Betsy McDonald
Intro to GIS
Final Project Paper
December 15, 2013
Introduction
With supportive regulatory policies and numerous financial incentives in place, properly
sited solar PV development in Massachusetts is becoming more and more attractive.
Communities may be looking for opportunities to develop large scale municipal projects, either
to support the electric load of municipal buildings, or potentially to site community owned solar
projects for residents and other electric customers who otherwise may not be able to site a system
on their own property, for technical, monetary, or any other purposes. With this in mind, my
analysis centers around the potential to site solar PV on landfills in the Commonwealth. Siting
solar PV at landfills can be advantageous, as landfills typically have large, open space, minimal
shading, and offer a new use for otherwise unusable or undesirable land. However, there are
several factors that can make landfill development challenging, including “permitting
restrictions, settlement issues, cap restrictions, system design, distance to interconnection,
topography and slope.”1 In 2011, the Massachusetts Department of Energy Resources issued
guidance pertaining to municipal development of solid waste landfills in Massachusetts,
followed by separate federal level collaborative guidance by the EPA and the National
Renewable Energy Laboratory in 2013. Both documents outline opportunities, challenges, and
best practices for siting PV on municipal solid waste landfills. With the understanding that a full
feasibility analysis would require detailed structural engineering and utility level analysis and
plan design that I am unable to complete for this project, my analysis at a basic level attempts to
assess the suitability of landfill landscapes for solar PV, by first identifying and then prioritizing
the sites with the highest potential (keeping in mind that the analysis is not able to address
certain structural and electrical design issues).
1
The Guide to Developing Solar Photovoltaics at Massachusetts Landfills (Rep.). (2011).
Retrieved November 5, 2013, from Massachusetts Department of Energy Resources
website: http://www.mass.gov/eea/docs/doer/green-communities/pubsreports/pvlandfillguide.pdf
Separate analyses were conducted for projects that are already capped, and projects that
have yet to be capped. This separation addresses shorter term development plans as well as long
term development plans. Landfills that are already closed and capped will face certain structural
integration challenges with the existing landfill cap, but if those challenges can be overcome,
they could benefit from solar development much sooner when compared to landfills that are still
active. Landfills that are still active and not yet capped can benefit from advanced planning for
future PV development – if sites with high solar potential are identified before they are
closed/capped, landfill owners can make adjustments in their closure plans that will help
facilitate solar development and pre-empt certain structural and permitting issues in the future.
While I ultimately also compare overall scores, I identified priority rankings by cap status so that
state and municipal level resources can be targeted most effectively for comprehensive energy
planning needs (short and long term power generation).
Spatial Questions
There are several spatial questions that pertain to siting solar PV on landfills. The following
spatial questions were used to create a site prioritization list for landfills that are already capped
and may be most suitable for near-term solar PV development, and a site prioritization list for
landfills that are still active but may be most suitable for future/long-term solar PV development
(and could benefit from pre-emptively modifying their landfill closure plans).
1. Which landfills currently have large scale solar PV developments onsite, and which
landfills already have approved permits for future PV development? (I will want to
remove these from consideration, as I want to look at landfills that aren’t yet slated for
development).
2. For existing solid waste landfills (active and inactive/capped) that do not yet have solar
onsite, how close are they to utility transmission lines?
3. How close are existing solid waste landfills (active and inactive/capped) to areas
designated as wetlands?
4. How much solar resource is available at existing landfill facilities? How much shading
exists (using canopy cover) onsite?
5. What is the acreage of the landfill, and what is the average slope for that area?
6. In which utility territories are high-potential sites located?
7. Which potential sites are overall most suitable for solar development? (These will be
prioritized) Which are least suitable?
