Exploring the trade-offs between spatial and spectral resolution in mapping invasive alien trees

Invasive alien plants, particularly trees, are a global problem because invasions have ecological, social, and economic impacts. Due to the rapid rate of tree invasions, continuous monitoring for management is important. Airborne hyperspectral imagery is ideal for monitoring but expensive to acquire, often prohibitively so for continuous monitoring. Conversely, spaceborne multispectral imagery is freely available and often has high temporal resolution, but the trade-off is lower spatial and spectral resolutions. Freely available spaceborne hyperspectral imagery has higher spectral resolution, but lower spatial resolution. In resource-constrained regions, freely available remote sensing imagery is often the only option for monitoring. To address trade-offs between spatial and spectral resolution in invasive alien tree mapping for resource-constrained regions, this study compares four sensors that are freely available in South Africa. These sensors cover a wide range of spatial and spectral resolutions (0.25–60 m and 3–285 bands respectively). The use of data fusion to overcome this trade-off was also explored. We found that all three spaceborne sensors performed similarly, with SPOT6 marginally resulting in the highest accuracy overall and for discriminating among alien taxa. Sentinel-2 exhibited the highest accuracy for discriminating alien taxa from other classes. Notably aerial photography collected as part of government airborne campaigns performed poorly. Data fusion of EMIT with Sentinel-2, i.e. imagery with higher spectral and higher spatial resolutions respectively, led to a marked improvement in accuracy (∼ 5 %). Therefore, in resource-constrained countries, using any of these spaceborne sensors for invasive alien tree mapping may provide robust classification results, but data fusion of sensors with high spatial and spectral resolutions is highly recommended.