Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/12800

Title: Agriculture pest and disease risk maps considering MSG satellite data and Land Surface Temperature.
Authors: Marques da Silva, José Rafael
Damásio, Carlos
Sousa, Adélia M. O.
Bugalho, Lourdes
Pessanha, Luis
Quaresma, Paulo
Keywords: Land Surface Temperature
LST
Satellite Application Facility
SAF
EUMETSAT
MSG
Pest Management
Pest risk maps
Issue Date: 2015
Publisher: International Journal of Applied Earth Observation and Geoinformation
Citation: MARQUES DA SILVA, JOSÉ R.; DAMÁSIO, CARLOS V.; SOUSA, ADÉLIA M. O.; BUGALHO, LOURDES; PESSANHA, LUÍS; QUARESMA, PAULO (2015). Agriculture pest and disease risk maps considering MSG satellite data and Land Surface Temperature. International Journal of Applied Earth Observation and Geoinformation, 38:40-50.
Abstract: Pest risk maps for agricultural use are usually constructed from data obtained from in-situ meteorological weather stations, which are relatively sparsely distributed and are often quite expensive to install and difficult to maintain. This leads to the creation of maps with relatively low spatial resolution, which are very much dependent on interpolation methodologies. Considering that agricultural applications typically require a more detailed scale analysis than has traditionally been available, remote sensing technology can offer better monitoring at increasing spatial and temporal resolutions, thereby improving pest management results and reducing costs. This article uses ground temperature, or land surface temperature (LST), data distributed by EUMETSAT/LSASAF (with a spatial resolution of 3 x 3 km (nadir resolution) and a revisiting time of 15 min) to generate one of the most commonly used parameters in pest modelling and monitoring: “thermal integral over air temperature (accumulated degree-days)”. The results show a clear association between the accumulated LST values over a threshold and the accumulated values computed from meteorological stations over the same threshold (specific to a particular tomato pest). The results are very promising and enable the production of risk maps for agricultural pests with a degree of spatial and temporal detail that is difficult to achieve using in-situ meteorological stations.
URI: http://hdl.handle.net/10174/12800
Type: article
Appears in Collections:ICAAM - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
ERU - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica

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