Find a full list of all publications in my CV. See my citation stats in Google Scholar. For all non open access publications I provide free author copies as PDF (see link behind each publication).
2023
[44] Hermann, M., Rothlisberger, M., Gessler, A., Rigling, A., Senf, C., Wohlgemuth, T., and Wernli, H. (2023) Analysis of multi-seasonal meteorological storylines leading to reduced forest greenness in Europe in 2000-2022. Biogeosciences, 20, 1155-1180. https://doi.org/10.5194/bg-20-1155-2023 (open access)
[43] Mandl, L., Stritih, A., Seidl, R., Ginzler, C., and Senf, C. (2023) Spaceborne LiDAR for characterizing mountain forest structure across scales. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.330 (open access)
[42] Stritih, A., Seidl, R. and Senf, C. (2023) Alternative stable states in the structure of mountain forests across the Alps. Landscape Ecology. https://doi.org/10.1007/s10980-023-01597-y (open access)
2022
[41] Grünig, M., Seidl, R. and Senf, C. (2022) Increasing aridity causes larger and more severe forest fires across Europe. Global Change Biology. https://doi.org/10.1111/gcb.16547 (open access)
[40] Senf, C. (2022) Seeing the system from above – The use and potential of remote sensing for studying ecosystem dynamics. Ecosystems. http://doi.org//10.1007/s10021-022-00777-2 (open access)
[39] Matsala, M., Senf, C., Bilous, A., Diachuk, P., Zadorozhniuk, R., Burianchuk, M. and Seidl, R. (2022) The impact of radioactive contamination on tree regeneration and forest development in the Chernobyl Exclusion Zone. Applied Vegetation Science, 25, e12631. https://doi.org/10.1111/avsc.12631 (open access)
[38] Senf, C. and Seidl, R. (2022) Post-disturbance canopy recovery and the resilience of Europe’s forests. Global Ecology and Biogeography, 31(1), 25-36. https://doi.org/10.1111/geb.13406 (open access)
2021
[37] Senf, C. and Seidl, R. (2021) Persistent impacts of the 2018 drought on forest disturbance regimes in Europe. Biogeosciences. https://doi.org/10.5194/bg-18-5223-2021 (open access)
[36] Munteanu, C., Senf, C., Nita, M. D., Sabatini, F. M., Oeser, J., Seidl, R., Kuemmerle, T. (2021) Identifying Romania’s high conservation value forests with historical spy satellites and modern remote sensing. Conservation Biology. https://doi.org/10.1111/cobi.13820 (open access)
[35] Sebald, J., Senf, C. and Seidl, R. (2021) Human or natural? Landscape context improves the attribution of forest disturbances mapped from Landsat in Central Europe. Remote Sensing of Environment, 262, 112502. https://doi.org/10.1016/j.rse.2021.112502 (open access)
[34] Senf, C. and Seidl, R. (2021) Storm and fire disturbance in Europe: Distribution and trends. Global Change Biology, 27(15), 3605-3619. https://doi.org/10.1111/gcb.15679 (open access)
[33] Senf, C., Sebald, J., and Seidl, R. (2021) Increasing canopy mortality affects the future demographic structure of Europe’s forests. One Earth, 4, 1-7. https://doi.org/10.1016/j.oneear.2021.04.008 (open access)
[32] Palahí, M., Valbuena, R., Senf, C., Acil N., Pugh T. A. M., Sadler J., Seidl R., Potapov P., Gardiner B., Hetemäki L., Chirici G., Francini S., Hlásny T., Lerink B. J. W., Olsson H., Olabarria J. R. G., Ascoli D., Asikainen A., Bauhus J., Berndes G., Donis J., Fridman J., Hanewinkel M., Jactel H., Lindner M., Marchetti M., Marušák R., Sheil D., Tomé M., Trasobares A., Verkerk P. J., Korhonen M. and Nabuurs G.J. (2021) Concerns about reported harvested area and biomass loss in European forests. Nature, 592, 7856, E15-17. https://doi.org/10.1038/s41586-021-03292-x (author copy: PDF)
[31] Suzuki, K. F., Kobayashu, Y., Seidl, R., Senf, C., Tatsumi, S., Koide, D., Azuma, W., Higa, M., Koyanagi, T. F., Qian, S., Kusano, Y., Matsubayashi, R., and Mori, A.S. (2021) The potential role of an alien tree species in supporting forest restoration: Lessons from Shiretoko National Park, Japan. Forest Ecology and Management, 493, 119253. https://doi.org/10.1016/j.foreco.2021.119253 (author copy: PDF)
[30] Stritih, A., Senf, C., Seidl, R., Grêt-Regamey, A. and Bebi, P. (2021) The impact of land-use legacies and recent management on natural disturbance susceptibility in mountain forests. Forest Ecology and Management, 484, 118950. https://doi.org/10.1016/j.foreco.2021.118950 (open access)
