UNSUPERVISED SEGMENTATION OF SMALLHOLDER FIELDS IN MOZAMBIQUE USING PLANETSCOPE IMAGERY

A large part of Earth's land surface is covered by dryland ecosystems, which are subject to climate extremes that are projected to increase under future climate scenarios. By using a mathematical vegetation model, we studied the impact of single years of extreme rainfall on the vegetation in the Sahel. We found a contrasting response of grasses and trees to these extremes, strongly dependent on the way precipitation is spread over the rainy season, as well as a long-term impact on CO₂ uptake.

Existing global scale above-ground biomass (AGB) maps are made at very high spatial resolution collecting data during several years. In this paper we discuss the use of a new data set from the SMOS satellite: the vegetation optical depth estimated from low microwave frequencies. It is shown that this new data set is highly sensitive to AGB. The spacial resolution of SMOS is coarse (40 km) but the new data set can be used to monitor AGB variations with time due to its high revisit frequency.

Anticipating impacts of changes in rainfall regimes on dryland ecosystems requires the understanding of the functional response to rainfall of those water limited environments. Here we show for two arid/semi-arid African regions based on satellite data that higher rainfall variability leads to a more dynamic vegetation response to rainfall. This applies irrespective of vegetation type. It moreover indicates that regions experiencing a higher rainfall variability may be more resilient to drought.

Relationships between ecosystem properties of semi-arid savanna and reflected solar radiance between 35 and 1800nm were investigated. Normalised combinations of reflectance for the near infrared, shortwave infrared, and 600 to 700nm were strongly affected by solar and viewing angle effects. Ecosystem properties of savannas were strongly correlated with reflectance at 350-1800nm, and normalised combinations of reflectance were strong predictors of the savanna ecosystem properties.

Limitations of satellite-based normalized difference vegetation index (NDVI) for monitoring vegetation trends are investigated using observations from the Widou Thiengoly test site in northern Senegal. NDVI do not reflect the large differences found in biomass production and species composition between grazed and ungrazed plots. This is problematic for vegetation trend analysis in the context of drastically increasing numbers of Sahelian livestock in recent decades.

The study compared evapotranspiration (ET) modelled by two remote sensing models and one hydrological model in a river catchment in Denmark. The results show that the spatial patterns of ET produced by the remote sensing models are more similar to each other than to the fluxes produced by the hydrological model. This indicates potential benefits to the hydrological modelling community from integrating spatial information derived through remote sensing methodology into the hydrological models.