基于OLI影像的县域冬小麦种植面积提取

Study on Planting Area Extraction of Winter Wheat Based on OLI Images at County Level

以河南省虞城县为研究区域,筛选冬小麦分蘖期至拔节期内的3期(分蘖期、越冬期、拔节期)高质量OLI遥感影像,进行辐射定标及FLAASH大气校正,以便将影像DN值转算为地表反射率,并利用全色波段进行影像融合处理以提高空间分辨率。以归一化差异水体指数(NDWI)、归一化差异建筑指数(NDBI)、归一化差异植被指数(NDVI)为基础,结合外业调查数据构建决策树模型,3期影像中NDWI大于0的像元为水体,NDBI大于0的像元为居民地,NDVI分别大于0.59、0.52、0.65的像元为冬小麦纯净像元,NDVI分别小于0.49、0.44、0.56的像元为其他地物,剩余部分为冬小麦混合像元,通过实地调研确定将混合像元面积折算为冬小麦实际种植面积的权重为0.46,最后计算虞城县冬小麦的实际种植面积。结果表明,冬小麦分蘖期至拔节期是遥感监测冬小麦种植面积的最佳时期,3期影像提取的2014年虞城县冬小麦种植面积分别为76 238.79 hm2、77 406.65 hm2、77 397.82 hm2,与往年统计数据和样地实测数据相比,精度达到了99%。

It is always an important piece of work to fully mine the remote sensing images information and improve the identification environment in agricultural crops remote sensing monitoring. The OLI images of landsat-8 satellite provided a new data source for agricultural crops remote sensing. Taking Yucheng County of Henan province as the study zone,the article analyzed the best period of remote sensing monito-ring of winter wheat planting area,selected three high-quality OLI images during the best period,and did the work of radiation calibration and FLAASH atmospheric correction,so as to convert the DN value of images into the surface reflectance and use the panchromatic band for image fusion to improve the spatial resolution. Based on NDVI,NDWI,NDBI,the field survey data were used to build the decision tree mo-del. The classification constraints were as follows： the pixel represented for the water body if its NDWI value is greater than zero,and the pixel represented for the residential land if its NDBI value is greater than zero,and the pixel represented for the pure pixel winter wheat if its NDVI value is greater than 0. 59, 0. 52,0. 65 respectively in the three OLI image,the pixel represented for other objects if its NDVI value is less than 0. 49,0. 44,0. 56 respectively in the three OLI image,other pixel represented for the mixed pixel＆amp;nbsp;winter wheat. The mixed pixel area of winter wheat was converted into the actual planting area of winter wheat according to the weight. The weight was determined 0. 46 based on the field survey data, and then the actual planting area of winter wheat in Yucheng was computed. The results showed that the period of winter wheat from tillering to jointing was the best time for remote sensing monitoring winter wheat plan-ting area. The winter wheat acreage in Yucheng County extracted from three images were 76 238. 79 ha, 77 406. 65 ha and 77 397. 82 ha respectively in 2014,the accuracy reaching to 99 percent compared with the statistics data of previous years. The measured data for extraction of winter wheat acreage provided an important technical support at the county level.