Author

Pratima Khatri‐Chhetri

Bay Area Environmental Research InstituteORCID 0000-0003-4689-2027Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Ecology· 2

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:imaging· 2 Approach:deep learning· 1 Research Focus:spatial domain detection· 1 Approach:statistical model· 1

Frequent Co-Authors

Alastair PottsiD· 1 shared Allan BurasiD· 1 shared Anette EltneriD· 1 shared Anna GöritziD· 1 shared Annett FrickiD· 1 shared Annette MenzeliD· 1 shared Antonia Dorea LudwigiD· 1 shared Arko LucieeriD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperEcology

Alastair PottsORCID

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2 papers

Recent·Most cited

EcologyRemote Sensing of EnvironmentPeer-reviewedJan 1, 2026

deadtrees.earth - An Open-Access and Interactive Database for Centimeter-Scale Aerial Imagery to Uncover Global Tree Mortality Dynamics

Clemens Mosig, Janusch Vajna-Jehle, Miguel D. Mahecha…·Marie‐Therese Schmehl

The paper introduces deadtrees.earth, an open-access database of high-resolution aerial imagery to map global tree mortality using community-sourced data and machine learning.

10 citations

imagingdeep learning

𝕏 PostBluesky

EcologybioRxivPreprintNov 19, 2025

Spatially explicit forest mortality forecasts are driven by autocorrelation, not ecological context

Keenan J. Ganz, Liz van Wagtendonk, Pratima Khatri‐Chhetri, L. Monika Moskal

This study shows that forest mortality forecasts using remote sensing data are driven by autocorrelation rather than ecological context, and highlights biases in aerial surveys.

1 citation

imagingstatistical model

𝕏 PostBluesky