Modeling population growth and the
implications of urban expansion in Belize, Central America
Central America lies between the tropical latitudes 5º to 30º N and
has a global reputation for sparkling blue waters and sunny beaches. These warm
paradises also contain a large percentage of the World’s biodiversity. Tropical
rain forests and coral reefs cover a relatively small area of the globe, yet
are home to thousands of rare species not found anywhere else. Because these
unique ecosystems require very particular sets of physical conditions, they are
often very sensitive to changes in the environment. Increasing human
populations and the development that accompanies them often threaten these
areas of biodiversity and run the risk of driving rare species to extinction.
Belize is of particular interest because it is the most
sparsely populated country in Central
America, leaving much of
the land relatively undeveloped. This country contains many ecosystems with
high biodiversity; mangrove forests line the coast, the second largest barrier
reef in the world lies less than a kilometer
off-shore, and over 90% of land is under tropical forest cover (Figure 1).
Figure 1: Extent of forest cover in Belize, Central America, represented by
the colours green and brown. Image provided by the
Biological Diversity of Belize Mapping Service
The government of Belize has recognized these sensitive
ecosystems by establishing protected areas in approximately 42% of available
land (Protected Area Conservation Trust). These designated areas include
terrestrial, marine, and even archeologically significant regions (Figure 2).
Figure 2: The
Protected Areas of Belize, Central America, including the
status the Government of Belize has designated these areas and the political
boundaries of all six districts. (Dataset provided by Jan Meerman).
The wide variety of environments
represented in these protected areas hope to maintain the integrity of
biodiversity and rare species within the country. Conserving the natural
environment in Belize while it is still relatively pristine
allows for the opportunity to employ a more preventative approach to
conservation, rather than a reactionary one.
Although the government of Belize has taken the initiative to recognize
these diverse ecosystems at the early stages of the country’s growth, changes
in population will affect protected areas drastically in the following decades.
The current growth rate of Belize (2.39%) is more than two times the rate of
global population growth (1.1%), so that if this trend continues, Belize will
double in approximately 30 years (Government of Belize; for population doubling
time see Appendix I). Encroachment by a growing population and the increase of
agricultural, industrial and commercial activities necessary to sustain this
expansion will threaten the surrounding environment (Joshi and Suthar, 2002). In addition, tourism contributes over 20%
GDP to the economy and the government has made developing tourism a “national
priority” (Belize Tourism Board).This economic reliance on the tourism industry
means more people are arriving in Belize each year. The number of visitors has
already increased since 1998 so that in recent years, the tourists almost outnumber
the residents (Immigration Department).
My intent for this term project was to
use ArcGIS (version 9) to address development in Belize by constructing predictive models,
displaying biological data in a spatial context, and relating the results to
physical features. In particular, I wanted to:
1. Predict the increase of Belize’s population over time by using current census data to model
growth estimates for the next 30 years (predicted doubling time).
2. Show the distribution of an estimated population increase for each district.
3. Demonstrate how predicted population
growth would compromise designated
DATA FOR BELIZE
geographical datasets for international countries can be more challenging than
using regional data sources such as USGS. Information is not always up to date
and it can be saved in files that are not compatible with ArcGIS.
The best source for my basemap data was downloaded
from the Digital Chart of the World website in the form of a zip file that
contained relevant features saved in interchange format (extension .e00). I
created a new geodatabase in Arc Catalogue called
‘Belize’ and using the ArcToolbox function Import features from Interchange file, I
added each feature class to a feature dataset ‘BelizeUTM’
so that each layer would have the same UTM projection (Figure 3).
3: Using the Import to Interchange File
tool in ArcToolbox.
I originally had a lot of difficulties
opening this data as the import function kept rejecting my output files. This
was reportedly caused by operating ArcGIS on a vast
network and I was able to successfully import the data by saving the converted
files in a temporary folder on the local hard drive. I also obtained a polygon
feature class from Jan Meerman (Biological Diversity
in Belize) which delineated the six districts of Belize as a shapefile
and another polygon feature class which showed the Protected Areas in Belize (See Figure 2). I imported both the
‘District’ and ‘ProtectedAreas’ feature classes to
the BelizeUTM dataset in Arc Catalogue.
hoped to find Digital Elevation Model and satellite imagery land use datasets,
however the region I focused on was extensive (22 ,966 km2), making DEMs
from sources such as SRTM too large and there was no adequate land-use data
Population data and current growth rate
was acquired from the Government of Belize. I used 2000 and 2004 census data
(Central Statistical Office) as archive and current populations, respectively.
