Juan Alonso Velasquez  
GIS, Cartography, and Spatial Data Visualization Portfolio 


Welcome and thank you for deciding to check out a bit of my GIS and Spatial Data Analysis work! Since learning GIS software, it has become one of my favorite skills that I hope to keep using and improving.
Please scroll through projects down below, and click for more information. Fullscreen on Desktop for the best experience. Please note that some images take time to load. #Carto2026

Email: alonsovelasquez235@gmail.com
Last updated
January, 2026

Pronghorn Habitat Connectivity Across the Mogollon Plateau, Arizona


Imagine you have a surface of habitat suitability for a species of interest, and you generate habitat “patches” from the most suitable habitat across your study extent. How can you find out how your species of interest moves from one patch to the next? What is the easiest way for them to make that journey, and are there any threats to their movement?

Using GIS and spatial analysis, we can model the least-cost paths between patches across a landscape—so let’s do it! This set of maps model habitat connectivity between Pronghorn habitat patches, species Antilocapra americana. These artiodactyls are most closely related to giraffes and okapis, and are the fastest land mammals in North America.

Using an old 2003 dataset from the Northern Arizona's Forest Ecosystem Restoration Analysis (ForestERA) program's Mogollon Plateau landscape assessment, habitat patches were generated from a habitat suitability threshold above 0.9, as the dataset metadata says that 72% of pronghorn observations were found within areas with a suitability score of 0.9 or higher (Hampton et al., 2003).

By inverting the habitat suitability dataset, less suitable pixels are considered higher travel cost to pronghorn. By adding the accumulated cost between two patches, the least-cost path between them can be identified, as well as a habitat “corridor” that uses an accumulated cost threshold to find a reasonable range of Pronghorn accessibility.

Lastly, looking at human development like roads, transmission lines, human-wildlife conflict points (farms, ranches, rural development), and urban land use, we can identify “threat influence” on Pronghorn habitat across the study extent. By weighting different threats differently (developed land high threat, transmission lines lower threat) we are left with a raster that tells us how usable land is for Pronghorn.

Even if a patch is deemed “Pronghorn habitat” because of environmental variables, it might not be usable if it’s converted to urban development, helping us identify possible habitat corridors and restoration projects to benefit the species. 




Sierra Costera de Oaxaca, Mexico


Under Construction


The Sierra Costera region of Mexico has been the target of conservation priorities by different organizations. Working with a single Digital Elevation Model (DEM), we can predict trends and landforms across the landscape using terrain analyses on high definition elevation data.

This section of my portfolio is under construction as I finish and refine some maps, but here are some starting points!






Highland, California



My hometown is the city of Highland, California.
I lived right along the edge of Califronia suburban sprawl and the San Bernardino National Forest.

It was because of my proximity to the chaparral ecosystem of the Southern California foothills that I became drawn to nature, and its geography.

I often went hiking up these hills. When there are no trees along the foothills, it’s easy to see the topography and different landscapes across the region!



I made this map as a christmas gift for my family. It has our house, our favorite restaurant, and the local park and schools I went to.


Recreating Sean McNaughton’s
Earth Scars Projections


I have always loved the geographic visualizations
produced by National Geographic, and I decided to
try to recreate an old famous one!

Sean McNaughton really captured the  largeness of our
world and all its wonders. I am working to learn graphic
design skills to complement my geospatial analysis skills.

I hope to grow and spread
like the fascination and
curiosity I have for the
natural world with
greater audiences, just
like NatGeo did for me.



Sean McNaughton’s
Earth Scars

           


National Parks, State Parks, and Ecoregions of New Mexico



I first learned how to use GIS software and programming languages like R and Python for spatial analysis and mapping for ecological and environmental research. National Parks that protect and share biodiverse landscapes with people from around the world are important and dear to me.

Here is a map of New Mexico’s National Parks, State Parks, and what ecologists call “ecoregions,” or regions of mostly similar biodiversity and species. These regions are defined by their unique climate, topography, and geographic features, like proximity to water or elevation.

You can see that there is a huge number of ecoregions within the state of New Mexico. There are more general “Level III Ecoregions” and more specific “Level IV Ecoregions” within them.

In just the state of New Mexico at the Level IV scale, there are over 50 unique ecoregions!



