Final Project- Suitability Analysis of Papaikou for Agriculture

Article: "Residents Protest Papaikou Development" West Hawaii Today
http://www.westhawaiitoday.com/articles/2009/01/18/local/local01.txt

* Please refer to the above article for context.

Introduction

Despite the current decline of the housing market in the US, housing developments continue to be built in areas where developers hope there will be an appeal to upperclass families looking to buy. For current development, Hawaii is an ideal location due to its tropical location as well as its governance by the US which allows for greater feasibility to build relative to non-US island territories. Although development in Hawaii has accommodated an increasing population as well as high rates of tourism, there has been difficulty finding adequate developable space and as a result, zoned land has been reclassified to permit building. However, due to the importance of the limited space to various investors (residents, tourists, developers, politicians, etc.), allowing or disallowing the reclassification of land has led to conflict. Such is the case in Papaikou, Hawaii where there has been plans to reclassify land, currently zoned for agriculture, as urban in order to allow for the development of Papaikou Point. According to West Hawaii Today, Papaikou Point would consist of 200 homes covering about 90 acres of land. Residents have protested the development claiming that they will lose valuable agricultural land as well as a loss of access to shoreline, increased traffic, and higher property taxes. To evaluate whether Papaikou Point should be developed, the current zoning of the development site for Papaikou Point was assessed. Additionally, a suitability analysis of Papaikou for agriculture was performed. Based on the analyses, it is advised that the land in Papaikou not be reclassified, and as a result, that the development be either suspended or have its area reduced in order to maintain economic stability for the current residents of Papaikou.

Methods

Shapefiles for the County of Hawaii were attained and included current land zoning as of March 2007, the boundary of Papaikou, agricultural lands by commodity, soil quality, precipitation levels, and a digital elevation model. To create the map representing the current zoning of the proposed site area, it was necessary to find the extent of the area through the Papaikou Point development proposal. Additionally, the zoning was regrouped in order to allow for easier understanding of the land. All lands that were zoned as agriculture were selected and displayed as a single layer. The same process was undertaken for the residential and commercial district zones. For the suitability analysis, a digital elevation model of Hawaii was attained through the USGS Seamless Server. The image was clipped in order to exclusively show elevation data for Hilo, which includes the town of Papaikou and the potential development site. A hillshade was added to the elevation image in order to show surface detail. Additionally, slope was calculated and displayed. Soil quality data was added and mapped for Hilo. The last two shapefiles added were for precipitation levels and agricultural commodities by area. The data was displayed for the entire island of Hawaii in order to allow for comparisons between Papaikou and the rest of the island. For agricultural commodities, sugarcane was selected and was the only commodity displayed due to its relevance and importance to Papaikou. By reviewing the statistics for the data, the extent of sugarcane area was found for Papaikou and a percent was generated to show the extent of sugarcane in Papaikou relative to the rest of the island.

Results

Based on the map of the current zoning of land in Papaikou, it is evident that most of the land is classified as agricultural while some is zoned as residential and even less as commercial district. As a result, there is very limited space for further development. Therefore, it would be necessary for the agricultural land to be reclassified as urban in order to allow for any substantial development project.

In order to understand the importance of the land within Papaikou for agriculture, a suitability analysis was performed. By analyzing the map of the total area of sugarcane in Hawaii, it was evident that most of the production is occurring on the north-eastern side of the island which includes Papaikou. After calculating the area of sugarcane in Hilo and Papaikou relative to the rest of the island, it was found that about 5% of the area of sugarcane production is occurring in Hilo, with 3% of the area found in Papaikou. Average precipitation was also evaluated for the entire island in order to show differences between Papaikou and other areas. Based on the map, Papaikou has higher average rates of precipitation relative to the rest of Hawaii. Elevation for Papaikou was found to be low relative to other areas. Similarly, the slope of the land in Papaikou was small. Both low elevations and small slope are conducive for agriculture and allow for a suitable surface for tropical crop production. In order to greater understand the quality of the land, the soil of Papaikou was evaluated and found to contain both highly erodible or potentially highly erodible soil, most likely due to Papaikou's proximity to the beach. As a result, developing on this land would increase soil erosion. In contrast, greater crop production would allow for the protection of the soil from wind and water degradation due to crop roots which stabilize soil. Overall, the suitability analysis reveals that Papaikou is highly suitable as an area for agriculture and in particular, for sugarcane production.

