BACI: 2015-2019

TOWARDS A BIOSPHERE ATMOSPHERE CHANGE INDEX

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Earth Observation | Biodiversity Patterns | Essential Ecosystem Variables | In-situ Observations | Regional Validation | Biosphere Atmosphere Change Index | Socioecological Research | Machine Learning for Environmental Data

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Earth Observations

1Babst, F., Poulter, B., Bodesheim, P., Mahecha, M. D., Frank, D. C. (2017). Improved tree-ring archives will support earth-system science. Nature Ecology & Evolution, 1: 0008. doi:10.1038/s41559-016-0008.
Postprint available
2Disney, M., Muller, J.-P., Kharbouche, S., Kaminski, T., Voßbeck, M., Lewis, P., Pinty, B. (2016). A new global fAPAR and LAI dataset derived from optimal Albedo estimates: Comparison with MODIS products. Remote Sensing, 8(4): 275. doi:10.3390/rs8040275.
3Erb, K.-H., Fetzel, T., Plutzar, C., Kastner, T., Lauk, C., Mayer, A., Niedertscheider, M., Körner, C., Haberl, H. (2016). Biomass turnover time in terrestrial ecosystems halved by land use. Nature geoscience, 9, 674-678. doi:10.1038/ngeo2782.
Postprint available
4Flach, M., Gans, F., Brenning, A., Denzler, J., Reichstein, M., Rodner, E., Bathiany, S., Bodesheim, P., Guanche, Y., Sippel, S., Mahecha, M. D. (2017). Multivariate anomaly detection for Earth observations: a comparison of algorithms and feature extraction techniques. Earth System Dynamics, 8(3), 677-696. doi:10.5194/esd-8-677-2017.
5Hamunyela, E., Reiche, J., Verbesselt, J., Herold, M. (2017). Using Space-Time Features to Improve Detection of Forest Disturbances from Landsat Time Series. Remote Sensing, 9(6): 515. doi:10.3390/rs9060515.
6Joshi, N., Baumann, M., Ehammer, A., Fensholt, R., Grogan, K., Hostert, P., Rudbeck Jepsen, M., Kuemmerle, T., Meyfroidt, P., Mitchard, E. T. A., Reiche, J., Ryan, C. M., Waske, B. (2016). A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring. Remote Sensing, 8(1): 70. doi:10.3390/rs8010070.
7Jung, M., Reichstein, M., Schwalm, C. R., Huntingford, C., Sitch, S., Ahlström, A., Arneth, A., Camps-Valls, G., Ciais, P., Friedlingstein, P., Gans, F., Ichii, K., Jain, A. K., Kato, E., Papale, D., Poulter, B., Raduly, B., Rödenbeck, C., Tramontana, G., Viovy, N., Wang, Y.-P., Weber, U., Zaehle, S., Zeng, N. (2017). Compensatory water effects link yearly global land CO2 sink changes to temperature. Nature, 541(7638), 516-520. doi:10.1038/nature20780.
Postprint available
8Koirala, S., Jung, M., Reichstein, M., de Graaf, I. E. M., Camps-Valls, G., Ichii, K., Papale, D., Raduly, B., Schwalm, C. R., Tramontana, G., Carvalhais, N. (2017). Global distribution of groundwater-vegetation spatial covariation. Geophysical Research Letters, 44(9), 4134-4142. doi:10.1002/2017GL072885.
Posprint available
9Papale, D., Black, T. A., Carvalhais, N., Cescatti, A., Chen, J., Jung, M., Kiely, G., Lasslop, G., Mahecha, M. D., Margolis, H., Merbold, L., Montagnani, L., Moors, E., Olesen, J. E., Reichstein, M., Tramontana, G., van Gorsel, E., Wohlfahrt, G., Ráduly, B. (2015). Effect of spatial sampling from European flux towers for estimating carbon and water fluxes with artificial neural networks. Journal of Geophysical Research: Biogeosciences, 120(10), 1941-1957. doi:10.1002/2015JG002997.
Postprint available
10Reiche, J., de Bruin, S., Hoekman, D., Verbesselt, J., Herold, M. (2015). A Bayesian Approach to Combine Landsat and ALOS PALSAR Time Series for Near Real-Time Deforestation Detection. Remote Sensing, 7(5), 4973-4996. doi:10.3390/rs70504973.
