Authors: Kroes, Joop; van Dam, Jos; Supit, Iwan; De Abelleyra, Diego; Veron, Santiago Ramón; de Wit, Allard; Boogaard, Hendrik; Angelini, Marcos Esteban; Damiano, Francisco; Groenendijk, Piet; Wesseling, Jan; Veldhuizen, Ab
Publication Date: 2019.
Language: English.
Abstract:
This paper studies the changes of groundwater, climate and land use in the Pampas of Argentina. These changes offer opportunities and threats. Lowering groundwater without irrigation causes drought and successive crop and yield damage. Rising groundwater may alleviate drought as capillary rise supports root water uptake and crop growth, thus narrowing the difference between potential and actual yields. However, rising groundwater may also limit soil water storage, cause flooding in metropolitan areas and have a negative impact on crop yields. Changing land use from continuous soy bean into crop rotations or natural vegetation may decrease groundwater recharge and thus decrease groundwater levels. In case of crop rotation however, leaching of nutrients like nitrate may increase. We quantified these impacts using integrated dynamic crop growth and soil hydrology modelling. The models were tested at field scale using a local dataset from Argentina. We applied distributed modelling at regional scale to evaluate the impacts on groundwater recharge and crop yields using long term weather data. The experiments showed that threats arise from continuous monotone land use. Opportunities are created when a proper balance is found between supply and demand of soil water using a larger differentiation of land use. Increasing the areas of land use types with higher evapotranspiration, like permanent grassland and trees, will contribute to a more stable hydrologic system with more water storage capacities in the soil system and lower groundwater levels. Modelling tools clearly support the evaluation of the impact of land use and climate change on groundwater levels and crop yields.
Instituto de Clima y Agua
Author affiliation: Kroes, Joop. Wageningen University and Research. Chair Soil Physics and Land Management; Holanda
Author affiliation: van Dam, Jos. Wageningen University and Research. Chair Soil Physics and Land Management; Holanda
Author affiliation: Supit, Iwan. Wageningen University and Research. Chair Water Systems and Global Change; Holanda
Author affiliation: De Abelleyra, Diego. INTA. Instituto de Clima y Agua; Argentina
Author affiliation: Veron, Santiago Ramón. INTA. Instituto de Clima y Agua; Argentina
Author affiliation: de Wit, Allard. Wageningen University and Research. Wageningen Environmental Research. Unit Earth Observation and Environmental Informatics; Holanda
Author affiliation: Boogaard, Hendrik. Wageningen University and Research. Wageningen Environmental Research. Unit Earth Observation and Environmental Informatics; Holanda
Author affiliation: Angelini, Marcos Esteban. INTA. Instituto de Suelos; Argentina. Wageningen University. Soil Geography and Landscape group; Holanda. International Soil Reference and Information Centre. World Soil Information; Holanda.
Author affiliation: Damiano, Francisco. INTA. Instuto de Clima y Agua; Argentina
Author affiliation: Groenendijk, Piet. Wageningen University and Research. Wageningen Environmental Research, Unit Sustainable Soil Use; Holanda
Author affiliation: Wesseling, Jan. Wageningen University and Research. Chair Soil Physics and Land Management; Holanda
Author affiliation: Veldhuizen, Ab. Wageningen University and Research. Wageningen Environmental Research. Unit Soil, Water and Land Dynamics; Holanda
Repository: INTA Digital (INTA). Instituto Nacional de Tecnología Agropecuaria
Authors: Bontemps, Sophie; Arias, Marcela; Cara, Cosmin; Dedieu, Gérard; Guzzonato, Eric; Hagolle, Olivier; Inglada, Jordi; Matton, Nicolas; Morin, David; Popescu, Ramona; Rabaute, Thierry; Savinaud, Mickael; Sepulcre, Guadalupe; Valero, Silvia; Ahmad, Ijaz; Bégué, Agnès; Wu, Bingfang; de Abelleyra, Diego; Diarra, Alhousseine; Dupuy, Stéphane; French, Andrew; Akhtar, Ibrar ul Hassan; Kussul, Nataliia; Lebourgeois, Valentine; Le Page, Michel; Newby, Terrence; Savin, Igor; Verón, Santiago Ramón; Koetz, Benjamin; Defourny, Pierre
Publication Date: 2015.
