Accurate mapping of weed distribution within a field is a first step towards effective weed management. The aim of this work was to improve the mapping of milk thistle (Silybum marianum) weed patches through unmanned aerial vehicle (UAV) images using auxiliary layers of information, such as spatial texture and estimated vegetation height from the UAV digital surface model. UAV multispectral images acquired in the visible and near-infrared parts of the spectrum were used as the main source of data, together with texture that was estimated for the image bands using a local variance filter. The digital surface model was created from structure from motion algorithms using the UAV image stereopairs. From this layer, the terrain elevation was estimated using a focal minimum filter followed by a low-pass filter. The plant height was computed by subtracting the terrain elevation from the digital surface model. Three classification algorithms (maximum likelihood, minimum distance and an object-based image classifier) were used to identify S. marianum from other vegetation using various combinations of inputs: image bands, texture and plant height. The resulting weed distribution maps were evaluated for their accuracy using field-surveyed data. Both texture and plant height have helped improve the accuracy of classification of S. marianum weed, increasing the overall accuracy of classification from 70% to 87% in 2015, and from 82% to 95% in 2016. Thus, as texture is easier to compute than plant height from a digital surface model, it may be preferable to be used in future weed mapping applications.

The brown marmorated stink bug, Halyomorpha halys Stål (Hemiptera: Pentatomidae), is native to Japan, China, Taiwan, and Korea. Its dispersion from Asia to the United States of America and Europe caused serious damage to fruit, vegetables, and high-value crops. In Greece, damages are reported in kiwi orchards in the regions of Pieria and Imathia, which are the main production areas of kiwifruit. Greek kiwifruit production is expected to increase twofold within the next years. The aim of this research is to study the terrain and canopy properties that may have an impact on the development of H. halys populations. Thus, five kiwi orchards in total were selected in the regions of Pieria and Imathia. Τen traps were installed from early June to late October within each selected kiwi orchard–two types of traps at every side of the orchards and the center. The installed traps were examined weekly and the number of the captured H. halys was recorded. During the same days, sentinel satellite images were analyzed to calculate the vegetation index, NDVI (Normalised Difference Vegetation Index), and NDWI (Normalised Difference Water Index). The results showed population variability within the kiwi orchards since the population of H. halys was higher in areas with high NDVI and NDWI values. Additionally, our research revealed that H. halys prefers to develop populations at higher altitudes at both regional and field scales. The results of this research can be used to reduce damages by H. halys in kiwi orchards using different rates of pesticides depending on the prediction of the population size. There are multiple benefits of the proposed practice, such as a reduction in the production cost of kiwifruits, an increase in farmers’ profit, and environmental protection.