Temporal Polarimetric Behavior of Oilseed Rape (Brassica napus L.) at C-Band for Early Season Sowing Date Monitoring

Abstract

Spatial monitoring of the sowing date plays an important role in crop yield estimation at the regional scale. The feasibility of using polarimetric synthetic aperture radar (SAR) data for early season monitoring of the sowing dates of oilseed rape (Brassica napus L.) fields is explored in this paper. Polarimetric SAR responses of six parameters, relying on polarization decomposition methods, were investigated as a function of days after sowing (DAS) during the entire growing season, by means of five consecutive Radarsat-2 images. A near-continuous temporal evolution of these parameters was observed, based on 88 oilseed rape fields. It provided a solid basis for determining the suitable temporal window and the best polarimetric parameters for sowing date monitoring. A high sensitivity of all polarimetric parameters to the DAS at different growing stages was shown. Simple linear models could be calibrated to estimate sowing dates at early growth OPEN ACCESS

Combined Analysis of Sentinel-1 and Rapideye Data for Improved Crop Type Classification: An Early Season Approach for Rapeseed and Cereals

“…Discrimination of cereals and rapeseed worked well and was most likely due to their different plant structure, with cereals being more vertically orientated and thin-leafed and rapeseed being more horizontally orientated and broader leafed. This leads to different backscatter patterns in VV and VH respectively and a higher possibility for separation of these classes (Mcnairn et al, 2002;Yang et al, 2014). Interesting are the results achieved for grassland, which were not expected, as the classification of grassland performed better in another study.…”

Compact Polarimetric Response of Rape (Brassica napus L.) at C-Band: Analysis and Growth Parameters Inversion

“…The number of input variables per node (mtry in R) was tested from 1/3 to the whole number of CP parameters, and then, the mtry values yielding the lowest RMSE were selected. Meanwhile, in this study, SAR observations at P1 contained little vegetation information, and at P5, as the crop entered into the productive and harvest stage, which seemed to be too late for farm practice, also showed fluctuated values for most of the CP parameters; as a result, only P2, P3 and P4 were stable and selected for the inversion of growth parameters [27].…”

“…The filtered C3 matrix was ortho-rectified using Mapready software with 30-m ASTER GDEM into the Universal Transverse Mercator (UTM) map projection. For more details about this SAR data processing procedure, the reader is referred to our previous work [27]. …”

“…Forty-four parcels among the 101 rape fields in the Remote Sens. 2017, 9, 591 5 of 22 test site were provided with sowing dates by a local farmer or a farmland manager; sowing dates of the left were calculated by the method proposed in the paper [27]. All of the sowing periods of the test site lasted from 8 May-31 May.…”

“…Their change trends were also compared with the objective to find the sensitive CP parameters for growth parameters and to analyze the scattering mechanisms of rape at different growth stages. At each principal scale, DAS of rape fields were calculated with the methods proposed in [27]; CP observables were averaged from rape fields with the same DAS. Growth parameters like LAI, stem height and biomass and related DAS were surveyed in each campaign with 11-14 representative rape fields.…”