Language: English.
Abstract:
Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10–20 meter), revisit frequency (five days) and coverage (global). In this context, the European Space Agency launched in 2014 the “Sentinel-2 for Agriculture” project, which aims to prepare the exploitation of Sentinel-2 data for agriculture monitoring through the development of open source processing chains for relevant products. The project generated an unprecedented data set, made of “Sentinel-2 like” time series and in situ data acquired in 2013 over 12 globally distributed sites. Earth Observation time series were mostly built on the SPOT4 (Take 5) data set, which was specifically designed to simulate Sentinel-2. They also included Landsat 8 and RapidEye imagery as complementary data sources. Images were pre-processed to Level 2A and the quality of the resulting time series was assessed. In situ data about cropland, crop type and biophysical variables were shared by site managers, most of them belonging to the “Joint Experiment for Crop Assessment and Monitoring” network. This data set allowed testing and comparing across sites the methodologies that will be at the core of the future “Sentinel-2 for Agriculture” system.
Author affiliation: Bontemps, Sophie. Université Catholique de Louvain; Bélgica
Author affiliation: Arias, Marcela. Universite de Toulose - Le Mirail; Francia
Author affiliation: Cara, Cosmin. CS Romania S.A.; Rumania
Author affiliation: Dedieu, Gérard. Universite de Toulose - Le Mirail; Francia
Author affiliation: Guzzonato, Eric. CS Systèmes d’Information; Francia
Author affiliation: Hagolle, Olivier. Universite de Toulose - Le Mirail; Francia
Author affiliation: Inglada, Jordi. Universite de Toulose - Le Mirail; Francia
Author affiliation: Matton, Nicolas. Université Catholique de Louvain; Bélgica
Author affiliation: Morin, David. Universite de Toulose - Le Mirail; Francia
Author affiliation: Popescu, Ramona. CS Romania S.A.; Rumania
Author affiliation: Rabaute, Thierry. CS Systèmes d’Information; Francia
Author affiliation: Savinaud, Mickael. CS Systèmes d’Information; Francia
Author affiliation: Sepulcre, Guadalupe. Université Catholique de Louvain; Bélgica
Author affiliation: Valero, Silvia. Universite de Toulose - Le Mirail; Francia
Author affiliation: Ahmad, Ijaz. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; Pakistán
Author affiliation: Bégué, Agnès. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; Francia
Author affiliation: Wu, Bingfang. Chinese Academy of Sciences; República de China
Author affiliation: de Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Author affiliation: Diarra, Alhousseine. Université Cadi Ayyad; Marruecos
Author affiliation: Dupuy, Stéphane. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; Francia
Author affiliation: French, Andrew. United States Department of Agriculture. Agricultural Research Service; Argentina
Author affiliation: Akhtar, Ibrar ul Hassan. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; Pakistán
Author affiliation: Kussul, Nataliia. National Academy of Sciences of Ukraine; Ucrania
Author affiliation: Lebourgeois, Valentine. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; Francia
Author affiliation: Le Page, Michel. Université Cadi Ayyad; Marruecos. Universite de Toulose - Le Mirail; Francia
Author affiliation: Newby, Terrence. Agricultural Research Council; Sudáfrica
Author affiliation: Savin, Igor. V.V. Dokuchaev Soil Science Institute; Rusia
Author affiliation: Verón, Santiago Ramón. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Author affiliation: Koetz, Benjamin. European Space Agency. European Space Research Institute; Italia
Author affiliation: Defourny, Pierre. Université Catholique de Louvain; Bélgica
Repository: CONICET Digital (CONICET). Consejo Nacional de Investigaciones Científicas y Técnicas
Authors: Bontemps, Sophie; Arias, Marcela; Cara, Cosmin; Dedieu, Gérard; Guzzonato, Eric; Hagolle, Olivier; Inglada, Jordi; Matton, Nicolas; Morin, David; Popescu, Ramona; Rabaute, Thierry; Savinaud, Mickael; Sepulcre, Guadalupe; Valero, Silvia; Ahmad, Ijaz; Bégué, Agnès; Wu, Bingfang; De Abelleyra, Diego; Diarra, Alhousseine; Dupuy, Stéphane; French, Andrew; Akhtar, Ibrar ul Hassan; Kussul, Nataliia; Lebourgeois, Valentine; Le Page, Michel; Newby, Terrence; Savin, Igor; Veron, Santiago Ramón; Koetz, Benjamin; Defourny, Pierre
Publication Date: 2015.
