Maps
Mapping the world, one data point at a time
Crafting Spatial Narratives
My cartographic journey began with ArcGIS Pro, a powerful tool for transforming raw geospatial data into compelling visual stories. These maps highlight my ability to analyze complex datasets, from satellite imagery to demographic layers, revealing hidden patterns in landscapes and societies. Whether mapping vegetation health with NDVI indices or creating 3D relief models of rugged terrains, each project pushed the boundaries of design and functionality, blending science with artistry to communicate insights that drive informed decisions.
Through ArcGIS Pro, I've honed skills in geoprocessing, symbology, and layout design, ensuring every map is not just accurate but also intuitive and engaging. This foundation ignited my passion for spatial storytelling, inspiring me to explore how maps can bridge data and human experience.
Planetary-Scale Remote Sensing
As the scale of my questions grew, I moved into the cloud. Using Google Earth Engine (GEE), I harness petabytes of satellite imagery (Landsat, Sentinel, MODIS) to monitor environmental change over decades. By writing custom JavaScript API scripts, I bypass the limitations of local hardware to perform multi-spectral analysis, land-cover classification, and time-series monitoring at a global scale.
Orinoco Mining Arc Study
In this targeted GEE project, I analyzed the Orinoco Mining Arc in Venezuela, leveraging high-resolution satellite data to assess mining impacts on ecosystems. By integrating Landsat and Sentinel imagery with machine learning algorithms, I mapped NDVI, surface reflectance, RF classification, and forest loss, revealing the human footprint on one of the world's richest mineral regions. This work sharpened my expertise in environmental justice and policy-driven cartography, inspiring me to advocate for sustainable resource management through data-driven narratives.
Spatial Data Science
The peak of my spatial workflow is R and RStudio. Moving to a code-first approach allows for 100% reproducibility and the integration of advanced statistics into map-making. Using packages like sf, elevatr, terra, and rayshader, I treat every map as a statistical graphic, ensuring that the visual output is as mathematically rigorous as it is aesthetically compelling.
Socio-Economic Analytics & Global Trends
Beyond aesthetics, I use R to solve complex spatial problems. I focus on mapping human systems: modeling poverty through proxy data, analyzing maritime traffic density from AIS data, and visualizing local GDP. These maps are designed to inform policy and uncover the hidden spatial patterns of human activity.
The Path Ahead
My journey with cartography is always evolving. If you'd like to discuss the intersection of data and geography or need help visualizing spatial patterns, please feel free to email me at hi[at]pablohernandezb.dev.
