Texas savanna experienced substantial woody plant encroachment during the past several decades, resulting in habitat fragmentation and species loss. A detailed map of woody plant abundance and distribution in this area is critically needed for management purpose. This study endeavors to map the fractional woody cover of Texas savanna at Landsat scale (30 m) in an affordable way. The top of atmosphere reflectance, thermal bands, and NDVI layer of Web-Enabled Landsat Data (WELD) of 2012 were used as predictors, together with mean annual precipitation. Classification and Regression Trees (CART) were calibrated against training data of a whole range of fractional woody cover, which were derived from 1-m resolution digital orthophotos of 2012. Validation indicates a reasonable pixel level accuracy of the result fractional woody cover map, with a R-squared value of 0.45. Moreover, the result map clearly depicts the distribution of woody plants across the study area, as reflected by the orthophotos. Furthermore, this new map proves an improvement over the existing Landsat Vegetation Continuous Fields (VCF) tree cover product. The method developed here, combining remote sensing and statistical techniques, can contribute to savanna management through revealing the abundance and distribution of woody plants.

The growth stage best suitable for wheat yield phenotyping has been a hot topic. This study provides a fresh insight into it, from the perspective of spectral correlation between wheat genotype replications. A number of 340 wheat genotypes and their replication were distributed in separate parts (west and east) of an experiment field (2019–2020) in Ashland, Kansas, USA. Unmanned aerial vehicle based hyperspectral images (400–100 nm) of the experiment field were taken over the late growing season, on 29 May 2020, 5 June 2020, and 12 June 2020, respectively. For each narrow spectral band, we calculated a coefficient of determination (R²) between the reflectance of genotype replications. Results suggest that R² is relatively stable within visible spectrum (450–700 nm) and within near-infrared (NIR) spectrum (770–1000 nm), though it tends to be higher for the visible bands. Moreover, while the R² of the visible bands decreases across the three dates, it increases for the near-infrared bands. These findings suggest that genetic information is better reflected in visible reflectance than in near-infrared reflectance. Among the three dates, the one when highest intra-genotype spectral correlation over visible spectrum was observed might be the best timing to discriminate yield levels of different genotypes.