Language: English.
Abstract:
Developing better agricultural monitoring capabilities based on Earth Observation data is critical for strengthening food production information and market transparency. The Sentinel-2 mission has the optimal capacity for regional to global agriculture monitoring in terms of resolution (10–20 meter), revisit frequency (five days) and coverage (global). In this context, the European Space Agency launched in 2014 the “Sentinel2 for Agriculture” project, which aims to prepare the exploitation of Sentinel-2 data for agriculture monitoring through the development of open source processing chains for relevant products. The project generated an unprecedented data set, made of “Sentinel-2 like” time series and in situ data acquired in 2013 over 12 globally distributed sites. Earth Observation time series were mostly built on the SPOT4 (Take 5) data set, which was specifically designed to simulate Sentinel-2. They also included Landsat 8 and RapidEye imagery as complementary data sources. Images were pre-processed to Level 2A and the quality of the resulting time series was assessed. In situ data about cropland, crop type and biophysical variables were shared by site managers, most of them belonging to the “Joint Experiment for Crop Assessment and Monitoring” network. This data set allowed testing and comparing across sites the methodologies that will be at the core of the future “Sentinel2 for Agriculture” system.
Instituto de Clima y Agua
Author affiliation: Bontemps, Sophie. Université Catholique de Louvain. Earth and Life Institute; Bélgica
Author affiliation: Arias, Marcela. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; Francia
Author affiliation: Cara, Cosmin. CS Romania S.A.; Rumania
Author affiliation: Dedieu, Gérard. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; Francia
Author affiliation: Guzzonato, Eric. CS Systèmes d’Information; Francia
Author affiliation: Hagolle, Olivier. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; Francia
Author affiliation: Inglada, Jordi. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; Francia
Author affiliation: Matton, Nicolas. Université Catholique de Louvain. Earth and Life Institute; Bélgica
Author affiliation: Morin, David. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; Francia
Author affiliation: Popescu, Ramona. CS Romania S.A.; Rumania
Author affiliation: Rabaute, Thierry. CS Systèmes d’Information; Francia
Author affiliation: Savinaud, Mickael. CS Systèmes d’Information; Francia
Author affiliation: Sepulcre, Guadalupe. Université Catholique de Louvain. Earth and Life Institute; Bélgica
Author affiliation: Valero, Silvia. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; Francia
Author affiliation: Ahmad, Ijaz. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; Pakistán
Author affiliation: Bégué, Agnès. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; Francia
Author affiliation: Wu, Bingfang. Chinese Academy of Sciences. Institute of Remote Sensing and Digital Earth; República de China
Author affiliation: De Abelleyra, Diego. INTA. Instituto de Clima y Agua; Argentina
Author affiliation: Diarra, Alhousseine. Université Cadi Ayyad. Faculté des Sciences Semlalia; Marruecos
Author affiliation: Dupuy, Stéphane. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; Francia
Author affiliation: French, Andrew. United States Department of Agriculture. Agricultural Research Service. Arid Land Agricultural Research Center; Argentina
Author affiliation: Akhtar, Ibrar ul Hassan. Pakistan Space and Upper Atmosphere Research Commission. Space Applications Research Complex. National Agriculture Information Center Directorate; Pakistán
Author affiliation: Kussul, Nataliia. National Academy of Sciences of Ukraine. Space Research Institute and State Space Agency of Ukraine; Ucrania
Author affiliation: Lebourgeois, Valentine. Centre de Coopération Internationale en Recherche Agronomique pour le Développerment; Francia
Author affiliation: Le Page, Michel. Université Cadi Ayyad. Faculté des Sciences Semlalia. Laboratoire Mixte International TREMA; Marruecos. Universite de Toulose - Le Mirail. Centre d’Etudes Spatiales de la BIOsphère; Francia
Author affiliation: Newby, Terrence. Agricultural Research Council; Sudáfrica
Author affiliation: Savin, Igor. V.V. Dokuchaev Soil Science Institute; Rusia
Author affiliation: Verón, Santiago Ramón. INTA. Instituto de Clima y Agua; Argentina
Author affiliation: Koetz, Benjamin. European Space Agency. European Space Research Institute; Italia
Author affiliation: Defourny, Pierre. Université Catholique de Louvain. Earth and Life Institute; Bélgica
Repository: INTA Digital (INTA). Instituto Nacional de Tecnología Agropecuaria
Authors: Verón, Santiago Ramón; de Abelleyra, Diego
Publication Date: 2014.
