Monitoring agricultural systems becomes increasingly important in the context of global
challenges like climate change, biodiversity loss, population growth, and the rising demand …

Many applications that target dynamic land surface processes require a temporal
observation frequency that is not easily satisfied using data from a single optical sensor …

Digitalisation in the agricultural sector continues to expand. At the same time demands for
an agricultural policy offering better support for sustainability become increasingly fervent …

Abstract Agricultural systems in Central Europe were redesigned during the last century to
attain maximum yields. The results often lead to homogeneous landscapes with only few …

Agricultural productivity varies greatly among agricultural systems and among regions in
Europe. A multilevel logistic regression model was applied to investigate the labour …

Many countries are reshaping their agricultural policies to better enhance biodiversity and
ecosystem services (BES) in farmlands, but measuring the effectiveness of policy …

Precise and timely information on crop spatial distribution over large areas is paramount to
agricultural monitoring, food security, and policy development. Currently, automatically …

Multi-modality datasets offer advantages for processing frameworks with complementary
information, particularly for large-scale cropland mapping. Extensive training datasets are …

The fostering of bioenergy by European and German energy policies in recent years has led
to a strong increase in the cultivation of energy crops, especially maize for biogas …

CONTEXT Efforts to bring together landscape analysis and farming systems have failed to
explain the drivers behind their spatial distribution. Since agricultural landscapes are an …