Articles | Volume 21, issue 2
https://doi.org/10.5194/bg-21-473-2024
https://doi.org/10.5194/bg-21-473-2024
Reviews and syntheses
 | 
25 Jan 2024
Reviews and syntheses |  | 25 Jan 2024

Reviews and syntheses: Remotely sensed optical time series for monitoring vegetation productivity

Lammert Kooistra, Katja Berger, Benjamin Brede, Lukas Valentin Graf, Helge Aasen, Jean-Louis Roujean, Miriam Machwitz, Martin Schlerf, Clement Atzberger, Egor Prikaziuk, Dessislava Ganeva, Enrico Tomelleri, Holly Croft, Pablo Reyes Muñoz, Virginia Garcia Millan, Roshanak Darvishzadeh, Gerbrand Koren, Ittai Herrmann, Offer Rozenstein, Santiago Belda, Miina Rautiainen, Stein Rune Karlsen, Cláudio Figueira Silva, Sofia Cerasoli, Jon Pierre, Emine Tanır Kayıkçı, Andrej Halabuk, Esra Tunc Gormus, Frank Fluit, Zhanzhang Cai, Marlena Kycko, Thomas Udelhoven, and Jochem Verrelst

Related authors

FEATURE FILTERING AND SELECTION FOR DRY MATTER ESTIMATION ON PERENNIAL RYEGRASS: A CASE STUDY OF VEGETATION INDICES
G. T. Alckmin, L. Kooistra, A. Lucieer, and R. Rawnsley
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1827–1831, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1827-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-1827-2019, 2019
AUTOMATIC APPLE TREE BLOSSOM ESTIMATION FROM UAV RGB IMAGERY
A. Tubau Comas, J. Valente, and L. Kooistra
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 631–635, https://doi.org/10.5194/isprs-archives-XLII-2-W13-631-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-631-2019, 2019
OPPORTUNITIES OF UAVS IN ORCHARD MANAGEMENT
C. Zhang, J. Valente, L. Kooistra, L. Guo, and W. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 673–680, https://doi.org/10.5194/isprs-archives-XLII-2-W13-673-2019,https://doi.org/10.5194/isprs-archives-XLII-2-W13-673-2019, 2019
DETECTING RUMEX OBTUSIFOLIUS WEED PLANTS IN GRASSLANDS FROM UAV RGB IMAGERY USING DEEP LEARNING
J. Valente, M. Doldersum, C. Roers, and L. Kooistra
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2-W5, 179–185, https://doi.org/10.5194/isprs-annals-IV-2-W5-179-2019,https://doi.org/10.5194/isprs-annals-IV-2-W5-179-2019, 2019
ASSESSING CHANGES IN POTATO CANOPY CAUSED BY LATE BLIGHT IN ORGANIC PRODUCTION SYSTEMS THROUGH UAV-BASED PUSHBROOM IMAGING SPECTROMETER
M. H. D. Franceschini, H. Bartholomeus, D. van Apeldoorn, J. Suomalainen, and L. Kooistra
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W6, 109–112, https://doi.org/10.5194/isprs-archives-XLII-2-W6-109-2017,https://doi.org/10.5194/isprs-archives-XLII-2-W6-109-2017, 2017

Related subject area

Remote Sensing: Terrestrial
Remote sensing reveals fire-driven enhancement of a C4 invasive alien grass on a small Mediterranean volcanic island
Riccardo Guarino, Daniele Cerra, Renzo Zaia, Alessandro Chiarucci, Pietro Lo Cascio, Duccio Rocchini, Piero Zannini, and Salvatore Pasta
Biogeosciences, 21, 2717–2730, https://doi.org/10.5194/bg-21-2717-2024,https://doi.org/10.5194/bg-21-2717-2024, 2024
Short summary
Divergent biophysical responses of western United States forests to wildfire driven by eco-climatic gradients
Surendra Shrestha, Christopher A. Williams, Brendan M. Rogers, John Rogan, and Dominik Kulakowski
Biogeosciences, 21, 2207–2226, https://doi.org/10.5194/bg-21-2207-2024,https://doi.org/10.5194/bg-21-2207-2024, 2024
Short summary
Synergistic use of Sentinel-2 and UAV-derived data for plant fractional cover distribution mapping of coastal meadows with digital elevation models
Ricardo Martínez Prentice, Miguel Villoslada, Raymond D. Ward, Thaisa F. Bergamo, Chris B. Joyce, and Kalev Sepp
Biogeosciences, 21, 1411–1431, https://doi.org/10.5194/bg-21-1411-2024,https://doi.org/10.5194/bg-21-1411-2024, 2024
Short summary
Data-based investigation of the effects of canopy structure and shadows on chlorophyll fluorescence in a deciduous oak forest
Hamadou Balde, Gabriel Hmimina, Yves Goulas, Gwendal Latouche, Abderrahmane Ounis, and Kamel Soudani
Biogeosciences, 21, 1259–1276, https://doi.org/10.5194/bg-21-1259-2024,https://doi.org/10.5194/bg-21-1259-2024, 2024
Short summary
Evaluation of five models for constructing forest NPP–age relationships in China based on 3121 field survey samples
Peng Li, Rong Shang, Jing M. Chen, Mingzhu Xu, Xudong Lin, Guirui Yu, Nianpeng He, and Li Xu
Biogeosciences, 21, 625–639, https://doi.org/10.5194/bg-21-625-2024,https://doi.org/10.5194/bg-21-625-2024, 2024
Short summary

Cited articles

Aasen, H., Honkavaara, E., Lucieer, A., and Zarco-Tejada, P.: Quantitative Remote Sensing at Ultra-High Resolution with UAV Spectroscopy: A Review of Sensor Technology, Measurement Procedures, and Data Correction Workflows, Remote Sens., 10, 1091, https://doi.org/10.3390/rs10071091, 2018. a, b
Abbas, S., Nichol, J. E., and Wong, M. S.: Trends in vegetation productivity related to climate change in China's Pearl River Delta, PLOS ONE, 16, e0245467, https://doi.org/10.1371/journal.pone.0245467, 2021. a
Abdi, A. M., Carrié, R., Sidemo-Holm, W., Cai, Z., Boke-Olén, N., Smith, H. G., Eklundh, L., and Ekroos, J.: Biodiversity decline with increasing crop productivity in agricultural fields revealed by satellite remote sensing, Ecol. Indic., 130, 108098, https://doi.org/10.1016/j.ecolind.2021.108098, 2021. a
Aleissaee, A. A., Kumar, A., Anwer, R. M., Khan, S., Cholakkal, H., Xia, G.-S., and Khan, F. S.: Transformers in Remote Sensing: A Survey, Remote Sens., 15, 1860, https://doi.org/10.3390/rs15071860, 2023. a
Alexandrov, G. A. and Matsunaga, T.: Normative productivity of the global vegetation, Carbon Balance Manage., 3, 1–13, https://doi.org/10.1186/1750-0680-3-8, 2008. a
Short summary
We reviewed optical remote sensing time series (TS) studies for monitoring vegetation productivity across ecosystems. Methods were categorized into trend analysis, land surface phenology, and assimilation into statistical or dynamic vegetation models. Due to progress in machine learning, TS processing methods will diversify, while modelling strategies will advance towards holistic processing. We propose integrating methods into a digital twin to improve the understanding of vegetation dynamics.
Altmetrics
Final-revised paper
Preprint