Using a geographic transect in Central Mexico, with an elevation/climate gradient, but uniformity in socio-economic conditions among study sites, this study evaluates the applicability of three widely-used remote sensing (RS) products to link weather conditions with the local abundance of the dengue virus mosquito vector, Aedes aegypti (Ae. aegypti). Field-derived entomological measures included estimates for the percentage of premises with the presence of Ae. aegypti pupae and the abundance of Ae. aegypti pupae per premises. Data on mosquito abundance from field surveys were matched with RS data and analyzed for correlation. Daily daytime and nighttime land surface temperature (LST) values were obtained from Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua cloud-free images within the four weeks preceding the field survey. Tropical Rainfall Measuring Mission (TRMM)-estimated rainfall accumulation was calculated for the four weeks preceding the field survey. Elevation was estimated through a digital elevation model (DEM). Strong correlations were found between mosquito abundance and RS-derived night LST, elevation and rainfall along the elevation/climate gradient. These findings show that RS data can be used to predict Ae. aegypti abundance, but further studies are needed to define the climatic and socio-economic conditions under which the correlations observed herein can be assumed to apply.

Turbidity is a commonly-used index of the factors that determine light penetration in the water column. Consistent estimation of turbidity is crucial to design environmental and restoration management plans, to predict fate of possible pollutants, and to estimate sedimentary fluxes into the ocean. Traditional methods monitoring fixed geographical locations at fixed intervals may not be representative of the mean water turbidity in estuaries between intervals, and can be expensive and time consuming. Although remote sensing offers a good solution to this limitation, it is still not widely used due in part to required complex processing of imagery. There are satellite-derived products, including the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra surface reflectance daily product (MOD09GQ) Band 1 (620–670 nm) which are now routinely available at 250 m spatial resolution and corrected for atmospheric effect. This study shows this product to be useful to estimate turbidity in Tampa Bay, Florida, after rainfall events (R2 = 0.76, n = 34). Within Tampa Bay, Hillsborough Bay (HB) and Old Tampa Bay (OTB) presented higher turbidity compared to Middle Tampa Bay (MTB) and Lower Tampa Bay (LTB)

Dengue fever (DF), a vector-borne flavivirus, is endemic to the tropical countries of the world with nearly 400 million people becoming infected each year and roughly one-third of the world's population living in areas of risk. The main vector for DF is the Aedes aegypti mosquito, which is also the same vector of yellow fever, chikungunya, and Zika viruses. To gain an understanding of the spatial aspects that can affect the epidemiological processes across the disease's geographical range, and the spatial interactions involved, we created and compared Bernoulli and Poisson family Boosted Regression Tree (BRT) models to quantify the overall annual risk of DF incidence by municipality, using the Magdalena River watershed of Colombia as a study site during the time period between 2012 and 2014. A wide range of environmental conditions make this site ideal to develop models that, with minor adjustments, could be applied in many other geographical areas. Our results show that these BRT methods can be successfully used to identify areas at risk and presents great potential for implementation in surveillance programs.

The introduction and spread of West Nile virus and the recent introduction of chikungunya and Zika viruses into the Americas have raised concern about the potential for various tropical pathogens to become established in North America. A historical analysis of yellow fever and malaria incidences in the United States suggests that it is not merely a temperate climate that keeps these pathogens from becoming established. Instead, socioeconomic changes are the most likely explanation for why these pathogens essentially disappeared from the United States yet remain a problem in tropical areas. In contrast to these anthroponotic pathogens that require humans in their transmission cycle, zoonotic pathogens are only slightly affected by socioeconomic factors, which is why West Nile virus became established in North America. In light of increasing globalization, we need to be concerned about the introduction of pathogens such as Rift Valley fever, Japanese encephalitis, and Venezuelan equine encephalitis viruses.

