How much is enough? Habitat mapping and the need for hyper-resolution

"Knowledge of the spatial distribution of habitat types on landscapes scales is a valuable asset in effective resource and conservation management. Increasingly such information is derived using remote sensing based approaches. Yet, researchers frequently face the difficult decision which remote sensing data to acquire for a particular task. Apart from specific sensor to sensor comparisons there is no general understanding on how fundamental sensor characteristics such as spectral and spatial resolution interplay in determining mapping success. We developed a general modelling framework for the identification of both sufficient and optimal sensor characteristics for a given modelling task with respect to both spectral and spatial resolution based on airborne hyperspectral imagery. The focus of our study lays on mapping habitat for different zoological communities in montane mixed forest stands in the Bavarian Forest national park, Germany alongside the determination of data requirements. Besides defining sensible limits in terms of spatial and spectral resolution the presented approach revealed some degree of complementarity between spatial and spectral resolution, where one can make up for shortcomings in the other. Estimating the expected increase in model accuracy for transitioning from less suitable data to more suitable data can help inform on suitable sensor choice or sensor-setups as well as evaluating the expected return of purchasing better data-sets. Finally, our approach also contributes to support the definition of sensor requirements for future missions in an objective, data-driven way.