Chapter II Potential Data Sources for Analysis

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Chapter II Potential Data Sources for Analysis by Mind Map: Chapter II Potential Data Sources for Analysis

1. Land cover

1.1. Heads up digitized in ArcMap Using 6inch aerial imagery for Palm Beach County and X-resolution aerial imagery for northern counties

1.2. Object based classification in ERDAS Imagine Using 1meter aerial imagery (JPG2000) from USGS for all counties

1.3. National Land Cover Database 2011 (NLCD2011) National Land Cover Database 2011 (NLCD 2011) is the most recent national land cover product created by the Multi-Resolution Land Characteristics (MRLC) Consortium. NLCD 2011 provides - for the first time - the capability to assess wall-to-wall, spatially explicit, national land cover changes and trends across the United States from 2001 to 2011. As with two previous NLCD land cover products NLCD 2011 keeps the same 16-class land cover classification scheme that has been applied consistently across the United States at a spatial resolution of 30 meters. NLCD 2011 is based primarily on a decision-tree classification of circa 2011 Landsat satellite data.

1.4. LiDAR data

2. Wetness / Precipitation

2.1. Wet / dry count data from field

2.2. WorldClim precipitation data

3. Temperature & Humidity

3.1. My spatial data patterns

3.1.1. Temp

3.1.2. RH

3.2. WorldClim Data

3.2.1. WorldClim version 2 has average monthly climate data for minimum, mean, and maximum temperature and for precipitation for 1970-2000. Available at approx 1km2 resolution Includes the following bioclimatic variables: BIO1 = Annual Mean Temperature BIO2 = Mean Diurnal Range (Mean of monthly (max temp - min temp)) BIO3 = Isothermality (BIO2/BIO7) (* 100) BIO4 = Temperature Seasonality (standard deviation *100) BIO5 = Max Temperature of Warmest Month BIO6 = Min Temperature of Coldest Month BIO7 = Temperature Annual Range (BIO5-BIO6) BIO8 = Mean Temperature of Wettest Quarter BIO9 = Mean Temperature of Driest Quarter BIO10 = Mean Temperature of Warmest Quarter BIO11 = Mean Temperature of Coldest Quarter BIO12 = Annual Precipitation BIO13 = Precipitation of Wettest Month BIO14 = Precipitation of Driest Month BIO15 = Precipitation Seasonality (Coefficient of Variation) BIO16 = Precipitation of Wettest Quarter BIO17 = Precipitation of Driest Quarter BIO18 = Precipitation of Warmest Quarter BIO19 = Precipitation of Coldest Quarter

3.2.1.1. Comparison of my data and WorldClim: WorldClim June AvgTemp (1km resolution) Raster, Microclimate iButton Avg Daily Temp, *Not on same color scale, just a reference

3.2.1.2. Comparison of my data and WorldClim: Matched Pairs: WorldClim June AvgTemp (1km resolution) Versus Microclimate iButton Avg Daily Temp

3.3. PRISM data

3.4. Landsat 8 data

3.5. MODIS data

3.6. Use of temperature and humidity data in literature

3.6.1. Ecological niche modeling of mosquito vectors of West Nile virus in St. John’s County, Florida, USA

3.6.2. Temperature Characterization of Different Urban Microhabitats of Aedes albopictus (Diptera Culicidae) in Central-Northern Italy

4. Socioeconomic