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Landslides, collapses and cracks are the main types of geological hazards, which threaten the safety of human life and property at all times. In emergency surveying and mapping, it is time-consuming and laborious to use the method of field artificial investigation and recognition and using satellite image to identify ground hazards, there are some problems, such as time lag, low resolution, and difficult to select the map on demand. In this paper, a 10 cm per pixel resolution photogrammetry of a geological hazard -prone area of Taohuagou, Shanxi Province, China is carried out by DJ 4 UAV. The digital orthophoto model (DOM), digital surface model (DSM) and three-dimensional point cloud model (3 DPCM) are generated in this region. The method of visual interpretation of cracks based on DOM (as main) -3DPCM (as auxiliary) and landslide and collapse based on 3DPCM (as main) - DOM and DSM (as auxiliary) are proposed. Based on the low altitude remote sensing image of UAV, the hape characteristics, geological characteristics and distribution of the identified hazards are analyzed.The results show that using UAV low altitude remote sensing image, the method of combination of main and auxiliary data can quickly and accurately identify landslide, collapse and crack, the accuracy of crack identification is 93％, and the accuracy of landslide and collapse identification is 100％. It mainly occurs in silty clay and mudstone geology and is greatly affected by slope foot excavation. This study can play a great role in the recognition of sudden hazards by low altitude remote sensing images of UAV.