English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Significant efforts have been made recently in the application of high-resolution remote sensing imagery (i.e., sub-meter) captured by unmanned aerial vehicles (UAVs) for precision agricultural applications for high-value crops such as wine grapes. However, at such high resolution, shadows will appear in the optical imagery effectively reducing the reflectance and emission signal received by imaging sensors. To date, research that evaluates procedures to identify the occurrence of shadows in imagery produced by UAVs is limited. In this study, the performance of four different shadow detection methods used in satellite imagery was evaluated for high-resolution UAV imagery collected over a California vineyard during the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) field campaigns. The performance of the shadow detection methods was compared and impacts of shadowed areas on the normalized difference vegetation index (NDVI) and estimated evapotranspiration (ET) using the Two-Source Energy Balance (TSEB) model are presented. The results indicated that two of the shadow detection methods, the supervised classification and index-based methods, had better performance than two other methods. Furthermore, assessment of shadowed pixels in the vine canopy led to significant differences in the calculated NDVI and ET in areas affected by shadows in the high-resolution imagery. Shadows are shown to have the greatest impact on modeled soil heat flux, while net radiation and sensible heat flux are less affected. Shadows also have an impact on the modeled Bowen ratio (ratio of sensible to latent heat) which can be used as an indicator of vine stress level.

irrigation science

Assessment of different methods for shadow detection in high-resolution optical imagery and evaluation of shadow impact on calculation of NDVI, and evapotranspiration