ReviewInternational journal of biometeorology2021
Cross-scale phenological monitoring in forest ecosystems: a content-analysis-based review.
Review in International journal of biometeorology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 9 citations in OpenAlex.
- Bridging data silos to holistically model plant macrophenology.The New phytologist · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
Phenology has been useful to better understand the climate-vegetation relationship, and it is considered an indicator of climate change impact. Phenological data have been generated through multiple remote sensing techniques and ground-based observations through professional or citizen science. The combination of both techniques is known as cross-scale phenological monitoring. However, no comparative analysis has been carried out to assess the advantages and disadvantages of each of these techniques to characterize the phenological cycle of forest ecosystem species. This work is a content-analysis-based review of scientific literature published between 2000 and 2018 related to cross-scale monitoring methods, to estimate the phenological variation in different forest ecosystems worldwide. For this study, 97 publications related to cross-scale phenological monitoring were selected. We found that 71% of the articles aimed to corroborate the data generated through satellite imagery using surface data from either phenocams, flux towers, or from citizen science networks. More publications were published by authors in the USA (30%), Canada (8%), and China (7%). The most commonly used vegetation index was the normalized difference vegetation index (65%). Some deficiencies in the evaluation of the phenological phases of autumn when compared with surface observations were found. Flux towers and phenocams were included as alternatives for ground-based monitoring. Cross-scale phenological monitoring has the potential to characterize the phenological response of vegetation accurately due to data combinations at two different observation scales. This work contributes to specifying the methodologies used in gathering phenological parameters of the world's forest ecosystems.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.