| review article | Q7318358 |
| scholarly article | Q13442814 |
| P50 | author | Marília S Carvalho | Q56373207 |
| P2093 | author name string | Cíntia Honório Vasconcelos | |
| Paulo Chagastelles Sabroza | |||
| Virginia Ragoni de Moraes Correia | |||
| P2860 | cites work | Increasing habitat suitability in the United States for the tick that transmits Lyme disease: a remote sensing approach | Q24817010 |
| Deriving meteorological variables across Africa for the study and control of vector-borne disease: a comparison of remote sensing and spatial interpolation of climate | Q30573158 | ||
| Towards a kala azar risk map for Sudan: mapping the potential distribution of Phlebotomus orientalis using digital data of environmental variables | Q30573254 | ||
| Using remotely sensed data to identify areas at risk for hantavirus pulmonary syndrome | Q30596759 | ||
| Vector-borne parasitic diseases: new trends in data collection and risk assessment | Q30652955 | ||
| New tools: potential medical applications of data from new and old environmental satellites | Q30652968 | ||
| Use of thermal and vegetation index data from earth observing satellites to evaluate the risk of schistosomiasis in Bahia, Brazil | Q30652974 | ||
| Validation of a mapping and prediction model for human fasciolosis transmission in Andean very high altitude endemic areas using remote sensing data | Q30652984 | ||
| Predicting the distribution of urinary schistosomiasis in Tanzania using satellite sensor data | Q30666746 | ||
| Satellite climatology and the environmental risk of Schistosoma mansoni in Ethiopia and east Africa | Q30671145 | ||
| Mapping disease incidence in suburban areas using remotely sensed data | Q30724548 | ||
| Mapping malaria risk in Africa: What can satellite data contribute? | Q30947245 | ||
| Geographic information systems and the distribution of Schistosoma mansoni in the Nile delta | Q30947401 | ||
| From predicting mosquito habitat to malaria seasons using remotely sensed data: practice, problems and perspectives | Q31066803 | ||
| Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data | Q32044576 | ||
| Satellites, space, time and the African trypanosomiases | Q34039024 | ||
| Earth observation, geographic information systems and Plasmodium falciparum malaria in sub-Saharan Africa | Q34039030 | ||
| Ticks and tick-borne disease systems in space and from space | Q34039034 | ||
| Environmental information systems for the control of arthropod vectors of disease | Q34052014 | ||
| Geographic information systems as a tool for control program management for schistosomiasis in Egypt | Q34264805 | ||
| Application of geographic information systems and remote sensing to schistosomiasis control in China | Q34264813 | ||
| Predicting the distribution of tsetse flies in West Africa using temporal Fourier processed meteorological satellite data | Q34392560 | ||
| Satellite imagery in the study and forecast of malaria | Q34521026 | ||
| Hantavirus pulmonary syndrome: at the crossroads | Q34616578 | ||
| Schistosomes, snails and satellites | Q34646750 | ||
| Univariate analysis of tsetse habitat in the common fly belt of southern Africa using climate and remotely sensed vegetation data | Q36885931 | ||
| Mapping tsetse habitat suitability in the common fly belt of southern Africa using multivariate analysis of climate and remotely sensed vegetation data | Q36885937 | ||
| Bancroftian filariasis distribution and diurnal temperature differences in the southern Nile delta | Q37062255 | ||
| Remote sensing and human health: new sensors and new opportunities | Q37093952 | ||
| Remote sensing and geographic information systems: charting Sin Nombre virus infections in deer mice | Q37093954 | ||
| Climate and infectious disease: use of remote sensing for detection of Vibrio cholerae by indirect measurement | Q37103393 | ||
| Predicting the risk of Lyme disease: habitat suitability for Ixodes scapularis in the north central United States | Q37320083 | ||
| Environmental information systems in malaria risk mapping and epidemic forecasting | Q38951840 | ||
| Local-scale variation in malaria infection amongst rural Gambian children estimated by satellite remote sensing | Q44143530 | ||
| Applications of remote sensing to the identification of the habitats of parasites and disease vectors | Q44162412 | ||
| Landscape surrounding human settlements and Anopheles albimanus (Diptera: Culicidae) abundance in Southern Chiapas, Mexico | Q44174191 | ||
| Landscape ecology and epidemiology of vector-borne diseases: tools for spatial analysis | Q46688754 | ||
| Use of satellite remote sensing and geographic information systems to model the distribution and abundance of snail intermediate hosts in Africa: a preliminary model for Biomphalaria pfeifferi in Ethiopia | Q46852103 | ||
| P433 | issue | 4 | |
| P921 | main subject | Brazil | Q155 |
| remote sensing | Q199687 | ||
| P304 | page(s) | 891-904 | |
| P577 | publication date | 2004-07-29 | |
| P1433 | published in | Cadernos de saúde pública | Q26839758 |
| P1476 | title | Remote sensing as a tool to survey endemic diseases in Brazil | |
| P478 | volume | 20 |
| Q43912294 | A remote sensing application to investigate urban endemics |
| Q57012323 | Dengue vector (Aedes aegypti) larval habitats in an urban environment of Costa Rica analysed with ASTER and QuickBird imagery |
| Q43167699 | Land use, land cover, and prevalence of canine visceral leishmaniasis in Teresina, Piauí State, Brazil: an approach using orbital remote sensing |
| Q45304289 | Production of transmission foci for cutaneous leishmaniasis: the case of Pau da Fome, Rio de Janeiro, Brazil |
| Q37344668 | Urban structure and dengue fever in Puntarenas, Costa Rica |
| Q66680390 | Using Earth observation images to inform risk assessment and mapping of climate change-related infectious diseases |
| Q55022974 | Wetlands and Malaria in the Amazon: Guidelines for the Use of Synthetic Aperture Radar Remote-Sensing. |
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