Global leaf chlorophyll content product from MERIS imagery (GLOBMAP MERIS LCC)

<p>Leaf chlorophyll content (LCC) is an indicator of plant physiological function and is an important parameter in estimating the carbon and water fluxes of terrestrial ecosystems. Here, we produced a new global 7-day LCC product (GLOBMAP MERIS LCC) at 300-m resolution from 2003.01 to 2012.03 using a neural network model based on radiative transfer model simulations from CCI MERIS surface reflectance data.&nbsp;It shows an improvement over the previous MERIS LCC product in capturing LCC seasonal variations in different plant functional types.</p> <p><strong>The following paper should be cited when using the data:</strong><br>Xu, M., Liu, R., Chen, J.M., Shang, R., Liu, Y., Qi, L., Croft, H., Ju, W., Zhang, Y., He, Y., Qiu, F., Li, J., Lin, Q., 2022. Retrieving global leaf chlorophyll content from MERIS data using a neural network method. Isprs J. Photogramm. Remote Sens. 192, 66&ndash;82. <a href="https://doi.org/10.1016/j.isprsjprs.2022.08.003">https://doi.org/10.1016/j.isprsjprs.2022.08.003</a>.</p> <p><strong>Due to the data volume limitation of Zenodo, the data we uploaded here are an example tile (h59v10) at 300-m resolution and a&nbsp;global 0.05&deg; composition of multi-year average LCC with a 7-day interval</strong><strong>. The original dataset of&nbsp;GLOBMAP MERIS LCC product can be downloaded through Google Drive sharing link:</strong></p> <p><a href="https://drive.google.com/drive/folders/1HNlBI2hHeUAW-o7HCgLOxbUEh1ak4AX2?usp=sharing">https://drive.google.com/drive/folders/1HNlBI2hHeUAW-o7HCgLOxbUEh1ak4AX2?usp=sharing</a></p> <p><strong>Data format description:<br></strong>Data type: int16<br>Projection: GCS_WGS_1984<br>Scaling factor: 0.1<br>Unit: ug/cm2</p> <p><strong>Related dataset:&nbsp;</strong>Mingzhu Xu, Ronggao Liu, Jing M. Chen, Yang Liu, &amp; Rong Shang. (2021). Global leaf chlorophyll content (LCC) product from MODIS imagery (2000-2020) (Version V1) [Data set]. Zenodo. <a href="https://doi.org/10.5281/zenodo.5805575">https://doi.org/10.5281/zenodo.5805575</a></p> <p>For any other questions, please send email to Mingzhu Xu (<a href="mailto:xumzhu@gmail.com">xumzhu@gmail.com</a>).</p>