TY - CHAP A1 - Cremer, Tobias A1 - Martetschläger, Lea A1 - Bartsch, Marco A1 - Riethmüller, Sina A1 - Schnautz, Carmel A1 - Gaiser, Thomas A1 - Bloch, Ralf T1 - Entwicklung ertragskundlicher und ökologischer Paramter in einem Brandenburger Alley Cropping System T2 - Tagungsband 9. Forum Agroforstsysteme, 27. & 28. September 2023 KW - Agroforst; Modellprojekt; Brandenburg; Reallabor Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:eb1-opus-7980 N1 - https://agroforst-info.de/nachlese-9-forum-agroforstsysteme/ ER - TY - JOUR A1 - Mouratiadou, Ioanna A1 - Lemke, Nahleen A1 - Chen, Cheng A1 - Wartenberg, Ariani A1 - Bloch, Ralf A1 - Donat, Marco A1 - Gaiser, Thomas A1 - Hanike Basavegowda, Deepak A1 - Helming, Katharina A1 - Ali Hosseini Yekani, Seyed A1 - Krull, Marcos A1 - Lingemann, Kai A1 - Macpherson, Joseph A1 - Melzer, Marvin A1 - Nendel, Claas A1 - Piorr, Annette A1 - Shaaban, Mostafa A1 - Zander, Peter A1 - Weltzien, Cornelia A1 - Bellingrath-Kimura, Sonoko Dorothea T1 - The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems JF - Environmental Science and Ecotechnology N2 - Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands. KW - Digital agriculture KW - Ecosystem services KW - Decision support system KW - Farming practices KW - Biodiversity KW - Modelling KW - Small-scale management Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:eb1-opus-8012 SN - 2666-4984 VL - 16 PB - Elsevier ER - TY - JOUR A1 - Bazzo, Clara Oliva Gonçalves A1 - Kamali, Bahareh A1 - Behrend, Dominik A1 - Hueging, Hubert A1 - Schleip, Inga A1 - Mosebach, Paul A1 - Behrendt, Axel A1 - Gaiser, Thomas T1 - Assessing the Effect of Field Disturbances On Biomass Estimation in Grasslands Using UAV-Derived Canopy Height Models JF - PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science N2 - Abstract Accurate estimation of biomass in grasslands is essential for understanding ecosystem health and productivity. Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools for biomass estimation using canopy height models derived from high-resolution imagery. However, the impact of field disturbances, such as lodging and molehills, on the accuracy of biomass estimation using UAV-derived canopy height models remains underexplored. This study aimed to assess the relationship between UAV-derived canopy height and both reference canopy height measurements and dry biomass, accounting for different management systems and disturbance scenarios. UAV data were collected using a multispectral camera, and ground-based measurements were obtained for validation. The results revealed that UAV-derived canopy height models remained accurate in estimating vegetation height, even in the presence of disturbances. However, the relationship between UAV-derived canopy height and dry biomass was affected by disturbances, leading to overestimation or underestimation of biomass depending on disturbance type and severity. The impact of disturbances on biomass estimation varied across cutting systems. These findings highlight the potential of UAV-derived canopy height models for estimating vegetation structure, but also underscore the need for caution in relying solely on these models for accurate biomass estimation in heterogeneous grasslands. Future research should explore strategies to enhance biomass estimation accuracy by integrating additional data sources and accounting for field disturbances. KW - - KW - Vegetation structure KW - Monitoring KW - Ecosystem services KW - Remote sensing Y1 - 2025 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:eb1-opus-9685 SN - 2512-2789 SN - 2512-2819 VL - 93 IS - 1 SP - 37 EP - 49 PB - Springer International Publishing CY - Cham ER -