%0 Journal Article
%T Three-dimensional Extension of the Unit-Feature Spatial Classification Method for Cloud Type<br>
%A ZHANG Chengwei
%A YU Fan
%A WANG Chenxi
%A YANG Jianyu Key Laboratory of Mesoscale Severe Weather of Ministry of Education
%A Nanjing University
%A Nanjing Meteorological Observatory of Shenzhen Air Traffic Management Station of CAAC
%A Shenzhen
%A <br>
%J 大气科学进展
%D 2011
%I 
%X We describe how the Unit-Feature Spatial Classification Method (UFSCM) can be used operationally to classify cloud types in satellite imagery efficiently and conveniently. By using a combination of Interactive Data Language (IDL) and Visual C++ (VC) code in combination to extend the technique in three dimensions (3-D), this paper provides an efficient method to implement interactive computer visualization of the 3-D discrimination matrix modification, so as to deal with the bi-spectral limitations of traditional two dimensional (2-D) UFSCM. The case study of cloud-type classification based on FY-2C satellite data (0600 UTC 18 and 0000 UTC 10 September 2007) is conducted by comparison with ground station data, and indicates that 3-D UFSCM makes more use of the pattern recognition information in multi-spectral imagery, resulting in more reasonable results and an improvement over the 2-D method.
%K cloud-type classification
%K unit-feature spatial classification method
%K three dimensions<br>
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=28A2F569B2458C17&jid=5434AFBF6CB6E7E8D67733B541F211C7&aid=FC0D4A4780D9473551212C38C2FAC0DF&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=38B194292C032A66&sid=ED9DF3402785F68D&eid=FED67FBA0A707330&journal_id=0256-1530&journal_name=大气科学进展&referenced_num=0&reference_num=34