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Sensors and Their Application in Phenological Studies
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Sensors and Their Application in Phenological Studies

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 4255

Special Issue Editors

Dr. Siddhartha Khare

E-Mail Website
Guest Editor
1. Department of Civil Engineering, Geomatics Engineering Specialization, Indian Institute of Technology Roorkee (IIT Roorkee), Roorkee, Uttarakhand 247667, India
2. Department of Biology, McGill University, Montreal, QC H3A 0G4, Canada
Interests: remote sensing; GIS; forestry; biodiversity; R programming
Prof. Dr. Sergio Rossi

E-Mail Website
Guest Editor
Département des Sciences Fondamentales, Université du Québec à Chicoutimi, Chicoutimi, QC G7H 2B1, Canada
Interests: quantitative ecology and ecophysiology; in particular on modelling the complex responses of plants to multiple environmental factors and predicting the phenological adaptation of trees to climate changes

Special Issue Information

Dear Colleagues,

The interest in phenological studies has experienced a surprising increase in the last decade, demonstrating the dramatic global effects of climate change on natural ecosystems. Phenology, and the timings of recurrent biological events, represents the close relationships between the organisms and their surrounding environment. Multispectral sensors mounted in remote or near-ground platforms can provide reliable data to estimate phenology at different time (from daily to annual) and spatial (from the individual to the landscape or the ecosystem) scales. 

The recent availability of visible, multispectral, and hyperspectral sensors offers new opportunities to detect phenology with high resolution and precision. The actual sensors installed for near-surface remote sensing, as well as airborne and satellite remote sensing, are able to collect information in wide spectral bands and capture broad-scale phenological patterns with a suitable degree of homogeneity and standardization. Under this perspective, we expect and welcome high-quality contributions on the evaluation and use of various sensors in phenological studies of plants and animals. Phenological records derived from visible, multispectral, and hyperspectral sensors are involved in numerous applications, including the fields of ecology, biogeography, climatology, forestry, agriculture, climate changes, and wildfire. This Special Issue brings together the recent advancements and development of sensors used for phenological studies. The topics include, but are not limited to, the following:

  1. Animal and plant phenology;
  2. Phenology at the level of individual, stand, community, ecosystem, or biome; 
  3. Comparison of satellite derived vegetation indices for vegetation phenology; 
  4. Comparison of time series visible, multispectral, and hyperspectral sensors;
  5. Relationship of sensor-derived phenology with direct or field observations; 
  6. Multi-scale and multi-temporal assessment of phenology;
  7. Phenological reconstructions based on sensor measurements;
  8. Sensor optimization;
  9. Calibration and validation of sensors for phenological investigations;
  10. Sensors and phenological networks;
  11. Technology and application of PhenoCams;
  12. Development of vegetation indices using sensors. 

Dr. Siddhartha Khare
Prof. Dr. Sergio Rossi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • phenology
  • multispectral
  • hyperspectral
  • time-series
  • PhenoCam
  • forestry
  • vegetation
  • temporal
  • optical satellite

Published Papers (2 papers)

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Research

8 pages, 1225 KiB  
Article
Towards an Automated Approach for Monitoring Tree Phenology Using Vehicle Dashcams in Urban Environments
by Doreen S. Boyd, Sally Crudge and Giles Foody
Sensors 2022, 22(19), 7672; https://doi.org/10.3390/s22197672 - 10 Oct 2022
Cited by 4 | Viewed by 1657
Abstract
Trees in urban environments hold significant value in providing ecosystem services, which will become increasingly important as urban populations grow. Tree phenology is highly sensitive to climatic variation, and resultant phenological shifts have significant impact on ecosystem function. Data on urban tree phenology [...] Read more.
Trees in urban environments hold significant value in providing ecosystem services, which will become increasingly important as urban populations grow. Tree phenology is highly sensitive to climatic variation, and resultant phenological shifts have significant impact on ecosystem function. Data on urban tree phenology is important to collect. Typical remote methods to monitor tree phenological transitions, such as satellite remote sensing and fixed digital camera networks, are limited by financial costs and coarse resolutions, both spatially and temporally and thus there exists a data gap in urban settings. Here, we report on a pilot study to evaluate the potential to estimate phenological metrics from imagery acquired with a conventional dashcam fitted to a car. Dashcam images were acquired daily in spring 2020, March to May, for a 2000 m stretch of road in Melksham, UK. This pilot study indicates that time series imagery of urban trees, from which meaningful phenological data can be extracted, is obtainable from a car-mounted dashcam. The method based on the YOLOv3 deep learning algorithm demonstrated suitability for automating stages of processing towards deriving a greenness metric from which the date of tree green-up was calculated. These dates of green-up are similar to those obtained by visual analyses, with a maximum of a 4-day difference; and differences in green-up between trees (species-dependent) were evident. Further work is required to fully automate such an approach for other remote sensing capture methods, and to scale-up through authoritative and citizen science agencies. Full article
(This article belongs to the Special Issue Sensors and Their Application in Phenological Studies)
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15 pages, 730 KiB  
Article
Characterizing Seasonal Radial Growth Dynamics of Balsam Fir in a Cold Environment Using Continuous Dendrometric Data: A Case Study in a 12-Year Soil Warming Experiment
by Shalini Oogathoo, Louis Duchesne, Daniel Houle and Daniel Kneeshaw
Sensors 2022, 22(14), 5155; https://doi.org/10.3390/s22145155 - 09 Jul 2022
Cited by 3 | Viewed by 1554
Abstract
Historical temperature records reveal that the boreal forest has been subjected to a significant lengthening of the thermal growing season since the middle of the last century, and climate models predict that this lengthening will continue in the future. Nevertheless, the potential phenological [...] Read more.
Historical temperature records reveal that the boreal forest has been subjected to a significant lengthening of the thermal growing season since the middle of the last century, and climate models predict that this lengthening will continue in the future. Nevertheless, the potential phenological response of trees to changes in growing season length remains relatively undocumented, particularly for evergreen boreal tree species growing in cold environments. Here, we used the recently defined zero growth (ZG) concept to extract and characterize the metrics of seasonal radial growth dynamics for 12 balsam fir trees subjected to a 12-year soil warming experiment using high resolution radius dendrometer measurements. The ZG concept provides an accurate determination of growth seasonality (onset, cessation, duration, growth rates, and total growth) for these slow-growing trees characterized by significant shrinkage in tree diameter due to dehydration in the winter. Our analysis revealed that, on average, growth onset starts at day 152 ± 7 (±1 SE, 31 May–1 June) and ceases at day 244 ± 27 (31 August–1 September), for a growing season duration of about 3 months (93 ± 26 days) over a 12-year period. Growing season duration is mainly determined by growth cessation, while growth onset varies little between years. A large part (80%) of the total growth occurs in the first 50 days of the growing season. Given the dynamics of growth, early growth cessation (shorter growing season) results in a higher average seasonal growth rate, meaning that longer growing seasons are not necessarily associated with greater tree growth. Soil warming induces earlier growth cessation, but increases the mean tree growth rate by 18.1% and the total annual growth by 9.1%, on average, as compared to the control trees. Our results suggest that a higher soil temperature for warmed trees contributes to providing better growth conditions and higher growth rates in the early growing season, when the soil temperature is low and the soil water content is elevated because of snowmelt. Attaining a critical soil temperature earlier, coupled with lower soil water content, may have contributed to the earlier growth cessation and shorter growing season of warmed trees. Full article
(This article belongs to the Special Issue Sensors and Their Application in Phenological Studies)
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