Download Dripping Images
Josefina Yuzn
Pablo Xavier, a 31-year-old construction worker from the Chicago area who declined to share his last name over fears that he could be attacked for creating the images, said he was tripping on shrooms last week when he came up with the idea for the image.
In the Liquify window, under the Brush Tool Options, adjust the brush size, density and pressure to any value that you feel comfortable working with and then using the Forward Warp Tool (W) click and drag from top to bottom to make a dripping effect as shown. When you are happy with the result, click OK in the Liquify window.
For this activity, you need to select an alt text option that matches each picture. The alt text options are numbered and appear below the images. There are 4 images and 8 alt text options, so there may be more than one alt text option for each image. You only need to select one alt text option, but notice how the alt text could change the meaning or context for the image.
Water stress caused by water scarcity has a negative impact on the wine industry. Several strategies have been implemented for optimizing water application in vineyards. In this regard, midday stem water potential (SWP) and thermal infrared (TIR) imaging for crop water stress index (CWSI) have been used to assess plant water stress on a vine-by-vine basis without considering the spatial variability. Unmanned Aerial Vehicle (UAV)-borne TIR images are used to assess the canopy temperature variability within vineyards that can be related to the vine water status. Nevertheless, when aerial TIR images are captured over canopy, internal shadow canopy pixels cannot be detected, leading to mixed information that negatively impacts the relationship between CWSI and SWP. This study proposes a methodology for automatic coregistration of thermal and multispectral images (ranging between 490 and 900 nm) obtained from a UAV to remove shadow canopy pixels using a modified scale invariant feature transformation (SIFT) computer vision algorithm and Kmeans++ clustering. Our results indicate that our proposed methodology improves the relationship between CWSI and SWP when shadow canopy pixels are removed from a drip-irrigated Cabernet Sauvignon vineyard. In particular, the coefficient of determination (R) increased from 0.64 to 0.77. In addition, values of the root mean square error (RMSE) and standard error (SE) decreased from 0.2 to 0.1 MPa and 0.24 to 0.16 MPa, respectively. Finally, this study shows that the negative effect of shadow canopy pixels was higher in those vines with water stress compared with well-watered vines.