Relevant Literature
Arnette, A. N., & Zobel, C. W. (2011). Spatial analysis of renewable energy potential in the
greater southern Appalachian mountains. Renewable Energy, 36, 2785-2798. doi:
10.1016/j.renene.2011.04.024

This article identifies relevant criteria for siting solar facilities, and discusses the use of
solar insolation data from NREL, elevation data from USGS, the importance of slope,
and land use. The article addresses criticisms of large scale solar PV development, and
notes that people may oppose it if it takes up land that could potentially be used for other
competing purposes (agriculture, residential/commercial development, etc). As a result
of this consideration, the analysis presented in this paper limited the suitable sites to only
those identified by NLCD with land covers classified as “barren” (the article considers
the “barren” classification to be otherwise unusable for other economic or development
purposes). My analysis anticipates a similar criticism but seeks to pre-empt it by only
considering landfills and not other spaces or other existing land uses (this isn’t to say that
other spaces wouldn’t be appropriate, but rather that I just wanted to prioritize landfills
for this assessment, as landfills are already relatively undesirable land uses that could be
repurposed through PV development). This article also considered land identified in the
Protected Areas Database for the U.S. The database provides information on whether
land is restricted for conservation purposes.
Guide to Developing Solar Photovoltaics at Massachusetts Landfills (Rep.). (2011). Retrieved
November 5, 2013, from Massachusetts Department of Energy Resources website:
http://www.mass.gov/eea/docs/doer/green-communities/pubs-reports/pvlandfillguide.pdf

This guidebook was extremely valuable in creating the criteria for my suitability
assessment, as it provides details regarding PV design and considerations and feasibility
characteristics. While it details numerous criteria, I found their inclusion of wetland
consideration very helpful, and based on the information provided in this guidebook, I
decided to include proximity to wetlands in my criteria. The guidebook indicates that
facilities located within 100 feet of wetlands are subject to additional scrutiny, so while I
did not exclude these locations from consideration in my analysis, I did give landfills
located close to wetlands lower scores. Further, while a suitability analysis is critical for
siting landfills, this guidebook indicates numerous other factors for consideration (such as
ownership structure) that would factor into a municipalities decision making process. A
suitability analysis (like the one I’m demonstrating at the state level) would be only the
first step (among many) in the process.
Janke, J. (2010). Multicriteria GIS modeling of wind and solar farms in Colorado. Renewable
Energy, 35, 2228-2234. doi: 10.1016/j.renene.2010.03.014

This article does not address landfills in particular, but it does detail a process for
assessing large scale wind and solar suitability more generally in Colorado. The article
outlines the criteria used for site assessment: renewable potential (using NREL annual
insolation data), land cover, population density, distance to roads and transmission lines,
and cities. The analysis assigned weights based on importance of the criteria, placing the
highest value on solar potential (based on the annual insolation) and proximity to
transmission lines. Using the reasoning in this article, I gave these two characteristics the
most weight in my own analysis.
Kiatreungwattana, K., Mosey, G., Jones-Johnson, S., Dufficy, C., Bourg, J., Conroy, A., ...
Brown, K. (2013, February). Best practices for siting solar photovoltaics on municipal
solid waste landfills (Rep.). Retrieved November 20, 2013, from Environmental Protection
Agency website.

This document does not specifically address application of GIS, but it does establish a
comprehensive list of criteria that are considered best practices for siting solar PV on
landfills. Among the relevant criteria, the article recommends a minimum area of two
acres of onsite development capacity, a grade or slope of 2-3% (with an upper maximum
of 10%), and a half mile distance to the nearest transmission line (this is the ideal, but the
article states that a distance of one to three miles may be acceptable). I plan to use the
guidelines established by this document as primary determinants for establishing site
prioritization.
Van Hoesen, J., & Letendre, S. (2010). Evaluating potential renewable energy resources in
Poultney, Vermont: A GIS-based approach to supporting rural community energy
planning. Renewable Energy, 35(9), 2114-2122. Retrieved from
http://dx.doi.org.ezproxy.library.tufts.edu/10.1016/j.renene.2010.01.0.

