Rapid Compaction Monitoring and Quality Control of Embankment Dam Construction Based on UAV Photogrammetry Technology: A Case Study

The compaction quality of embankment dams directly affects the safe operation of power stations. The traditional monitoring method has the shortcomings of limited sample and time consumption. Compaction quality can be reflected by the compression ratio (CR) of the filling material. A novel method based on unmanned aerial vehicle (UAV) photogrammetry technology, which can rapidly acquire the CR of the entire filling area, is proposed in the present paper. Specifically, the CR nephogram is obtained by processing the terra information of the compaction body collected by the UAV. Validation of the CR results is performed by comparing them with the results obtained via leveling measurements. Mean absolute error between CR results and leveling measurements results is less than 1%, and the corresponding settlement value error is millimeter-level, reflecting a fairly good agreement. Furthermore, the reduced-scale experiment shows that the UAV-based CR method is more stable than manual measurements, and the efficiency is increased by more than five times, which meets the requirements of compaction quality monitoring and quality control. The CR nephogram obtained can reflect the compaction quality information rapidly, comprehensively, and accurately, thereby guiding the quality control of embankment dam construction

Evolution and Climate Drivers of NDVI of Natural Vegetation during the Growing Season in the Arid Region of Northwest China

Vegetation plays an important role in linking water, atmosphere, and soil. The dynamic change in vegetation is an important indicator for the regulation of the terrestrial carbon balance and climate change. This study applied trend analysis, detrended correlation analysis, and the Hierarchical Partitioning Algorithm (HPA) to GIMMS NDVI3g data, meteorological data, and natural vegetation types for the period 1983 to 2015 to analyze the temporal and spatial changes in NDVI during the growing season and its driving factors in the arid region of northwestern China. The results showed that: (1) the growing season length (GSL) was delayed, with a regional trend of 8 d/33 a, due to a significant advancement in the start of the growing season (SOS, −7 d/33 a) and an insignificant delay to the end of growing season (EOS, 2 d/33 a). (2) The regional change in NDVI was mainly driven by temperature and precipitation, contributing to variations in NDVI of forest of 36% and 15%, respectively, and in the NDVI of grassland, of 35% and 21%, respectively. In particular, changes to forested land and medium-coverage grassland (Mgra) were closely related to temperature and precipitation, respectively. (3) The spatial distribution of the mean NDVI of forest was closely related with precipitation, temperature, and solar radiation, with these meteorological variables explaining 20%, 15%, and 10% of the variation in NDVI, respectively. Precipitation and solar radiation explained 29% and 17% of the variation in the NDVI of grassland, respectively. The study reveals the spatial–temporal evolution and driving mechanism of the NDVI of natural vegetation in the arid region of Northwest China, which can provide theoretical and data support for regional vegetation restoration and conservation

Additional file 1: of Microdissection of the Ah01 chromosome in upland cotton and microcloning of resistance gene anologs from the single chromosome

The nucleotide sequences of three newly identified RGA genes. (TXT 1 kb