연구정보
Remote Sensing and GIS as an Advance Space Technologies for Rare Vegetation Monitoring in Gobustan State National Park, Azerbaijan
아제르바이잔 국외연구자료 기타 Maral H. Zeynalova, Rustam B. Rustamov, Adil Y. Gambarov, Yelena M. Gambarova Journal of Geographic Information System 발간일 : 2016-11-29 등록일 : 2016-11-29 원문링크
This paper describes remote sensing methodologies for monitoring rare vegetation with special emphasis on the Image Statistic Analysis for set of training samples and classification. At first 5 types of Rare Vegetation communities were defined and the Initial classification scheme was designed on that base. After preliminary Statistic Analysis for training samples, a modification algorithm of the classification scheme was defined: one led us to creating a 4 class’s scheme (Final classification scheme). The different methods analysis such as signature statistics, signature separability and scatter plots are used. According to the results, the average separability (Transformed Divergence) is 1951.14, minimum is 1732.44 and maximum is 2000 which shows an acceptable level of accuracy. Contingency Matrix computed on the results of the training on Final classi- fication scheme achieves better results, in terms of overall accuracy, than the training on Initial classification scheme.
본 페이지에 등재된 자료는 운영기관(KIEP) 및 EMERiCs의 공식적인 입장을 대변하고 있지 않습니다.
이전글 | Lo sviluppo costruttivo della basilica di Ererouk (Armenia), secoli VI-X: una ri... | 2016-11-29 |
---|---|---|
다음글 | Some Aspects of Civil Procedural Acts Classification (Uzbekistan) | 2016-11-29 |