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In viticulture, downy mildew is one of the most common diseases that, if not adequately treated, can diminish production yield. However, the uncontrolled use of pesticides to alleviate its occurrence can pose significant risks for farmers, consumers, and the environment. This paper presents a new framework for the early detection and estimation of the mildew's appearance in viticulture fields. The framework utilizes a protocol for the real-time acquisition of drones' high-resolution RGB images and a cloud-docker-based video or image inference process using object detection CNN models. The authors implemented their framework proposition using open-source tools and experimented with their proposed implementation on the debina grape variety in Zitsa, Greece, during downy mildew outbursts. The authors present evaluation results of deep learning Faster R-CNN object detection models trained on their downy mildew annotated dataset, using the different object classifiers of VGG16, ViTDet, MobileNetV3, EfficientNet, SqueezeNet, and ResNet. The authors compare Faster R-CNN and YOLO object detectors in terms of accuracy and speed. From their experimentation, the embedded device model ViTDet showed the worst accuracy results compared to the fast inferences of YOLOv8, while MobileNetV3 significantly outperformed YOLOv8 in terms of both accuracy and speed. Regarding cloud inferences, large ResNet models performed well in terms of accuracy, while YOLOv5 faster inferences presented significant object classification losses. [ABSTRACT FROM AUTHOR]

Geological heritage or geoheritage is of at least equal significance to - and sometimes also interwoven with - cultural heritage. Hence, it holds the potential of scientific, educational, cultural, aesthetic, and touristic value. Nevertheless, geoheritage has not attracted the same level of attention as cultural heritage to date, especially regarding its sustainable management and suitable conservation strategies. Yet actions and measures are mandatory to preserve and highlight geological heritage and to reduce threats that may cause its deterioration or even extinction. To this end, geospatial science and technology provide the means for documenting and dealing with geological heritage throughout the individual steps of the geoheritage management process. In this study, we present a holistic approach to geoheritage management at the national level for Greece, based on the implementation of a Geographical Information Systems (GIS) database that also enables the coupling of geoheritage with a plethora of readily available geospatial information from remote sensing and other sources. The results demonstrate that an appropriate, geospatial record of geological heritage can have a crucial contribution to geoheritage management from its identification, to its monitoring, protection, and exploitation for educational, scientific, recreational, and other purposes. [ABSTRACT FROM AUTHOR]