Google Earth影像辅助的农作物面积地面样方调查

地面样方调查是农作物种植面积遥感监测的重要环节,一般采用差分GPS(DGPS,differential GPS)实地测量的方式实现,是一项耗时、耗力的业务工作。该文利用经DGPS实测点校正后的Google Earth影像,以中国农业科学院(万庄)农业高新技术产业园及周边地区范围(3.1 km×2.0 km)为研究区域,探索了基于Google Earth影像辅助的农作物面积地面样方调查,比较了该方法与完全采用GPS实地测量在调查精度和效率方面的差异。针对不同的GE影像来源,文中定义基于GE客户端COM API编程下载后的影像为A级影像、经在线GE影像校正后的影像为B级影像、经DGPS实测点校正后的影像为C级影像。与实测的检查点相比,0.5 m以上空间分辨率的A级影像X、Y 2个方向中误差232.7 m,B级影像中误差5.4 m,C级影像中误差1.0 m。B级影像中误差符合《数字航空摄影测量空中三角测量规范》1:25000平地的平面位置中误差不大于8.75 m的要求,C级影像中误差符合1:10000平地的平面位置中误差不大于3.5 m的要求。在测区内选择结构组成简单、中等和较为复杂的3个样方类型,量算B和C级影像的面积量算精度,与DGPS实测面积比较,平均误差仅有0.108%和0.018%。从样方相对位置确定、地块和农田边界的修正3个方面用于地面样方的辅助测量,在业务工作中进行了初步应用,陕西省2015年冬小麦种植面积地面样方调查的实际效果表明,GE影像辅助调查比GPS实测方法在时间方面减少了64.2%,路程节约82.5%,调查效率提高了73.3%以上。

Crop area ground sample survey using Google Earth image-aided

Abstract: By using Google Earth (GE) image revised by differential global positioning system (DGPS) actual measurement points, this paper conducts a ground sample survey of crop planting areas, and compares the difference in survey accuracy and efficiency between this method and the method completely using GPS field measurement. The study area is the Agricultural High-tech Industrial Park of Chinese Academy of Agricultural Sciences (Wanzhuang) and its surrounding area with the area of 3.1 km × 2.0 km. The paper defines the data from the different GE image sources. The images downloaded based on GE Client COM API programming are defined as A-level data, the images revised by online GE images are defined as B-level data, and the images revised by DGPS actual measurement points are defined as C-level data. Compared with the checkpoints of DGPS actual measurement, A-level data of the GE images with spatial resolution of over 0.5 m have a mean square error of 232.7 m in X and Y directions, and for B-level and C-level data it is 5.4 m and 1.0 m, respectively. The B-level data meet the requirement that "The mean square error in planimetric position of 1:25000 should be no more than 8.75 m", and the C-level data meet the demand that "the mean square error in planimetric position of 1:10000 flat ground should be no more than 3.5 m", which are specified in the Digital Aerophotogrammetry Aerial Trigonometric Survey Specifications. Choosing the samples with 3 structure levels, i.e. simple, medium and complex level in the Langfang survey area, the area measurement accuracy of B-level and C-level data is measured, and the average errors are 0.108% and 0.018% respectively through the comparison with DGPS actual measurement areas. The larger the crop area, the higher the accuracy of the measurement. The survey meets the accuracy requirement of large scale ground sample survey. With respect to GE online coordinate, the average minimal mean square error of B-level data is 0.5 m, and the average maximum mean square error is 1.0 m. The average mean square error in XY direction is 0.5 m, and its relative accuracy meets the requirement of mapping specification of 1:2 000. If only the ground sample changing trend among different years is described without considering the absolute calibration accuracy, applying the B-level data GE images has a stronger charting ability. In order to evaluate ground survey efficiency based on this method, it is applied in the winter wheat ground survey of central plain area of Shaanxi Province in 2015, and the contrast test is conducted with conventional GPS field measurement method. The result of the contrast test shows that, the GE image-aided survey has reduced the time by 64.2% and the walking distance by 82.5% based on GPS measurement method. As a result, the survey efficiency is improved by 73.3%. Ground sample survey is an important link for crop area survey with remote sensing monitoring. Usually, it is achieved by using DGPS field measurement, which is a time and effort consuming job in a large scale crop area survey. The GE image-aided ground sample survey method proposed in this paper can save the time and labor. With the use of more and more available high spatial resolution satellite images and aerial survey images, this method will have a broader application prospect.