Project Problems                                     PROJECT INDEX
    Upon doing this project, some methodological and operational problems were found in the process.  Some of the network S:// drive data contained unknown data classifications where image legends were undefined and/or lacked proper titles, thus making some of the data indecipherable and unusable, even though they might have contained some relevant information for my analysis

    I consequently spent a good deal of time downloading many of the same S:// drive layers (and more) off of the internet in order to obtain the missing metadata and datatable information, without knowing that they were already available in the overflow lab through ACCESS.  However, even with the additional databases, infromation was still lacking where some datatable values remained undefined.  The source website also did not provide enough adequate information pertaining to the data, although it aided in providing additional background knowledge of the island.

    Another problem was the amount of what seemed to be relevant data available for my project.  As most of the layers could have been used in my analysis, I found it hard to determine how many layers could be used while still keeping the project managable.  Many more layers could have been chosen (such as data concerning water/airsheds, nearby recreational facilities, etc.) and used to further strengthen my analysis but were not due to time, project scope, and manageability constraints.

    However, even by limiting the number of chosen layers to around 20, I subsequently found it hard to organized the growing number as I reclassified, overlaid, and performed numeraous other operations, ending up with around 80 saved layers by the end of the project.  Data organization became difficult near the final stages of my analyis where many layer names were too similar to each other, a fault of mine.  Some layers were just differentiated from each other using numbers such as AREARECLSS, AREARECLSS1, AREARECLSS2, etc., creating confusion as to which layers were used when and how during each analysis step.

    Pixel resolution of my raster images was also too course, with each cell representing about 100 hectares (1km2).  I had initially planned to determine actual lodge sites within the suitable areas and perform a friction surface to analyze the hunting and hiking (on-foot) distances that could be travelled around the potential lodge site location and surrounding areas.  However, by the time I found out the sizes of the remaining suitable areas, they only consisted of about 4 and 17 pixels and would not be able to show an appropriate friction surface.  A maximum of only around 30 pixels (~30km2) around the suitable areas would be relevant to my friction analysis.