This article looked at development potential for wind, biomass, and solar technologies in
a rural town in Vermont. The article is particularly helpful in the detailed methodology –
it describes energy potential maps which were created and subsequently used to solicit
community input for project development. It also lists the data sources for assessing solar
potential including USGS National Elevation Dataset and the National Biomass Carbon
Dataset 2000 (used to assess canopy cover). The methodology also incorporates use of
state orthophotos. While I used NLCD data for canopy cover and not the National
Biomass Carbon Dataset, this article provided a good reference point for developing a
systematic assessment of solar potential using GIS.
Data Sources
Data Set
MassDEP
Land
Disposal of
Solid Waste
Details
Source
Year
vector
2011
MassGIS
http://www.mass.gov/anf/research-and-tech/itserv-and-support/application-serv/office-ofgeographic-informationmassgis/datalayers/towns.html
vector
2009
TRANSLINES_ARC
MassGIS
http://www.mass.gov/anf/research-and-tech/itserv-and-support/application-serv/office-ofgeographic-informationmassgis/datalayers/trnslns.html
vector
2007
Massachusetts_DEM_1_
arc_second_NHD_project
ed
National Map
(USGS Data
Portal)
http://www.mass.gov/anf/research-and-tech/itserv-and-support/application-serv/office-ofgeographic-informationmassgis/datalayers/imgelev5k.html
raster
Mass GIS
http://www.mass.gov/anf/research-and-tech/itserv-and-support/application-serv/office-ofgeographic-informationmassgis/datalayers/depwetlands112000.html
vector
2009
Mass DEP
http://www.mass.gov/eea/agencies/massdep/se
rvice/energy/landfills/renewable-energyprojects-at-closed-landfills.html
table
2012
Mass DEP
http://www.mass.gov/eea/agencies/massdep/se
rvice/energy/landfills/landfills-with-post-closureuse-permits-for-renewables.html
table
2013
TOWNS_POLY
MassGIS
Power Lines
DEP
Wetlands
(1:12,000)
WETLANDSDEP_POLY
MA Landfill
Profiles
lfenergy
Landfills
with PostClosure Use
Permits for
Renewable
Energy
Format
http://www.mass.gov/anf/research-and-tech/itserv-and-support/application-serv/office-ofgeographic-informationmassgis/datalayers/sw.html
SW_LD_POLY
Community
Boundaries
Mass DEM
URL
Canopy
Cover
canopy13_011007
NLCD Zone 13
http://www.mrlc.gov/finddata.php
raster
NREL
Insolation/S
olar
Resource
Data
DNI
NREL
http://www.nrel.gov/gis/data_solar.html
vector
2001
2005-2009
Steps for data creation, processing, and analysis
1. While many of the data layers were already clipped to Massachusetts, I pre-processed
certain layers in order to make sure they were appropriate for my project area (state of
Massachusetts). This applied to the NREL insolation data and canopy cover data, both of
which needed to be projected to
NAD_1983_StatePlane_Massachusetts_Mainland_FIPS_2001. The other MassGIS data
layers were already in this projection.
2. I started by selecting by attribute to remove unnecessary fields from my transmission line
data set in order to make sure that I am only looking at proximity to power lines and sub
stations (and not the ski lifts, landing strips, and airports, etc. that are in the original
dataset).
3. Next, two different tables of data (one with info on which landfills already have PV
onsite or who have been approved for PV, and one with all landfills in MA with details
on additional post-closure uses and permits) were procured from the DEPs website. I had
to reformat them, but was ultimately able to merge them into one table using the landfill
address as a unique identifier. Once they were merged into one table, I was able to bring
that excel worksheet into ArcMap. Using the LNK field as an identifier, I joined my
excel table with the Landfill Poly site data set I have from MassGIS.
