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Date of publication: April 4, 2022

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Date of publication: April 4, 2022

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Canopy Chlorophyll Content for the Netherlands

by Elnaz Neinavaz

Canopy chlorophyll Content (CCC) is the total amount of chlorophyll a and b pigments in a contiguous group of plants per unit ground area often expressed in mg/m2 (Gitelson et al., 2005). It is a product of leaf chlorophyll content (i.e., the chlorophyll content of a fresh green leaf divided by its one-side area (µmg/cm2)) and the leaf area index. CCC is a terrestrial ecosystem functional EBV that describes the distribution of chlorophyll pig ...(continue reading)

Data: netCDF (5.18GB)
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Canopy Chlorophyll ContentSentinel-2Netherlandse-shapeRemote Sensing-EBVs

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Canopy chlorophyll Content (CCC) is the total amount of chlorophyll a and b pigments in a contiguous group of plants per unit ground area often expressed in mg/m2 (Gitelson et al., 2005). It is a product of leaf chlorophyll content (i.e., the chlorophyll content of a fresh green leaf divided by its one-side area (µmg/cm2)) and the leaf area index. CCC is a terrestrial ecosystem functional EBV that describes the distribution of chlorophyll pigments within the 3D canopy surface. Thus, This defines the total photosynthetically active radiation absorbed by the canopy (Gitelson et al., 2003; Ustin et al., 2009). The chlorophyll content is thought to be one of a constellation of co-evolved traits that vary together across species in relation to contrasting environmental conditions (Reich et al., 2003). Monitoring the dynamics of the CCC helps to understand the adaptation of forest, crop, and other plant canopies to such factors (Feret et al. 2017). As a result, the amount and spatial distribution of chlorophyll content is vital for measuring and understanding plant growth, ecosystem primary productivity and ecosystem dynamics. The canopy chlorophyll products for the Netherlands on monthly basis are generated under Showcase. 4, pilot 4.3. myVARIABLE of the e-shape project, which commits to the biodiversity conservation requirements, inter alia, and assess the status and trends of biodiversity. In this context, GEO BON, one of the flagships of GEO, is developing the framework of the Essential Biodiversity Variables (EBVs). The EBVs are a minimum set of complementary measurements that capture major dimensions of biodiversity change and are produced by integrating primary observations, (from e.g. in-situ monitoring or remote sensing), in space and time. Canopy chlorophyll content is considered as remote sensing biodiversity products by remote sensing and ecology communities. Féret, J, B., A.A. Gitelson, S.D. Noble, S. Jacquemoud PROSPECT-D: towards modeling leaf optical properties through a complete lifecycle Remote Sens. Environ., 193 (2017), pp. 204-215 Gitelson, A.A, Andrés Viña Verónica Ciganda Donald C. Rundquist Timothy J. Arkebauer (2005), Remote estimation of canopy chlorophyll content in crops. Geophysical Research Letters 32(8). https://doi.org/10.1029/2005GL022688 Gitelson, A. A., Vina, A., Arkebauer, T. J., Rundquist, D. C., Keydan, G., & Leavitt, B. (2003). Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters, 30(5), 52–54. Retrieved from http://www.sciencedirect.com/science/article/B6WPY-49H70PP-497/2/4cd9159e3f39a07a15c0f430abd8bbd4 Reich, P. B., Buschena, C., Tjoelker, M. G., Wrage, K., Knops, J., Tilman, D. & Machado, J. L. 2003. Variation in growth rate and ecophysiology among 34 grassland and savanna species under contrasting N supply: a test of functional group differences. New Phytologist, 157, 617-631. Ustin, S. L., Gitelson, A. A., Jacquemoud, S., Schaepman, M., Asner, G. P., Gamon, J. A., & Zarco-Tejada, P. (2009). Retrieval of foliar information about plant pigment systems from high-resolution spectroscopy. Remote Sensing of Environment, 113(Supplement 1), S67–S77. Retrieved from http://www.sciencedirect.com/science/article/B6V6V-4W7RJYR-1/2/58a4cb652674c7aea4caed7df189aacc.
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Sentinel-2A images with 10-meter resolution acquired in 2020 (from January to November) on the monthly basis, on a relatively cloud-free date(s), (< 10% cloud cover), and were used to predict the CCC for the Netherlands. For retrieval of the CCC, two simple ratio vegetation indices optimized for forests and non-forest vegetation were applied (Ali et al., 2020a; Ali et al., 2020b). Ali, A. M., Darvishzadeh, R., Skidmore, A., Heurich, M., Paganini, M., Heiden, U., & Mücher, S. (2020a). Evaluating prediction models for mapping canopy chlorophyll content across biomes. Remote Sensing, 12(11), 1788. Ali, A. M., Darvishzadeh, R., Skidmore, A., Gara, T. W., O’Connor, B., Roeoesli, C., ... & Paganini, M. (2020b). Comparing methods for mapping canopy chlorophyll content in a mixed mountain forest using Sentinel-2 data. International Journal of Applied Earth Observation and Geoinformation, 87, 102037. geotiff dataset download links: https://dikke.itc.utwente.nl:5001/sharing/XhROrVF8C, https://dikke.itc.utwente.nl:5001/sharing/dxpmUlfuo, https://dikke.itc.utwente.nl:5001/sharing/RdBnKbdFD, https://dikke.itc.utwente.nl:5001/sharing/FMalUW5qF, https://dikke.itc.utwente.nl:5001/sharing/RvrQrrhVg, https://dikke.itc.utwente.nl:5001/sharing/EBG9k7cb1, https://dikke.itc.utwente.nl:5001/sharing/77pz5Puc5, https://dikke.itc.utwente.nl:5001/sharing/z2wGyLyns, https://dikke.itc.utwente.nl:5001/sharing/mkNTzdjL2, https://dikke.itc.utwente.nl:5001/sharing/KxinWzVUi, https://dikke.itc.utwente.nl:5001/sharing/iH6z73q8K, https://dikke.itc.utwente.nl:5001/sharing/9TqcI5l5T
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The email of the person or other creator type principally responsible for creating this data. e.neinavaz@utwente.nl
e.neinavaz@utwente.nl
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Please select the CC license from the list. We recommend the use of CC BY 4.0

