朱骥, 施建成, 张祥信, 张素梅. 基于AVHRR/2 10 d合成数据的青藏高原亚像元雪填图[J]. 武汉大学学报 ( 信息科学版), 2017, 42(12): 1725-1730. DOI: 10.13203/j.whugis20150394
引用本文: 朱骥, 施建成, 张祥信, 张素梅. 基于AVHRR/2 10 d合成数据的青藏高原亚像元雪填图[J]. 武汉大学学报 ( 信息科学版), 2017, 42(12): 1725-1730. DOI: 10.13203/j.whugis20150394
ZHU Ji, SHI Jiancheng, ZHANG Xiangxin, ZHANG Sumei. Subpixel Snow Mapping Using AVHRR/2 10-Day Compositing Data of Qinghai-Tibet Plateau[J]. Geomatics and Information Science of Wuhan University, 2017, 42(12): 1725-1730. DOI: 10.13203/j.whugis20150394
Citation: ZHU Ji, SHI Jiancheng, ZHANG Xiangxin, ZHANG Sumei. Subpixel Snow Mapping Using AVHRR/2 10-Day Compositing Data of Qinghai-Tibet Plateau[J]. Geomatics and Information Science of Wuhan University, 2017, 42(12): 1725-1730. DOI: 10.13203/j.whugis20150394

基于AVHRR/2 10 d合成数据的青藏高原亚像元雪填图

Subpixel Snow Mapping Using AVHRR/2 10-Day Compositing Data of Qinghai-Tibet Plateau

  • 摘要: 为了满足水文和气象模型对长时段积雪面积数据的需求,基于第二代甚高分辨率辐射计(second series of advanced very high resolution radiometer,AVHRR/2)的10 d合成数据提出了一种青藏高原地区AVHRR/2数据亚像元雪填图算法,将中分辨率遥感数据亚像元级积雪面积数据集延伸至30 a时间跨度。本文算法以多端元线性光谱混合分析模型为基础,以归一化植被指数、第一波段、第二波段等作为选取端元的指标,直接从AVHRR/2图像中自动选取所需雪端元与非雪端元。基于TM数据对该算法的AVHRR/2数据亚像元雪填图结果进行验证,其均方根误差接近0.1,在青藏高原山区具有较高的精度。

     

    Abstract: Because there are not AVHRR/3 data and MODIS data before 1998, the time length of their data are not long enough to meet the needs of hydrology and meteorology. However, AVHRR/2 data can extend to 30 years ago. For AVHRR/2 data don't have the data of 1.6 μm waveband, which AVHRR/3 data and MODIS data have, the existing subpixel snow mapping algorithm of moderate resolution data cannot be used to implement the subpixel snow mapping of AVHRR/2 data. Therefore, in order to satisfy the needs of hydrological and meteorological modeling for the long-term data of snow covered area, an algorithm of subpixel snow mapping was established using AVHRR/2 10-day composited data of Qinghai-Tibet Plateau in the work. Moreover, linear spectral mixture model and multiple endmember spectral mixture analysis were introduced into the algorithm. According to the algorithm, the percent data of subpixel snow covered area can be obtained from AVHRR/2 data, and the subpixel snow covered area data can be extended to more than 30 years.For obtaining the required endmembers of ground objects, the method of selecting endmembers was found, in light of which snow endmembers and non-snow endmembers were selected automatically from AVHRR/2 images using the data of NDVI, channel 1 and channel 2 as the indices of selecting the endmembers, and the obtained snow and non-snow endmembers were saved in respective databases. In the work, this algorithm was validated against TM data, and the root-mean-square errors of the validation result are close to 0.1. For such a mountainous region as Qinghai-Tibet Plateau, this algorithm is very reliable and feasible.Because the used AVHRR/2 data are the 10-day composed data, the daily subpixel snow covered area cannot be obtained. In future, it is necessary to implement the pre-processing of AVHRR/2 data, and to obtain usable daily AVHRR/2 data. Then, after the obtained daily AVHRR/2 data were mapped at subpixel scale, the daily subpixel snow area data from AVHRR/2 data will be obtained.

     

/

返回文章
返回