About Dion Kucera

I’m a remote-sensing/GIS scientist who helps cities, NGOs, and research teams turn satellite data into urban decisions. My work focuses on NDVI, LST, vegetative cooling, urban heat, and equity mapping from neighborhood scale to global time-series. I have more than 9 years’ experience with GIS workflows.

Text reading 'PhD • 9+ years' experience' with a graduation cap icon.
Icon of an open book next to the text 'Peer-Reviewed Publications'
Text reading 'Landsat, Sentinel, and More' with satellite icons
Icon of a document with a checkmark next to the text 'Policy-Relevant Output'.

Background

  • Ph.D. Plant Biology - urban ecology/plant ecology concentration - UC Riverside 2024

  • M.S. Environmental Science - applied ecology concentration - Indiana University (Bloomington) 2016

  • B.S. Environmental Science - cum laude - energy and climate concentration - Cal Poly Humboldt 2014

  • 2024–2025 - Postdoc at UC Riverside performing large-scale (spatial and temporal) socioecological analyses using Landsat/Sentinel and ancillary data.

Examples of What I Can deliver

  • Urban heat & canopy planning: NDVI/LST diagnostics, equity overlays, and priority planting zones.

  • Long-term trends (1985–present): Landsat/Sentinel time-series with confidence and drivers.

  • Invasive species mapping: Sentinel-2 classifications with accuracy assessment and change detection.

  • WUI fire & burn severity: MTBS × urban extent overlap, recurrence, and spatial drivers.


    Outputs are policy-ready with maps, concise briefs, and optional web dashboards. Reproducible code is available on request so your team can rerun and extend.

Why this matters
Cities are warming, budgets are tight, and equity gaps are real. My goal is to make complex remote sensing simple and actionable so you can target interventions where they’ll have the greatest impact.

Selected Case Studies

Map of the United States showing income-NDVI data with yellow circles indicating standard deviations and red dots showing negative income-NDVI. The legend explains the size of circles correlating with STD deviations, ranging from less than -1.5 to greater than 2.5. The map includes a scale bar for kilometers and sources at the bottom.

National-scale Luxury Effect Analysis

A full list of peer-reviewed published works can be found at Google Scholar.

A young man with dark, curly hair, wearing a navy blue polo shirt, standing outdoors in front of green plants, smiling at the camera.
Satellite image of a large body of water with various inlets and connecting waterways, surrounded by agricultural land and urban areas.

How I work

  1. Define the decision. We clarify the question and who needs to act on the results.

  2. Build & validate. I assemble a transparent pipeline (GEE/ArcGIS/Python), with QA/QC and clear assumptions.

  3. Deliver for action. You get a short, defensible brief and visuals your stakeholders can use immediately.

Map of El Paso, TX, showing census tracts color-coded by their mean ordinal priority index for tree planting prioritization. The map includes a compass arrow pointing north, scale bar in kilometers, and labels for various neighborhoods and landmarks.

El Paso tree-planting priority index (ongoing)

Satellite image of a coastal area with red and orange landmasses, blue water bodies, and several small white spots in the water resembling boats or buoys.
Map of the greater Los Angeles urban region showing NDVI vegetation index levels, with areas colored in varying shades of green indicating plant health and coverage.

Los Angeles Multi-decadal Greenness/Temperature Study

Contact me

Tell me a bit about your project so I can prep before we talk:

  • Area of interest / location

  • Service you need (or your question)

  • Desired timeline (ASAP, <1 month, 1–3 months)

  • Anything you’ve already tried or datasets you have

Prefer email?