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Yordanov M, d'Andrimont R, Martinez-Sanchez L, Lemoine G, Fasbender D, van der Velde M. Crop Identification Using Deep Learning on LUCAS Crop Cover Photos. Sensors (Basel) 2023; 23:6298. [PMID: 37514593 PMCID: PMC10383911 DOI: 10.3390/s23146298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 07/30/2023]
Abstract
Massive and high-quality in situ data are essential for Earth-observation-based agricultural monitoring. However, field surveying requires considerable organizational effort and money. Using computer vision to recognize crop types on geo-tagged photos could be a game changer allowing for the provision of timely and accurate crop-specific information. This study presents the first use of the largest multi-year set of labelled close-up in situ photos systematically collected across the European Union from the Land Use Cover Area frame Survey (LUCAS). Benefiting from this unique in situ dataset, this study aims to benchmark and test computer vision models to recognize major crops on close-up photos statistically distributed spatially and through time between 2006 and 2018 in a practical agricultural policy relevant context. The methodology makes use of crop calendars from various sources to ascertain the mature stage of the crop, of an extensive paradigm for the hyper-parameterization of MobileNet from random parameter initialization, and of various techniques from information theory in order to carry out more accurate post-processing filtering on results. The work has produced a dataset of 169,460 images of mature crops for the 12 classes, out of which 15,876 were manually selected as representing a clean sample without any foreign objects or unfavorable conditions. The best-performing model achieved a macro F1 (M-F1) of 0.75 on an imbalanced test dataset of 8642 photos. Using metrics from information theory, namely the equivalence reference probability, resulted in an increase of 6%. The most unfavorable conditions for taking such images, across all crop classes, were found to be too early or late in the season. The proposed methodology shows the possibility of using minimal auxiliary data outside the images themselves in order to achieve an M-F1 of 0.82 for labelling between 12 major European crops.
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Affiliation(s)
| | | | | | - Guido Lemoine
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy
| | - Dominique Fasbender
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy
- Walloon Institute of Evaluation, Foresight and Statistics (IWEPS), 5001 Namur, Belgium
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2
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Nóia Júnior RDS, Deswarte JC, Cohan JP, Martre P, van der Velde M, Lecerf R, Webber H, Ewert F, Ruane AC, Slafer GA, Asseng S. The extreme 2016 wheat yield failure in France. Glob Chang Biol 2023; 29:3130-3146. [PMID: 36951185 DOI: 10.1111/gcb.16662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 12/11/2022] [Accepted: 01/08/2023] [Indexed: 05/03/2023]
Abstract
France suffered, in 2016, the most extreme wheat yield decline in recent history, with some districts losing 55% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information, and yield physiology. The 2016 yield was composed of up to 40% fewer grains that were up to 30% lighter than expected across eight research stations in France. The flowering stage was affected by prolonged cloud cover and heavy rainfall when 31% of the loss in grain yield was incurred from reduced solar radiation and 19% from floret damage. Grain filling was also affected as 26% of grain yield loss was caused by soil anoxia, 11% by fungal foliar diseases, and 10% by ear blight. Compounding climate effects caused the extreme yield decline. The likelihood of these compound factors recurring under future climate change is estimated to change with a higher frequency of extremely low wheat yields.
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Affiliation(s)
- Rogério de S Nóia Júnior
- Department of Life Science Engineering, Digital Agriculture, HEF World Agricultural Systems Center, Technical University of Munich, Freising, Germany
| | | | | | - Pierre Martre
- LEPSE, Univ Montpellier, INRAE, Institut Agro Montpellier, Montpellier, France
| | | | - Remi Lecerf
- European Commission, Joint Research Centre, Ispra, Italy
| | - Heidi Webber
- Leibniz-Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
- Brandenburg Technical University (BTU), Cottbus, Germany
| | - Frank Ewert
- Leibniz-Centre for Agricultural Landscape Research (ZALF), Müncheberg, Germany
- Crop Science Group, INRES, University of Bonn, Bonn, Germany
| | - Alex C Ruane
- NASA Goddard Institute for Space Studies, New York, New York, USA
| | - Gustavo A Slafer
- Department of Crop and Forest Sciences, University of Lleida - AGROTECNIO Center, Lleida, Spain
- ICREA, Catalonian Institution for Research and Advanced Studies, Barcelona, Spain
| | - Senthold Asseng
- Department of Life Science Engineering, Digital Agriculture, HEF World Agricultural Systems Center, Technical University of Munich, Freising, Germany
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3
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Martinez-Sanchez L, Borio D, d'Andrimont R, van der Velde M. Skyline variations allow estimating distance to trees on landscape photos using semantic segmentation. ECOL INFORM 2022. [DOI: 10.1016/j.ecoinf.2022.101757] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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4
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Balkovič J, Madaras M, Skalský R, Folberth C, Smatanová M, Schmid E, van der Velde M, Kraxner F, Obersteiner M. Verifiable soil organic carbon modelling to facilitate regional reporting of cropland carbon change: A test case in the Czech Republic. J Environ Manage 2020; 274:111206. [PMID: 32818829 DOI: 10.1016/j.jenvman.2020.111206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 07/08/2020] [Accepted: 08/05/2020] [Indexed: 06/11/2023]
