Radarsat backscattering from an agricultural scene

Abstract

Orbital remote sensing in the microwave electromagnetic region has been presented as an important tool for agriculture monitoring. The satellite systems in operation have almost all-weather capability and high spatial resolution, which are features appropriated for agriculture. However, for full exploration of these data, an understanding of the relationships between the characteristics of each system and agricultural targets is necessary. This paper describes the behavior of backscattering coefficient (sigma°) derived from calibrated data of Radarsat images from an agricultural area. It is shown that in a dispersion diagram of sigma° there are three main regions in which most of the fields can be classified. The first one is characterized by low backscattering values, with pastures and bare soils; the second one has intermediate backscattering coefficients and comprises well grown crops mainly; and a third one, with high backscattering coefficients, in which there are fields with strong structures causing a kind of double bounce effect. The results of this research indicate that the use of Radarsat images is optimized when a multitemporal analysis is done making the best use of the agricultural calendar and of the dynamics of different cultures.

Discrimination of agricultural crops in a tropical semi-arid region of Brazil based on L-band polarimetric airborne SAR data

“…1c illustrates the planting rows in concentric circles with their relative parallel (A) and perpendicular (B) coffee crop row orientation in relation to the sensor lookdirection. Since planting row direction is an important factor that influences the backscatter of the agricultural crops (Paris, 1983;Brisco et al, 1991;Formaggio et al, 2001) the coffee crop was separated in two classes: Coffee-II (parallel coffee; A in Fig. 1c), and Coffee-⊥ (perpendicular coffee; B in Fig.…”

“…Based on the land use reference map (Fig. 1b) the two cotton fields in this sub-area were separated in Cotton-1 (more developed) and Cotton-2 (less developed) due to the fact that microwave interaction is sensitive to geometric and structural aspects of crops (Brisco and Brown, 1998;Formaggio et al, 2001).…”

Simulated multipolarized MAPSAR images to distinguish agricultural crops

“…Coffee cultivation under central pivot irrigation is a common practice in this area and for this reason planting rows were arranged in concentric circles. Planting row direction, relative to the sensor look direction, is an important factor influencing backscatter in agricultural crops (Brisco et al, 1991;Formaggio et al, 2001;McNairn and Brisco, 2004). For this reason, the circular coffee fields were divided into two classes: Coffee-|| (Parallel Coffee, A in Figure 2b) and Coffee-⊥ (Perpendicular Coffee, B in Figure 2b).…”

“…Various researchers have demonstrated the potential of SAR images for agricultural applications, with the best results obtained using multipolarized images (Formaggio et al, 2001;McNairn and Brisco, 2004;Stankiewicz, 2006;Silva et al, 2009;Ulaby et al, 1980). However, there is a lack of studies on the use of SAR considering the management characteristics and crops typically cultivated under Brazilian conditions.…”

Full issue in PDF / Numéro complet en form PDF

“…Although it is possible to acquire two simultaneous polarizations in the fine beam selective dual polarization (SDP) mode (Formaggio et al, 2001), this data is available only at 8 m resolution. Although it is possible to acquire two simultaneous polarizations in the fine beam selective dual polarization (SDP) mode (Formaggio et al, 2001), this data is available only at 8 m resolution.…”