In addition to the maps created, a graph showing home sales in Papaikou was included. Since 2005, there has been a decrease in the total number of homes sold in Papaikou.

Conclusion/ Discussion

From the analyses, it can be surmised that the land within Papaikou, including within the proposed site for the Papaikou Point development, is highly suitable for sugar cane production and therefore, should not be reclassified to permit development. A low elevation, small slope, and high levels of of precipitation creates fertile soil in Papaikou and allow for abundant sugarcane production.


About 17% of the residents of Papaikou rely on agriculture, hunting, fishing, and forestry for income. Decreasing the amount of land would have a negative impact on the the economy of Papaikou, whose residents fall within the middle to lower class relative to the rest of Hawaii. In 2008, the median income for Papaikou was $50, 278 compared to Hawaii which had a median income of $67, 214 (http://www.city-data.com/city/Papaikou-Hawaii.html). With a population slightly over 1, 0000 individuals and 500 homes, Papaikou is a rural town with close community relationships. Increasing the population with the addition of 200 housing developments would result in greater waste, stress on the land, traffic, and overall, present problems that the small community of Papaikou will have to face without enough resources to diminish the impact of a higher population. Highly erodible soil or the potential for highly erodible soil in Papaikou is also cause for concern when considering development. Efforts to stabilize the soil to ensure safety will cost the county money that could otherwise be directed towards benefiting the economy of Papaikou. By continuing crop production on the land, the soil can be stabilized by the roots of crops and less funds will need to be directed towards mitigating soil erosion.

Overall, the county of Hawaii needs to consider the economic stability of Papaikou when deciding whether or not it is appropriate to rezone agricultural land as urban in order to permit the building of the Papaikou Point development. Since 2005, home sales in Papaikou have been in steady decline (http://www.city-data.com/city/Papaikou-Hawaii.html). Therefore, it does not appear to be financially viable to build a development until the housing market begins to rebound. It is advised that the Land Use Commission does not approve the reclassification of agricultural land due to its importance for economic stability in Papaikou. As a result, the fully proposed 90 acre development will either need to be reduced in size or temporarily suspended until agreements have been made with the residents of Papaikou. Offering the residents financial support, implementing social programs, or creating more jobs in other industries are possible ways in which the county of Hawaii and the developers of Papaikou Point can move forward with building while considering the needs of the community. Ultimately, the Papaikou residents should have a voice in the decision process regarding the rezoning of agricultural land. Above all, the county of Hawaii should make the livelihoods of residents a priority and evaluate the potential impact that the development will have on the economy.


While this analysis highlights the suitability of the land for agriculture, it is limited by the data available on soil quality. A more detailed analysis on soil quality relative to the rest of Hawaii would strengthen the claim that Papaikou contains land that is important for agriculture and therefore, should not be developed. Additional analyses might include evaluating the impact that the development will have on traffic and waste management in Papaikou.


Maps

Home Sales Chart


















*Source: www.city-data.com/city/Papaikou-Hawaii.html




Map Projection: North American Datum 1983, UTM Zone 4


Data Sources:
1. www.city-data.com/city/Papaikou-Hawaii.html
2. Hawaii Statewide GIS Program http://hawaii.gov/dbedt/gis/
3. USGS Seamless Server www.usgs.gov
4. Papaikou Ohana

http://sites.google.com/site/papaikouohana/
5. West Hawaii Today www.westhawaiitoday.com/articles/2009/01/18/local
/local01.txt
6. http://www.citytowninfo.com/places/hawaii/papaikou

