Remote sensing is the science of identifying, quantifying, and or monitoring phenomena or objects from a distance. Oftentimes, remote sensing refers to the monitoring and gathering of information about the Earth and its biotic and abiotic processes. This technology relies upon the detection and measurement of electromagnetic radiation that is emitted or reflected from surfaces as wavelengths. These reflected wavelengths can then be used to describe the characteristics of a phenomenon or object, and long-term monitoring can be used to detect changes in the characteristics of that phenomenon or object. Remote sensing is used to monitor such things as deforestation, climate change, and the progression of algal blooms.
Today, instruments capable of passively detecting a broad range of wavelengths (e.g. visible, infrared, microwave) collect most of the remote sensing data. These instruments are mounted on satellites, aircraft, spacecraft, weather buoys, and ships. The long-range capabilities of these sensors allow scientists to collect data from large, inaccessible, and/or dangerous areas.
Remote Sensing and Vector-borne Diseases
Remote sensing is becoming an important tool for the study of vector-borne diseases. Ecological models that incorporate biological data and spatial and temporal remote sensing data can improve our ability to predict the patterns and intensity of diseases. For example, the geographic range of an infected host species can be predicted by incorporating the known geographic locations of infected individuals of that species and the biological and environmental data collected via remote sensing.
These ecological modeling techniques can also be used to study processes that influence the distribution patterns of disease strains by incorporating epidemiologic and genetic data with geographic and remote sensing data. Perhaps the most relevant application of these models, in terms of controlling and preventing vector-borne diseases, is the ability to predict future outbreaks of a disease and the future prevalence of diseased host species by using remote sensing to identifying factors that contribute to disease spread.
Remote sensing can also be used to predict how large-scale changes might affect the ecology and epidemiology of disease species and their hosts. Remote sensing and other spatial data sets can be used to quantify natural (climate change and variability) and anthropogenic (fragmentation, land use intensification, urbanization, etc.) changes and can be readily incorporated into predictive models to assess future scenarios. For example, these models can be used to predict the impact that habitat fragmentation at a migration stopover site will have on the transmission of avian influenza between migratory birds and humans.
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