A UAV-mounted dual-wavelength LiDAR for leaf water content retrieval

• Applicants: Dr. Teja Kattenborn; Professor Dr.-Ing. Alexander Reiterer
• Subject Area: Measurement Systems
• Term: since 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 541018379

With global and climate change, many regions will experience more intense and frequent drought events. Droughts are causing significant ecological and agricultural challenges, including increased likelihood of plant mortality, reduced productivity, and ascended vulnerability to pests and pathogens. A central metric for tracking such drought impacts on vegetation is the leaf water content (g/cm2). However, efficient and accurate methods for monitoring leaf water content are lacking. Optical remote sensing from drones or satellites provides promising technologies for an effective monitoring of leaf water content across large areas. However, current methods for estimating leaf water content are mainly based on passive sensors with limited accuracy and require sun light with clear sky conditions. Moreover, passive sensors can only inform properties of leaves of the uppermost canopy layers and, hence, provide limited value for understanding leaf water dynamics within plants, vegetation stands or ecosystems. For the first phase of the SPP, we propose to develop a novel leaf water content retrieval based on active remote sensing with a UAV-based dual-wavelength LiDAR system. With terrestrial systems, pioneering studies have highlighted the potential of dual-wavelength LiDAR for an accurate leaf water content retrieval in 3D. To exploit this potential for an efficient monitoring across larger spatial scales, we will develop the first UAV-compatible dual-wavelength LiDAR, which will be specifically tailored for leaf water content retrieval. The initial development of the sensor and the retrieval algorithm will be guided by radiative transfer modelling and conducted in a laboratory environment. The LiDAR will then be mounted on UAVs and thoroughly tested and optimized across several experimental sites. These sites will cover a wide range of plant species, functional properties and vegetation structural complexities. The proposed UAV-compatible LiDAR will be of enormous value for several applications in the context of drought-related vegetation assessments, including precision farming, urban green management and ecosystem monitoring. In the second phase of the SPP, we plant to 1) further optimize the LiDAR in terms of energy-use, data-efficiency and weight, 2) advance UAV-compatible dual-wavelength LiDAR technologies for retrieving further essential leaf biochemicals (e.g. pigments or nutrients contents) and 3) harness the proposed UAV-LiDAR technology in concert with Earth observation satellite data for large-scale assessments of leaf water content.

• DFG Programme: Priority Programmes
• Subproject of: SPP 2433: Metrology on flying platforms
• International Connection: Finland
• Co-Investigators: Professor Dr. Hannes Feilhauer; Professor Dr. Martin Herold; Dr. Ronny Richter; Professorin Dr. Christiane Werner; Professor Dr. Christian Wirth
• Cooperation Partners: Professor Dr. Juha Hyyppä; Dr. Samuli Juntilla