1. China, India, US, Indonesia, Russia, Brazil, Pakistan, Japan, Bangladesh, Nigeria

2. Nigeria, Guinea, Egypt

3. Uruguay, Paraguay, Bolivia, Ecaudor, Chile

4. 15

5. Leninoboad, Jalabad, Zareh Sharan, Turgay, Zhezkasgan, Taldykorgan, Kyzylorda, Almaty, Bishkek, Talas, Karakol, Nukus, Shymkent, Dashkhovuz, Urgench, Naryn, Tashkent, Namangan, Andizhan, Osh, Gulistan, Fergana, Dzhizak, Navoi, Bukhara, Samarkand, Kashi, Chardzhev, Karshi, Dushanbe, Ashgabat, Kulob, Qurghonteppa, Mary, Termez, Feyzabad, Taloqan, Konduz, Mazar-E Sharif, Sheberghan, Aybak, Baghlan, Meymaneh, Mahmud-E Eraqi, Charikar, Qal eh-ye, Asadabad, Bamian, Mehtar Lam, Kabul, Chaghcharan, Mayda Shahr, Srinagar, Peshawar, Baraki Barak, Islamabad, Rawalpindi, Gardez, Ghazni, Dzhambul

6. 452, 298, 000

7. Most Populous: Ethiopia; Least Populous: Vatican City

8. Poland, Czech Republic, Slovakia, Austria, Slovenia, Romania, Croatia, Bosnia and Herzegovina, Yugoslavia

9. Monaco

10. Libya, Niger, Sudan, Nigeria, Central African Republic, Cameroon

Bonus: Nicosia

Lab 8- Corey Rovzar

Write-Up

Interpolation is the process by which unknown values in a dataset are predicted based upon known samples. It employs the principle of spatial autocorrelation in order to determine the interrelatedness between points, and if there is interrelatedness, it will determine whether or not there is a spatial pattern. Two types of interpolation include Inverse Distance Weighting (IDW) and Kriging. IDW is a deterministic technique that involves using a linear-weighted combination set of sample points in order to interpolate uknown values. Known points closer to the interpolated value will have greater weight, wheareas those farther will have less weight. Overall, this method is beneficial when a data set consists of many samples that capture the extent of local surface variation. In contrast, Kriging is a statistical interpolation technique that considers the distance and direction between sample points in order evaluate interrelatedness between points and determine surface variations. A weighted average technique is used to measure relatedness between sample points and interpolate unknown values. A fixed or variable search radius is used to predict values while the surface does not pass through any of the points. Kriging is best applied to topics such as geology and soil composition, where spatially correlated distance and directional bias for the sample points is known.

For this lab, precipitaion levels for Los Angeles County were evaluated through interpolation by considering the normal precipitation levels and total season-to-date levels that were measured at various rain guages. The first steps involved for the interpolation were to collect the data from the LA DWP website. The station names, normal precipitation levels, and season-to-date precipitation levels were entered into an excel sheet and exported as a .dbf file. Additionally, the latitude and longitude for each station was recorded in excel and similarly exported as a .dbf file. A shapefile of LA County as well as the .dbf files were loaded into ArcMap. The X,Y data was added based on the Latitude and Longitude data of the stations. The final steps were to use interpolation, and in this case, IDW and Kriging, to interpolate unknown precipitation values for normal and season-to-date levels. Finally, the raster calculator was used to generate maps depciting the difference between the season-to-date precipitation levels and the normal precipitation levels using both IDW and Kriging. Based on the maps, it is evident that the highest amount of rainfall occured in the eastern areas of LA County. Additionally, the normal precipitation values in the northern areas of LA County (around where the Station Fire occured) appear to be higher than the season-to-date values. Overall, there appears to be less precipitation for this season-to-date compared with normal precipitation levels, which is interesting when you consider that this year is an El Nino year. Darker areas on the difference maps depict areas where the season normal levels are greater than the season-to-date levels. Variations in precipitation levels are important to consider when evaluating fire hazard, especially in areas where soil composition and vegetation type are susceptible to fire. However, it is also necessary to understand that the season-to-date values do not account for the rest of the season in which rainfall could dramatically increase or decrease.

Overall, I feel that the IDW method is best for interpolating precipitation levels in LA County because the sample data points are substantial and provide accurate measurements of precipitation levels for normal seasons as well as the season-to-date. Because IDW is a deterministic method, interpolation is based primarily on the differences between the data points and not so much on stastical analysis. Therefore, unknown values are greatly influenced by the proximity of known values. Because precipitation levels tend to be similar in close areas of similar elevation, IDW interpolation would be useful in determining unknown levels, with greater weight being given to rain guages that are closest to the unknown values. Kriging would not be as accurate because the spatially correlated distance and directional bias for the data set are not known.

