| Gobi is a unique landscape in arid environment.Study on morphological characteristics of gravels on Gobi surface has important significance on research of formation and evolution of Gobi and the influence of sand transportation,as well as the regional ecological protection and economic development.Currently,the study of characteristic parameters of gravels covering large area with high-precision is few.The main reason is:(1)the accuracy of ground measurement is high,but is difficult to get many samples as the efficiency limitation of manual measurement,(2)remote sensing estimation covers large area,but is difficult to acquire frequency distribution of gravel feature.With the development of the close-range photogrammetry and remote sensing technologies,it becomes more and more convenient for acquirement of digital images with wide coverage and high ground resolution.Therefore,it is of great scientific significance and application prospect to develop high-resolution image analysis method by combining with the advanced image analysis and processing technology in the field of computer information.So far,automatic method for gravel morphological characteristics calculation based on machine learning in the formation of the Gobi evolution studies haven't been seen in the report.Therefore,this study put forward an image-based,rapid and accurate measurement method for gravel morphological characteristics calculation,e.g.gravel coverage,diameter,aspect ratio and orientation,using machine learning algorithm.The accuracy of this method was verified by field measurement and manual digitization.Applicating this method,using three kind of data sources,i.e.field photographs,images near the ground collected by Unmanned Aerial Vehicle(UAV)and satellite images,has completed the research of morphology characteristics and spatial distribution of gravels on Gobi surface from air-to-ground,with pluvial fan(93° 0' 0 " E,43° 10' 0" N)at south slope of Tianshan mountain in Hami,Xinjiang as study area.The main results are as follows.(1)A rapid,accurate morphological characteristics determination method(Morphological characteristics gain effectively technique,Mc GET)of gravels on Gobi surface was developed by combining the decision tree algorithm and watershed transformation.The accuracy of morphological characteristics obtained by McGET was evaluated by compared with field measurement and manual digitization.Results of comparative analysis between McGET and field measurement show the mean gravel diameter measured by field measurement agreed well with that calculated by McGET for large gravels(y = 1.00x+ 2.74,R2 =0.89,P<0.001).Results of comparative analysis between McGET and manual digitization show the gravel coverage calculated by McGET is of very high accuracy,ranged from 92.6% to 99.9%.Unless the surface is covered by a large number of overlapped gravels,McGET can obtain accurate mean gravel size data with accuracy not lower than 69%.Mean gravel aspect ratio obtained by McGET is of high precision ranging from 88% to 99%.Unless the image contains a large number of round gravels,McGET can obtain consistent gravel orientation distribution with manual digitization.More importantly,McGET significantly shorten time cost on obtaining gravels morphological characteristics in field and laboratory.Therefore,McGET can handle a large number of samples in a short time,obtaining the accurate and diverse gravel morphological characteristics.(2)On the scales of quadrat(1m × 1m),landscape(3 ha)and regional(300 km2),the range of application of McGET are different.On the quadrat scale,McGET can get all the morphological characteristics of a single gravel,including gravel coverage,size,shape,orientation,etc.Just limited by the scope of image cover,gravels extracted on quadrat scale is around 4 mm to 256 mm,seeming more suitable for the study of Gobi surface covering fine gravels.On landscape scale,single gravel also can be extracted.Restricted by ground resolution,gravel size is above 32 mm,seeming more suitable for coarse gravel extraction.On the regional scale,only the mean value of gravel characteristics within the pixel can be calculated,which is suitable for large scale gravel size classification research through remote sensing inversion.(3)With the usage of McGET,Structure from motion(SfM)and remote sensing technology,taking images captured on the ground,high resolution images captured by UAV and remote sensing image as data source,morphology characteristics of gravel on Gobi surface were estimated on quadrat scale,landscape scale and regional scale,respectively.On the quadrat scale,the gravel coverage was with mean value of 75%;the gravel diameter was with mean value of 15 mm,unimodal and left skewed distribution;the gravel aspect ratio was mean value of 1.57.On landscape scale,from the center to the edge of the fan,the gravel coverage of three sample zones were 34.22%,26.85%,21.88%;the mean gravel diameter of three sample zones were 130,95,78 mm.On regional scale,with gravel characteristics determined from samples and the surface reflectance of 7 OLI bands as the data source,estimation model of the gravel size was built based on remote sensing data with high precision(R2 = 0.549).(4)Through synthesis analysis of gravel character determination results on quadrat scale,landscape scale and regional scale,changes of gravel characteristics with the factors such as altitude,slope,were analyzed.Then spatial variability of gravel characteristics on landscape and regional scale were obtained.On the landscape scale,along the direction of elevation change,gravel coverage spatial distribution had little relationship with elevation,but may be affected by vegetation distribution and local topography.With geomorphic unit as analysis unit,in the region near the center of the fan,gravel coverage and diameter on the flat were significantly larger than on the slope;in the region near the middle of the fan,the difference of gravel coverage and diameter on the flat or slope is not big;in the region near the edge of the fan,gravel coverage and diameter on the flat were both slightly less than on the slope.On spatial variability study of gravel characters on landscape scale,the influence of the local topography can not be ignored.On regional scale,from the center to the edge of the pluvial fan,gravel coverage and diameter on the surface of Gobi both decreased,while the aspect ratio increased slightly.Linear regression analysis showed that,as the elevation increased 100 m above sea level,gravel coverage increased at the rate of 2.2%,mean gravel diameter increased at the rate of 0.5 mm,and mean aspect ratio slightly decreased at the rate of 0.004.Along the direction of elevation change,gravel and the mean diameter decreased and dropped faster in the region of the center and edge of the fan.With the increase of horizontal distance,the rate of descent was 1.83 mm/km,0.31 mm/km and 0.15 mm/km.On the same elevation gradient,gravel diameter near the central axis of the pluvial fan axis is larger,and near both sides were smaller.In the center of the fan,the difference of gravel diameter between on the central axis or sides of the fan was biggest,which was more than 3 mm.While it was smallest in the middle of the fan,which was near 2 mm.From the center to the edge of the fan,the gravel coverage and diameter on the flat dropped from fast to slowly,while on the slope dropped relative gradually.On the regional scale,the spatial variability of gravel diameter was greatly influenced by slope from macrorelief. |
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