Language: English.
Abstract:
Despite the effect of water content on radar backscattering is well known, isolating the contributions from soil, vegetation, and vegetation superficial water content (wetness) is still challenging. This work aim to characterize the backscatter response over maize crops in the Argentine pampas with differing soil and vegetation water content and wetness considering multipolarimetric X and C band radar. Two images (RADARSAT-2 and TerraSAR-X) were acquired with a 20' time difference over the same study area. Simultaneously with acquisitions, field measurements of superficial soil moisture, dry and wet vegetation biomass and height were performed over irrigated and non irrigated and standing and non emerged crop fields. Soil moisture showed high r2for backscatter and several polarimetric decompositions approaches. On the contrary low correlation was found for maize crop growth parameters. X and C band radar indexes seem to saturate at low maize biomass values but could be associated to superficial crop wetness.
Author affiliation: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Author affiliation: de Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria; Argentina
Repository: CONICET Digital (CONICET). Consejo Nacional de Investigaciones Científicas y Técnicas
Authors: de Abelleyra, Diego; Verón, Santiago Ramón
Publication Date: 2014.
Language: English.
Abstract:
Realizing the full benefits of MODIS' temporal resolution requires, among others, the correction of the directional effect (i.e. the combined impact of the variation of the measurement geometry and of the observed land surface upon the registered radiant flux). While different BRDF methods have been proposed to address this effect, its performance has been evaluated at coarse spatial resolutions making it difficult to assess its applicability to, for example, crop monitoring. Here we test 2 approaches based on two different assumptions: the Classic approach that relies on the hypothesis of stable target and a recent Alternative that is based on the idea that despite reflectance magnitude may change rapidly, the BRDF shape varies slowly in time. Additionally, we segmented the growing season into different numbers of periods for the BRDF correction (a single period along the growing season, 3 periods based in phenology and 9–12 periods of fixed 16-days). The resulting 6 methods were compared over annual crops (wheat, maize and soybean) at 250 m spatial resolution from a site located in the Argentine Pampas. We used MOD and MYD 09 GQ and GA as inputs and compared the corrected daily red and infrared reflectances and the NDVI time series against the filtered benchmark (input time series with quality filters applied) by means of the high frequency variability (i.e. noise). We also tested whether corrected time series were better correlated with soybean PAR interception and biomass. Our results showed that methods' performance was more explained by the number of periods than by the approach (Classic or Alternative). Single period methods decreased noise by 52%, 55% and 4% for red, infrared and NDVI time series. The use of 3 periods improved the correction performance to 63, 64 and 24% for red, infrared and NVDI time series respectively, while the highest reductions (65, 68 and 32% for red, infrared and NVDI) were found with 16-day intervals (9–12 periods) considering a magnitude inversion process. Wheat displayed the lowest noise reduction compared to the other crops. BRDF parameters obtained from different methods were associated to crop structure, suggesting that they have biophysical meaning. The decrease in noise obtained with correction methods was translated into a better assessment of the fraction of intercepted PAR and biomass. These promising results suggest the possibility of extensive field crop monitoring at an unprecedented temporal resolution.
Author affiliation: de Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Author affiliation: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Repository: CONICET Digital (CONICET). Consejo Nacional de Investigaciones Científicas y Técnicas
Publication Date: 2015.
Language: English.
