Cardille Computational Landscape Ecology Lab
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Research

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My research focuses on understanding environmental change by studying the causes and consequences of spatial variation in ecological processes. 
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Here are some of the major research themes and associated projects you might like to know more about:

Advanced Remote Sensing and Change Detection Algorithms

This area focuses on developing novel algorithms and methodologies to interpret satellite data for monitoring stability and change across large spatial and temporal scales.
The variants of BULC : Bayesian Updating of Land Cover​

SAR

Other Remote Sensing and Change Detection projects
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General Overview
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 Geo-AI and Next-Generation Geospatial Science

​Our lab advances Geo-AI and next-generation geospatial science by integrating Large Language Models into remote sensing research and education. The studies highlighted here focus on rigorously evaluating AI performance and trustworthiness in complex geospatial analysis, positioning Geo-AI as a scalable and accountable tool for future geospatial science.
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Related Papers

  • Cardille et al., 2025 --  Cloud-Based Geospatial Benchmark and LLM evaluation
  • Aygün et al., 2025 --  AI system to help scientists write empirical software

Aquatic Remote Sensing and Lake Health

Through a few of the studies highlighted here, we demonstrate how satellite and UAV observations, combined with robust statistical and computational approaches, can be used to quantify key physical, thermal, optical, and biogeochemical lake properties, including water clarity, dissolved organic matter, surface temperature, ice phenology, and algal blooms. These papers position aquatic remote sensing as a scalable and policy-relevant framework for lake health assessment, supporting climate change research, large-area monitoring, and conservation prioritization.
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Related Papers
  • Korver et al., 2024 – Surface water temperature observations and ice phenology estimations for 1.4 million lakes globally.
  • Deutsch et al., 2022 – Assessing the current water clarity status of ~100,000 lakes across southern Canada : A remote sensing approach
  • Danaher et al., 2022 – Prioritizing conservation in sub-Saharan African lakes based on freshwater biodiversity and algal bloom metrics
  • Koll-Egyed* T, et al., 2021. Multiple images improve lake CDOM estimation: building better Landsat 8 empirical algorithms across southern Canada.
  • Deutsch* ES, et al., 2021 -- Landsat 8 lake water clarity empirical algorithms: large-scale calibration and validation using government and citizen science data from across Canada.

​Landscape Ecology and Land-use Planning

Research in this theme examines how ecological processes operate within landscapes shaped by rapid land-use change, and increasing environmental pressures. The work focuses on translating landscape ecology and geospatial analysis into decision-relevant tools that support land-use planning, conservation policy, and climate adaptation. Projects address ecological connectivity and wildlife corridors, protected-area expansion strategies, and coastal exposure to sea-level rise, producing spatial outputs that can be directly integrated into planning, policy, and long-term environmental management.
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Related Papers
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  • Willard-Stepan et al., 2025 -- Assessing the exposure of buildings to long-term sea level rise across the Global South
  • Crowley MA & Cardille JA, 2020 -- Remote sensing’s recent and future contributions to landscape ecology.
  • Parrot L et al., 2019 -- Planning for ecological connectivity across scales of governance in a multifunctional regional landscape
  • ​Wulder et al., 2018 -- Context and Opportunities for Expanding Protected Areas in Canada​​

Books

This section highlights authored and edited books that support education and practice in remote sensing, landscape ecology, and geospatial analysis. These works combine conceptual foundations with hands-on, reproducible workflows, emphasizing accessibility, rigorous review, and real-world application. Together, they provide resources for students, researchers, and practitioners seeking to understand environmental patterns and processes across scales, from introductory spatial analysis and landscape metrics to advanced cloud-based remote sensing and large-scale Earth observation applications.
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Related Links
  • Cardille et al., 2023 --  Cloud-Based Remote Sensing with Google Earth Engine
  • Cardille, J.A. & Turner, 2017 -- Learning Landscape Ecology, 2nd edition – co-authored chapters with lab guides

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Full list of Publications
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  • Home
  • Research
    • Remote Sensing & Change Detection
    • Geo-AI
    • Aquatic
    • Landscape Ecology
    • Books
  • Team
    • Current lab members
    • Past lab members
    • Invitation To Students
    • Funding
  • Courses
  • Publications
  • Service
  • Contact