Can Reconstructed Land Surface Temperature Data From Space Predict a West Nile Virus Outbreak?

Andreo, Verónica; Metz, J.C.M.; Neteler, Markus; Rosà, Roberto; Marcantonio, Matteo; Billinis, Charalambos; Rizzoli, Annapaola; Papa, Anne‐Laure

doi:10.5194/isprs-archives-xlii-4-w2-19-2017

Cited by 4 publications

(2 citation statements)

References 31 publications

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“…Land Surface Temperature (LST) is derived from Earth emissivity, therefore it is available from multiple sources ( 19 – 21 ). LST is considered being correlated with air temperature, which has been demonstrated being an environmental driver of WN fever outbreaks ( 22 , 23 ). EVE uses satellite products from the NASA MODerate resolution Imaging Spectroradiometer (MODIS) on board the satellites TERRA ( 20 ) and AQUA ( 24 ) ( Figure 3 ).…”

Section: Methodsmentioning

confidence: 99%

An integrated system for the management of environmental data to support veterinary epidemiology

et al. 2023

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Environmental and climatic fluctuations can greatly influence the dynamics of infectious diseases of veterinary concern, or interfere with the implementation of relevant control measures. Including environmental and climatic aspects in epidemiological studies could provide policy makers with new insights to assign resources for measures to prevent or limit the spread of animal diseases, particularly those with zoonotic potential. The ever-increasing number of technologies and tools permits acquiring environmental data from various sources, including ground-based sensors and Satellite Earth Observation (SEO). However, the high heterogeneity of these datasets often requires at least some basic GIS (Geographic Information Systems) and/or coding skills to use them in further analysis. Therefore, the high availability of data does not always correspond to widespread use for research purposes. The development of an integrated data pre-processing system makes it possible to obtain information that could be easily and directly used in subsequent epidemiological analyses, supporting both research activities and the management of disease outbreaks. Indeed, such an approach allows for the reduction of the time spent on searching, downloading, processing and validating environmental data, thereby optimizing available resources and reducing any possible errors directly related to data collection. Although multitudes of free services that allow obtaining SEO data exist nowadays (either raw or pre-processed through a specific coding language), the availability and quality of information can be sub-optimal when dealing with very small scale and local data. In fact, some information sets (e.g., air temperature, rainfall), usually derived from ground-based sensors (e.g., agro-meteo station), are managed, processed and redistributed by agencies operating on a local scale which are often not directly accessible by the most common free SEO services (e.g., Google Earth Engine). The EVE (Environmental data for Veterinary Epidemiology) system has been developed to acquire, pre-process and archive a set of environmental information at various scales, in order to facilitate and speed up access by epidemiologists, researchers and decision-makers, also accounting for the integration of SEO information with locally sensed data.

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Section: Methodsmentioning

confidence: 99%

An integrated system for the management of environmental data to support veterinary epidemiology

et al. 2023

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“…As such, many research fields and applications, namely evapotranspiration, climate change, hydrology, vegetation monitoring, urban climate, public health, among others, require gap-free time series of this variable as inputs to better understand the spatio-temporal changes of different study targets [39][40][41][42].…”

Section: Discussionmentioning

confidence: 99%

A New Fully Gap-Free Time Series of Land Surface Temperature from MODIS LST Data

2017

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Temperature time series with high spatial and temporal resolutions are important for several applications. The new MODIS Land Surface Temperature (LST) collection 6 provides numerous improvements compared to collection 5. However, being remotely sensed data in the thermal range, LST shows gaps in cloud-covered areas. We present a novel method to fully reconstruct MODIS daily LST products for central Europe at 1 km resolution and globally, at 3 arc-min. We combined temporal and spatial interpolation, using emissivity and elevation as covariates for the spatial interpolation. The reconstructed MODIS LST for central Europe was calibrated to air temperature data through linear models that yielded R 2 values around 0.8 and RMSE of 0.5 K. This new method proves to scale well for both local and global reconstruction. We show examples for the identification of extreme events to demonstrate the ability of these new LST products to capture and represent spatial and temporal details. A time series of global monthly average, minimum and maximum LST data and long-term averages is freely available for download.

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A systematic review of environmental factors related to WNV circulation in European and Mediterranean countries

et al. 2023

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Can Reconstructed Land Surface Temperature Data From Space Predict a West Nile Virus Outbreak?

Cited by 4 publications

References 31 publications

An integrated system for the management of environmental data to support veterinary epidemiology

An integrated system for the management of environmental data to support veterinary epidemiology

A New Fully Gap-Free Time Series of Land Surface Temperature from MODIS LST Data

A systematic review of environmental factors related to WNV circulation in European and Mediterranean countries

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