The population in each of the six districts of Belize and the division between urban and rural
areas were also based upon CSO data. I added a new field to the attribute table
of the political polygon of Belize and entered total population numbers for
2000 and 2004. I exported this feature class as ‘TotalPopulation’
into the BelizeUTM dataset. I added new fields to the
attribute table of the district feature class and entered district population
and urban and rural populations. I also
calculated a new field for the proportion of total population represented in
each district (Figure 4). I exported this feature class as ‘DistrictPopulation’.
4: Attribute tables for TotalPopulation and DistrictPopulation feature classes.
Population growth can be estimated using
exponential or logistical equations. These formulas take the initial population
N0 and calculate increases
or decreases over t amount of time.
Each equation uses different parameters to incorporate variables that affect
population growth. A basic exponential equation uses only time and growth rate,
whereas a logistical equation also requires estimates of population carrying
capacity, which defines the limit of a population to expand due to resources or
space. Calculating the carrying capacity of human populations is virtually
impossible, so for the scope of this project, I chose to use an exponential
Nt = N0*ert
or put more simply
Population at time t
= Initial population * e(growth rate r * time t)
The exponential growth equation does not take into account immigration,
emigration, or limits to resources and space.
In order to examine population growth in Belize, I first made a new toolbox in Arc
Catalogue called ‘Belize’. I constructed a model in this toolbox
called ‘TotalPopulation’ and used the exponential
growth equation in Model Builder to calculate population estimates over 30
years (projected doubling time for the population). The model adds a new field
to the attribute table of the TotalPopulation feature
class and names it according to year. The model then multiplies the initial
population (year 2004) by the growth rate and time. I found that model builder
does not enable complex mathematical functions such as exponents so I
calculated this figure by hand and added it to a new field in the attribute
table called ‘GrowthRate’ using the Editor toolbar. I estimated the
population of Belize for years 2005 - 2035 in 5 year
intervals by running the model 7 times (Figure 5).
5: TotalPopulation model in ArcToolbox
used to calculate the estimated population of Belize between 2005-2035 in 5 year intervals.
Each step of the model calculates the
predicted population of a year based upon the preceding year’s estimate. This
way I could use the same GrowthRate figure as t remained constant. After running the
model, I displayed the population estimates using Chart - Bar Graph under Symbology (Figure
6: Estimated population growth of Belize for
the next 30 years.
six districts of Belize each contain unique topographical and
environmental features. In addition, current data shows that the population is
not evenly distributed between districts (Figure 7). In order to display the
variation in population between each individual district, I could not apply the
exponential equation used in my TotalPopulation
model. This formula requires district growth rates, which involve calculations
of factors and data unavailable to me. Instead, I used proportional
distribution because between the years 2000 and 2004, each district contained a
relatively similar percentage of people even though the total population
Population within each district of Belize for the year 2004.
8: Population within each district of Belize for the years 2000 and 2004
projected on an ArcMap. The Excel chart indicates the
district proportion of the total population does not change.
I estimated district population growth by
building another model in my Belize toolbox called ‘DistrictPopulation’,
and used the predicted total population numbers generated in my TotalPopulation model to derive the proportional
distribution of people in each district between 2005 - 2035
in 5 year intervals. The model adds a new field named by year to the
District attribute table and multiplies the total population estimate to each
district proportion (Figure 9).
9: DistrictPopulation model in ArcToolbox
used to calculate the proportion of the population in each district between 2005-2035 in 5 year intervals. (NOTE: The model is
longer than displayed).
I entered the population estimate for
each year because Model Builder could not join these numbers from one feature
class to the other. I could have created redundant fields in the District attribute
table of total population, however entering a single
number into the model saved me time as this dataset was relatively small. If I
was to apply this model to a larger group of districts, I would use redundant
fields to remodel population estimates and calculate district proportion from
the single table. I felt comfortable operating under the assumption that growth
would occur at a constant proportion because this model did not generate any
new data, but merely showed the possible distribution of total population
estimates within the country.
10: Estimated population growth of each district of Belize for the next 30
determine the effect that population growth would have on sensitive ecosystems,
I looked at how the expansion of city limits would encroach upon neighboring
Protected Areas. The feature class ‘Towns’(from the
Digital Chart of the World dataset) represent single points of populated areas
in Belize without distinguishing between rural
villages or urban cities. In order to examine population expansion, I first had
to ensure that urban and rural areas would not grow at different rates. The
tendency of cities to expand more rapidly than rural areas is known as
urbanization. If urbanization is significant in each district, population
increases would be concentrated in a few cities and the proportion of the
population residing in rural areas would decrease over time. Again, using data
from 2000 and 2004 I found that growth occurred evenly between urban and rural
areas, maintaining the ratio of city dwellers to remote villagers (Figure 11).