Essential Biodiversity Variables

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Genetic composition
Intraspecific genetic diversity
Genetic differentiation
Effective population size
Inbreeding
Other
Species populations
Species distributions
Species abundances
Other
Species traits
Morphology
Physiology
Phenology
Movement
Other
Community composition
Community abundance
Taxonomic and phylogenetic diversity
Trait diversity
Interaction diversity
Other
Ecosystem functioning
Primary productivity
Ecosystem phenology
Ecosystem disturbances
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Ecosystem structure
Live cover fraction
Ecosystem distribution
Ecosystem Vertical Profile
Other
Ecosystem services
Pollination
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Cross-cutting

Biological entity

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Scenario

Spatial domain

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Sub-national/Local
Name of the continent/region/country/area, separated by comma
southWest lat: 5622120, lon: 523740
northEast lat: 5942330, lon: 798180

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decadal
annually
monthly
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daily
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Environmental domain *

Terrestrial
Marine
Freshwater
Miscellaneous information about the data, not captured elsewhere. E-shape is a unique initiative that brings together decades of public investment in Earth Observation and in cloud capabilities into services for the decision-makers, the citizens, the industry and the researchers. It allows Europe to position itself as global force in Earth observation by leveraging Copernicus, making use of existing European capacities and improving user uptake of the data from GEO assets. In the e-shape initiative, 27 cloud-based pilot applications under the seven thematic areas address societal challenges, foster entrepreneurship and support sustainable development, in alignment to the three main GEO priorities (e.g., SDGs, Paris Agreement and Sendaï Framework).