[29] Jung, H., Senf, C., Beudert, B., and Krueger, T. (2021) Bayesian hierarchical modelling of nitrate concentration in a forest stream affected by large-scale forest dieback. Water Resources Research, 57(2), e2020WR027264. https://doi.org/10.1029/2020WR027264 (open access)
[28] Oeser, J., Heurich, M., Senf, C., Pflugmacher, D., and Kuemmerle, T. (2021) Satellite-based habitat monitoring reveals long-term dynamics of deer habitat in response to forest disturbances. Ecological Applications, 31(3), e2269. https://doi.org/10.1002/eap.2269 (open access)
[27] Senf, C. and Seidl, R. (2021) Mapping the forest disturbance regimes of Europe. Nature Sustainability, 4, 63-70. https://doi.org/10.1038/s41893-020-00609-y (author copy: PDF)
2020
[26] Senf, C., Buras, A., Zang, C. S., Rammig, A., and Seidl. R. (2020) Excess forest mortality is consistently linked to drought across Europe. Nature Communications, 11, 6200. https://doi.org/10.1038/s41467-020-19924-1 (open access)
[25] Senf, C., Mori, A., Müller, J. and Seidl. R. (2020) The response of canopy height diversity to natural disturbances in two temperate forest landscapes. Landscape Ecology, 35, 2101-2112. https://doi.org/10.1007/s10980-020-01085-7 (open access)
[24] Kowalski, K., Senf, C., Hostert, P. and Pflugmacher, D. (2020) Characterizing spring phenology of temperate broadleaf forests using Landsat and Sentinel-2 time series. International Journal of Applied Earth Observations and Geoinformation, 92, 102172. https://doi.org/10.1016/j.jag.2020.102172 (open access)
[23] Jung, H., Senf, C., Jordan, P., and Krueger, T. (2020) Benchmarking inference methods for water quality monitoring and status classification. Environmental Monitoring and Assessment, 192, 261. https://doi.org/10.1007/s10661-020-8223-4 (open access)
[22] Seidl, R., Honkaniemi, J., Aakala, T., Aleinikov, A., Angelstam, P., Bouchard, M., Boucher, D., Boulanger, Y., Burton, P. J., De Grandpré, L., Gauthier, S., Hansen, W. D., Jespen, J. U., Jõgiste, K., Kneeshaw, D. D., Kuuluvainenm, T., Lisitsyna, O., Makoto, K., Mori, A. S., Pureswaran, D. S., Shorohova, E., Shubnitsina, E., Taylor, A. R., Vladimirova, N., Voode, F., Senf, C. (2020) Globally consistent climate sensitivity of natural disturbances across boreal and temperate forest ecosystems. Ecography, 43, 967-978. https://doi.org/10.1111/ecog.04995 (open access)
[21] Senf, C., Laštovička, J., Okujeni, A., Heurich, M., and van der Linden, S. (2020) A generalized regression-based unmixing model for mapping forest cover fractions throughout three decades of Landsat data. Remote Sensing of Environment, 240, 111691. https://doi.org/10.1016/j.rse.2020.111691 (author copy: PDF)
2019
[20] Senf, C., Müller, J., and Seidl, R. (2019) Post-disturbance recovery of forest cover and tree height differ with management in Central Europe. Landscape Ecology, 34, 2837-2850. https://doi.org/10.1007/s10980-019-00921-9 (open access)
[19] Sebald, J., Senf, C., Heiser, M., Scheidl, C., Pflugmacher, D., and Seidl, R. (2019) The effects of forest cover and disturbance on torrential hazards: Large-scale evidence from the Eastern Alps. Environmental Research Letters, 14(11), 114032. https://doi.org/10.1088/1748-9326/ab4937 (open access)
[18] Oeser, J., Heurich, M., Senf, C., Pflugmacher, D., Belotti, E., and Kuemmerle, T. (2019) Habitat metrics based on multi-temporal Landsat imagery for mapping large mammal habitat. Remote Sensing in Ecology and Conservation. https://doi.org/10.1002/rse2.122 (open access)
[17] Lebek, E. K., Senf, C., Frantz, D., Monteiro, J. A. F., and Krueger, T. (2019) Interdependent effects of climate variability and forest cover change on streamflow dynamics: a case study in the Upper Umvoti River Basin, South Africa. Regional Environmental Change, 19(7), 1963-1971. https://doi.org/10.1007/s10113-019-01521-8 (author copy: PDF)
2018
[16] Senf, C., Pflugmacher, D., Zhiqiang, Y., Sebald, J., Knorrn, J., Neumann, M., Hostert, P. and Seidl, R. (2018) Canopy mortality has doubled across Europe’s temperate forests in the last three decades. Nature Communications, 9, 4978. https://doi.org/10.1038/s41467-018-07539-6 (open access)