11: Towns feature class projected on an ArcMap. The
Excel chart indicates the distribution between rural and urban populations for
the years 2000 and 2004.
measured population expansion using the Euclidean
Distance function in ArcToolbox. By calculating
the distance from each Town to another, I projected growth of these populated
areas in increments of kilometers (Figure 12).
12: Euclidean Distance function measuring the distance (in meters) between
I set the increments to 1000 meters in Symbology and designated radial increases of less than 5 km
as red, orange and yellow (moving away from Town centers).These regions pose
the most immediate threat to endangered ecosystems, as even small settlements
can easily reach diameters of 10 km. Values represented in green are still in
danger of encroaching upon Protected Areas, however, this growth depends
entirely upon the magnitude and direction of urban sprawl. Due to the large
percentage of land designated as parks or reserves, more than half of the Towns
currently lie within 5 km of a Protected Area and all Towns lie within 20 km
(Figure 13). Therefore, if each Town feature expanded up to 20 km, the
surrounding ecosystems would be drastically reduced.
13: The vicinity of Protected Areas to populated areas in Belize.
also used the Euclidean Distance
function to project the expansion of roads. These thoroughfares connect
populated areas and are associated with construction, pollution, and often
become the first areas to be developed. Population growth would increase the
demand for wider existing roads and the formation of new ones (Figure 14).
14: The expansion of existing roads and the Protected Areas that they
was able to determine population growth in Belize using Model Builder to predict
population estimates, ArcMap to display these results
in their spatial context, and ArcToolbox functions to
observe population expansion within the vicinity of protected ecosystems. ArcGIS software
allowed me to approach the future development of Belize by examining both numerical
representations of biological results and relate the implications of growth in
physical space. Being able to use a variety of data types such as values,
points, and areas in a particular problem strengthens the ability of the
analysis to address more than one question. In this case, population estimates
could have been calculated and displayed in tabular format which would neglect
the spatial context to which it applies. Looking at these estimates in GIS form
serves as a reminder of how an increase in numbers is related to a geographical
area and encourages the further examination of what these changes imply. For my project, I would have liked to
continue to study the effects of population growth by calculating flow in the
streams of Belize and estimating the expansion of land-use
from areas instead of points. Provided with a high resolution DEM and hydrography data, I could delineate watersheds where the
effect of increased runoff or stream blockage might change drainage areas
providing valuable water sources to the population (using ****). Using
satellite images to build a polygon feature class of all human related land-use
would allow me to incorporate agricultural and industrial areas instead of
unrepresentative points of populated places. In addition, water quality data
from marine monitoring points would enable me to analyze the potential effects
on Marine Protected Areas from increases in pollutants, discharge, and boat use
with tools such as Tracking Analyst.
capabilities of ArcGIS are adept at analyzing a
multitude of information, however there are some limitations. To perform any
kind of ecological modeling, users must be able to calculate a variety of
functions. Unfortunately, in the Calculate
Field tool complex functions such as exponents and logs are not
possible. A looping function in Model
Builder would also improve efficiency so that data does not have to be entered
exercise in ArcGIS gave me the opportunity to
approach estimating the population growth in Belize using a variety of analyses. Without
being limited by unavailable data, more of the functions in this software may
have been utilized to address my project. The wide range of possible solutions
to a single question makes this tool very useful for fields such as
Conservation. By illustrating areas of interest like Protected Areas, the
effects of biological and physical changes can be examined. The use of
multifaceted programs such as ArcGIS has the
potential to improve the accuracy of conservation planning which can hope to
prevent the degradation of biodiverse ecosystems in
This project was completed with helpful
advice from correspondence with Jan Meerman
(Biological Diversity in Belize) and Dr. Jay Raney (Bureau of Economic
Geology, University of Texas at Austin) in addition to modeling guidance and
suggestions from Dr. David Maidment (University of Texas at Austin).
ArcGIS version 9x. ESRI 2003.
Belize Tourism Board (Ministry of Tourism)
Statistical Office (Ministry of Finance)
Chart of the World
Jan Meerman (Biological Diversity in Belize)
K.N. and Suthar, C.R. 2002. Changing urban land use
and its impact on the environment (a case study of Jaipur
Area Conservation Trust
APPENDIX I: Population Doubling Time
order to estimate the amount of time it will take for a population to double, a
simple calculation can be used.
Rate of Belize =
2.39% (Government of Belize)
When a population doubles, N =
Using the exponential growth equation, N0*ert = 2 N0
Canceling the N0 on each side leaves ert
Growth rate r is known,
therefore solving for t rt
= ln 2
Results in 0.69/r
Therefore, doubling time is 0.69/0.0239
= 28.9 years