The assessment of UAV-based multispectral imagery to monitor lichen-dominated biological soil crusts response to fog and disturbances, Central Namib

No Thumbnail Available



Journal Title

Journal ISSN

Volume Title


Namibia University of Science and Technology


Lichen-dominated biological soil crusts (BSCs or biocrusts) are a major contributor to biodiversity and ecosystem services of desert environments. There appropriate monitoring of lichen fields of the hyperarid coastal Namib Desert is important to understanding their greater ecological functions, such as vital CO2 sinks, and for management of socio-economic land use practices (i.e. mining, tourism, off-road tracks) which destroy the endemic, fragile and slow recovering lichens. Thanks to advanced remote sensing techniques such as the use of Unmanned Aerial Vehicles (UAVs or drones), lichen fields can be monitored, whilst minimising the environmental impact of traditional ground-based ecological research, as well as overcoming challenges in monitoring lichens with the satellite datasets, piloted aircraft. The objectives of this study was to assess the effects of hourly sunshine intensity on the use of UAV-based multispectral imagery for monitoring lichen-dominated biological soil crusts in the hyper-arid Central Namib Desert. We then assess the applications UAV-based NDVI to observe lichen photosynthetic activity response to moisture input, topography and disturbances, as well as to assess the influence of micro-topography and disturbances in off-road tracks on lichen coverage. We tested the performance of UAV-based Parrot Sequoia multispectral sensor by acquiring time series flights from 08:00 to 17:00 during a fog day. Time series of radiometrically and atmospherically corrected and uncorrected multispectral image datasets (i.e. reflectance images and vegetation indices) were compare it to solar elevation. Influence of brightness effects in sample plot on image values was tested with one-way ANOVA and Tukey HSD pot-hoc test for pairwise comparisons. There was statistical significant difference in means of the sample plots with p < 0.05. We also gathered time series UAV-based NDVI images on fog and non-fog day derived the temporal patterns of lichen photosynthetic activity in responding to wet and dry conditions, overtime. These UAV observations were supported with ground cover observation of lichens. Statistical analysis was performed to determine presence of significant differences of lichen cover and NDVI response between micro-topographic habitats (i.e. ridges, windward and leeward sides of the relief), and as well in landforms such as plains, river washes and tracks. The oneway ANOVA and Student-test (t-tests), were considered significant at p < 0.05 for both UAV and ground 15 observations. Polynomial regression analysis of the relationship between elevation and ground lichen cover and NDVI was significantly correlated with p-values of < 0.05. Well illuminated good quality images can be captured at low solar elevation, in morning images at 08:00 and in the later afternoon at 17:00. Midday images taken between 10:00 and 15:00 at higher solar elevation are heavily impacted by brightness effects. The radiometrically corrected images and NDVI were more accurate than the raw uncorrected images. UAV-based NDVI can estimate photosynthetic activity when lichens are hydrated by fog or higher air humidity, as opposed to when they are desiccated and photosynthetic activity is inhibited. Elevation is good predictor lichen cover and photosynthetic activity. Lichen cover is heavily impacted by off-road tracks. The topographic attribute influence the distribution of lichen cover and lichen species diversity. This research study has provided insights into a means to monitor these sensitive environments. It also enables informed decision making to manage natural resource and regulate socio-economic land-use.


Thesis submitted in partial fulfillment of the requirements for the degree of Master of Natural Resources Management at the Namibia University of Science and Technology


Unmanned Aerial Vehicle (UAV) remote sensing, biological soil crusts (BSCs), Namib Desert Lichen fields, multi-spectral imagery, fog-driven ecosystems, off-road driving disturbance


Nambwandja, A.N. (2022). The assessment of UAV-based multispectral imagery to monitor lichen-dominated biological soil crusts response to fog and disturbances, Central Namib [Unpublished Masters Thesis]. Namibia University of Science and Technology.