Abstract
Regional monitoring, reporting and verification of soil organic carbon change occurring in managed cropland are indispensable to support carbon-related policies. Rapidly evolving gridded agronomic models can facilitate these efforts throughout Europe. However, their performance in modelling soil carbon dynamics at regional scale is yet unexplored. Importantly, as such models are often driven by large-scale inputs, they need to be benchmarked against field experiments. We elucidate the level of detail that needs to be incorporated in gridded models to robustly estimate regional soil carbon dynamics in managed cropland, testing the approach for regions in the Czech Republic. We first calibrated the biogeochemical Environmental Policy Integrated Climate (EPIC) model against long-term experiments. Subsequently, we examined the EPIC model within a top-down gridded modelling framework constructed for European agricultural soils from Europe-wide datasets and regional land-use statistics. We explored the top-down, as opposed to a bottom-up, modelling approach for reporting agronomically relevant and verifiable soil carbon dynamics. In comparison with a no-input baseline, the regional EPIC model suggested soil carbon changes (~0.1-0.5 Mg C ha-1 y-1) consistent with empirical-based studies for all studied agricultural practices. However, inaccurate soil information, crop management inputs, or inappropriate model calibration may undermine regional modelling of cropland management effect on carbon since each of the three components carry uncertainty (~0.5-1.5 Mg C ha-1 y-1) that is substantially larger than the actual effect of agricultural practices relative to the no-input baseline. Besides, inaccurate soil data obtained from the background datasets biased the simulated carbon trends compared to observations, thus hampering the model's verifiability at the locations of field experiments. Encouragingly, the top-down agricultural management derived from regional land-use statistics proved suitable for the estimation of soil carbon dynamics consistently with actual field practices. Despite sensitivity to biophysical parameters, we found a robust scalability of the soil organic carbon routine for various climatic regions and soil types represented in the Czech experiments. The model performed better than the tier 1 methodology of the Intergovernmental Panel on Climate Change, which indicates a great potential for improved carbon change modelling over larger political regions.
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Affiliation(s)
- Juraj Balkovič
- International Institute for Applied Systems Analysis, Ecosystems Services and Management Program, Schlossplatz 1, A-2361, Laxenburg, Austria; Faculty of Natural Sciences, Comenius University in Bratislava, Ilkovičova 6, 842 15, Bratislava, Slovak Republic.
| | - Mikuláš Madaras
- Crop Research Institute, Division of Crop Management Systems, Drnovská 507/73, 161 06, Praha 6 - Ruzyně, Czech Republic.
| | - Rastislav Skalský
- International Institute for Applied Systems Analysis, Ecosystems Services and Management Program, Schlossplatz 1, A-2361, Laxenburg, Austria; National Agricultural and Food Centre, Soil Science and Conservation Research Institute, Trenčianska 55, 821 09, Bratislava, Slovak Republic.
| | - Christian Folberth
- International Institute for Applied Systems Analysis, Ecosystems Services and Management Program, Schlossplatz 1, A-2361, Laxenburg, Austria.
| | - Michaela Smatanová
- Central Institute for Supervising and Testing in Agriculture, Hroznová 63/2, 656 06, Brno, Czech Republic.
| | - Erwin Schmid
- Institute for Sustainable Economic Development, University of Natural Resources and Life Sciences, Vienna, Feistmantelstrasse 4, 1180, Vienna, Austria.
| | | | - Florian Kraxner
- International Institute for Applied Systems Analysis, Ecosystems Services and Management Program, Schlossplatz 1, A-2361, Laxenburg, Austria.
| | - Michael Obersteiner
- International Institute for Applied Systems Analysis, Ecosystems Services and Management Program, Schlossplatz 1, A-2361, Laxenburg, Austria; Environmental Change Institute, University of Oxford, South Parks Road, Oxford, OX1 3QY, United Kingdom.
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5
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d'Andrimont R, Yordanov M, Martinez-Sanchez L, Eiselt B, Palmieri A, Dominici P, Gallego J, Reuter HI, Joebges C, Lemoine G, van der Velde M. Harmonised LUCAS in-situ land cover and use database for field surveys from 2006 to 2018 in the European Union. Sci Data 2020; 7:352. [PMID: 33067440 PMCID: PMC7567823 DOI: 10.1038/s41597-020-00675-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 09/09/2020] [Indexed: 11/14/2022] Open
Abstract
Accurately characterizing land surface changes with Earth Observation requires geo-located ground truth. In the European Union (EU), a tri-annual surveyed sample of land cover and land use has been collected since 2006 under the Land Use/Cover Area frame Survey (LUCAS). A total of 1351293 observations at 651780 unique locations for 106 variables along with 5.4 million photos were collected during five LUCAS surveys. Until now, these data have never been harmonised into one database, limiting full exploitation of the information. This paper describes the LUCAS point sampling/surveying methodology, including collection of standard variables such as land cover, environmental parameters, and full resolution landscape and point photos, and then describes the harmonisation process. The resulting harmonised database is the most comprehensive in-situ dataset on land cover and use in the EU. The database is valuable for geo-spatial and statistical analysis of land use and land cover change. Furthermore, its potential to provide multi-temporal in-situ data will be enhanced by recent computational advances such as deep learning.
