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7 Using the Map <br />Version 06.16.01, 2006- 03 -03, Color, Acrobat Distiller <br />Although the main focus in TSTool is time series, many time series are associated with a location such as <br />a station, area, or sensor. This chapter discusses the relationship between time series and spatial data and <br />provides an overview of using map - related features in TSTool. Time series concepts (such as time series <br />identifiers) are discussed in detail in Chapter 2 — Introduction. Information about the map display tool <br />used in TSTool is provided in the GeoView Mapping Tools Appendix. <br />7.1 Time Series and Map Layer Relationships <br />An example is useful to provide an overview of the relationship between time series and map layers <br />Map layers often indicate physical features (e.g., rivers, cities, roads, data collection stations) or features <br />that are overlaid on physical features (e.g., political boundaries, weather fronts, regions or points of <br />interest). A layer's data consist of <br />1. Features — the coordinate information that defines the shape that is drawn. <br />2. Attributes —a tabular list of data values associated with the features. <br />3. Metadata — data about the layer, including the source, coordinate system, history, etc. <br />4. Projection — the coordinate system for the coordinates, which is usually noted in metadata but <br />may also be indicated by a projection file or similar. <br />5. Symbology — to be visualized, a layer must be associated with a symbol (e.g., point symbol, line <br />width, polygon fill color), labels, and other visualization information. <br />The features and attributes are the primary data, and the other information facilitates using the features <br />and attributes. <br />Consider a data collection station, represented by a point on the map. This station may be located near a <br />river and collect streamflow stage (water depth). The station software may convert the stage to flow or <br />may allow this to be done by software. The station may also collect "climate" (meteorological) data such <br />as precipitation, temperature, wind speed and direction, etc. Each measurement type requires a sensor <br />and the cost of hardware typically controls the number and sensitivity of measuring devices. For data <br />management, the station is typically assigned an alphanumeric station identifier and each data type that is <br />collected is assigned an alphanumeric data type. The data are saved locally as date /value information and <br />are then transmitted to or requested from a data collecting system. The date /value information is <br />essentially time series. Data units and handling of missing data are considered during implementation of <br />data collection systems. Measurements may be taken regularly (e.g., once every fifteen minutes) or may <br />occur at irregular intervals, perhaps in response to some change in conditions. In nomenclature used with <br />TSTool, the former are called regular time series and the latter irregular, reflected by the data interval <br />(time step). <br />For the discussion purposes, consider only a meteorological station that measures precipitation and <br />temperature. For mapping purposes, a choice may be made to focus on the physical nature of the map, in <br />which case a single "Met Stations" (or "Climate Stations ") layer may be shown, using a single symbol. <br />This is suitable if the measurement types for such a station are consistent throughout a system or only one <br />data type is of interest. It is frequently the case that the real -time data that are collected are managed in a <br />database, with data being archived over time, for example resulting in the following time series for <br />precipitation data: <br />99 Using the Map - 1 <br />