The potential of Pathfinder AVHRR data for providing surrogate climatic variables across Africa and Europe for epidemiological applications

作者: Robert M Green , Simon I Hay , None

DOI: 10.1016/S0034-4257(01)00270-X

关键词: Remote sensingEnvironmental scienceVegetationVapour Pressure DeficitContext (language use)Linear regressionLatitudeAdvanced very-high-resolution radiometerElevationNormalized Difference Vegetation Index

摘要: Surface climatic conditions are key determinants of arthropod vector distribution and abundance consequently affect transmission rates any diseases they may carry. Remotely sensed observations by satellite sensors the only feasible means obtaining regional continental scale measurements climate at regular intervals for real-time epidemiological applications such as disease early warning systems. The potential Pathfinder AVHRR Land (PAL) data to provide surrogate variables near-surface air temperature vapour pressure deficit (VPD) over Africa Europe were assessed in this context. For years 1988-1990 1992, correlations examined between meteorological ground (monthly mean VPD(grd)) derived from Advanced Very High Resolution Radiometer (AVHRR) (LST VPD(sat)). indices both daily composite PAL so that their relative performance could be determined. Furthermore, divided into African European subsets, tropical/sub-tropical temperate latitudes assessed.Significant shown LST all months. Temporal variability existed strength throughout twelve-month period, with pattern consistent years. adjusted r(2) values increased when elevation Normalised Difference Vegetation Index (NDVI) included, addition LST, predictor temperature. Attempts derive monthly estimates atmospheric moisture availability resulted an over-estimation VPD(sat) compared observations, VPD(grd). use was more accurate than those obtained using maximum 10-day data. A subset 1992 then used build linear regression models direct retrieval accuracy retrieved greatest NDVI included variables, root square errors varying 1.83°C 3.18 °C a 2.38 twelve

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