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Affiliation(s)
| | | | | | - Beatrice Eiselt
- European Commission, Eurostat (ESTAT), Luxembourg, Luxembourg
| | | | - Paolo Dominici
- European Commission, Eurostat (ESTAT), Luxembourg, Luxembourg
| | - Javier Gallego
- European Commission Joint Research Centre (JRC), Ispra, Italy
| | | | | | - Guido Lemoine
- European Commission Joint Research Centre (JRC), Ispra, Italy
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6
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d’Andrimont R, Taymans M, Lemoine G, Ceglar A, Yordanov M, van der Velde M. Detecting flowering phenology in oil seed rape parcels with Sentinel-1 and -2 time series. Remote Sens Environ 2020; 239:111660. [PMID: 32184531 PMCID: PMC7043338 DOI: 10.1016/j.rse.2020.111660] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
A novel methodology is proposed to robustly map oil seed rape (OSR) flowering phenology from time series generated from the Copernicus Sentinel-1 (S1) and Sentinel-2 (S2) sensors. The time series are averaged at parcel level, initially for a set of 229 reference parcels for which multiple phenological observations on OSR flowering have been collected from April 21 to May 19, 2018. The set of OSR parcels is extended to a regional sample of 32,355 OSR parcels derived from a regional S2 classification. The study area comprises the northern Brandenburg and Mecklenburg-Vorpommern (N) and the southern Bavaria (S) regions in Germany. A method was developed to automatically compute peak flowering at parcel level from the S2 time signature of the Normalized Difference Yellow Index (NDYI) and from the local minimum in S1 VV polarized backscattering coefficients. Peak flowering was determined at a temporal accuracy of 1 to 4 days. A systematic flowering delay of 1 day was observed in the S1 detection compared to S2. Peak flowering differed by 12 days between the N and S. Considerable local variation was observed in the N-S parcel-level flowering gradient. Additional in-situ phenology observations at 70 Deutscher Wetterdienst (DWD) stations confirm the spatial and temporal consistency between S1 and S2 signatures and flowering phenology across both regions. Conditions during flowering strongly determine OSR yield, therefore, the capacity to continuously characterize spatially the timing of key flowering dates across large areas is key. To illustrate this, expected flowering dates were simulated assuming a single OSR variety with a 425 growing degree days (GDD) requirement to reach flowering. This GDD requirement was calculated based on parcel-level peak flowering dates and temperatures accumulated from 25-km gridded meteorological data. The correlation between simulated and S2 observed peak flowering dates still equaled 0.84 and 0.54 for the N and S respectively. These Sentinel-based parcel-level flowering parameters can be combined with weather data to support in-season predictions of OSR yield, area, and production. Our approach identified the unique temporal signatures of S1 and S2 associated with OSR flowering and can now be applied to monitor OSR phenology for parcels across the globe.
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Elshout PMF, van Zelm R, van der Velde M, Steinmann Z, Huijbregts MAJ. Global relative species loss due to first-generation biofuel production for the transport sector. Glob Change Biol Bioenergy 2019; 11:763-772. [PMID: 31423154 PMCID: PMC6686982 DOI: 10.1111/gcbb.12597] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Revised: 12/09/2018] [Accepted: 12/23/2018] [Indexed: 06/10/2023]
Abstract
The global demand for biofuels in the transport sector may lead to significant biodiversity impacts via multiple human pressures. Biodiversity assessments of biofuels, however, seldom simultaneously address several impact pathways, which can lead to biased comparisons with fossil fuels. The goal of the present study was to quantify the direct influence of habitat loss, water consumption and greenhouse gas (GHG) emissions on potential global species richness loss due to the current production of first-generation biodiesel from soybean and rapeseed and bioethanol from sugarcane and corn. We found that the global relative species loss due to biofuel production exceeded that of fossil petrol and diesel production in more than 90% of the locations considered. Habitat loss was the dominating stressor with Chinese corn, Brazilian soybean and Brazilian sugarcane having a particularly large biodiversity impact. Spatial variation within countries was high, with 90th percentiles differing by a factor of 9 to 22 between locations. We conclude that displacing fossil fuels with first-generation biofuels will likely negatively affect global biodiversity, no matter which feedstock is used or where it is produced. Environmental policy may therefore focus on the introduction of other renewable options in the transport sector.