Abstract:
Understanding regional impacts of recent climate trends can help anticipate how further climate change will affect agricultural productivity. We here used panel models to estimate the contribution of growing season precipitation (P), average temperature (T) and diurnal temperature range (DTR) on wheat, maize and soy yield and yield trends between 1971 and 2012 from 33 counties of the Argentine Pampas. A parallel analysis was conducted on a per county basis by adjusting a linear model to the first difference (i.e., subtracting from each value the previous year value) in yield and first difference in weather variables to estimate crop sensitivity to interannual changes in P, T, and DTR. Our results show a relatively small but significant negative impact of climate trends on yield which is consistent with the estimated crop and county specific sensitivity of yield to interannual changes in P, T and DTR and their temporal trends. Median yield loss from climate trends for the 1971−2012 period amounted to 5.4 % of average yields for maize, 5.1 % for wheat, and 2.6 % for soy. Crop yield gains for this time period could have been 15–20 % higher if climate remained without directional changes in the Pampas. On average, crop yield responded more to trends in T and DTR than in P. Translated into economic terms the observed reductions in maize, wheat, and soy yields due to climate trends in the Pampas would equal $1.1 B using 2013 producer prices. These results add to the increasing evidence that climate trends are slowing yield increase.
Author affiliation: Verón, Santiago Ramón. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Author affiliation: de Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Clima y Agua; Argentina
Author affiliation: Lobell, David B.. University Of Stanford; Estados Unidos
Keywords: CLIMATE; TENDS; MAIZE; SOY; Agricultura; Agricultura, Silvicultura y Pesca; CIENCIAS AGRÍCOLAS.
Repository: CONICET Digital (CONICET). Consejo Nacional de Investigaciones Científicas y Técnicas
Publication Date: 2015.
Language: English.
Abstract:
Understanding regional impacts of recent climate trends can help anticipate how further climate change will affect agricultural productivity. We here used panel models to estimate the contribution of growing season precipitation (P), average temperature (T) and diurnal temperature range (DTR) on wheat, maize and soy yield and yield trends between 1971 and 2012 from 33 counties of the Argentine Pampas. A parallel analysis was conducted on a per county basis by adjusting a linear model to the first difference (i.e., subtracting from each value the previous year value) in yield and first difference in weather variables to estimate crop sensitivity to interannual changes in P, T, and DTR. Our results show a relatively small but significant negative impact of climate trends on yield which is consistent with the estimated crop and county specific sensitivity of yield to interannual changes in P, T and DTR and their temporal trends. Median yield loss from climate trends for the 1971−2012 period amounted to 5.4 % of average yields for maize, 5.1 % for wheat, and 2.6 % for soy. Crop yield gains for this time period could have been 15–20 % higher if climate remained without directional changes in the Pampas. On average, crop yield responded more to trends in T and DTR than in P. Translated into economic terms the observed reductions in maize, wheat, and soy yields due to climate trends in the Pampas would equal $1.1 B using 2013 producer prices. These results add to the increasing evidence that climate trends are slowing yield increase.
Author affiliation: Verón, Santiago Ramón. INTA. Instituto de Clima y Agua; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina
Author affiliation: De Abelleyra, Diego. INTA. Instituto de Clima y Agua; Argentina
Author affiliation: Lobell, David B. Stanford University. Department of Environmental Earth System Science and Program on Food Security and Environment; Estados Unidos
Repository: INTA Digital (INTA). Instituto Nacional de Tecnología Agropecuaria
Authors: Bégue, Agnes; Arvor, Damian; Bellon, Beatriz; Betbeder, Julie; De Abelleyra, Diego; Ferraz, Rodrigo; Lebourgeois, Valentine; Lelong, Camille; Simoes, Margareth; Veron, Santiago Ramón
Publication Date: 2018.
Language: English.