Just imagine the scale of ecoregions across the entire United States — the entire North American Continent, or even the world.


Protecting
Tapirus pinchaque —
the Mountain Tapir’s
Range and Protection



I want to use GIS, spatial analysis, and the power of
visualization to convince audiences of the importance of our
world’s natural systems.

Here, I map the range of Tapirus pinchaque,
the Mountain Tapir, and compare it to protected areas that
intersect its habitat.

The mountain Tapir is a species of tapir native to the cloud
forests of Colombia, Ecuador, and Peru. It is critically
endangered, so the collaboration of conservation work
between the three countries it inhabits is crucial.

As you can see, Ecuador protects much of the
mountain tapir’s habitat within the country,
followed by Peru and Colombia. Colombia has the
largest swath of mountain tapir habitat, yet the
smallest proportion of its habitat protected.


Analyzing Landscapes —
the Topographic Relative Moisture Index (TRMI)



I am currently completing my first year of the Master of Environmental Management program at Duke University’s Nicholas School of the Environment.

I decided to go straight from undergrad to graduate school because I wanted to advance my skills with geospatial analysis, and broaden my knowledge of ecology, conservation, resource management, and science communication.

Here is a map of Grandfather Mountain, North Carolina. For my Fundamentals of Geospatial Analysis class, we had to develop a Topographic Relative Moisture Index (TRMI) for a region.

A landscape can vary in the amount of moisture and heat it recieves due to its geography. This is really important in ecology and conservation work, as certain species prefer very specific ranges of moisture and temperature.

A slope facing southwest recieves more warmth from the sun in the northern hemisphere, and ridges are generally drier than valleys. Using these basic principles, we can combine steepness, aspect (the direction a slope is facing), configuration (the shape of a land area — is it concave like a bowl or convex like a hill?), and relative slope position to estimate moisture of an area.

The higher the TRMI the wetter the area.
You can check your TRMI by placing streams over it — here, they line up with our estimated wet areas well!




Short-Term Housing in Barcelona — Airbnb’s
and Gentrification    

For my Advanced GIS class during my senior year of
college, I was tasked with venturing outside my comfort
zone and using GIS to analyze problems outside of the
environmental sciences.

I asked the question, can the density of short-term housing
rentals and indicators of inequality show us a relationship
between Airbnb’s and gentrification?

This took some heavy duty
geoprocessing tools, as well
as careful statsitical analyses.

If you are curious to know more,
check out the academic side of my
GIS portfolio, where you can see
the methodology of my project
laid out more clearly!

TLDR, most short-term housing
listings are listed right next to
common tourist attractions, driving
the availabilitity of housing down
and the price of units up, pushing
residents further away from the
most people-friendly parts of the
city.




Interpolating Surfaces —
Yellowstone Lake



A useful tool of spatial analysis, interpolation is when points of values are used to estimate the range of those values over an area, called a “surface.”

Here, depth across Yellowstone Lake is interpolated using a variety of different interpolation methods, with a comparison “true depth” that can help us see which methods are most accurate. These interpolation methods are laid out in the white panels.

Another way we can assess an interpolation method’s accuracy is by  visualizing the interpolation error. We can do this by subtracting the interpolated surface values from the true depth values that we know.

Imagine we lay the true depth surface on top of the interpolated depth surface, then find the difference at each pixel. This leaves us with varying degrees of error as visualized in the black panel on the left.

Doing this we can see that Trend is the worst interpolation method, but Natural Neighbor and Kriging do fairly modest jobs.

Reintroducing the Razorback Quahog to the Plum Island Estuary Using Site Suitability Analysis


For my final project of my first semester of GIS at my master’s program, I was tasked with identifying which potential reintroduction sites to select for the reintroduction of the Razorback Quahog.

The Razorback Quahog was a clam very important to the fishing economy of coastal cities along the northeast, but human development, overfishing, pathogens, and pollution has driven their populations to very low numbers. In the case of the Plum Island Estuary, it was locally extinct.

If we are to reintroduce a species back to its original habitat, we have to make sure a population will survive local environmental stressors.

Stessor 1: Sufficient Adjacent Salt Marsh Habitat

The salt marsh stickleback fish is believed to mitigate high exposure to the pathogen that contributed to the Razorback Quahog population crash in the early 2000s. By ensuring that there is at least 5 hectares of saltmarsh within a specific radius of the reintroduction site, we can have more sitcklback fish exposure to mitigate the spread of the pathogen.