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Affiliation(s)
- Pieter M. F. Elshout
- Department of Environmental ScienceInstitute for Water and Wetland Research, Radboud University NijmegenNijmegenThe Netherlands
| | - Rosalie van Zelm
- Department of Environmental ScienceInstitute for Water and Wetland Research, Radboud University NijmegenNijmegenThe Netherlands
| | | | - Zoran Steinmann
- Department of Environmental ScienceInstitute for Water and Wetland Research, Radboud University NijmegenNijmegenThe Netherlands
| | - Mark A. J. Huijbregts
- Department of Environmental ScienceInstitute for Water and Wetland Research, Radboud University NijmegenNijmegenThe Netherlands
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8
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Balkovič J, Skalský R, Folberth C, Khabarov N, Schmid E, Madaras M, Obersteiner M, van der Velde M. Impacts and Uncertainties of +2°C of Climate Change and Soil Degradation on European Crop Calorie Supply. Earths Future 2018; 6:373-395. [PMID: 29938209 PMCID: PMC5993244 DOI: 10.1002/2017ef000629] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Revised: 01/24/2018] [Accepted: 01/30/2018] [Indexed: 05/25/2023]
Abstract
Even if global warming is kept below +2°C, European agriculture will be significantly impacted. Soil degradation may amplify these impacts substantially and thus hamper crop production further. We quantify biophysical consequences and bracket uncertainty of +2°C warming on calories supply from 10 major crops and vulnerability to soil degradation in Europe using crop modeling. The Environmental Policy Integrated Climate (EPIC) model together with regional climate projections from the European branch of the Coordinated Regional Downscaling Experiment (EURO-CORDEX) was used for this purpose. A robustly positive calorie yield change was estimated for the EU Member States except for some regions in Southern and South-Eastern Europe. The mean impacts range from +30 Gcal ha-1 in the north, through +25 and +20 Gcal ha-1 in Western and Eastern Europe, respectively, to +10 Gcal ha-1 in the south if soil degradation and heat impacts are not accounted for. Elevated CO2 and increased temperature are the dominant drivers of the simulated yield changes in high-input agricultural systems. The growth stimulus due to elevated CO2 may offset potentially negative yield impacts of temperature increase by +2°C in most of Europe. Soil degradation causes a calorie vulnerability ranging from 0 to 50 Gcal ha-1 due to insufficient compensation for nutrient depletion and this might undermine climate benefits in many regions, if not prevented by adaptation measures, especially in Eastern and North-Eastern Europe. Uncertainties due to future potentials for crop intensification are about 2-50 times higher than climate change impacts.
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Affiliation(s)
- Juraj Balkovič
- International Institute for Applied Systems AnalysisEcosystem Services and Management ProgramLaxenburgAustria
- Department of Soil Science, Faculty of Natural SciencesComenius University in BratislavaBratislavaSlovak Republic
| | - Rastislav Skalský
- International Institute for Applied Systems AnalysisEcosystem Services and Management ProgramLaxenburgAustria
- National Agricultural and Food CentreSoil Science and Conservation Research InstituteBratislavaSlovak Republic
| | - Christian Folberth
- International Institute for Applied Systems AnalysisEcosystem Services and Management ProgramLaxenburgAustria
| | - Nikolay Khabarov
- International Institute for Applied Systems AnalysisEcosystem Services and Management ProgramLaxenburgAustria
| | - Erwin Schmid
- Institute for Sustainable Economic DevelopmentUniversity of Natural Resource and Life Sciences, ViennaViennaAustria
| | - Mikuláš Madaras
- Division of Crop Management Systems, Crop Research InstitutePragueCzech Republic
| | - Michael Obersteiner
- International Institute for Applied Systems AnalysisEcosystem Services and Management ProgramLaxenburgAustria
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9
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Folberth C, Skalský R, Moltchanova E, Balkovič J, Azevedo LB, Obersteiner M, van der Velde M. Uncertainty in soil data can outweigh climate impact signals in global crop yield simulations. Nat Commun 2016; 7:11872. [PMID: 27323866 PMCID: PMC4919520 DOI: 10.1038/ncomms11872] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Accepted: 05/04/2016] [Indexed: 11/29/2022] Open
Abstract
Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Recently, the influence of climate data and weather variability on GGCM outcomes has come under detailed scrutiny, unlike the influence of soil data. Here we compare yield variability caused by the soil type selected for GGCM simulations to weather-induced yield variability. Without fertilizer application, soil-type-related yield variability generally outweighs the simulated inter-annual variability in yield due to weather. Increasing applications of fertilizer and irrigation reduce this variability until it is practically negligible. Importantly, estimated climate change effects on yield can be either negative or positive depending on the chosen soil type. Soils thus have the capacity to either buffer or amplify these impacts. Our findings call for improvements in soil data available for crop modelling and more explicit accounting for soil variability in GGCM simulations. Global gridded crop models are increasingly used to assess climate change impacts on food production. Here, the authors assess crop yield uncertainty associated with soil data input, reporting that soil type strongly influences yield estimates, and may either buffer or amplify climate-related impacts.