Lab 6- Corey Rovzar

ArcGIS Tutorial





























Fire Hazard Map



















Write-Up

In order to create the fire hazard model for the Station Fire, it was first necessary to do some background reading on the fire in order to allow for a basic understanding of the area. Important information that I ascertained was that the Station Fire occurred during the late summer of 2009 north of Los Angeles in the Angeles National Forest and was one of the largest wildfires of summer 2009 (http://www.cnn.com/2009/US/08/31/california.wildfires/index.html). The next step in the process was to find perimeter, elevation, vegetation, fuel rank, as well as any supplemental data in order to perform the analysis. Although I was able to find data for the Station Fire relatively quickly, it was difficult for me to decide what to include. The California Department of Forestry and Wildfires provides many different shapefiles concerning California wildfires. It was difficult for me to assess which data were important and relevant, and which were not. In the end, I decided that ultimately the perimeter, vegetation type, and digital elevation data were the most important to depict in my fire hazard map. Understanding the type of vegetation and the slope of the land, allowed for an analysis of fire susceptibility. Additionally I felt that including a small map showing the fuel rank of the land cover would also be useful in understanding the potential for fires. Although there was more data concerning surface fuels and other fire hazards, I wanted to overall highlight the effect that vegetation type has on propagation of fires.

After collecting the data needed, I began my analysis. The first step was to select the Station Fire perimeter from the shapefile containing all the California wildfire perimenters, and create a new layer. Using the Station Fire perimeter layer, the raster images of the digital elevation model, vegetation type, and fuel rank shapefiles were clipped. Clipping the raster images was a difficult process that required transformations and adjusting the settings for the raster images. A hillshade was created for the clipped digital elevation model, and was then overlayed with the vegetation type layer in order to display a slope-vegetation map of the Station Fire. Hydrological Tigerline data from the US Census website was also added to the map in order to show the location of various creeks. Other Tigerline data including major roads and areas of interest were going to be added, however, I found that there were few major roads and areas of interest within the Station Fire Boundary. Most of the area was encompassed by the Angeles National Forest. After performing a slope-vegetation analysis, an additional map showing the fuel-rank for the land cover of the Station Fire was created. The categories of Non-fuel, moderate, high, and very high were ascribed to the different levels of flammability for the land cover. The final stages of the analysis included adding an inset window to show where the Station Fire occurred as well as including map elements (scale bar, title, north arrow, etc.).

Overall, the main purpose of my fire hazard map was to facilitate understanding as to possible factors that perpetuated the Station Fire as well as the potential for another fire to occur in this area. By evaluating the slope-vegetation map, it is clear that most of the area is covered by shrub at moderate elevation. By then comparing this map to the fuel-rank map, it is evident that the area covered by shrub correlates with a very high ranking as fuel for fires. Therefore, a potential theory for the intensity of the Station Fire could be that it originated in an area that contained high levels of vegetation that was extremely flammable. Understanding the underlying factors that may have contributed to the intensity of the Station Fire allows for greater awareness of fire potential in areas with the same conditions.

Lab 5- Corey Rovzar

Suitability Analysis



























Essay

When evaluating landuse and possible locations for structures, it is important to analyze different areas and determine which areas will be most suitable. Suitability analysis is a useful tool in determining areas that are most suitable for specific uses. In particular, suitability analysis provides a visual display of areas most suitable for certain landuses based on a variety of factors. When running a landfill suitability analysis, the factors considered might include slope of elevation, distance of areas to landfills, soil drainage, proximity to streams (stream buffers), land cover, and an overall final analysis of the most suitable areas for landfills. Depending on the region being observed, other factors may also be analyzed such as population densities, protected areas, etc.

In this particular exercise, the aforementioned factors were classified with calculated ranges and then visually displayed on separate maps of the county in order to allow for individual analysis. Although most of the classifications and calculations were objective, the land cover classification was based upon my own perception of where a landfill would be most suitable based upon the overall extent and type of vegetation. Therefore, some degree of bias was introduced into the analysis. Additionally, a final analysis map was created which displayed the overall most suitable areas for landfills based upon weighted values for each of the factors.

