In this paper we aim to show a proof-of-principle approach to detect and monitor weed management using glyphosate-based herbicides in agricultural practices. In a case study in Germany, we demonstrate the application of Sentinel-2 multispectral time-series data. Spectral broadband vegetation indices were analysed to observe vegetation traits and weed damage arising from herbicide-based management. The approach has been validated with stakeholder information about herbicide treatment using commercial products. As a result, broadband NDVI calculated from Sentinel-2 data showed explicit feedback after the glyphosate-based herbicide treatment. Vegetation damage could be detected after just two days following of glyphosate-based herbicide treatment. This trend was observed in three different application scenarios, i.e., during growing stage, before harvest and after harvest. The findings of the study demonstrate the feasibility of satellite based broadband NDVI data for the detection of glyphosate-based herbicide treatment and, e.g., the monitoring of latency to harvesting. The presented results can be used to implement monitoring concepts to provide the necessary transparency about weed treatment in agricultural practices and to support environmental monitoring.

Balancing biodiversity conservation with land use for agricultural production is a major societal challenge. Conservation activities must be prioritized since funds and resources for conservation are insufficient in the context of current threats, and conservation competes with other societal priorities. In order to contribute to conservation priority-setting literature, we applied an environmental model, Pressure–State–Response (PSR), to develop a set of criteria for identifying priority areas for biodiversity conservation in Vietnam. Our empirical data have been compiled from 185 respondents and categorized into three groups: Governmental Administration and Organizations, Universities and Research Institutions, and Protected Areas. The Analytic Hierarchy Process (AHP) theory was used to identify the weight of all criteria. Our results show that the priority levels for biodiversity conservation identified by these three factors are 41% for “Pressure”, 26% for “State”, and 33% for “Response”. Based on these three factors, seven criteria and seventeen indicators were developed to determine priority areas for biodiversity conservation. Besides, our study also reveals that the groups of Governmental Administration and organizations and Protected Areas put a focus on the “Pressure” factor, while the group of Universities and Research Institutions emphasized the importance of the “Response” factor in the evaluation process. We suggest that these criteria and indicators be used to identify priority areas for biodiversity conservation in Vietnam.