There are a host of softwares that do GIS functionalities. Some of them are based on the image analysis and many of them are focusing on the spatial analysis. Some of them are proprietary and many are freeware and open source. A big chunk of "spatial analysis" capability in GIS is to do "statistical analysis" on the geographic data. This part has been neglected in many of the GIS softwares. Primarily due to the satisfying effect of maps on derivation of final conclusions about the spatial effects. This view however is increasingly changing as the assurances that a scientific conclusion and more importantly statistical analysis can provide for different dsiciplines is un-matched.
Among the most promising and free software for the spatial data analysis, R has emerged as the force to reckon with. The number of functions and formulas in the spatial analysis papers that can be used for data analysis is increasingly high in R (although other software like Goda are also very good in providing functions for the analysis). However the nature of R which relies on two things community development and community help shows more promise. Over the past decade we have seen treamendous development in R spatial packages. These packages and functions although very useful, they need to be tested in the community and improved by the volunteer developers. As such, some of the primary functions of GIS are missing in R. For example despite rich facilities in R for visualization, a straiforward map representation and interactive map facility is missing in R. Some might say, it is not there because it shouldnt be there. R is statistical analysis software not a GIS. The answer to that I think is simply the promise of open source and power of community. If some people someday decide to add an inherent visaulizaiton capability to R it would not be a problem.
Some have developed a workaround for this problem which is the connection to the open source GIS software like SAGA, GRASS and so on which in my opinion is not very straightforward. I will try to discuss these possibilities in the future posts.
Among the most promising and free software for the spatial data analysis, R has emerged as the force to reckon with. The number of functions and formulas in the spatial analysis papers that can be used for data analysis is increasingly high in R (although other software like Goda are also very good in providing functions for the analysis). However the nature of R which relies on two things community development and community help shows more promise. Over the past decade we have seen treamendous development in R spatial packages. These packages and functions although very useful, they need to be tested in the community and improved by the volunteer developers. As such, some of the primary functions of GIS are missing in R. For example despite rich facilities in R for visualization, a straiforward map representation and interactive map facility is missing in R. Some might say, it is not there because it shouldnt be there. R is statistical analysis software not a GIS. The answer to that I think is simply the promise of open source and power of community. If some people someday decide to add an inherent visaulizaiton capability to R it would not be a problem.
Some have developed a workaround for this problem which is the connection to the open source GIS software like SAGA, GRASS and so on which in my opinion is not very straightforward. I will try to discuss these possibilities in the future posts.
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