[15] Sommerfeld, A.†, Senf, C.†, Buma, B., D’Amato, A. W., Després, T., Díaz-Hormazábal, I., Fraver, S., Frelich, L. E., Gutiérrez, Á. G., Hart, S. J., Harvey, B. J., He, H. S., Hlásny, T., Holz, A., Kitzberger, T., Kulakowski, D., Lindenmayer, D., Mori, A. S., Müller, J., Paritsis, J., Perry, G., Stephens, S., Svoboda, M., Turner, M. G., Veblen, T. T., and Seidl, R. (2018) Patterns and drivers of recent disturbances across the temperate forest biome. †Both authors contributed equally. Nature Communications, 9, 4355. https://doi.org/10.1038/s41467-018-06788-9 (open access)
[14] Senf, C. and Seidl R. (2018) Natural disturbances are spatially diverse but temporally synchronized across temperate forest landscapes in Europe. Global Change Biology, 24(3), 1201-1211. https://doi.org/10.1111/gcb.13897 (author copy: PDF)
2017
[13] Senf, C., Pflugmacher, D., Hostert, P. and Seidl, R. (2017) Using Landsat time series for characterizing forest disturbance dynamics in the coupled human and natural systems of Central Europe. ISPRS Journal of Photogrammetry and Remote Sensing, 130, 453-463. https://doi.org/10.1016/j.isprsjprs.2017.07.004 (author copy: PDF)
[12] Oeser, J., Pflugmacher, D., Senf, C., Heurich, M. and Hostert, P. (2017) Using intra-annual Landsat time series for attributing forest disturbance agents in Central Europe. Forests, 8, 251. https://doi.org/10.3390/f8070251 (open access)
[11] Senf, C., Seidl, R. and Hostert, P. (2017) Remote sensing of forest insect disturbances: current state and future directions. International Journal of Applied Earth Observation and Geo-information, 60, 49-60. https://doi.org/10.1016/j.jag.2017.04.004 (author copy: PDF)
[10] Senf, C., Pflugmacher, D., Heurich, M. and Krueger T. (2017) A Bayesian hierarchical model for estimating spatial and temporal variation in vegetation phenology from Landsat time series. Remote Sensing of Environment, 194, 155-160. https://doi.org/10.1016/j.rse.2017.03.020 (author copy: PDF)
[9] Leitão, J. P., Schwieder, M. and Senf, C. (2017) sgdm: an R package for performing sparse generalized dissimilarity modelling, including tools for gdm. ISPRS International Journal of Geo-Information, 6(1), 23-35. https://doi.org/10.3390/ijgi6010023 (open access)
[8] Senf, C., Campbell, E., Wulder, M. A., Pflugmacher, D. and Hostert P. (2017) A multi-scale analysis of western spruce budworm spatiotemporal outbreak patterns. Landscape Ecology, 32(3), 501-514. https://doi.org/10.1007/s10980-016-0460-0 (author copy: PDF)
[7] Kehoe, L., Senf, C., Meyer, C., Gerstner, K., Kreft, H. and Kuemmerle, T. (2017) Land cover and land-use intensity rival biomes in predicting global species richness. Ecography, 40, 1118-1128. https://doi.org/10.1111/ecog.02508 (open access)
2016
[6] Senf, C., Wulder, M. A., Campbell, E. and Hostert P. (2016) Using Landsat to assess the relationship between spatiotemporal patterns of western spruce budworm outbreaks and regional-scale weather variability. Canadian Journal of Remote Sensing, 42(6), 706-718. https://doi.org/10.1080/07038992.2016.1220828 (author copy: PDF)
2015
[5] Senf, C., Pflugmacher, D., Wulder, M. A. and Hostert, P. (2015) Characterizing spectral-temporal patterns of defoliator and bark beetle disturbances using Landsat time series. Remote Sensing of Environment, 170, 166-177. https://doi.org/10.1016/j.rse.2015.09.019 (author copy: PDF)
[4] Held, M., Rabe, A., Senf, C., van der Linden, S. and Hostert, P. (2015) Analyzing Hyperspectral and Hypertemporal Data by Decoupling Feature Redundancy and Feature Relevance. IEEE Geoscience and Remote Sensing Letters, 12(5), 983-987. https://doi.org/ 10.1109/LGRS.2014.2371242 (author copy: PDF)
[3] Senf, C., Leitão, J.P., Pflugmacher, D., van der Linden, S. and Hostert, P. (2015) Mapping land cover in complex Mediterranean landscapes using Landsat: Improved classification accuracies from integrating multi-seasonal and synthetic imagery. Remote Sensing of Environment, 156, 527-536. https://doi.org/10.1016/j.rse.2014.10.018 (author copy: PDF)
2014
[2] Schwieder, M., Leitão, J.P., Suess, S., Senf, C. and Hostert, P. (2014) Estimating fractional shrub cover using simulated EnMAP data: A comparison of three machine learning regression techniques. Remote Sensing, 6(4), 3427-3445. https://doi.org/10.3390/rs6043427 (open access)
2013
[1] Senf, C., Pflugmacher, D., van der Linden, S. and Hostert, P. (2013) Mapping Rubber Plantations and Natural Forests in Xishuangbanna (Southwest China) Using Multi-Spectral Phenological Metrics from MODIS Time Series. Remote Sensing, 5(6), 2795-2812. https://doi.org/10.3390/rs5062795 (open access)