CAJ | 학술논문

农田测绘与粮食安全密切相关，高效经济的农田测绘是中国政府部门重点关注的工作之一。农田田块是农田测绘的基本要素，从遥感影像中提取农田田块信息是当前研究的热点。然而，丘陵地区农田形状不规则、光谱特征不明显导致农田信息提取困难，该文通过研究最优的农田分割尺度来提高农田田块信息提取的精度。首先，利用各向异性扩散算子在由Sobel得到的梯度图上生成多尺度梯度影像。然后，通过信息熵差异分析得到有效尺度范围。其次，利用标记分水岭算法对农田梯度影像进行分割获得多尺度农田信息。最后，利用非监督的全局评价方法在已得的有效尺度范围内确定农田提取的最优尺度，同时确定最优的农田提取结果。对比试验结果表明，该文方法能够有效地提取丘陵地区的农田田块，精度可以达到73.06%，比Mean-shift方法提取的精度高22.48%。该研究可为中国农田测绘提供技术参考。
농전측회여양식안전밀절상관，고효경제적농전측회시중국정부부문중점관주적공작지일。농전전괴시농전측회적기본요소，종요감영상중제취농전전괴신식시당전연구적열점。연이，구릉지구농전형상불규칙、광보특정불명현도치농전신식제취곤난，해문통과연구최우적농전분할척도래제고농전전괴신식제취적정도。수선，이용각향이성확산산자재유Sobel득도적제도도상생성다척도제도영상。연후，통과신식적차이분석득도유효척도범위。기차，이용표기분수령산법대농전제도영상진행분할획득다척도농전신식。최후，이용비감독적전국평개방법재이득적유효척도범위내학정농전제취적최우척도，동시학정최우적농전제취결과。대비시험결과표명，해문방법능구유효지제취구릉지구적농전전괴，정도가이체도73.06%，비Mean-shift방법제취적정도고22.48%。해연구가위중국농전측회제공기술삼고。
The growing population and accelerating urbanization have caused much illegal occupation of farmland, which seriously threat to national food security, social stability and economic development of our country. Farmland information extraction has become a hot issue in agricultural research field in the world. In addition, farmland mapping is closely related to the food security and is one of the most concerned issues of government departments. However, traditional technology of surveying and mapping is time consuming and labor costing, which is unable to adapt to the precise and effective information acquisition of farmland. The high resolution remote sensing imagery can provide more details of ground truth than low resolution imagery. However, the information mining in high resolution remote sensing imagery faces a big challenge caused by the complex ground environment. Farmland blocks in high resolution remote sensing imagery have various shapes, complicated texture and heterogeneous spectrum. The shape information is one of the most important content of farmland mapping. In this study, high resolution remote sensing imagery from QuickBird was used to precisely extract farmland in hilly area. And the method of farmland extraction combining multi-scale segmentation and optimal scale selection was put forward. Firstly, gradient image is generated by using Sobel gradient operator. In order to enhance the edge information and reduce the irrelevant information for farmland extraction, the multi-scale gradient images are filtered with anisotropic diffusion operator. Secondly, effective scale range of multi-scale gradient images is determined through the entropy difference analysis, which can reduce the amount of calculation of the multi-scale analysis in next stage. Thirdly, a marker driven watershed transform based on minima extension and minima imposition is applied to segment the multi-scale gradient images to produce multi-scale shape information of farmland with precious boundaries. Finally, the optimal scale identification for multi-scale segmentation is obtained by unsupervised segmentation evaluation method based on the global Moran’I and variance to automatically get the farmland block without manual intervention. The experimental results show that the multi-scale segmentation and optimal scale identification approach can be used to accurately discriminate farmland in hilly area. Farmland extraction accuracy of the proposed method is 73.06% which is 22.40%higher than the Mean-shift segmentation method with a better performance in farmland extraction in hilly area. The results can basically meet the requirements of drawing and revision for the large scale thematic mapping of farmland, showing that the proposed method can provide a technical assistance for the surveying and mapping of farmland.