of multi-temporal ERS-1 SAR data to discriminate between agricultural crops , 1995 .

[27]  Xavier Blaes,et al.  Retrieving crop parameters based on tandem ERS 1/2 interferometric coherence images , 2003 .

[28]  Julius T. Tou,et al.  Pattern Recognition Principles , 1974 .