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Affiliation(s)
- Christian Folberth
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria.,Department of Geography, Ludwig Maximilian University, 80333 Munich, Germany
| | - Rastislav Skalský
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria.,Soil Science and Conservation Research Institute, National Agricultural and Food Centre, 82713 Bratislava, Slovak Republic
| | - Elena Moltchanova
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria.,School of Mathematics and Statistics, University of Canterbury, Christchurch 8140, New Zealand
| | - Juraj Balkovič
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria.,Department of Soil Science, Faculty of Natural Sciences, Comenius University, 84104 Bratislava, Slovak Republic
| | - Ligia B Azevedo
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria
| | - Michael Obersteiner
- Ecosystem Services and Management Program, International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria
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10
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Frank D, Reichstein M, Bahn M, Thonicke K, Frank D, Mahecha MD, Smith P, van der Velde M, Vicca S, Babst F, Beer C, Buchmann N, Canadell JG, Ciais P, Cramer W, Ibrom A, Miglietta F, Poulter B, Rammig A, Seneviratne SI, Walz A, Wattenbach M, Zavala MA, Zscheischler J. Effects of climate extremes on the terrestrial carbon cycle: concepts, processes and potential future impacts. Glob Chang Biol 2015; 21:2861-80. [PMID: 25752680 PMCID: PMC4676934 DOI: 10.1111/gcb.12916] [Citation(s) in RCA: 219] [Impact Index Per Article: 24.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2013] [Accepted: 01/24/2015] [Indexed: 05/19/2023]
Abstract
Extreme droughts, heat waves, frosts, precipitation, wind storms and other climate extremes may impact the structure, composition and functioning of terrestrial ecosystems, and thus carbon cycling and its feedbacks to the climate system. Yet, the interconnected avenues through which climate extremes drive ecological and physiological processes and alter the carbon balance are poorly understood. Here, we review the literature on carbon cycle relevant responses of ecosystems to extreme climatic events. Given that impacts of climate extremes are considered disturbances, we assume the respective general disturbance-induced mechanisms and processes to also operate in an extreme context. The paucity of well-defined studies currently renders a quantitative meta-analysis impossible, but permits us to develop a deductive framework for identifying the main mechanisms (and coupling thereof) through which climate extremes may act on the carbon cycle. We find that ecosystem responses can exceed the duration of the climate impacts via lagged effects on the carbon cycle. The expected regional impacts of future climate extremes will depend on changes in the probability and severity of their occurrence, on the compound effects and timing of different climate extremes, and on the vulnerability of each land-cover type modulated by management. Although processes and sensitivities differ among biomes, based on expert opinion, we expect forests to exhibit the largest net effect of extremes due to their large carbon pools and fluxes, potentially large indirect and lagged impacts, and long recovery time to regain previous stocks. At the global scale, we presume that droughts have the strongest and most widespread effects on terrestrial carbon cycling. Comparing impacts of climate extremes identified via remote sensing vs. ground-based observational case studies reveals that many regions in the (sub-)tropics are understudied. Hence, regional investigations are needed to allow a global upscaling of the impacts of climate extremes on global carbon-climate feedbacks.
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Affiliation(s)
- Dorothea Frank
- Max Planck Institute for Biogeochemistry07745, Jena, Germany
- Correspondence: Dorothea Frank, tel. + 49 3641 576284, fax + 49 3641 577200, e-mail:
| | | | - Michael Bahn
- Institute of Ecology, University of Innsbruck6020, Innsbruck, Austria
| | - Kirsten Thonicke
- Potsdam Institute for Climate Impact Research (PIK) e.V.14773, Potsdam, Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB)14195, Berlin, Germany
| | - David Frank
- Swiss Federal Research Institute WSL8903, Birmensdorf, Switzerland
- Oeschger Centre for Climate Change Research, University of BernCH-3012, Bern, Switzerland
| | | | - Pete Smith
- Institute of Biological and Environmental Sciences, University of Aberdeen23 St Machar Drive, Aberdeen, AB24 3UU, UK
| | - Marijn van der Velde
- Ecosystems Services and Management Program, International Institute of Applied Systems Analysis (IIASA)A-2361, Laxenburg, Austria
| | - Sara Vicca
- Research Group of Plant and Vegetation Ecology, Biology Department, University of AntwerpWilrijk, Belgium
| | - Flurin Babst