11Reiche, J., Lucas, R., Mitchell, A. L., Verbesselt, J., Hoekman, D. H., Haarpaintner, J., Kellndorfer, J. M., Rosenqvist, A., Lehmann, E. A., Woodcock, C. E., Seifert, F. M., Herold, M. (2016). Combining satellite data for better tropical forest monitoring. Nature Climate Change, 6, 120-122. doi:10.1038/nclimate2919.
Postprint available
12Sippel, S., Lange, H., Mahecha, M. D., Hauhs, M., Bodesheim, P., Kaminski, T., Gans, F., Rosso, O. A. (2016). Diagnosing the dynamics of observed and simulated ecosystem gross primary productivity with time causal information theory quantifiers. PLoS One, 11(10): e0164960. doi:10.1371/journal.pone.0164960.
13Sippel, S., Zscheischler, J., Reichstein, M. (2016). Ecosystem impacts of climate extremes crucially depend on the timing (commentary). Proc.Natl.Acad.Sci.USA, 113(21), 5768-5770. doi:10.1073/pnas.1605667113.
14Tramontana, G., Jung, M., Schwalm, C. R., Ichii, K., Camps-Valls, G., Ráduly, B., Reichstein, M., Arain, M. A., Cescatti, A., Kiely, G., Merbold, L., Serrano-Ortiz, P., Sickert, S., Wolf, S., Papale, D. (2016). Predicting carbon dioxide and energy fluxes across global FLUXNET sites with regression algorithms. Biogeosciences, 13(14), 4291-4313. doi:10.5194/bg-13-4291-2016.
15Vaglio Laurin, G., Hawthorne, W. D., Chiti, T., Di Paola, A., Cazzolla Gatti, R., Marconi, S., Noce, S., Grieco, E., Pirotti, F., Valentini, R. (2016). Does degradation from selective logging and illegal activities differently impact forest resources? A case study in Ghana. iForest - Biogeosciences and Forestry, 9, 354-362. doi:10.3832/ifor1779-008.
16Vaglio Laurin, G., Pirotti, F., Callegari, M., Chen, Q., Cuozzo, G., Lingua, E., Notarnicola, C., Papale, D. (2017). Potential of ALOS2 and NDVI to estimate forest above-ground biomass, and comparison with lidar-derived estimates. Remote Sensing, 9: 18. doi:10.3390/rs9010018.
17Vaglio Laurin, G., Puletti, N., Chen, Q., Corona, P., Papale, D., Valentini, R. (2016). Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests. International Journal of Applied Earth Observation and Geoinformation, 52, 371-379. doi:10.1016/j.jag.2016.07.008.
18Vaglio Laurin, G., Puletti, N., Hawthorne, W., Liesenberg, V., Corona, P., Papale, D., Chen, Q., Valentini, R. (2016). Discrimination of tropical forest types, dominant species, and mapping of functional guilds by hyperspectral and simulated multispectral Sentinel-2 data. Remote Sensing of Environment, 176, 163-176. doi:10.1016/j.rse.2016.01.017.
Postprint available
19Vittucci, C., Ferrazzoli, P., Kerr, Y., Richaume, P., Guerriero, L., Rahmoune, R., Vaglio Laurin, G. (2016). SMOS retrieval over forests: Exploitation of optical depth and tests of soil moisture estimates. Remote Sensing of Environment, 180, 115-127. doi:10.1016/j.rse.2016.03.004.
20Zscheischler, J., Mahecha, M. D., Avitabile, V., Calle, L., Carvalhais, N., Ciais, P., Gans, F., Gruber, N., Hartmann, J., Herold, M., Ichii, K., Jung, M., Landschützer, P., Laruelle, G. G., Lauerwald, R., Papale, D., Peylin, P., Poulter, B., Ray, D., Regnier, P., Rödenbeck, C., Roman-Cuesta, R. M., Schwalm, C., Tramontana, G., Tyukavina, A. T., Valentini, R., van der Werf, G., West, T. O., Wolf, J. E., Reichstein, M. (2017). Reviews and syntheses: An empirical spatiotemporal description of the global surface–atmosphere carbon fluxes: opportunities and data limitations. Biogeosciences, 14(15), 3685-3703. doi:10.5194/bg-14-3685-2017.