LaNGIF: The program`s goal is to develop methods for monitoring plant-health, animal- health and human-health problems, through Geographic Information System (GIS), Remote Sensing, GPS and Geospatial mapping platform. Some programs -Surveillance Epidemiological Plant-Health System (SINAVEF – Master Project) -Animal Health and disease monitoring (SIPOVE – State Project) -Medical Geography and e-Health (CIACYT - New Project) -Human health and environmental (Next Project) -Electoral Geography (Next Project) The Purpose of LaNGIF

Research lines of LaNGIF Geographic and environmental approach: 1. Animal, Human and Plant Health 2. Spatial analysis and Modelling (geographic distribution) 3. Climatology and Climate change 4. Social and Anthropological area 5. Geoinformatic Applications 6. Remote Sensing (Farm and Satellite) and Thermography 7. Environmental history

INPUTS - LaNGIF 2. Spatial analysis and Modelling All system have inputs, outputs and processes. For the first, wanted important inputs to explain the problem (environmental issue). Key inputs: -Field data (SCOPEmx - geospatial mapping platform -Host -Biology or Physiology -Climate confort and Favorables weather conditions -Potencial distribution -Demographic data and population characteristics -Economic data Galindo et al., 2012; Magarey, 2012; Nietshcke et al., 2007; Ballau and Pazer, 1985;

PROCESSES - LaNGIF 2. Spatial analysis and Modelling The processes used are spatial analysys types (traditional and contemporary geography methods) supported to geo-technologies. Key processes: -Spatial Interpolations -Multi-criterial and multivariate analysis -Statistical and spectral analysis -Distribution modeling ecology and antrophic -Hotspot and zonespot -Location theory -Landscape epidemiology Galindo et al., 2012; Meade & Emch, 2010; Magarey, 2007; Ribas & Saurí, 2006; Phillips et al., 2006; Delgado 2003; Haggett, 1976

OUTPUTS - LaNGIF 2. Spatial analysis and Modelling When one knows how analyze its elements and patterns, one can usaually determine what diseases can occur. Key outputs: -Geospatial metadata -Health or disease status -Index spatial -Risk mapping and disease infection model -Climate matching -Risk assessment -Validation -Input to another process Galindo et al., 2012; Meade & Emch, 2010; Magarey, 2007

SCALE AND DIMENSION - LaNGIF 2. Spatial analysis and Modelling Space is a continuum. A scale is the proportion a map, or other model, bears to the thing it represents. Relationship between scale of analysis and units of observations. Galindo et al., 2012; Meade & Emch, 2010; Magarey, 2007

CASE STUDY – PLANT HEALTH Spatial variability of diseases of sugarcane in Huasteca potosina (Mexico): implications for monitoring with remote sensing. -Use of remote sensing for recognition of pest in sugarcane -Spatial and spectral scaling -Data multi and hiper-spectral -Content of photosynthetic pigments CROPSCAN MR 5 visibleIRCIRM

CASE STUDY – PLANT HEALTH