Interpolation Lab

 

Interpolation is the process of determining unknown values based on their spatial relationship to existing values. Without knowing specific values for specific locations, interpolation can infer the value of that location based on its relationship to the locations with known value. Many methods of Interpolation exist, each calculating the unknown values in a unique way. The methods used in this lab are IDW (Inverse Distance Weighting), Kriging, and Spline.  IDW uses a linear-weighted combination set of sample points to determine unknown value. It uses the theory that the farther two cells are from each other the less influence they have one each other. This follows Tobler’s law of distance decay where things generally become less and less connected as distance between them increases. So points that are closer to the known values are weighted heavier than points that are farther from the known values. Kriging on the other hand “assumes that the distance or direction between sample points reflects a correlation that can be used to explain variation in the surface”,(Childs 3). Kriging predicts values of a specified radius using a sophisticated weighted average technique.  The Spline method estimates values in an attempt to minimize surface curvature. It attempts to create a smooth layer that runs through all input values filling in the unknown values in between.

For this lab we interpolated the current amount of rainfall in Los Angeles County along with traditional Normal rainfall values for Los Angeles County. First we constructed a table in excel with all the rain gauge stations in L.A. county and added their latitude and longitude coordinates, which we had to convert into decimal degree format.  Columns for current rainfall and normal rainfall were made and then the excel table was exported as a .dbf file.  In Arcmap a Los Angeles county Boundary shapefile was added and then the excel table was added. The rain gauge stations were displayed using “display X-Y values”, based on the Latitude/longitude coordinates.  Two different interpolation methods were then applied to the data points resulting in two different outputs. One was based on the IDW method.  The other was based on the Kriging method. Both these methods were applied to the Normal rainfall value and the Current rainfall values. Once the interpolations were performed difference maps were made using the raster calculator to show the difference between current rainfall value and normal rainfall values.  It appears that the eastern part of the county received more rainfall than the western portion, and the current rainfall value are less than what normal rainfall values usually are.

I think the Inverse distance weighting technique is the best interpolation method to use for this task. Because of the nature of precipitation usually there is a gradual change in values, with areas of similarity generally decreasing with distance from each other. The IDW method is a deterministic interpolation technique that creates a surface based on measured points where as kriging is a geostatistical approach which is a more advanced surface prediction technique. Kriging would not be as accurate for this data set because a directional bias in the data values is not known. 

Spatial Analysis 2

As global climate change continues to alter local and state patterns of vegetation growth and weather an ever increasing demand for rapid collection and analysis of data is created.  As climate change is increasing average summertime temperatures and decreasing rainfall throughout the winter more extreme fire conditions are being created that are sweeping through Northern and Southern California.  Fire crews are burdened by more work than they can possibly handle without calling in extra support from all over the state and nation.  Fire crews can be more efficient if they are given as much information about potential fire hazard areas before the fires start. This way they can address these areas using mitigation tactics before fires start.  If fire crews know that an area is prone to extreme fire behavior they can perform vegetation management techniques such as clearing the brush ahead of time, doing controlled burns, or speaking to homeowners about managing their properties responsibly.

A site analyses can be used like the one in this lab to determine areas that are more hazardous than others when exposed to fire. Factors in this lab were slope and vegetation type. Of course other factors exist in determine the extremity of a fire like wind, relative humidity, and elevation, but for the purposes of this lab we are only taking into account these two factors.  The lab focus was on the station fire location which occurred in Los Angeles County in the summer of 2010. The slope factor was created from a digital elevation model obtained from the USGS seamless server application, using the spatial analysis/slope tool in ArcGis. Once a slope layer was created it was then reclassified into different categories of increasing hazard levels, steeper being more hazardous.  A similar task was performed using a raster layer of vegetation types throughout Los Angeles. The vegetation layer was converted into vector format and then reclassified using NFPA vegetation standards to classify the hazard level of each vegetation type.  Once both slope and vegetation layers were reclassified into hazard level layers they were combined into one hazard layer using the raster calculator. The layer you see covering the station fire shows the overall hazard levels given slope and vegetation type.

The map that was created during this lab can be extremely useful in explaining why the Station fire was as intense and devastating as it was. Almost the entire area was very steep and covered by chaparral type vegetation that burns very well. Other factors that are not displayed in the map are the wind and the temperatures during the fire.  These factors also play a very large role in a fires’ ferocity, but are more difficult to create a map layer from because of their rapidly changing nature.  Aside from these minor deficiencies, site analyses can still be an extremely powerful tool when implemented into certain fields such as fire behavior.  With the addition of some remote sensing technology and a fast computer processor this operation could be done in a matter of hours for the entire state of California making it extremely valuable for wildland fire department throughout the country.  

