RSRU – Projects

Time-series Analysis of Hyper-temporal satellite data, using High Performance Computing

The purpose of the research is to unlock the wealth of information in the large data sets of hyper-temporal (daily, 10-daily), coarse resolution satellite images using advanced time-series analysis in a High Performance Computing (HPC) environment. Sustainable development requires spatially-explicit information on environmental change and long-term satellite data archives (e.g. MODIS, AVHRR) are the only sources of such information at regional scales.
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Satellite Derived Vegetation phenology

20 years of AVHRR satellite imagery were used to model vegetation phenology, allowing unique analyses of patterns across the entire southern Africa. Vegetation phenology examines life cycle events such as bud burst, flowering, and leaf senescence.
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Advanced Fire Information System (AFIS)

Veld and fynbos fires in southern Africa during the dry seasons account for costly damage to human life and settlements, infrastructure, land cover, stock and game annually. In partnership with Eskom, the University of Maryland and NASA, and with funding from the South African government, the CSIR has developed the advanced fire information system (AFIS) to locate fires in near-real time over southern Africa.
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Automated feature extraction in urban areas

One of the fundamental difficulties that authorities face when planning a response to the formation and growth of informal settlements is the lack of spatial and temporal data. Such data allow us to identify and quantify services and infrastructure, which are required to improve our understanding of settlement morphology, population distribution and emerging settlement patterns.
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Vegetation monitoring in Kruger National Park

The objective of this research is to monitor herbaceous (grass) biomass production in Kruger National Park (KNP). Data on end-of-season herbaceous biomass, have been collected at approximately 533 locations in KNP since 1989, providing the opportunity to create spatial maps of herbaceous biomass production using remote sensing data (AVHRR and MODIS). These dynamic maps of herbaceous biomass are essential inputs to fire and wildlife management models.
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Advancing ICT for DRM in Africa (AÏDA)

The CSIR Meraka Institute forms part of the European Union (EU) Framework 7 program through the Advancing ICT for DRM in Africa (AÏDA) project. The AÏDA project aims at acquiring and sharing knowledge about affordable ICT (Information and Communication Technologies) solutions in Africa with the ambition to reduce the risk of natural disasters and to improve the capacity to respond to disasters.
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Automated land-cover change detection

Researchers at the Meraka Institute of the CSIR have taken on the challenge of automated land-cover change detection by applying novel signal processing, time-series analyses and machine learning methods to the problem, using high-performance computing resources. The multidisciplinary research involves computer scientists, electronic engineers, ecologists and remote sensing specialists.
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