基于地块形态特征的农田作物行向识别方法验证  

Verification of Farmland Crop Row Direction Recognition Method based on Plot Morphological Characteristics

作　　者：曲福恒[1] 丁天雨 郑兴明[2,3] 马晶 王楷文 Fuheng QU;DINGTianyu;Xingming ZHENG;Jing MA;Kaiwen WANG(College of Computer Science and Technology,Changchun University of Science and Technology,Changchun 130022,China;Northeast Institute of Geography and Agroecology,Chinese Academy of Sciences,Changchun 130102,China;Changchun Jingyuetan Remote Sensing Test Site,Chinese Academy of Sciences,Changchun 130102,China)

机构地区：[1]长春理工大学计算机科学技术学院,吉林长春130022 [2]中国科学院东北地理与农业生态研究所,吉林长春130102 [3]中国科学院长春净月潭遥感实验站,吉林长春130102

出　　处：《遥感技术与应用》2024年第5期1213-1222,共10页Remote Sensing Technology and Application

基　　金：黑土地保护与利用科技创新工程专项资助项目(XDA28100500);国家自然科学基金面上项目(42371381、42201435);国家民用基础设施陆地观测卫星共性支撑平台(CASPLOS-CCSI)。

摘　　要：作物行结构作为耕地表面的典型周期性结构特征,其方向会对测量雷达后向散射系数和光学反射率的结果造成显著影响。针对高分辨遥感影像纹理特征提取作物行向时效率低、计算资源需求大导致难以应用于大区域的问题,以黑龙江省友谊县为研究区,将地块作为最小研究对象,验证利用地块形态特征识别作物行向的可行性。本研究利用多种图像处理算法计算地块长边与短边的长度比值(长宽比),分析作物行向和地块长边方向之间的相关性,对比不同地块长宽比对作物行向识别率和识别精度的影响。结果表明:随着地块长宽比阈值增加,行向的识别率从82.0%降低到34.8%,行向识别均方根误差(Root Mean Square Error,RMSE)从21.46°降低至1.78°;在不同长宽比阈值条件下,直线检测器算法识别作物行向的平均精度(R^(2)=0.93,RMSE=9.53°)高于概率霍夫变换(R^(2)=0.81,RMSE=20.80°)。该方法可以实现对大范围农田地块作物行向的识别,为遥感卫星影像识别作物行方向提供新的思路。The row structure of crops as a typical periodic feature of the cultivated land surface,and its direction will can significantly affect the results of radar backscatter coefficients and optical reflectivity.The key problem of low extraction efficiency and large demand for computational resources when using the texture features of high-resolution remote sensing images to extract crop row direction,it is difficult to be applied on a large scale.In this paper,the feasibility of using the morphological characteristics of the plot to identify the row direction of crops was verified with the premise that the plot was the minimum research object,based on the YouYi County of Heilongjiang Province as the research area.The algorithm uses a variety of images processing algorithms to calculate the length ratio(aspect ratio)between the long side and the short side of the plot,analyzes the relationships between the row direction of the crop and the direction of the long side and the influence of the aspect ratio of different plots on the recognition rate and accuracy.The results show that:With the increase of plot aspect ratio threshold,the recognition rate of row direction decreased from 82.0%to 34.8%,and the Root Mean Square Error(RMSE)of row direction recognition decreased from 21.46°to 1.78°;Under different aspect ratio thresholds,the average accuracy of Line Segment Detector(LSD)algorithm in identifying crop row direction(determination coefficient R²=0.93,RMSE=9.53°)is higher than that of probabilistic Hough transform(R²=0.81,RMSE=20.80°);The approach proposed in this paper can effectively achieve the identification of crop row direction in a large range of farmland plots,which provide a new idea for the research of remote sensing satellite images in identifying crop row direction.

关 键 词：光学遥感 作物行向 直线检测 长宽比 农田 

分 类 号：S127[农业科学—农业基础科学]