Investigating the spatio-temporal patterns of wildfires in California

• Goal: Find relationship between fire perimeters and bodies of water in Los Angles County
• Datasets Used:
• Wildland-Urban Interface 2020 (Census Block-level WUI data of LA County), Fire Perimeter data, California Counties Population Data, Primary Roads in CA
• Methodology + Analysis:
• Select by Location
• find intersection between” California_Fires_Perimeter” layer and “LA_county” layer → add selected features to new layer on map
• Load shapefiles for California Major Rivers and Creeks and California Major Lakes and Reservoirs
• Add topographic base map and surrounding counties to make chosen county stand out
• Result:
• Fires do fall along various rivers and creeks in LA but mostly around San Gabriel Mountains
• Reasons for these fires near major rivers and reservoirs can be explained through more desert-like terrain in the mountains rather than suburban areas.



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County of LA's fire perimeter between 2012-2022

• Goal: Find relationship between fire perimeters and bodies of water in Los Angeles County
• Datasets Used:
• Wildland-Urban Interface 2020 (Census Block-level WUI data of LA County), Fire Perimeter Data, California Counties Population Data, Primary Roads in CA
• Methodology + Analysis:
• First to create a choropleth denoting a population by right clicking counties_LA feature > data > export features. Edit the symbology > primary symbology : graduated colors > field = POP2020.
• Now we want to create the wildfire perimeter layer, just turn on CA_fire_perim layer > change symbology to a different color.
• For blocks designated as WUI for counties look through the attribute table of counties_LA > select by attribute and choose Where WUIFLAG2020 is not equal to 0 so it is selecting all (1=intermix; 2=interface).
• Result:
• Seems that most fires seem to be in mountainous areas where a lot of people don’t reside in or areas with lots of vegetation
• In close zoomed in extent of map, you can see detail of patterning of Wildland-Urban Interface blocks which has to do with the homes that interact with undeveloped wildland vegetation at urban and undeveloped areas.
• We can also see the majority of WUI blocks are more common in areas with undeveloped land.



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Modeling Tiger Habitats

• Goal: Find portions of protected areas, having the best environment to support tigers
• Datasets Used:
• Boundary, Protect, roads, forest, DEM (76 SRTM 1 Arc-SEcond digital elevation model images within Thailand), Mammals
• Methodology + Analysis:
• Needed to fulfill 5 criterion:
1. Suitable habitat cannot be within 1km of a road
2. Suitable Habitat area must have following combination of preys:
1. 1+ of Sambar or Eld_Deer
2. Also must not have more than 1 Gaur
3. The roundness of suitable habitat area(s) should be less than 1800. (Roundness = ratio of area to perimeter or area/perimeter)
4. Slope of suitable habitat area(s) should be less than 30˚
• GIS Tools Utilized:
• [criterion 1] Buffer tool for each road and erasing the zone from the protected area
• [criterion 2] Select-by-attribute to select only the forest polygons of suitable vegetation types (4 mentioned earlier)
  • Intersect tool also used to get the portion vegetation types are suitable in criterion 1 and forest
• [criterion 3]‘Add join` tool to add information in ‘mammals’ table to ‘protect layer’ [since they both share the same unique Protect_ID]
  • In new layer select features where sambar or eld_deer is 1 or more
  • Use intersect to get only data within criterion 2 and info specified above
• [criterion 4]New column is made ‘Roundness’ and then ‘calculate field’ tool used to select features with roundness less than 1800 → select-by-attribute
• [criterion 5]Mosaic Dataset and add necessary rasters to it → generate slope with slope tool → extract cells w/ slope value less than 30 with Raster Calculator → convert raster to polygon → intersect tool with criterion 4 and selected slope polygons
• Result:
• 25 features meet all 5 criteria. Tigers are found in mixed deciduous forests out of any forests in Thailand due to resources that forests provide which can’t be found anywhere else.



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Trade and Service Area Analysis of Santa Maria County Gas Stations

• Goal: Find equal competition trade areas for gas stations in santa barbara
• Datasets Used:
• SMC Census Block 2010
• Gas Station Location Coordinates
• Methodology + Analysis:
• Use network analyst tool to perform service area analysis based on distance
• Outline the trade areas
• Load shapefiles for California Major Rivers and Creeks and California Major Lakes and Reservoirs
• Add topographic base map and surrounding counties to make chosen county stand out
• Result:
• polygons that outline that equal competition trade areas



Figure 4.1: Service Area Analysis: Station 21 (Santa Maria)






Figure 4.2: Network Analysis of Santa Maria to Santa Barbara






Figure 4.3: Network Analysis of Santa Maria to Santa Barbara but with barriers

Work with the County of Santa Barbara Surveyor Office

• Objective: generate shapefiles of indexing polygons, by using techniques that involve tracing the assessor's parcel polygons,
  and/or coordinate geometry input registered to the assessor’s parcel polygon basemap.


• Datasets Used:
• Methodology + Analysis:
• STEPS TO GEOREFERENCE MAP PARCEL
1. locate map parcel from excel sheet on surveyor website
2. Make sure the data on pdf map matches the excel sheet description
3. Find what street intersection and locate it on the map using *select by attribute*
4. Measure and make sure it matches the measurements on ArcGIS [feet]
5. Now trace and fill polygons for parcels. [edit > create > polygon]
6. When done, merge [merge > hit merge on bottom right]
7. Make sure to press save in the ribbon and save work and relabel parcel


• Result:
• These indexing polygons will be used for joining tabular index information about the recorded map it references with a hyperlink to the scanned PDF of the recorded map available online
• These indexing polygons are then used to improve the completeness of geospatial indexing systems currently in use at the county.



Parcel 1: R013/001






Parcel 2: R013/009






Parcel 3: R013/004DR