Linking remote sensing and crop models for regional simulations for rainfed and irrigation crops

About Carmen Cecilia Silva Diaz

About the project

Crop type maps are important to represent spatial and temporal heterogeneity of agricultural lands, identify region-specific challenges, quantify the system’s response to climate change, and develop strategies for sustainable agriculture. During the last decades, satellite sensors i.e., optical and synthetic aperture radar (SAR) sensors have provided new opportunities for producing crop type maps compared with the costly and time-consuming traditional approaches. The recent emergences of Sentinel-1&2 data with high spatial, temporal, and spectral resolutions have placed science at a stage to produce crop type maps at the resolution up to 10 m at continental scale. In Germany, two recent studies have used intra-annual reflectance composites from Sentinel-2 and Landsat for producing these maps. Figure 1 depicts the patterns for three consecutive years of 2017-2019 in Ilmenaue catchment, Lower Saxony. Notwithstanding the associated uncertainty in the method applied to produce these maps (especially regarding winter crops), changes in the relative shares of crop areas have been discerned even within three years. However, such detailed information has not been integrated in crop models for more reliable crop yield estimation. The rare applications on contribution of crop type maps to crop models are based on a crucial assumption of time-unaltered crop areas and have not considered the change in vegetative patterns. Considering such spatio-temporal variations is crucial for reliable crop model parameterization and estimation of crop yields and CWD at field level. At regional scale, underrating these factors influences crop yield aggregation (from original grid level simulation) and as a result influence the reliability of results for management purposes. However, so far, this particular aspect has not been received enough attention in literature.


University of Bonn, Germany

Period of collaboration

From Mar 2023 to present


  • First Examiner: Dr. Bahareh Kamali
  • Second Examiner: Dr. Thomas Gaiser
Bahareh Kamali
Scientist and lecturer