Remote sensing · Land change science

Shi Qiu 邱实

Assistant Research Professor

Department of Natural Resources and the Environment
University of Connecticut

Understanding a changing Earth.
Building the algorithms to observe it.

I study land change and develop remote sensing algorithms, with a focus on cloud detection, satellite time series, and physics-informed machine learning.

Email ↗Google Scholar ↗ORCID ↗
Shi Qiu outdoors beside a waterfall and rocky gorge
Shi Qiu · University of ConnecticutLand change & remote sensing
Science into practiceAlgorithms, observations, and open research tools
2,598 citationsGoogle Scholar · CV snapshot, August 2026
30 m · 35 yearsU.S. land disturbance mapping, 1988–2022
01 / Research

Observing change. Explaining why.

01 — LAND

Land disturbance
& environmental change

Mapping where, when, and how landscapes change. My work characterizes disturbance agents and the changing roles of human activity and natural processes across the United States.

Land changeDisturbance agents
02 — CLOUD

Cloud detection
& physics-informed AI

Developing cloud, shadow, and cirrus detection algorithms for Landsat and Sentinel-2. Fmask supports quality assessment in NASA’s Harmonized Landsat Sentinel-2 products.

FmaskMachine learning
03 — TIME

Consistent observations
& satellite time series

Improving image compositing, preprocessing, and the consistency of satellite records to support reliable monitoring of Earth’s surface over time.

LandsatTime-series analysis
02 / Publications

Research in print

Google Scholar ↗

* Corresponding author · Search links open Google Scholar unless a publisher link is available.34 entries

2026

Physics-informed machine learning for cloud detection

Qiu S.*, Zhu Z.*, Yang X., Ju J., Zhou Q., Neigh C.

Remote Sensing of Environment, 347, 115672, 2026. Has been selected as the cloud detection algorithm for the next collection of NASA’s Harmonized Landsat Sentinel-2.

Journal article
↗
2026

Satellite imagery reveals increasing volatility in human nighttime activity

Li, T.*, Wang, Z., Kyba, C. C. M., Román, M. O., Seto, K. C., Yang, Y., Qiu, S., Kuester, T., Fragkias, M., Chen, X., Meyer, T. H., Rittenhouse, C. D., Tai, X., Cullerton, M., Hong, F., Grinstead, A., Song, K., Suh, J. W., Yang, X., Kalb, V. L., Deng, C., Zhu, Z.*

Nature, 652, 379–386, 2026

Journal article
↗
2023

Evaluation of Landsat image compositing algorithms

Qiu, S.*, Zhu, Z.*, Olofsson P., Woodcock C.E., and Jin S.

Remote Sensing of Environment, 285: 113375, 2023. One of the benchmarks of the development of Google AlphaEarth Satellite Embedding Dataset.

Journal article
↗
—

Satellite evidence of pandemic-induced changes in human activities

Qiu S.* et al.

In preparation

In preparation
—

Pitfalls and best practices in dense Earth observation time series

Zhu Z.*, Qiu S.* et al.

Nature Reviews Earth & Environment. In preparation. Invited review article.

In preparation
—

Satellite data reveal the structural reshaping of U.S. urbanization by the Great Recession

Hong F.*, Seto K., Deng C., Qiu S., Fragkias M., Suh J.W., Zhu Z.*

Nature Cities, under 1st review

Under review
03 / Software & data

Tools for the research community

Fmask ↗

Cloud and cloud shadow detection for Landsat and Sentinel-2 imagery. Adopted in NASA’s HLS processing.

Python · MATLAB / Cloud detection

COLD 2.0 & ODACA ↗

Continuous monitoring of land disturbance and object-based classification of disturbance agents.

MATLAB · Python / Land change

MFmask ↗

Cloud and cloud shadow detection designed specifically for mountainous landscapes.

MATLAB / Mountainous terrain

Cmask ↗

Cirrus cloud masking using time-series observations from the Landsat cirrus band.

MATLAB / Cirrus detection

Preprocessing tools ↗

BRDF normalization and topographic correction for consistent satellite observations.

MATLAB · Python / Image processing

Landsat 7 orbit drift ↗

Analysis and reporting on the implications of orbital drift for Landsat 7’s science capability.

