Large-scale deformation monitoring in mining area by D-InSAR and 3D laser scanning technology integration

Large-scale deformation can not be detected by traditional D-InSAR technique because of the limit of its detectable deformation gradient,we propose a method that combines SAR data with point cloud data obtained by 3D laser scanning to improve the gradient of deformation detection.The proposed method takes advantage of high-density of 3D laser scanning point cloud data and its high precision of point positioning after 3D modeling.The specifc process can be described as follows:frst,large-scale deformation points in the interferogram are masked out based on interferometric coherence;second,the interferogram with holes is unwrapped to obtain a deformation map with holes,and last,the holes in the deformation map are flled with point cloud data using inverse distance weighting algorithm,which will achieve seamless connection of monitoring region.We took the embankment dam above working face of a certain mining area in Shandong province as an example to study large-scale deformation in mining area using the proposed method.The results show that the maximum absolute error is 64 mm,relative error of maximum subsidence value is 4.95%,and they are consistent with leveling data of ground observation stations,which confrms the feasibility of this method.The method we presented provides new ways and means for achieving large-scale deformation monitoring by D-InSAR in mining area.

DEVELOPMENT OF AN AUTOMATIC WEIGHING PLATFORM FOR MONITORING BODYWEIGHT OF BROILER CHICKENS IN COMMERCIAL PRODUCTION

Bodyweight is a key indicator of broiler production as it measures the production efficiency and indicates the health of a flock.Currently,broiler weight(i.e.,bodyweight)is primarily weighed manually,which is timeconsuming and labor-intensive,and tends to create stress in birds.This study aimed to develop an automatic and stress-free weighing platform for monitoring the weight of floor-reared broiler chickens in commercial production.The developed system consists of a weighing platform,a real-time communication terminal,computer software and a smart phone applet userinterface.The system collected weight data of chickens on the weighing platform at intervals of 6 s,followed by filtering of outliers and repeating readings.The performance and stability of this system was systematically evaluated under commercial production conditions.With the adoption of data preprocessing protocol,the average error of the new automatic weighing system was only 10.3 g,with an average accuracy 99.5%with the standard deviation of 2.3%.Further regression analysis showed a strong agreement between estimated weight and the standard weight obtained by the established live-bird sales system.The variance(an indicator of flock uniformity)of broiler weight estimated using automatic weighing platforms was in accordance with the standard weight.The weighing system demonstrated superior stability for different growth stages,rearing seasons,growth rate types(medium-and slow-growing chickens)and sexes.The system is applicable for daily weight monitoring in floor-reared broiler houses to improve feeding management,growth monitoring and finishing day prediction.Its application in commercial farms would improve the sustainability of poultry industry.