4. Once all of the DEP data was joined to the solid waste landfill data, I refined this data set
to meet some additional basic criteria. I only wanted to consider data for municipal solid
waste landfills (the MassGIS data layer had other types of locations, including Ash, C&D
Waste, Sludge, Tires, Woodwaste). I selected by attribute so that only MSW landfills
remained. I selected by attribute and removed all the sites that already have PV onsite, as
I don’t want to consider/assess these for future development (I saved these sites in a
separate layer file for future comparison purposes). I also removed landfills that had been
capped and already had other uses (ie some have been slated for soccer fields, parking
garages). I also selected by attribute to remove all landfills that are under 2 acres in area
(as this is the minimum area recommended for site development).
5. I used the Select by Location feature to remove landfills that are more than 3 miles from
transmission lines. As this had been identified as an upper limit, I didn’t want to consider
landfills that had lines further away than 3 miles.
6. After I pared down the landfill data, I created two data layers – one that has only
closed/capped landfills, and one that has only active (and inactive but uncapped) landfills.
I wanted to assess suitability for these two categories separately.
7. Using a process similar to what is detailed in some of the suitability reports as well as the
exercise we did in class for siting wind facilities in Beijing, I reclassified canopy cover,
insolation data, DEM data (to get to slope – low slope is preferable), proximity to
transmission lines, and proximity to wetlands, and then create preference grids for each
of these based on the criteria I found in the peer-reviewed articles, the Department of
Energy Resources report, and the EPA report. Before doing this, I converted all the files
to raster grids. See below for criteria ranking details, and see reclassified criteria maps at
the end of this document.
8. After creating reclassified feature maps, I did an overlay of the reclassified data sets in
order to create final suitability zones. See below for weighting details. I wanted to
weight transmission lines the most, with insolation data weighted second highest. I then
used the zonal statistics as a table tool to get a mean score for the land area in each
landfill polygon. After the zonal statistics tool created tables, I joined them to the
appropriate data layers (capped landfills, uncapped landfills, and landfills with existing
solar PV onsite). I then sorted each data layer to find the 5 sites with the highest ranking
in each of those categories. Due to concerns about the accuracy of canopy data, I did my
best to visually locate these landfills using Google Earth and assess shading, within
reason.
Criteria for Ranking
With the aforementioned questions, literature review, and process in mind, I selected the
following criteria for determination of suitability: proximity to transmission lines (closer is
better, with a max of 3 miles), total solar resource (higher insolation values are better), canopy
cover (less cover is better), slope (smaller slope is better), and proximity to wetlands (further
from wetlands is better).
Overall Criteria
Weight
0.30
Criteria for Suitability
Proximity to Transmission Lines (miles)*
Value
0-.50
.50-.75
.75-1.00
1.00-2.00
2.00-3.00
Score
5
4
3
2
1
Insolation (kWh/m2/day annual)
4.00-4.041
3.80-4.00
3.60-3.80
3.49-3.60
0.0-3.49
5
4
3
2
1
0.25
Canopy Cover (%)
0.00-20.00
20.00-40.00
40.00-60.00
60.00-80.00
5
4
3
2
0.175
80.00-100.00
1
Slope
0.00-2.00
2.00-4.00
4.00-6.00
6.00-8.00
8.00-Max
5
4
3
2
1
0.175
Proximity to Wetlands (feet)*
0.00-100.0
100.00-1,500.00
1,500.00-15,000.00
15,000.00-150,000.00
Max
1
2
3
4
5
0.10
*Input to GIS as Meters
Difficulties
One of the first difficulties I faced was in preparing the more detailed landfill data
(obtained from excel/table data obtained on the DEP’s website). Some of the landfill names and
addresses were spelled slightly differently, and this made manual clean-up of the (almost 500)
original landfill sites an important first step. Availability of time appropriate data was another
challenge in how I was able to conduct the analysis, and a challenge in the ultimate validity of
the findings. While my review of literature confirmed that shading was a very important factor, I
knew that the canopy data was last updated in 2001, and I struggled deciding whether to use
canopy cover at all as part of the analysis. I was unable to determine whether it was not updated
in 2006 (with the rest of the NLCD data) due to lack of funding, or whether the data had been
determined to be unhelpful. Knowing that shading is a relatively significant factor in
