A considerable amount of environmental analysis depends upon raster data. The variety of
continuous phenomena that define our world, such as elevation, land cover, and precipitation, are
captured and represented in GIS-friendly raster data using a combination of remote sensing
technologies and computational modeling to derive the finished products. Of course, a defining
feature of any raster is the shape and size of the pixels. Choosing one’s scale of analysis – which,
when working with raster data means choosing the resolution (cell size) of the rasters to be studied –
is an important consideration for any environmental study.
In this project, you will study a portion of land in the San Fernando Valley section of Los Angeles
using raster data at three different scales: 30m, 10m, and 1m. The study area is a bounding rectangle
slightly larger than the Browns Canyon Wash, a canyon within the Santa Susana Mountains.
Precipitation that falls in the wash drains to form Browns Canyon Creek, a tributary of the Los
Angeles River. Browns Canyon Wash is thus a watershed, also called a catchment or basin, which is
itself a sub-watershed of the Los Angeles River watershed.
Your first task is to create rasters of hillshade, slope, and aspect of the study area using the digital
elevation model (DEM) data and visually compare the results. Your second task is to assess the
hydrology of the area by studying how water flows and accumulates over the terrain. Your analysis
will yield an outline of the estimated watershed boundary of the Browns Canyon Wash at each
resolution. You will compare the boundary derived from the three different DEM scales with each
other and with the official USGS watershed boundary shapefile. The workflow has already been
completed for the 10m DEM; you will run the workflows for the 1m and 30m DEMs and compare
the results for all three and the USGS boundary.
Raster data at different scales serve different purposes. Small cell size, such as 1m, provides highly
precise information. This level of precision is useful for some but not all studies (see Avelino, et al.
2016, cited below). Working with such precise data means working with relatively larger file sizes
and the larger amounts of resources – data storage space, bandwidth (for cloud computing), and
time – required. Data with larger cell sizes provide less precise results but can be better aligned to
certain projects’ goals; and it can be much easier to work with. As with all things spatial, you will
need to match the data you use with the goal and parameters of any particular project.
Note: While we encourage discussion of challenges encountered and troubleshooting, each student
is expected to undertake their own technical work, provide screen captures/map of their own
outputs, and complete their own written report
• Analyze land surface parameters at different scales.
• Evaluate different methodological choices for terrain and hydrological analyses
• Synthesize methodological considerations and geoprocessing outputs via a high-quality written
report