Scientific report / Landsat

35 years of U.S. land disturbance

Explore the 30 m U.S. Land Disturbance Agent Dataset, 1988–2022.

Explore the interactive map ↗

30 m Global Land Disturbance Dataset (2018–2023): available upon request.

04 / Academic life

Experience & teaching

Download full CV (DOCX) ↓

Appointments

Assistant Research Professor

University of Connecticut
Natural Resources and the Environment

Postdoctoral Research Associate

University of Connecticut
Natural Resources and the Environment

Visiting Research Assistant

Texas Tech University · Geosciences

Visiting Scholar

Texas Tech University · Geosciences

Education

Ph.D. in Remote Sensing

University of Electronic Science and Technology of China

B.E. in Spatial Information & Digital Technology

Chengdu University of Technology

In the classroom

Remote Sensing Image Processing

Instructor · University of Connecticut

Climate Change Adaptation Science

Guest Instructor · Land disturbance monitoring using remote sensing

Remote Sensing of Environment

Instructor · University of Connecticut

Remote Sensing of Environment

Guest Instructor · Cloud detection in optical remote sensing imagery

Mentoring

M.S. dissertation and guiding committee for Mari Cullerton (2022–2024), Department of Natural Resources and the Environment, University of Connecticut.

Methods & computing

Python, MATLAB, C#, Java, JavaScript
Google Earth Engine, HPC, ArcGIS, QGIS, ENVI

05 / Sponsored research

Active research support

NASA · Co-PI

Enhancing Spatial and Temporal Capabilities of NASA HLS and SLI Data

May 2026–August 2030 · Total award: $935,536

NASA · Co-PI

Operational cloud detection algorithm for NASA’s Harmonized Landsat Sentinel-2

August 2025–July 2027 · Total award: $60,000

USDA · Co-PI

Mapping understory vegetation change using animal- and space-borne sensor

October 2024–September 2027 · Total award: $60,000

NASA · Co-I

Continuation and Improvement of a Moderate Spatial Resolution Data Record of 21st Century Global Land Cover and Land Cover Change

October 2025–October 2028 · Total award: $276,796

Past research support
  • NASA · Co-I · Improvements of QA band and new science data layers proposed for the NASA Harmonized Landsat and Sentinel-2 product. April 2023–March 2026 · Total award: $299,992.
  • Eversource · Co-PI · Estimating roadside tree risk to grid resilience and reliability using PlanetScope time series. September 2023–August 2025 · Total award: $88,000.

Amounts represent total project awards. Pending proposals are listed separately in the full CV.

06 / Community

Service & recognition

Professional & university service

  • NASA HLS Science Group · 2025–present
  • Editorial board, Remote Sensing of Environment · 2023–present
  • NRE Graduate Program/Admission Committee, UConn · 2024–present
  • NRE Seminar Committee, UConn · 2024–2026
  • Session convener · AGU 2025, remote sensing data fusion, time series, and AI; AAG 2024, land change using satellite time series

Honors & reviewing

  • Best reviewer, Remote Sensing of Environment
    2023 (#2), 2021 (#17), and 2020 (#17)
  • National Scholarship · University of Electronic Science and Technology of China, 2017
  • Outstanding Student Award · Chengdu University of Technology, 2011 and 2009
  • Journal reviewer for Science, Remote Sensing of Environment (80+ assignments), IEEE Transactions on Geoscience and Remote Sensing, and other journals.
Selected presentations & posters
  • Satellite evidence for a shift from human-directed to wild disturbances in the US · AGU 2025, New Orleans · Talk
  • Physics-informed machine learning for cloud detection · AGU 2025, New Orleans · Poster
  • Comparison of machine learning models for mapping medium-resolution land cover and land change · AAG 2024, Honolulu · Talk
  • Evaluation of Landsat image compositing algorithms · Pecora 22, Denver, 2022 · Talk
  • Detection and characterization of land disturbances based on Landsat time series · AGU 2021, New Orleans · Talk
07 / Contact

Let’s connect.

For research collaborations, questions about remote sensing algorithms, or data requests, please get in touch.

shi.qiu@uconn.edu ↗

Department of Natural Resources and the Environment
University of Connecticut · Storrs, CT, USA