Stressor 2: Storm Surge

Stormwater Discharge is a major concern for the survivability of shellfish. If a major storm moves through an estuary, the water rushing through mouths of rivers peak in speed, sometimes creating enough force to displace shellfish attached to the beds of the ecosystem.

In order to mitigate the likelihood of this happening, we can place gauge stations at the mouths of major streams that feed into the estuary. By measuring peak water velocity during periods of storm surge, we can assume that this peak energy dissipates it moves through the estuary over the estuary bed.

When the bed of an estuary is mapped, we can identify how much “resistance” its surface creates for rushing water. This data can be used as a “resistance raster” that mitigates how fast water is moving throughout the estuary. When total accumulated resistance is equal to the peak velocity at gauge stations, we can assume that the water’s velocity has dissipated and is now safe, unlikely to dislodge shellfish.

This leaves us with “danger zones” of storm surge impact to avoid when selecting our suitable reintroduction sites!

Stressor 3: Nutrient Pollution

Nutrient pollution, namely from Nitrogen and Phosphorus, can create algal blooms that suffocate aquatic ecosystems. Algae near the surface of the water blocks incoming light, and when the algae dies and sinks to the bed of the estuary, the decomposition sucks oxygen out of the water through microbial respiration, creating dead zones that are uninhabitable by marine life like shellfish at the bottom of the estuary.

To avoid this from happening to our reintroduced clames, we can using interpolation methods to estimate the concentrations of Nitrogen and Phosphorus from sample points across the estuary.

We can then turn this into a ratio of Nitrogen to Phosphorus, and avoid locations where the ratio of Nitrogen to Phosporus creates algal blooms (in this case, between 13 and 18 uM/L).

We now know which sites would be safe from dead zones in the event of an algal bloom!




Combining Suitability Indicators

After identifying which sites are same from different environmental stressors, we can combine these metrics to identify the safest reintroduction sites for the Razorback Quahog. After an analysis of over 20 potential reintroduction sites, only 3 of them are deemed safe.

Doing this kind of spatial analysis mitigates the use of funds and resources on reintroducing populations to locations they are unlikely to survive, maximizing resource use and survival of reintroduced populations!


Identifying Flood Risk en la Ciudad de Mérida, Mexico — the City of Mérida, Mexico


During the summer of 2024, I traveled to Mérida, a city in the Yucatan Peninsula of Mexico to assist in identifying flood risk, or, el riesgo de inundaciones, with a cohort of colleagues through the Resilient Urban Latin America (RULA) - International Research Experience for Students (IRES).

Working with local scientists, students, government officials, and locals, my cohort and I did research on how flooding affects residents and the effectiveness of nature-based solutions in mitigating that flooding. Located within the Yucatán Peninsula and built on top of Karstic limestone topography, Mérida is a city hit hard with climate change. A city of concrete, floods are common place and temperatures soar during the summer. Implementing nature-based solutions can help!
                       




Although a map of flood risk already existed — “Mapa de Riesgo de Inundaciones Existente” — it was coarse, and didn’t identify flood risk at a level helpful to residents that need to know which parts of their neighborhood were safe or at risk. Additionally, if we were to place nature-based solutions like rain gardens — jardines de lluvia —  throughout the city, we would need to know which specific streets throughout a neighborhood flood.





To get a more granular idea of flood risk and where to place nature-based solutions that soak up excess water, we started with the neighborhood of median to low average income: Juan Pablo Segundo. We looked at high resolution data across the neighborhood, starting with elevation — elevación.








Next, we looked at vegetation throughout the neighborhood using a special index called NDVI — normalized differentiated vegetation index. Where there is more vegetation, there is less of a need to implement nature-based solutions.














Next, we looked at street specific elevation — where are places of sudden, deep elevation?






Lastly, we asked local residents to map their experience with flood risk. We used a method called Participatory Mapping, where local experts and residents who have experienced flooding in the daily lives draw on a map where they remembr instances of water inundation. We can create polygons of data over places marked on the map, and translate this to our map of flood risk.







We are left with a flood risk map of differentiated risk: Riesgo Alto, Riesgo Medio Alto, Riesgo Medio, Riesgo Medio Bajo, Riesgo Bajo, and Riesgo Muy Bajo.
                 
