Juan Sanchez
1.
Assignment 7
Write a description of what you would like to do on your project (what is the question or questions
you would like to answer, the issue you are tackling, etc.)
Which communities in Massachusetts have the most opportunities for green jobs creation?
For my final project, I would like to explore how renewable energy sources and the
retrofitting/construction industry could potentially create green job opportunities in Massachusetts. The
American Recovery Reinvestment Act of 2009 is allocating billions of dollars nationwide to encourage
energy efficiency in buildings and the creation of renewable energy projects that will generate good
green paying jobs. Therefore, identifying the areas where exist the highest potential for developing or
using renewable energy sources is key to determine where this jobs are currently located or in the near
future. I will specifically look at the wind, solar, and biomass resources and potential building in need of
retrofitting in every town (zip code) of the Commonwealth. For my poster, I expect to create a series of
maps showing the individual resources by community, and a general “opportunity map” showing the
locations where these resources overlap, providing more opportunities for green job creation.
2.
Provide at least four briefly annotated examples of similar analyses (some or all of these should
come from peer-reviewed journals if possible) - briefly annotated means that you have a paragraph
about each example - if you cannot find examples of exactly what you are doing, find examples at
least in the same general field or one using similar data sets
A- Assessment of bio-energy potential in Sicily: A GIS support methodology.
In this study the team of researches used GIS to asses the economic potential of biomass as a possible
generator of energy production for the Sicily region in Italy. The research team used the following data
layers; land use, transportation facilities, urban cartography, terrain, climate types, potential civil and
industrial users of biomass, roads, civil biomass production, and agricultural crops. In order to evaluate the
potential of biomass production the team ranked the biomass in directly usable, usable after
homogenization, usable after air treatment system, and usable after chemical treatment.
B- Potential renewable energy resources of the Lerma Valley, Salta, Argentina for its strategic territorial
planning.
This study was conducted in the Lerma Valley, Salta, Argentina as part of a strategic regional planning
proposal for this area. Its goal was to determine what economic opportunities the renewable energy
resources available could provide to the population. The team of researchers used solar, wind, biomass and
hydraulic data to create a map of potential opportunities. They used a mapping raster format to define the
ideal locations (more layers overlap) where the most possibilities of economic development will occur using
renewable sources. GIS allowed researchers to better visualize the information gathered and made it
available in a more organized and interacted manner.
C- Wind energy potential mapping in Karnataka, India, using GIS
The purpose of this study was to map the wind potential in the province of Kamataka, India. The study used
GIS to analyze the variability of the wind speed considering spatial and seasonal aspects. The team of
researches ranked the wind speed by poor, marginal, good to very good, and excellent in order to categorize
the wind potential of the area. This categorization was done by overlaying the thematic layers.
D- Spatial data analysis and integration for regional-scale geothermal potential mapping, West Java,
Indonesia
This study was designed to map the potential geo-thermal resources in West Java, Indonesia using datadriven methods. The research team categorized the geo-thermal potential by weak negative, weak positive,
strong negative, and strong positive, in order to identify the area with the most potential. The spatial data
sets used for this analysis were; locations of geothermal prospects and hot springs, geological features,
earthquake epicenters and “Bouguer” gravity data.
3.
Describe the methods you think you will use (because we haven't covered analysis in detail yet,
this may be very preliminary)
I will use the political boundaries for the state of Massachusetts as the reference spatial area for this project.
Then, I will download data for wind, biomass, and solar resource from the National Resource Energy
Laboratory. I will also download a data set by census block groups of the housing structure age and
housing amenities to obtain an approximation of the existing building structures in Massachusetts.
Next, I will use the overlay tool to place the energy resource layers selected and the building layer “on top”
of each other to determine where the most overlaps exists. Finally, I will break the data into quintiles to
provide a rank of categories. The categories in this rank will be call, very low, low, moderate, high and very
high. This categorization will identify the towns or areas with the most potential or green job creation in the
state.
4.
List the data layers you will need for this project (if you know where you will get them from, list the
source, otherwise indicate that you will need help locating this data set) and include the minimum
accuracy you will accept (e.g., for the location of a stream, does it need to be within 500 feet of its
actual location or within 10 feet? Your answer will depend on your analysis purpose and the scale
of your project). Note: This section of your report could take the form of a table with each data layer
occupying one row.
Data layer
Source
Accuracy
Political boundaries for MA
Mass Gis
Not relevant
Housing structure age in MA
Mass Gis Census
Not relevant
Housing Amenities
Mass Gis Census
Not relevant
Wind data for MA
NREL
Not relevant
Biomass data for MA
NREL
Not relevant
Solar data for MA
NREL
Not relevant
References
Beccali, Marco, Pietro Columba, Vincenzo D’Alberti, and Vincenzo Franzitta. 2009. Assessment of
Bioenergy Potential in Sicily: A GIS-based support methodology. Biomass and Bioenergy 33, (1) (1):
79-87.
Belmonte, S., V. Núñez, J. G. Viramonte, and J. Franco. Potential renewable energy resources of the Lerma
Valley, Salta, Argentina for its strategic territorial planning. Renewable and Sustainable Energy
Reviews In Press, Corrected Proof.
Carranza, Emmanuel John M., Hendro Wibowo, Sally D. Barritt, and Prihadi Sumintadireja. 2008. Spatial
data analysis and integration for regional-scale geothermal potential mapping, West Java, Indonesia.
Geothermics 37, (3) (6): 267-99.
Ramachandra, T. V., and B. V. Shruthi. 2005. Wind energy potential mapping in Karnataka, India, using
GIS. Energy Conversion and Management 46, (9-10) (6): 1561-78.