| Texto completo | |
| Autor(es): |
Cunha, Isabella A.
;
Melo, Derlei D.
;
do Amaral, Lucas R.
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | Engenharia Agrícola; v. 45, p. 14-pg., 2025-01-01. |
| Resumo | |
Obtaining reliable yield data is a challenge. Optical remote sensing (RS) can be an alternative for yield prediction. However, one of its limitations lies in its wavelength, which captures only information from the top of the crop canopy. In contrast, synthetic aperture radar (SAR) has greater interaction with plants due to its distinct wavelength. Therefore, this study aimed to investigate whether the inclusion of SAR images in a dataset composed of optical vegetation indices (VIs) derived from different acquisition principles could enhance yield prediction performance. Using yield monitor data as reference for oat and sorghum crops, we employed four optical vegetation indices (EVI, TCG, PVI, and SFDVI) from Sentinel-2 and three SAR variables (VH, VV, and DPSVI) from Sentinel-1 at the peak vegetative stage of the crops. In addition, for SAR images, we tested three different backscatter normalizations: sigma 0, beta 0, and gamma 0. Correlation analysis, principal component analysis, and machine learning techniques were applied for prediction using the Random Forest algorithm under multiple scenarios, aiming to compare predictive performance with and without SAR data inclusion. When only one vegetation index was used, the addition of SAR data contributed to yield prediction. However, when multiple optical vegetation indices were employed together, SAR data no longer added predictive power to the model. Thus, for short-stature crops such as oat and sorghum, the inclusion of SAR data does not provide predictive gains; therefore, the use of optical vegetation indices derived from different acquisition principles is sufficient for yield prediction. (AU) | |
| Processo FAPESP: | 24/14044-4 - Mapeamento pedológico detalhado e zonas de manejo: características, aplicações e complementaridade entre as abordagens |
| Beneficiário: | Derlei Dias Melo |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado |
| Processo FAPESP: | 22/03160-8 - Mapeamento da variabilidade espacial dos solos e amostragem otimizada com o apoio de técnicas de sensoriamento: bases para uma agricultura de precisão mais eficiente e sustentável |
| Beneficiário: | Lucas Rios do Amaral |
| Modalidade de apoio: | Auxílio à Pesquisa - Projeto Inicial |