A sampling system for estimating the cultivation of wheat (Triticum aestivum L) from LANDSAT data

Using digitally processed MSS/LANDSAT data as auxiliary variable, a methodology to estimate wheat (Triticum aestivum L) area by means of sampling techniques was developed. To perform this research, aerial photographs covering 720 sq km in Cruz Alta test site at the NW of Rio Grande do Sul State, were visually analyzed. LANDSAT digital data were analyzed using non-supervised and supervised classification algorithms; as post-processing the classification was submitted to spatial filtering. To estimate wheat area, the regression estimation method was applied and different sample sizes and various sampling units (10, 20, 30, 40 and 60 sq km) were tested. Based on the four decision criteria established for this research, it was concluded that: (1) as the size of sampling units decreased the percentage of sampled area required to obtain similar estimation performance also decreased; (2) the lowest percentage of the area sampled for wheat estimation with relatively high precision and accuracy through regression estimation was 90% using 10 sq km s the sampling unit; and (3) wheat area estimation by direct expansion (using only aerial photographs) was less precise and accurate when compared to those obtained by means of regression estimation.