- Potsdam Institute for Climate Impact Research (PIK) e.V.14773, Potsdam, Germany
- Laboratory of Tree-Ring Research, The University of Arizona1215 E Lowell St, Tucson, AZ, 85721, USA
| | - Christian Beer
- Max Planck Institute for Biogeochemistry07745, Jena, Germany
- Department of Environmental Science and Analytical Chemistry (ACES), Bolin Centre for Climate Research, Stockholm University10691, Stockholm, Sweden
| | | | - Josep G Canadell
- Global Carbon Project, CSIRO Oceans and Atmosphere FlagshipGPO Box 3023, Canberra, ACT, 2601, Australia
| | - Philippe Ciais
- IPSL – Laboratoire des Sciences du Climat et de l’Environnement CEA-CNRS-UVSQ91191, Gif sur Yvette, France
| | - Wolfgang Cramer
- Institut Méditerranéen de Biodiversité et d’Ecologie marine et continentale (IMBE), Aix Marseille Université, CNRS, IRD, Avignon UniversitéAix-en-Provence, France
| | - Andreas Ibrom
- Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU)Frederiksborgvej 399, 4000, Roskilde, Denmark
| | - Franco Miglietta
- IBIMET-CNRVia Caproni, 8, 50145, Firenze, Italy
- FoxLab, Fondazione E.MachVia Mach 1, 30158, San Michele a/Adige, Trento, Italy
| | - Ben Poulter
- IPSL – Laboratoire des Sciences du Climat et de l’Environnement CEA-CNRS-UVSQ91191, Gif sur Yvette, France
| | - Anja Rammig
- Oeschger Centre for Climate Change Research, University of BernCH-3012, Bern, Switzerland
- Institute of Biological and Environmental Sciences, University of Aberdeen23 St Machar Drive, Aberdeen, AB24 3UU, UK
| | | | - Ariane Walz
- Institute of Earth and Environmental Science, University of Potsdam14476, Potsdam, Germany
| | - Martin Wattenbach
- Helmholtz Centre Potsdam, GFZ German Research Centre For Geosciences14473, Potsdam, Germany
| | - Miguel A Zavala
- Forest Ecology and Restoration Group, Universidad de AlcaláAlcalá de Henares, Madrid, Spain
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Fritz S, See L, McCallum I, You L, Bun A, Moltchanova E, Duerauer M, Albrecht F, Schill C, Perger C, Havlik P, Mosnier A, Thornton P, Wood-Sichra U, Herrero M, Becker-Reshef I, Justice C, Hansen M, Gong P, Abdel Aziz S, Cipriani A, Cumani R, Cecchi G, Conchedda G, Ferreira S, Gomez A, Haffani M, Kayitakire F, Malanding J, Mueller R, Newby T, Nonguierma A, Olusegun A, Ortner S, Rajak DR, Rocha J, Schepaschenko D, Schepaschenko M, Terekhov A, Tiangwa A, Vancutsem C, Vintrou E, Wenbin W, van der Velde M, Dunwoody A, Kraxner F, Obersteiner M. Mapping global cropland and field size. Glob Chang Biol 2015; 21:1980-92. [PMID: 25640302 DOI: 10.1111/gcb.12838] [Citation(s) in RCA: 134] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2014] [Revised: 11/30/2014] [Accepted: 12/08/2014] [Indexed: 05/19/2023]
Abstract
A new 1 km global IIASA-IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo-Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA-IFPRI cropland product has been validated using very high-resolution satellite imagery via Geo-Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo-Wiki. The first ever global field size map was produced at the same resolution as the IIASA-IFPRI cropland map based on interpolation of field size data collected via a Geo-Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.
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Affiliation(s)
- Steffen Fritz
- International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, A-2361, Laxenburg, Austria
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Peñuelas J, Poulter B, Sardans J, Ciais P, van der Velde M, Bopp L, Boucher O, Godderis Y, Hinsinger P, Llusia J, Nardin E, Vicca S, Obersteiner M, Janssens IA. Human-induced nitrogen-phosphorus imbalances alter natural and managed ecosystems across the globe. Nat Commun 2014; 4:2934. [PMID: 24343268 DOI: 10.1038/ncomms3934] [Citation(s) in RCA: 437] [Impact Index Per Article: 43.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2013] [Accepted: 11/14/2013] [Indexed: 11/09/2022] Open
Abstract
The availability of carbon from rising atmospheric carbon dioxide levels and of nitrogen from various human-induced inputs to ecosystems is continuously increasing; however, these increases are not paralleled by a similar increase in phosphorus inputs. The inexorable change in the stoichiometry of carbon and nitrogen relative to phosphorus has no equivalent in Earth's history. Here we report the profound and yet uncertain consequences of the human imprint on the phosphorus cycle and nitrogen:phosphorus stoichiometry for the structure, functioning and diversity of terrestrial and aquatic organisms and ecosystems. A mass balance approach is used to show that limited phosphorus and nitrogen availability are likely to jointly reduce future carbon storage by natural ecosystems during this century. Further, if phosphorus fertilizers cannot be made increasingly accessible, the crop yields projections of the Millennium Ecosystem Assessment imply an increase of the nutrient deficit in developing regions.