Site Suitability Analysis

The implications of installing a new landfill or expanding an existing landfill can be extremely controversial and extremely complex with the possibility of endangering many people if precautions are ignored or overlooked.  California’s largest toxic waste landfill located in the central valley in Kettleman city plans to expand its facility, but concerned state officials placed a moratorium on the expansion until an investigation regarding effects of the landfill on drinking water is completed.  Reports of higher than normal levels of arsenic have been found along with birth defects in the area.  Whether these are directly related to the landfill or a byproduct of the pesticides and other chemicals widely used by the agricultural community has yet to be determined.

As far as the expansion of landfill, a site suitability analysis still needs to be performed. A site suitability analysis takes many different factors into account and then determines where the best locations for a specific activity to take place should be, or where a specific structure should be built.  Different activities as well as different types of structures obviously use different factors to narrow down the best place. Generally a site suitability analysis finds locations where all the desirable factors are overlapping, or where all the undesirable locations are not present.  It is a very efficient way to determine the best site for building, or performing a certain activity.

In the case of the landfill expansion site suitability test five factors were taken into account to determine the best locations to enlarge the current landfill.  Slope, distance from streams, land cover, distance from the existing landfills, and the drainage of different type of soils were the five factors that were used to determine the ideal expansion sites.  While some site suitability analyses treat each factor equally our analysis weights each factor based upon its overall importance. The type of soil and its drainage properties along with the slope of the terrain were each weighted at .3, while distance from streams was weighted as .2; land cover and distance to existing landfills were weighted as .1. The weighting of all five factors gave a final output combining all five factors into one standardized ranking system.

While a site suitability analysis is very useful for visualization of an areas viable options for expansion, it must also be backed up by field operations.  The city of Kettleman may already be experiencing negative effects of the landfill and would be further impacted by any type of expansion.  The investigation must be completed determining the impacts of the landfill in its current state.  In general site suitability test are useful in determining viable areas that should then be followed up by extensive field work to assess the areas that are being suggested.

Overall Suitability Analysis Function is an extremely powerful tool to have access to.  It not only saves huge amounts of time, labor, and money it is one of the most efficient ways of assessing land suitability.  While it is an extremely useful guide to model reality, it should never substitute reality.  Suitability analyses should always be confirmed in the field and many more tests should be conducted to confirm your finding.  Suitability Analysis is to be used as a model that should always backed up by tangible evidence such as drainage properties, slope surveys, soil composition, watershed examinations, etc.  Suitability analyses will continue to be a valuable tool as long as they are used responsibly and are always checked for accuracy.    

I believe the concept of limiting Medical Marijuana dispensaries to locate in only in areas that are not within 1000ft of areas that children and adolescents congregate, such as schools, parks, and libraries, is a good concept that should be implemented if more dispensaries are to be developed.  It is quite clear from the map on the right that plenty of viable options for new locations are available within the city of Los Angeles. I don't think medical marijuana dispensaries rely on their 1000 foot proximity to youth hubs, nor do medical marijuana patients find any more inconvenience from traveling the extra distance.  I think not having the dispensaries within 1000ft of schools, libraries, and parks helps to remove some of the temptation of  youths attempting to buy marijuana and helps to promote learning in schools by removing any potential distraction.  Medical Marijuana Dispensary Owners might argue that these 1000ft buffer zones remove potentially profitable areas to place their business, but I think the map shows that many options are still left open. On another more moral note, are we, as capitalist citizens of the California, more concerned with whether a small business profits or whether our children are learning and playing in a safe environment that is free of temptations to start using marijuana which may lead to further drug use. Overall I think the main issue here is to limit the exposure to children, but still have enough locations for the patients to access their marijuana needs.  By mapping areas that have high concentrations of children and excluding dispensaries this will be achieving, it will also reveal all the locations where a dispensary might be needed.  While the limitations stated in the LA times article limiting new dispensaries to 70 is also a good idea because it would hopefully distribute the dispensaries throughout Los Angeles. Another way to achieve this might be to put specific limitations on the urban densities allowed. like for example applying buffer zones on each new dispensary to limit densification. I think the ideas are good but there is still much more that can be done to limit the exposure to children while protecting the livelihood of the dispensaries and their patients.