【摘要】 利用遥感数据以月度或更短时间周期对密云水库水面面积进行连续动态监测,对及时掌握水库的水资源动态变化十分重要。为了减少提取过程中的系统误差和人为误差,真实准确地反映水面的实际变化趋势,以密云水库水面面积提取为例,试验利用掩膜主动轮廓模型进行水库水面提取。基于2006-2008年多期北京一号小卫星32 m多光谱影像,利用掩膜主动轮廓模型从各时相图像中提取水库水面,并计算面积。利用人机交互解译法从6期同期获取的高分辨率影像上提取水库水面作为验证数据,验证多光谱影像上水面提取精度。结果表明,掩膜主动轮廓模型多期提取结果的平均精度为97.54%,与验证数据线性拟合的R2为0.896 1,表明该方法进行水库水面连续动态监测,水库面积提取结果具有较高的稳定性,不同时相间具有较高的可比性,能够准确地反映水库水面面积变化的趋势。该方法为水库水面面积提取方法的探索提出了一种新的思路。更多还原

【Abstract】 Continuous monitoring on Miyun Reservoir monthly,or with an even shorter period,plays an important role on knowing the change of Miyun Reservoir water area timely.Because the monitoring period is very short,the change between two neighboring monitoring status is small and it is not easy to find the change trend due to the existing of errors while water area extracting.To reduce the system errors and human errors as much as possible,we try to extract water area from multiple Beijing-1 small satellite multispectral images using an improved active contour model,which we named Masked Active Contour Model(MACM).The MACM we proposed is based on Ron Kimme’s active contour model.We improve Ron Kimme’s model by extending its applying range from grey images to color images or multispectral images,introducing a mask image which automatically change during the evolution of the level set function to make the image meet the demand of bimodal image,and replacing the fixed time step with a converging one for fast convergence,etc..These improvements make the model more practical.Multiple Miyun Reservoir Water areas were extracted using the MACM from the Beijing-1 small satellite 32-meter multispectral images received ranging from 2006 to 2008.To evaluate the accuracy,Miyun Reservoir Water areas of six different periods were extracted interactively from the high resolution panchromatic images of Beijing-1 small satellite,which were received very near or even the same as the day on which the corresponding multispectral images were received.The accuracy assessment results show that the mean accuracy of the water areas extracted using MACM is 97.54% and the square of the correlation coefficient with the reference data is 0.896 1.Our researches show that the water areas produced by the MACM are accurate and stable enough compared with the reference data and comparable between different periods.So extracting reservoir water from remote sensing images using the MACM can improve the stability of continuous monitoring and reflect the change trend of reservoir water area accurately.Our research gives a new approach for the automatic extraction of water area from remote sensing images.更多还原