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Affiliation(s)
- Josep Peñuelas
- 1] CSIC, Global Ecology Unit CREAF-CEAB-UAB, Cerdanyola del Vallès, 08193 Catalonia, Spain [2] CREAF, Cerdanyola del Vallès, 08193 Catalonia, Spain
| | - Benjamin Poulter
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, 91191 Gif-sur-Yvette, France
| | - Jordi Sardans
- 1] CSIC, Global Ecology Unit CREAF-CEAB-UAB, Cerdanyola del Vallès, 08193 Catalonia, Spain [2] CREAF, Cerdanyola del Vallès, 08193 Catalonia, Spain
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, 91191 Gif-sur-Yvette, France
| | - Marijn van der Velde
- International Institute for Applied Systems Analysis (IIASA), Ecosystems Services and Management, Schlossplatz 1, A-2361 Laxenburg, Austria
| | - Laurent Bopp
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL, 91191 Gif-sur-Yvette, France
| | - Olivier Boucher
- Laboratoire de Météorologie Dynamique, IPSL, CNRS/UPMC, 75005 Paris, France
| | - Yves Godderis
- Géosciences-Environnement Toulouse, CNRS-Observatoire Midi-Pyrénées, 31400 Toulouse, France
| | | | - Joan Llusia
- 1] CSIC, Global Ecology Unit CREAF-CEAB-UAB, Cerdanyola del Vallès, 08193 Catalonia, Spain [2] CREAF, Cerdanyola del Vallès, 08193 Catalonia, Spain
| | - Elise Nardin
- Géosciences-Environnement Toulouse, CNRS-Observatoire Midi-Pyrénées, 31400 Toulouse, France
| | - Sara Vicca
- Research Group of Plant and Vegetation Ecology (PLECO), Department of Biology, University of Antwerp, B-2610 Wilrijk, Belgium
| | - Michael Obersteiner
- International Institute for Applied Systems Analysis (IIASA), Ecosystems Services and Management, Schlossplatz 1, A-2361 Laxenburg, Austria
| | - Ivan A Janssens
- Research Group of Plant and Vegetation Ecology (PLECO), Department of Biology, University of Antwerp, B-2610 Wilrijk, Belgium
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van der Velde M, Folberth C, Balkovič J, Ciais P, Fritz S, Janssens IA, Obersteiner M, See L, Skalský R, Xiong W, Peñuelas J. African crop yield reductions due to increasingly unbalanced Nitrogen and Phosphorus consumption. Glob Chang Biol 2014; 20:1278-88. [PMID: 24470387 DOI: 10.1111/gcb.12481] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2013] [Revised: 11/01/2013] [Accepted: 11/15/2013] [Indexed: 05/21/2023]
Abstract
The impact of soil nutrient depletion on crop production has been known for decades, but robust assessments of the impact of increasingly unbalanced nitrogen (N) and phosphorus (P) application rates on crop production are lacking. Here, we use crop response functions based on 741 FAO maize crop trials and EPIC crop modeling across Africa to examine maize yield deficits resulting from unbalanced N : P applications under low, medium, and high input scenarios, for past (1975), current, and future N : P mass ratios of respectively, 1 : 0.29, 1 : 0.15, and 1 : 0.05. At low N inputs (10 kg ha(-1)), current yield deficits amount to 10% but will increase up to 27% under the assumed future N : P ratio, while at medium N inputs (50 kg N ha(-1)), future yield losses could amount to over 40%. The EPIC crop model was then used to simulate maize yields across Africa. The model results showed relative median future yield reductions at low N inputs of 40%, and 50% at medium and high inputs, albeit with large spatial variability. Dominant low-quality soils such as Ferralsols, which are strongly adsorbing P, and Arenosols with a low nutrient retention capacity, are associated with a strong yield decline, although Arenosols show very variable crop yield losses at low inputs. Optimal N : P ratios, i.e. those where the lowest amount of applied P produces the highest yield (given N input) where calculated with EPIC to be as low as 1 : 0.5. Finally, we estimated the additional P required given current N inputs, and given N inputs that would allow Africa to close yield gaps (ca. 70%). At current N inputs, P consumption would have to increase 2.3-fold to be optimal, and to increase 11.7-fold to close yield gaps. The P demand to overcome these yield deficits would provide a significant additional pressure on current global extraction of P resources.
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Affiliation(s)
- Marijn van der Velde
- Ecosystems Services and Management Program, International Institute for Applied Systems Analysis (IIASA), Schlossplatz 1, Laxenburg, A-2361, Austria
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Xiong W, Balkovič J, van der Velde M, Zhang X, Izaurralde RC, Skalský R, Lin E, Mueller N, Obersteiner M. A calibration procedure to improve global rice yield simulations with EPIC. Ecol Modell 2014. [DOI: 10.1016/j.ecolmodel.2013.10.026] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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See L, Comber A, Salk C, Fritz S, van der Velde M, Perger C, Schill C, McCallum I, Kraxner F, Obersteiner M. Comparing the quality of crowdsourced data contributed by expert and non-experts. PLoS One 2013; 8:e69958. [PMID: 23936126 PMCID: PMC3729953 DOI: 10.1371/journal.pone.0069958] [Citation(s) in RCA: 118] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2013] [Accepted: 06/12/2013] [Indexed: 11/19/2022] Open
Abstract
There is currently a lack of in-situ environmental data for the calibration and validation of remotely sensed products and for the development and verification of models. Crowdsourcing is increasingly being seen as one potentially powerful way of increasing the supply of in-situ data but there are a number of concerns over the subsequent use of the data, in particular over data quality. This paper examined crowdsourced data from the Geo-Wiki crowdsourcing tool for land cover validation to determine whether there were significant differences in quality between the answers provided by experts and non-experts in the domain of remote sensing and therefore the extent to which crowdsourced data describing human impact and land cover can be used in further scientific research. The results showed that there was little difference between experts and non-experts in identifying human impact although results varied by land cover while experts were better than non-experts in identifying the land cover type. This suggests the need to create training materials with more examples in those areas where difficulties in identification were encountered, and to offer some method for contributors to reflect on the information they contribute, perhaps by feeding back the evaluations of their contributed data or by making additional training materials available. Accuracies were also found to be higher when the volunteers were more consistent in their responses at a given location and when they indicated higher confidence, which suggests that these additional pieces of information could be used in the development of robust measures of quality in the future.
