A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at mid-growing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington) of Kansas (total of 457 ha). Three basic tests were conducted on the data: (1) spatial dependence on each of the yield and vegetation indices (VIs) using Moran’s I test; (2) model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS) and spatial econometric (SPL) models; and (3) model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test) for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG) was tested positive and statistically significant for most of the fields (p < 0.05), except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02) was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to inform precision agricultural management decisions.

North America’s midcontinent forest–prairie ecotone is currently exhibiting extensive eastern redcedar (ERC) (Juniperus virginiana L.) encroachment. Rapid expansion of ERC has major impacts on the species composition and forest structure within this region and suppresses previously dominant oak (Quercus) species. In Kansas, the growing-stock volume of ERC increased by 15,000% during 1965–2010. The overarching goal of this study was to evaluate the spatio-temporal dynamics of ERC in the forest–prairie ecotone of Kansas and understand its effects on deciduous forests. This was achieved through two specific objectives: (i) characterize an effective image classification approach to map ERC expansion, and (ii) assess ERC expansion between 1986 and 2017 in three study areas within the forest–prairie ecotone of Kansas, and especially expansion into deciduous forests. The analysis was based on satellite imagery acquired by Landsat TM and OLI sensors during 1986–2017. The use of multi-seasonal layer-stacks with a Support Vector Machine (SVM)-supervised classification was found to be the most effective approach to classify ERC distribution with high accuracy. The overall accuracies for the change maps generated for the three study areas ranged between 0.95 (95 CI: ±0.02) and 0.96 (±0.03). The total ERC cover increased in excess of 6000 acres in each study area during the 30-year period. The estimated percent increase of ERC cover was 139%, 539%, and 283% for the Tuttle Creek reservoir, Perry reservoir, and Bourbon County north study areas, respectively. This astounding rate of expansion had significant impacts on the deciduous forests where the conversion of deciduous woodlands to ERC, as a percentage of the total encroachment, were 48%, 56%, and 71%, for the Tuttle Creek reservoir, Perry reservoir, and Bourbon County north study areas, respectively. These results strongly affirm that control measures should be implemented immediately to restore the threatened deciduous woodlands of the region.

Conversion of mature oak (Quercus spp.) dominated woodlands to shade-tolerant species is a well-documented problem across the eastern United States. However, oak woodland restoration within the woodland-prairie ecotone of Kansas at the western edge of the eastern deciduous forests has not been systematically studied before. Hence, an oak-dominated woodland is being used to study the effects of prescribed burning and mechanical thinning to encourage oak regeneration within this region. A repeated measures design is employed with burn and thin treatments, administered in 2015 after conducting a pretreatment stand inventory. Resampling was done after two growing seasons. Pretreatment inventory revealed oak dominance in the tree class, while competitive species such as Cercis canadensis, Ulmus americana, and Juniperus virginiana collectively dominated the seedling and sapling classes. Thinning reduced the tree density significantly, but when thinning was not followed by a burn, both total and Cercis canadensis seedling densities increased significantly. The burn treatment, on the other hand, controlled Juniperus virginiana seedlings successfully while oak regeneration increased. Hence, the most promising results were observed when thinning and burning were combined. However, control of C. canadensis seedlings remains the major challenge in the future given its vigorous recovery two growing seasons after burning.

Charles J. Barden, Stephen B. Jones, Larry E. Biles; Extension Forestry Education: Reaching the People Who Make Decisions, Journal of Forestry, Volume 94,

Sources of eastern redcedar(Juniperus virginianaL.) were established as a provenance test near Colby, Kansas, U.S. in 1980. Height, diameter, number of stems, crown density, branch angle, and general vigor were evaluated with ANOVA, cluster analysis, simple correlation, and regression analysis techniques. Clear source and cluster differences were found. Total height at 23 years ranged from 3.6 to 5.4 m (11.8 to 17.7 ft), dbh (diameter at breast height) ranged from 2.5 to 14.4 cm (1 to 5.7 in), and mean survival rate was 78%. Sources from the central plains grew best. Selection of fast-growing sources may begin at five years after field planting.