5. Methodological &
5. Methodological &
Operational Problems
Methodological Problems
Knowledge in Earth Science, Biology , and Soil Science required to analyze all the factors. <2.5 percent of slope requirement which I chose in general idea might not appropriate this area because I found that most of builtup area had various slope even over 4.5 percent of slope some area. Soil composition of this area is mostly Regosol soil meaning the soil is very young and hard to trace the changes in long term period with soil composition. So, I just used the two soil types such as rocky and sandy soil to prove the water downstream routes. However, since soil itself has many characteristics influenced by many surrounded environment, my hypothesis was not quite match and I found that I need more knowledge of each field for the accuracy.
First impression with land use map was the area has the biggest area classified as Open space and undeveloped area. It seemed to be this area in danger anytime by city sprawl in future. Focusing on the proximity of the builtup area as a major component which makes the water in danger, my analysis was limited into a common sense but long way to prove it.
The protected watershed lands are owned by the GVWD and by the Province, 12% and 88%, respectively. The provincial lands are administered under the terms of a 999-year lease. The lease identifies two significant conditions for the lessee, including: the watershed lands be used "only for the protection and the purposes of its source of water supply." and the GVWD maintain an organization "for the protection and preservation of the timber upon the demised lands from fire.
Weighting the constraints and factors were quite subjective. Over powering in water constraint led the other factors useless. Overlying the load-distance and builtup-distance gave me the same weight and I misinterpreted the relationship between slope and streamline direction. Underground stream flow could not be effected surface slope as the result showed.
The dates of the data were different such as orthophotos were taken in 1993, and land use data of 2001 which I used were just released last month. So, some slight errors were expected in comparison.
Operational Problem
Some functions such as overlay did not work because data were from the different source so that they could not have the same column and row numbers. But idrisi asked me to match two files' rowIcolumn numbers. (Figure. opration & error msg) For an example, I used the land use data of entire GVRD and my analysis area was North Vancouver Capilano lake area. Most of my collected data handles only the area what I interested in. Eventurally, I had to go back to ArcView and made a theme file and then export to idrisi
Importing file from an ERSI shape file was easy but manipulating attributes needed another operation at the ArcView. For an example, the *.shp file, even with metadata having the elevation, could not do "surface" order at IDRISI. Simply it is because it was not composed in grid. As far as I understood the conversion in IDRISI from vector file to raster file was the transformation lines, points or polygons to grid cell format. However, it was not like that. The process was long and time consuming; ArcView -> TIN transform -> Convert to Grid -> Select Extension -> Export ASCII raster format -> Select Export source -> Import -> Conversion ASCII..
Often I got a blank screen or a message requiring something alien such as format match; byte, binary, integer, or real grid number of an images. Even with the same area and the same projection, it simply denied to operate and showing the message like "error 942" I couldn't find the meaning at the index about "error 942". Many meaningless message made me tired.
After the process in Arcview to transform to grid, the image lost the original shapes even though I increased the cell numbers or tried to match the original size. Also it lost all the precision because it had few choices forming the data; interger, real, or byte which are not accepting huge tail of precision numbers.
To work on IDRISI, all of my raw datasets from the GVRD and Selkirk Remote Sensing had to be translated through FME. But many files failed to be translated so that each time I failed, I shrank my criteria elements or tried to find another substitute rather than called Jasper or Apana. I did this not only because they were not available all the time or they got the same results but also because I felt that I had some other files to manipulate. But overall, it was my mistake changing the criteria often and only sticking on the available data. It could have been an much more accurate analysis.