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Affiliation(s)
- Linda See
- International Institute for Applied Systems Analysis, Ecosystem Services and Management Program, Laxenburg, Austria.
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van der Velde M, See L, You L, Balkovič J, Fritz S, Khabarov N, Obersteiner M, Wood S. Affordable nutrient solutions for improved food security as evidenced by crop trials. PLoS One 2013; 8:e60075. [PMID: 23565186 PMCID: PMC3615004 DOI: 10.1371/journal.pone.0060075] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2012] [Accepted: 02/21/2013] [Indexed: 11/29/2022] Open
Abstract
The continuing depletion of nutrients from agricultural soils in Sub-Saharan African is accompanied by a lack of substantial progress in crop yield improvement. In this paper we investigate yield gaps for corn under two scenarios: a micro-dosing scenario with marginal increases in nitrogen (N) and phosphorus (P) of 10 kg ha−1 and a larger yet still conservative scenario with proposed N and P applications of 80 and 20 kg ha−1 respectively. The yield gaps are calculated from a database of historical FAO crop fertilizer trials at 1358 locations for Sub-Saharan Africa and South America. Our approach allows connecting experimental field scale data with continental policy recommendations. Two critical findings emerged from the analysis. The first is the degree to which P limits increases in corn yields. For example, under a micro-dosing scenario, in Africa, the addition of small amounts of N alone resulted in mean yield increases of 8% while the addition of only P increased mean yields by 26%, with implications for designing better balanced fertilizer distribution schemes. The second finding was the relatively large amount of yield increase possible for a small, yet affordable amount of fertilizer application. Using African and South American fertilizer prices we show that the level of investment needed to achieve these results is considerably less than 1% of Agricultural GDP for both a micro-dosing scenario and for the scenario involving higher yet still conservative fertilizer application rates. In the latter scenario realistic mean yield increases ranged between 28 to 85% in South America and 71 to 190% in Africa (mean plus one standard deviation). External investment in this low technology solution has the potential to kick start development and could complement other interventions such as better crop varieties and improved economic instruments to support farmers.
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Affiliation(s)
- Marijn van der Velde
- International Institute for Applied Systems Analysis (IIASA), Ecosystem Services and Management Program, Laxenburg, Austria.
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Fritz S, See L, van der Velde M, Nalepa RA, Perger C, Schill C, McCallum I, Schepaschenko D, Kraxner F, Cai X, Zhang X, Ortner S, Hazarika R, Cipriani A, Di Bella C, Rabia AH, Garcia A, Vakolyuk M, Singha K, Beget ME, Erasmi S, Albrecht F, Shaw B, Obersteiner M. Downgrading recent estimates of land available for biofuel production. Environ Sci Technol 2013; 47:1688-1694. [PMID: 23308357 DOI: 10.1021/es303141h] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Recent estimates of additional land available for bioenergy production range from 320 to 1411 million ha. These estimates were generated from four scenarios regarding the types of land suitable for bioenergy production using coarse-resolution inputs of soil productivity, slope, climate, and land cover. In this paper, these maps of land availability were assessed using high-resolution satellite imagery. Samples from these maps were selected and crowdsourcing of Google Earth images was used to determine the type of land cover and the degree of human impact. Based on this sample, a set of rules was formulated to downward adjust the original estimates for each of the four scenarios that were previously used to generate the maps of land availability for bioenergy production. The adjusted land availability estimates range from 56 to 1035 million ha depending upon the scenario and the ruleset used when the sample is corrected for bias. Large forest areas not intended for biofuel production purposes were present in all scenarios. However, these numbers should not be considered as definitive estimates but should be used to highlight the uncertainty in attempting to quantify land availability for biofuel production when using coarse-resolution inputs with implications for further policy development.
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Affiliation(s)
- Steffen Fritz
- International Institute of Applied Systems Analysis (IIASA), Ecosystem Services and Management Program, Schlossplatz 1, Laxenburg, A-2361, Austria.
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Fritz S, See L, You L, Justice C, Becker-Reshef I, Bydekerke L, Cumani R, Defourny P, Erb K, Foley J, Gilliams S, Gong P, Hansen M, Hertel T, Herold M, Herrero M, Kayitakire F, Latham J, Leo O, McCallum I, Obersteiner M, Ramankutty N, Rocha J, Tang H, Thornton P, Vancutsem C, van der Velde M, Wood S, Woodcock C. The Need for Improved Maps of Global Cropland. ACTA ACUST UNITED AC 2013. [DOI: 10.1002/2013eo030006] [Citation(s) in RCA: 57] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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