摘要
通过基于高时间分辨率的"环境一号"卫星数据的变化向量分析(CVA)冬小麦遥感识别方法,并以地理国情普查数据为调整单元对识别结果进行修正,达到提高冬小麦遥感识别精度的目的。结果表明,使用CVA方法可提高冬小麦遥感识别精度,以国情普查数据为调整单元可在一定程度上降低遥感影像配准误差影响,对其他农作物遥感识别具有一定的参考意义。
This paper discusses the winter wheat planting area has been acquired with the method of CVA based on multi- temporal HJ- 1- A satellite＇CCD data which have a short cycle time. Furthermore the cultivated parcel data was used as adjust units to correct the measurement result; it has solved the registration error of multi- temporal image at a certain extent and improved the accuracy of winter wheat area measurement. The conclusions show that： the method of CVA is more sensitive to the spectrum change,the cultivated parcel data was used as adjust units to correct the measurement result. This approach can be used on the other crop area survey but not only winter wheat.
出处
《测绘与空间地理信息》
2016年第4期135-136,139,共3页
Geomatics & Spatial Information Technology
关键词
遥感
变化向量分析法(CVA)
冬小麦
地理国情监测
农作物种植面积
remote sensing
Changed Vector Analysis（CVA）
winter wheat
geographic national conditions monitoring
crop planting area