Suitability analysis is especially useful when issues and concerns arise surrounding the location of damaging and toxic structures or facilities. In Los Angeles, there is currently a debate regarding the expansion of the Central Valley toxic waste landfill which is the largest in the state. High levels of arsenic have been found in the drinking water of nearby Kettlemen City and residents are concerned that high concentrations of toxins in the water and soil have contributed to birth defects. However, it is unclear whether the birth defects in Kettlemen City are attributable to the proximity to the landfill. Health officials have not observed higher than expected birth defects in relation to neighboring cities. Whether or not the birth defects are attributable to the landfill, it is important that residents are not exposed to any of the runoff from the landfill. The presence of high levels of arsenic in drinking water is cause for concern and should lead health officials to evaluate whether the landfill might already be too close to Kettlemen City and that the landfill’s expansion would magnify pollution levels that could then affect more cities. However, it is also important to understand the potential sites for other landfills and if it is feasible to implement new landfills in areas further away from cities.

In order to address these issues, it would be beneficial for health officials to run a suitability analysis for the region surrounding the landfill as well as statewide regions for potential landfills. Evaluating factors such as elevation, soil drainage, proximity to streams, vegetation type, and distance of nearby places to landfills, would allow for greater understanding as to the overall area that the Central Valley landfill affects as well as elements that may increase the range of pollution. By analyzing each factor individually, the cause for runoff from the landfill can be more clearly defined. For example, the Kettlemen City might be located relatively far from the landfill, however if it is at the bottom of a slope with the landfill at the top then there would be greater runoff entering the city. Suitability analysis could also be useful in this situation in determining other sites for potential landfills. If it was determined that indeed the Central Valley landfill was contributing to higher birth defects in Kettlemen City and therefore, it could not be expanded, then there would be a need for more landfills in other areas. Running a suitability analysis for California could provide a spatial overview of areas most suitable for landfills that would have the least amount of damage to people, the environment, and financially.

Overall, suitability analysis can provide visual evidence of the possible effects that the location of various places and structures may have on nearby areas. However, it is important to realize that suitability analysis is a model and not a perfect replication of reality. While it may be beneficial to use suitability analysis as a guide, in the end it is important to evaluate other aspects of an area when determining its suitability for a specific landuse. Additionally, the area should continue to be monitored to make sure that there is minimal damage to people and the environment, with minimal costs. Ultimately, suitability analysis is beneficial economically, environmentally, and socially.

Challenge Quiz 1- Corey Rovzar

Brief

I agree that medical marijuana dispenseries should be at least 1,000 feet from places where children congregate such as schools, libraries, parks, etc. in the city of Los Angeles. Although 1,000 feet may seem like a large area, after mapping out schools, parks, and institutions within the city of Los Angeles and creating 1,000 foot buffers around them, it was clearly displayed that there are many areas for dispensary locations. By limiting the dispensary locations, there will hopefully be less exposure to children and better peace of mind for parents. Costs would include that dispensaries would be a little more difficult to locate as well as less money generated by the industry. Additionally, other areas where children congregate may not be represented on the map. As a result, it is necessary to clearly define and map these areas in order to get a more precise idea of whether a 1,000 foot no dispensary zone is feasible and appeases those who wish to have more dispensaries and those wh0 do not. Other benefits to having 1,000 foot buffer zone is that there will be greater control over the overall distribution of the dispensaries. Areas with a high number of places exposed to children will have more no dispensary zones whereas areas where there are less children will be allowed to have more dispensaries. Overall, the primary concern surrounding the location of medical marijuana dispensaries should be how it will affect the children in the area. Limiting the exposure to dispensaries for children as well as having enough locations for dispensaries should be the optimal goal. By clearly identifying and labeling areas that have high exposure to children, there will be greater clarity regarding where dispensaries should be located. In the end, it may require that only areas with high densities of children (ex. schools and libraries) have no-dispensary zones; whereas areas with moderate or smaller densities (ex. museums, parks, etc.) will be allowed to contain dispensaries.

Lab 4- Corey Rovzar

Reference Map of Iraq