摘要
利用GDAL开源类库相关函数可以读取多源遥感影像的物理大小、坐标投影系统、传感器波段和影像范围等信息。介绍了多源遥感影像在GDAL框架下的解析模式与方法,从底层开发的关键技术上做了相应的改进和优化,扩展了GDAL读取和快速显示遥感影像的方法。研究结果显示:获取2.13 GB遥感影像像元值,利用RasterIO函数所需要的时间为4.3 s左右,按照论文所用遥感影像按照屏幕缩放窗口大小进行缓存和采样的方法仅需要2.1 s;传统的采样方法无法申请超过2 GB大小的内存空间,论文提出的分块处理技术,能够满足大数据量的应用需求,并且能够提高系统内存应用效率和加快遥感影像缩放过程中的加载速度。
GDAL is a powerful open source library that supports reading and writing of more than 120 types of raster and GIS vector data. By using related functions of GDAL open source library, the physical size of the multi-source remote sensing image coordinate projection information, band information and image range information were obtained. The mode and method to resolve multi-source remote sensing images under GDAL framework were introduced. Some key technologies from the bottom of GDAL methods were improved and optimized and the methods of quickly reading and displaying Geo-images were expanded. The results show that getting a pixel from a remote sensing image of 2.13GB took 4.3 seconds by the RasterlO function and the new method took only 2.1 seconds; The traditional method can＇ t apply to sample an image larger than 2GB, while the block processing technology method described in this paper can meet the requirement of large-size image, and improved the memory application efficiency of the system and also speed up the loading and scaling of the remote sensing image.
出处
《中南林业科技大学学报》
CAS
CSCD
北大核心
2013年第1期58-62,共5页
Journal of Central South University of Forestry & Technology
基金
"十二五"国家高技术研究发展计划(863计划)课题(2012AA102001):"数字化森林资源监测关键技术研究"
林业公益性行业科研专项(201104028):"林分结构与生长模拟技术研究"
国家重大专项项目(E0305/1112/02):"高分湿地资源应用监测示范"
湖南省高校科技成果产业化培育项目(11CY019)
