The major difficulty in monitoring lake areas based on low or moderate resolution Remote Sensing (RS) data is how to improve the accuracy and applicability of unmixing of mixed pixels, considering both the complexity of objects and limitations of time and space. To solve the problem, this paper proposes an efficient model uniting double-edge extraction with unmixing of mixed pixels, the accuracy and applicability of which is attested by computing lake areas of northwestern China using AVHRR images.
The Sustainable Development Information Sharing System (SDINFO) of China is a distributed information management network system composed of databases of different types. This system consists of one general data center and 19 sub-centers. Housing the information provided by sectional administrative authorities, the system contains 1 TB volume of data that can be shared in 224 fields of 37 categories under 5 major sectors. Of the volume, 30GB can be shared through the central system. This paper introduces the content of those data, then the system architecture, and presents the key technologies to manage the mass and varied data in the Sustainable Development Information Sharing System, which are laid emphasis on. These technologies include multiple resource data standardization and reconstruction technology, heterogeneous databases integration technology, mass spatial data manipulation technology, distributed information publication technology, and information search technology, which are all discussed in details in this article.
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