本文介绍的是ICAMS软件的应用，目前，从最新的传感器获得的数据量最近有所增加。美国宇航局开发的地球观测系统(EOS)就是一些类似的例子(Lam et al.， 1998)。这用于以有效的方式分析数据集。这对于利用卫星图像的时间序列进行快速变化检测，分析飓风、火灾、地震等自然灾害的数量是有帮助的(Olea et al.， 2013)。本篇澳洲传媒学论文代写文章由澳洲论文通AssignmentPass辅导网整理，供大家参考阅读。
In the present times, there has been a recent increase in the access of the data volumes from the latest sensors. Some of the examples of the same is the Earth’s Observation System (EOS) developed by NASA (Lam et al., 1998). This is used for the analysis of the datasets in an effective manner. This can be helpful in the analysis of the number of natural disasters such as hurricanes, fires and earthquakes by the use of the time series of satellite images for rapid change detection (Olea et al., 2013).
By the development of the software called as ICAMS (Image Characterization and Modeling System), there may be addressing of the requirement related to the same by focusing on a number of spatial analysis tools. ICAMS has been described widely by Quatrochi et al (1997) and Lam et al (1998). Thus, it is the software module which has been created in such a manner that it provides a number of spatial analytical functions for the purpose of remote sensing of images. Some of the most important function of ICAMS includes fractal analysis, variogram analysis, spatial auto correction analysis, analysis of the texture (Pratolongo, Paula, 2013).
The term fractals were coined for the very first time by Mandelbrot (1997). In the present times there have been a large number of applications of fractals which may range from the processes such as stimulation and the generation of the extra-terrestrial planets and objects which may be there in motion pictures and video games. It is important to analysis the remote sensing by the use of the fractal model (Lam, 1990). The derivation related to the fractals can be arising from some of the most important patterns of nature such as curves, the surfaces which may not be regular and it can very tough to analyze the same from some of the basic concepts related to classical geometry (Smith et al, 2014). The most important concept behind the use of fractals is to implement the use of the self-similarity for finding D. Self similar may be used for giving the definition of the curves where each part can be considered to be a reduced scale image (Haer & Toon, 2013).