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5 December 2016 Remote sensing applications for sustainable agriculture in South Africa (Conference Presentation)
Caren Jarmain, Adriaan Van Niekerk, Ruben Goudriaan
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Proceedings Volume 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII; 99980C (2016) https://doi.org/10.1117/12.2241860
Event: SPIE Remote Sensing, 2016, Edinburgh, United Kingdom
Abstract
Agriculture contributes greatly to the economy of South Africa (SA), through job creation and produce exports. SA is classified as a semi-arid country and due to its low rainfall, fierce competition exists for the available water resources. Balancing the need for water resources on the one hand, with the importance of agricultural production on the other, is often challenging. A lot of emphasis is placed on prudent water management and enhanced crop water use efficiency. Suitable information and tools are key in empowering both water resources managers and (crop) producers for sustainable agricultural production. Information and tools available at frequent intervals throughout the production season and at a range of levels - from the field to the catchment and for the entire country – has become essential. The frequency and availability of remote sensing data, developments in algorithms to produce information related to the water cycle and crop growth and hence the actual information sets produced over time, makes for fitting solutions. Though much progress has been made over the past years to integrate these spatial data products into water management and agricultural systems, it is likely still in its infancy. In the paper, some flagship projects related to sustainable agriculture and water management – both research and applied - are showcased.
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Caren Jarmain, Adriaan Van Niekerk, and Ruben Goudriaan "Remote sensing applications for sustainable agriculture in South Africa (Conference Presentation)", Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99980C (5 December 2016); https://doi.org/10.1117/12.2241860
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KEYWORDS
Agriculture
Remote sensing
Algorithm development
Research management
Applied research
Data integration
Current controlled current source
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