Abstract:
For agronomic, environmental, and economic reasons, the need for spatialized information about agricultural practices is expected to rapidly increase. In this context, we reviewed the literature on remote sensing for mapping cropping practices. The reviewed studies were grouped into three categories of practices: crop succession (crop rotation and fallowing), cropping pattern (single tree crop planting pattern, sequential cropping, and intercropping/agroforestry), and cropping techniques (irrigation, soil tillage, harvest and post-harvest practices, crop varieties, and agro-ecological infrastructures). We observed that the majority of the studies were exploratory investigations, tested on a local scale with a high dependence on ground data, and used only one type of remote sensing sensor. Furthermore, to be correctly implemented, most of the methods relied heavily on local knowledge on the management practices, the environment, and the biological material. These limitations point to future research directions, such as the use of land stratification, multi-sensor data combination, and expert knowledge-driven methods. Finally, the new spatial technologies, and particularly the Sentinel constellation, are expected to improve the monitoring of cropping practices in the challenging context of food security and better management of agro-environmental issues
Inst. de Clima y Agua
Author affiliation: Bégue, Agnes. CIRAD, UMR TETIS; Francia. CIRAD, Université Montpellier, Francia
Author affiliation: Arvor, Damian. Centre National de la Recherche Scientifique (CNRS); Francia
Author affiliation: Bellon, Beatriz. CIRAD, UMR TETIS; Francia. CIRAD, Université Montpellier, Francia
Author affiliation: Betbeder, Julie. CIRAD, Université Montpellier, Francia. CIRAD, UPR Forests & Societies; Francia
Author affiliation: De Abelleyra, Diego. INTA. Instituto de Clima y Agua; Argentina
Author affiliation: Ferraz, Rodrigo. EMBRAPA Solos; Brasil
Author affiliation: Lebourgeois, Valentine. CIRAD, UMR TETIS; Francia. CIRAD, Université Montpellier, Francia
Author affiliation: Lelong, Camille. CIRAD, UMR TETIS; Francia. CIRAD, Université Montpellier, Francia
Author affiliation: Simoes, Margareth. EMBRAPA Solos; Brasil. Rio de Janeiro State University; Brasil
Author affiliation: Verón, Santiago Ramón. INTA. Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires. Facultad de Agronomía; Argentina
Repository: INTA Digital (INTA). Instituto Nacional de Tecnología Agropecuaria
Authors: Waldner, François; de Abelleyra, Diego; Verón, Santiago Ramón; Zhang, Miao; Wu, Bingfang; Plotnikov, Dmitry; Bartalevev, Sergey; Lavreniuk, Mykola; Skakun, Sergii; Kussul, Nataliia; Le Maire, Guerric; Dupuy, Stéphane; Jarvis, Ian; Defourny, Pierre
Publication Date: 2016.
Language: English.
Abstract:
Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) mean composites (red and near-infrared channels). Different strategies were devised to assess the accuracy of the classification methods: confusion matrices and derived accuracy indicators with and without equalizing class proportions, assessing the pairwise difference error rates and accounting for the spatial resolution bias. The robustness of the accuracy with respect to a reduction of the quantity of calibration data available was also assessed by a bootstrap approach in which the amount of training data was systematically reduced. Methods reached overall accuracies ranging from 85% to 95%, which demonstrates the ability of 250 m imagery to resolve fields down to 20 ha. Despite significantly different error rates, the site effect was found to persistently dominate the method effect. This was confirmed even after removing the share of the classification due to the spatial resolution of the satellite data (from 10% to 30%). This underlines the effect of other agrosystems characteristics such as cloudiness, crop diversity, and calendar on the ability to perform accurately. All methods have potential for large area cropland mapping as they provided accurate results with 20% of the calibration data, e.g. 2% of the study area in Ukraine. To better address the global cropland diversity, results advocate movement towards a set of cropland classification methods that could be applied regionally according to their respective performance in specific landscapes.
Author affiliation: Waldner, François. Université Catholique de Louvain; Bélgica
Author affiliation: de Abelleyra, Diego. Instituto Nacional de Tecnología Agropecuaria; Argentina
Author affiliation: Verón, Santiago Ramón. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina. Instituto Nacional de Tecnología Agropecuaria; Argentina. Université Catholique de Louvain; Bélgica
Author affiliation: Zhang, Miao. Chinese Academy of Sciences; República de China
Author affiliation: Wu, Bingfang. Chinese Academy of Sciences; República de China
Author affiliation: Plotnikov, Dmitry. Space Research Institute Of Russian Academy Of Sciences; Rusia. Université Catholique de Louvain; Bélgica
Author affiliation: Bartalevev, Sergey. Space Research Institute Of Russian Academy Of Sciences; Rusia
Author affiliation: Lavreniuk, Mykola. Space Research Institute Nas And Ssa; Ucrania
Author affiliation: Skakun, Sergii. Space Research Institute Nas And Ssa; Ucrania
Author affiliation: Kussul, Nataliia. Space Research Institute Nas And Ssa; Ucrania. Université Catholique de Louvain; Bélgica
Author affiliation: Le Maire, Guerric. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil
Author affiliation: Dupuy, Stéphane. No especifica;
Author affiliation: Jarvis, Ian. Lethbridge Research Centre. Agriculture And Agri-foods; Canadá
Author affiliation: Defourny, Pierre. Université Catholique de Louvain; Bélgica
Repository: CONICET Digital (CONICET). Consejo Nacional de Investigaciones Científicas y Técnicas
Authors: Waldner, François; De Abelleyra, Diego; Veron, Santiago Ramón; Zhang, Miao; Wu, Bingfang; Plotnikov, Dmitry; Bartalev, Sergey; Lavreniuk, Mykola; Skakun, Sergii; Kussul, Nataliia; Le Maire, Guerric; Dupuy, Stéphane; Jarvis, Ian; Defourny, Pierre
Publication Date: 2016.
