Automatic recognition of desert plant types by machine vision can support the research on wind prevention and sand fixation, ecosystem value assessment, vegetation restoration and reconstruction, and reduce the dependence on plant expert identification. At present, the research on the machine discrimination model of desert plants mainly relies on the standardized high-quality plant specimen images, lacking the desert plant images obtained under complex natural conditions. This dataset provides typical desert plant images of Xinjiang that can be used for the model training of deep learning image classification, including 15,550 digital camera images of desert plants in Xinjiang obtained under different seasons, natural backgrounds and lighting conditions, and covering 19 typical desert plant types. Suaeda salsa has the smallest number of images and Artemisia desertorum has the biggest, 465 and 1,240 respectively, with a median of 800, which has met the training needs of mainstream deep learning model. This dataset can provide basic data for desert plant image segmentation, target detection and automatic recognition.

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This dataset is a collection of UAV visible light images of Tianshan spruces (superior mountain forest tree species in Xinjiang) for deep learning training. Tianshan spruces are the most important conifer species in ecological function in Tianshan region, Xinjiang. It is particularly important to effectively identify and divide Tianshan spruce forest through remote sensing technology, which provides important support for collecting the information of Tianshan spruce single factors. In this study, combining with mountain terrain and environmental factors, we developed a UAV field operation plan to collect visible light remote sensing image data of Nanshan Practice Forest Farm of Xinjiang Agricultural University, which were spliced into orthophographic projective images after data filtering, geometric correction and ortho correction and other pre-processing methods. We then adopted Labelme software to plot and classify Tianshan spruces and obtained a dataset of 1,128 UAV visible light images of Tianshan spruces for deep learning training in 2017.