It was an incredible experience to tackles geohazard exposure and risk with students and professors from the local university, and learn how to work with local experts on addressing environmental problems in their hometown.
   
Although just a component of our work that summer, the flood risk map showed us where to prioritize nature-based solution efforts. The next thing we did with our time there was assess the functionality of rain gardens implemented by the city government.
                 
My cohort and I wanted to share our results with Mérida’s public and all the locals that we worked with, so we made a Geostory through Geonode to summarize our work that summer. Similar to an ArcGIS story map, you can interact with the maps on the Geostory and scroll through different sections of our summer work. Check it out below!





The WA Map
I often create maps as gifts for people, or for myself.
Here is a map for one of my close friends that I made
for their birthday! I feel like I’ve come a long way in
half a year.









































MEOW
And here is a map of the Marine Ecoregions fo the World (MEOW). It’s visualized using the Spilhaus Projection, where all the oceans of the world are connected. Although disconcerting to wrap one’s head around, it’s beautiful to see the world onnected in such a way.



An Analysis of the World Ecoregions and Their Protected Areas

As you can tell, I love ecoregions.

I am also profficient in programming with R and Python, and for a Python coding class I did a spatial analysis on the world’s ecoregions and protected areas. Which ecoregions around the world have their extents covered by Protected Areas? Which ecoregions have little to no protection? Are there any trends in which biomes are better protected than others?

Ecoregions that are interesting and flashy like Tundra and Mangroves are generally offered protections over biomes that are thought of as less interesting, or are easier for humans to develop like grasslands and dry forest.

Understanding these trends can help us assess which ecoregions and biomes around the world are being left behind in terms of protections. Where do we focus our efforts?        
                           
One day, I would love to recreate these visualizations in ArcGIS to make them more visually appealing and understandable for wider audiences.


One Child One Tree - Mwana Tera Igiti


Although not spatial data analysis, this is a project I wanted to include because I think it demonstrates the power of science communication and its importance.

For my senior undergraduate capstone project, I was 1 of 10 students selected to complete the senior capstone requirement with a client in Kigali, Rwanda — One Child One Tree, or Mwana Tera Igiti in the native langauge Knyarwanda.

One Child One Tree (OCOT) is a non-profit organization based out of the University of Kigali Mental Health and Behavior Research Group that wants to research and bolster the community cohesion, knowledge of environmental science, and intrinsic aspiration of children throughout the country of Rwanda through tree-planting at elementary schools.

Intrinsic aspiration is an individual’s belief that they can successfully contribute to personal and community growth. Within the case of Rwanda, the genocide against the Tutsi of 1994 left Rwanda deeply divided, with communities destroyed and countless lives lost throughout the entire country.

It is an event that the country is still rebuilding from, and communicating its history to the youth of Rwanda leaves communities fractured. The University of Rwanda wants to understand how to best develop community cohesion among its youth while encouraging them that they can grow up to make positive differences in their country.

Enter One Child One Tree, where researchers supply elementary schools with lesson plans on environmental science — specifically on the forest ecosystems of Rwanda — and trees for children to choose and plant together on school property. These
child-planted forests are called “Children’s Forests” by OCOT,
and are taken care of by the larger school community over time.
It’s a project all children contribute to, where they learn the
value of their individual and communal efforts through
environmental science and stewardship!

My capstone team was tasked with researching Rwandan
ecology, culture, and history to develop lesson plans to
disseminate to different elementary schools across the nation
under their Environmental Education system. We visited
Kigali and met with school teachers, school children, and interviewed them on how these lesson plans could be most
helpful to them.  

In our lesson plans, we developed environmental science
curricula  and visualizations and activities to accompany
the lessons. We wanted to make them engaging and absorbable
for the children, but also to get them to think about their role
in the larger community and the impact they can make!

Through our lesson plans, One Child One Tree recieved new
funding for the continuation of their program! They are
expanding to more schools throughout the country, and the
number of children’s forests are growing — literally!

This project reminds me that communicating science to larger audiences is incredibly important for a number of reasons. Not only are children being taught how their local ecosystems work, but they’re also taught to care for them and that their impact matters. I hope to continue to communicate science and the importance of understanding our environment throughout my professional career!