Leaf area is a component of crop growth and yield prediction models. Few studies have used the structure from motion (SfM) algorithm, which is based on the principles of traditional stereophotogrammetry, to obtain the leaf area index (LAI). Thus, the objective of this study was to follow the evolution of the LAI and percentage of land cover (%COV) in coffee plants, using pre-established equations and plant measurements obtained from generated 3D point clouds, combined with the application of the SfM algorithm to digital images recorded by a camera coupled to a UAV (unmanned aerial vehicle). The experiment was conducted in a coffee plantation located in southeastern Brazil. A rotary wing UAV containing a conventional camera was used. The images were collected once pera month, for 12 months. Image processing was performed using PhotoScan software. Regression analysis and spatial analysis were performed using R and GeoDa software, respectively. The resulting %COV data had R2 and RMSE values of 89% and 3.41, respectively, while those for LAI had R2 and RMSE of 88% and 0.47, respectively. Significant %COV results were obtained in the months of January, February and March of 2018. There was significant autocorrelation for the LAI values from January to May 2018, with most blocks in the central and center-west regions presenting LAI values > 3.0. It was possible to monitor the temporal and spatial behavior of the LAI and %COV, allowing for the conclusion that this methodology generated results that are consistent with the literature.

Precise estimation of local head loss ($hl$ ) remains a challenge for the hydraulic design of drip irrigation. This study develops a robust protocol for estimating the emitter $hl$ based on the Borda-Carnot principle. The method requires cross-sectional flow area measurements with and without emitter obstruction and a contraction coefficient, which is determined by the empirical relationship of the obstruction ratio. For comparison purposes, cross-sectional flow areas were also measured with a profile projector, which resulted in absolute deviations lower than 2.6%. Observed and predicted single-emitter $hl$ deviation values were consistent with previous studies; the three examined emitting pipe types had deviation values of $-6.67\%$ , 21.6%, and 1.07%. Thus, the proposed methodology for estimating the cross-sectional area can be applied without compromising $hl$ estimates using a single flat inline emitter operated by the proposed semiempirical model.