a b s t r a c tWorldwide, coral reef ecosystems are being increasingly threatened by sediments loads from river discharges, which in turn are influenced by changing rainfall patterns due to climate change and by growing human activity in their watersheds. In this case study, we explored the applicability of using remote sensing (RS) technology to estimate and monitor the relationship between water quality at the coral reefs around the Rosario Islands, in the Caribbean Sea, and the rainfall patterns in the Magdalena River watershed. From the Moderate Resolution Imaging Spectroradiometer (MODIS), this study used the water surface reflectance product (MOD09GQ) to estimate water surface reflectance as a proxy for sediment concentration and the land cover product (MCD12Q1 V51) to characterize land cover of the watershed. Rainfall was estimated by using the 3B43 V7 product from the Tropical Rainforest Measuring Mission (TRMM). For the first trimester of each year, we investigated the inter-annual temporal variation in water surface reflectance at the Rosario Islands and at the three main mouths of the Magdalena River watershed. No increasing or decreasing trends of water surface reflectance were detected for any of the sites for the study period 2001-2014 (p > 0.05) but significant correlations were detected among the trends of each site at the watershed mouths (r = 0.57-0.90, p < 0.05) and between them and the inter-annual variation in rainfall on the watershed (r = 0.63-0.67, p < 0.05). Those trimesters with above-normal water surface reflectance at the mouths and above-normal rainfall at the watershed coincided with La Niña conditions while the opposite was the case during El Niño conditions. Although, a preliminary analysis of inter-annual land cover trends found only cropland cover in the watershed to be significantly correlated with water surface reflectance at two of the watershed mouths (r = 0.58 and 0.63, p < 0.05), the validation analysis draw only a 40.7% of accuracy in this land cover classification. This requires further analysis to confirm the impact of the cropland on the water quality at the watershed outlets. Spatial analysis with MOD09GQ imagery detected the overpass of river plumes from Barbacoas Bay over the Rosario Islands waters.

Abstract. Monitoring algal blooms using traditional methods is expensive and labor intensive. The use of satellite technology can attenuate such limitations. A common problem associated with the application of such technology is the need to eliminate the effects of atmosphere, which can be, at least, a time-consuming task. Thus, a remote sensed algal bloom monitoring system needs a simple algorithm which is nonsensitive to atmospheric correction and that could be applied to small aquatic systems. A slope algorithm (SA red−NIR ) was developed to detect and map the extension of algal blooms using the Landsat 8/Operational Land Imager. SA red−NIR was shown to have advantages over other commonly used indices to monitor algal blooms, such as normalized difference vegetation index (NDVI), normalized difference water index, and floating algae index. SA red−NIR was shown to be less sensitive to different atmospheric corrections, less sensitive to thin clouds, and less susceptible to confusion when classifying water and moderate bloom conditions. Based on ground truth data from Eagle Creek Reservoir, Indiana, SA red−NIR showed an accuracy of 88.46% while NDVI only showed a 46.15% accuracy. Finally, based on qualitative and quantitative results, SA red−NIR can be used as a tool to improve the governance of small size water resources.

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The recent explosive outbreaks of Zika and chikungunya throughout the Americas has raised concerns about the threats that these and similar diseases may pose to the United States (U.S.). The commonly accepted association between tropical climates and the endemicity of these diseases has led to concerns about the possibility of their redistribution due to climate change and transmission arising from cases imported from endemic regions initiating outbreaks in the United States. While such possibilities are indeed well founded, the analysis of historical records not only confirms the potential critical role of traveling and globalization but also reveals that the climate in the United States currently is suitable for local transmission of these viruses. Thus, the main factors preventing these diseases from occurring in the United States today are more likely socioeconomic such as lifestyle, housing infrastructure, and good sanitation. As long as such conditions are maintained, it seems unlikely that local transmission will occur to any great degree, particularly in the northern states. Indeed, a contributing factor to explain the current endemicity of these diseases in less-developed American countries may be well explained by socioeconomic and some lifestyle characteristics in such countries.