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|Type:||Artigo de Periódico|
|Title:||Using Temporal Stability To Estimate Soya Bean Yield: A Case Study In Parana State, Brazil|
|Abstract:||Crop identification is an important task in the process of yield estimation; however, sometimes it can be difficult when using images of medium to low spatial resolution due to mixing of heterogeneous areas within the pixel. Therefore, selecting pixels that best represent an area/crop could be an alternative to input data in yield estimate models. The objective of this study was to select soya bean pixels based on temporal stability technique and test the ability of these pixels to predict yield. The study was conducted at county level in Parana state, Brazil, during 11 years of soya bean growing season. To estimate yield, we created a linear regression model and used accumulated enhanced vegetation index during four periods according to soya bean phenological stages, which are as follows: emergence to maturity, emergence to flowering, flowering to grain filling, and flowering to maturity. Among all periods of the crop season, emergence to flowering showed the lowest precision while flowering to maturity was the period with the best agreements when compared with official data; the root mean square error ranged from 0.07 to 0.37 t ha(-1). The temporal stability method has proven to be an efficient tool to select pixel that could represent the crop for predicting yield. In addition, we could verify the most suitable period for making soya bean yield prediction.|
|Editor:||TAYLOR & FRANCIS LTD|
|Citation:||International Journal Of Remote Sensing. TAYLOR & FRANCIS LTD, n. 37, n. 5, p. 1223 - 1242.|
|Appears in Collections:||Unicamp - Artigos e Outros Documentos|
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