Issue link: https://read.dmtmag.com/i/53167
The aerial imagery of yesterday once consisted of low-resolution imagery, using a relatively inefficient process of acquiring black-and-white imagery via film cans, analog planimeters, chemical rooms and mosa- icking hardcopy photographs by hand. Due to improve- ments in technology, today's NAIP orthoimagery is 100-percent digital, consisting of 0.5- to one-meter resolution in four radiometric bands of red, green, blue and near-infrared. This helps provide a more-detailed set of information in a significantly reduced timeline. The multispectral nature of NAIP imagery enables analysts, farmers and companies to measure the areas of farmlands as well as help improve how they evaluate the health and wellbeing of crops. With color infrared bands, analysts can perform additional data extraction, such as Normalized Difference Vegetation Index, to evaluate plant stresses for an entire state or region. Some researchers also use MSI and HSI to help detect diseases that aren't readily seen by the naked eye, such as citrus greening. This information helps maintain the health and well- being of crops as well as identify a healthy crop yield for the season. Having such information will help the industry determine how much of a state or region's crop will be available to consumers, helping to estab- lish costs and control product demand. MSI also has empowered states and other gov- ernment agencies in developing derivative products such as land-use/land-cover data and impermeability- assessment layers. All in all, agricultural geospatial data end up matriculating as one of the many impor- tant pieces of technology that help in many ways, including bringing food to the dinner table and provid- ing alternative fuels for vehicles. Intelligence enables better planning and forecasting of business opportunities, which can lead to further business for individual farmers and the industry as a whole. Digital Farmer's Almanac Information gathered from MSI-derived intelligence can go much further than a single farm. Taking the collective data derived from NAIP imagery, predictive analytics can be used to determine future best-man- agement practices, conduct environmental forecasting and improve the business practices of farmers and the USDA. This information can go further by combin- ing weather models and climate data in conjunction with imagery-derived data products to create a digital farmer's almanac. The ability to predict a season's crop yield can help determine what prices consumers will see in grocery stores. Taking that information, and adding in weather analyses and how these events have impacted the land, can help determine the current season's crop as well as that of the next several years. Also, a better understanding of this information can help determine export prices and actually help forecast commodity prices. Intelligence also enables better planning and fore- Intelligence from imagery, along with weather analysis, can help predict a season's crop yield and determine consumer prices at grocery stores over several years. 20 GEO W ORLD /JANUAR Y 2O12 casting of business opportunities. Understanding weather patterns and their affect on the land can determine what types of crops should be planted and how much a season would yield. Such information can lead to further business for individual farmers and the industry as a whole—technical innovation enhancing economic competitiveness. From a regulation perspective, such geospatial infor- mation can help position the United States for the Imagery/LIDAR Special Issue Industry Applications USDA FSA APFO USDA FSA APFO