determining suitability for solar, I decided to keep the data in my analysis, but weight it less
prominently than I would have had I been confident the data was more accurate. As another
example of a challenge with evolving data, the data containing post-closure use was last updated
in 2012. It is likely that additional landfills have received or applied for post-closure uses (PV or
otherwise) since then, and had I had those more recent permit status notes in my updated file, the
prioritizations may have turned out differently. Additionally, while the specific criteria were all
identified through a literature review, the specific value categories and weights were assigned
based on more general understandings that certain criteria (proximity to transmission lines,
insolation data, canopy) were more significant than others. I struggled in assigning specific
weights, knowing that small differences could have a potentially large difference on my
suitability zones and the final list of sites. I also had a hard time deciding whether or not (and if
so, how) I would consider proximity to populations in my analysis. I knew that sites ideally
wouldn’t be in residential settings, but it also wouldn’t be advantageous to have them too far
away. What I couldn’t find was a general rationale for what ideal distance is appropriate. I tried
importing census block data several times and played around with different classifications (with
very close and very far being ranked with the lowest values), but ultimately I was not confident
that I was displaying it appropriately. I also struggled with this because municipal solar projects
intended to offset the load of municipal buildings may prefer different distances to community
owned solar projects within a given municipality. I think breaking out municipal level goals
(instead of lumping these two together) would have helped to a certain degree. I also don’t have
a real grasp on how politically viable these projects are and what type of pushback they have
received. I ultimately decided to abandon this sixth criteria, acknowledging that my analysis is
less accurate as a result.
With these difficulties and limitations in mind, it was important for me to remember that
these rankings would never be static, and that at best they are a jumping off point (with many
future steps to follow) for considering solar development. Overall, I think the analysis
demonstrates the basic process of site suitability assessment and the prioritization of
geographically ideal sites, keeping in mind that there are numerous additional technical and
social factors that may influence site determination, and that the criteria considered in this
analysis provide only a basic and approximate understanding of suitability. I do think it could be
improved going forward with a meaningful consideration of proximity to high population density
locations.
Concluding thoughts
With the limitations identified above, this analysis presents an approximate prioritization
of 5 capped and 5 uncapped MSW landfills that are particularly geographically suited for solar
PV development, based on the selected criteria and available data sets. Capped and uncapped
landfills were identified separately due to the unique challenges and opportunities each category
faces for solar PV development. While no sites achieved the highest score feasible (a mean
score of 5, which would have required a perfect score for each individual criteria factor), several
of them ranked with total scores over 4. Only 2 (out of 42) sites that currently have solar or are
in the process of installing solar achieved a score over 4. Further, several of these landfill
locations were not even within the suitability zone identified by this analysis. A comparison of
geographically ideal sites for future development with sites that already have or are currently
installing solar reinforces the understanding that additional factors influence site selection.
Future iterations of this type of analysis may attempt to visualize some of these additional
factors. As I mentioned above, going forward, it may be helpful to more explicitly break out
municipal goals in installing solar PV (to cover municipal load vs. to help develop participatory
community solar projects). More specific delineation of goals may help with considerations of
political will or viability and the importance of proximity to urban centers, as examples.
Additional Images and Screenshots
Individual Factor/Criteria Maps, Reclassified
Transmission Lines – Reclass (Data Source: MassGIS)
Insolation – Reclass (Data Source: MassGIS, NREL)
Slope – Reclass (Data Source: MassGIS, USGS National MAP)
Canopy Cover – Reclass (Data Source: MassGIS, NLCD)
Wetlands – Reclass (Data Source: MassGIS)