Language: English.
Abstract:
Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiometer (MODIS) mean composites (red and near-infrared channels). Different strategies were devised to assess the accuracy of the classification methods: confusion matrices and derived accuracy indicators with and without equalizing class proportions, assessing the pairwise difference error rates and accounting for the spatial resolution bias. The robustness of the accuracy with respect to a reduction of the quantity of calibration data available was also assessed by a bootstrap approach in which the amount of training data was systematically reduced. Methods reached overall accuracies ranging from 85% to 95%, which demonstrates the ability of 250 m imagery to resolve fields down to 20 ha. Despite significantly different error rates, the site effect was found to persistently dominate the method effect. This was confirmed even after removing the share of the classification due to the spatial resolution of the satellite data (from 10% to 30%). This underlines the effect of other agrosystems characteristics such as cloudiness, crop diversity, and calendar on the ability to perform accurately. All methods have potential for large area cropland mapping as they provided accurate results with 20% of the calibration data, e.g. 2% of the study area in Ukraine. To better address the global cropland diversity, results advocate movement towards a set of cropland classification methods that could be applied regionally according to their respective performance in specific landscapes.
Instituto de Clima y Agua
Author affiliation: Waldner, François. Université catholique de Louvain. Earth and Life Institute - Environment, Croix du Sud; Belgica
Author affiliation: De Abelleyra, Diego. INTA. Instituto de Clima y Agua; Argentina
Author affiliation: Veron, Santiago Ramón. INTA. Instituto de Clima y Agua; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; Argentina
Author affiliation: Zhang, Miao. Chinese Academy of Science. Institute of Remote Sensing and Digital Earth; China
Author affiliation: Wu, Bingfang. Chinese Academy of Science. Institute of Remote Sensing and Digital Earth; China
Author affiliation: Plotnikov, Dmitry. Russian Academy of Sciences. Space Research Institute. Terrestrial Ecosystems Monitoring Laboratory; Rusia
Author affiliation: Bartalev, Sergey. Russian Academy of Sciences. Space Research Institute. Terrestrial Ecosystems Monitoring Laboratory; Rusia
Author affiliation: Lavreniuk, Mykola. Space Research Institute NAS and SSA. Department of Space Information Technologies; Ucrania
Author affiliation: Skakun, Sergii. Space Research Institute NAS and SSA. Department of Space Information Technologies; Ucrania. University of Maryland. Department of Geographical Sciences; Estados Unidos
Author affiliation: Kussul, Nataliia. Space Research Institute NAS and SSA. Department of Space Information Technologies; Ucrania
Author affiliation: Le Maire, Guerric. UMR Eco&Sols, CIRAD; Francia. Empresa Brasileira de Pesquisa Agropecuária. Meio Ambiante; Brasil
Author affiliation: Dupuy, Stéphane. Centre de Coopération Internationale en Recherche Agronomique pour le Développement. Territoires, Environnement, Télédétection et Information Spatiale; Francia
Author affiliation: Jarvis, Ian. Agriculture and Agri-Food Canada. Science and Technology Branch. Agri-Climate, Geomatics and Earth Observation; Canadá
Author affiliation: Defourny, Pierre. Université Catholique de Louvain. Earth and Life Institute - Environment, Croix du Sud; Belgica
Repository: INTA Digital (INTA). Instituto Nacional de Tecnología Agropecuaria