Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 353

The DOI matches its Crossref record; 145 of the 145 references it cites were found in a registry or an index.

Remote sensing in forestry: current challenges, considerations and directions

Open access
Fassnacht, Fabian Ewald, White, Joanne C, Wulder, Michael A, Næsset, Erik·2024·Forestry: An International Journal of Forest Research

Abstract

Remote sensing has developed into an omnipresent technology in the scientific field of forestry and is also increasingly used in an operational fashion. However, the pace and level of uptake of remote sensing technologies into operational forest inventory and monitoring programs varies notably by geographic region. Herein, we highlight some key challenges that remote sensing research can address in the near future to further increase the acceptance, suitability and integration of remotely sensed data into operational forest inventory and monitoring programs. We particularly emphasize three recurrent themes: (1) user uptake, (2) technical challenges of remote sensing related to forest inventories and (3) challenges related to map validation. Our key recommendations concerning these three thematic areas include (1) a need to communicate and learn from success stories in those geographic regions where user uptake was successful due to multi-disciplinary collaborations supported by administrative incentives, (2) a shift from regional case studies towards studies addressing ‘real world’ problems focusing on forest attributes that match the spatial scales and thematic information needs of end users and (3) an increased effort to develop, communicate, and apply best-practices for map and model validation including an effort to inform current and future remote sensing scientists regarding the need for and the functionalities of these best practices. Finally, we present information regarding the use of remote sensing for forest inventory and monitoring, combined with recommendations where possible, and highlighting areas of opportunity for additional investigation.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/forestry/cpad024

Cites

145 of 145 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 145 references

Metadata

Authors
Fassnacht, F. E., White, J. C., Wulder, M. A., & Næsset, E.
Venue
Forestry: An International Journal of Forest Research
Published
2023-05-10
Volume
97
Issue
1
Pages
11-37
ISSN
  • 0015-752X (ISSN-L)
  • 1464-3626
OpenAlex
W4376139050
Cited by
353
References
145
FWCI
29.40
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Remote sensing in forestry: current challenges, considerations and directions. https://app.cochat.ai/papers/10.1093/forestry/cpad024
The paper
Fassnacht, F. E., White, J. C., Wulder, M. A., & Næsset, E. (2024). Remote sensing in forestry: current challenges, considerations and directions. Forestry: An International Journal of Forest Research. https://doi.org/10.1093/forestry/cpad024

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.