Glossary of Terms | Geospatial Data and Weather Risk Mapping in Agriculture Risk Management

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

Agrometeorology - Agrometeorology deals with all the weather-sensitive elements of agriculture production. The spectrum of subjects is thus rather wide. It includes pollination, animal migration, human and animal health, transport of pathogens by wind, irrigation, micro-climate manipulation and artificial climates, weather risk assessments, the use of weather forecasts in farming, crop yield and phenology forecasts and particularly advice to farmers. Current agrometeorology relies on a package of new tools, which definemodern agrometeorology. They include data acquisition techniques (ground observation, aircraft and satellite), data transmission techniques (including the Internet) and data analysis (models and other software).

Attribute data. Attribute (tabular) data is the descriptive data that GIS links to map features. Attribute data is collected and compiled for specific areas like states, census tracts, cities, and so on and often comes packaged with map data. When implementing a GIS, the most common sources of attribute data are your own organization's databases combined with data sets you buy or acquire from other sources to fill in gaps.

C

Climate - in a narrow sense is usually defined as the average weather, or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period is 30 years. These quantities are most often surface variables such as temperature, precipitation, and wind. Climate in a wider sense is the state, including a statistical description, of the climate system.

Climate system - means the totality of the atmosphere, hydrosphere, biosphere and geosphere and their interactions. Variation in climate is one of the main determinants of agricultural production in all countries.

Climate variability - refers to variations in the mean state and other statistics (such as standard deviations, the occurrence of extremes, etc.) of the climate on all temporal and spatial scales beyond that of individual weather events. Variability may be due to natural internal processes within the climate system (internal variability), or to variations in natural or anthropogenic external forcing (external variability).

D

Data Models - Data models are the rules the GIS follows, such as "county lines do not overlap," and are essential for defining what is in the GIS as well as supporting the use of GIS software. All spatial data models fall into two basic categories:

G

GIS (Geographic Information System) – Short for Geographic Information Systems, tools used to gather, transform, manipulate, analyze, and produce information related to the surface of the Earth. GIS integrates hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information. This data may exist as maps, 3D virtual models, tables, and/or lists. GISs can be as complex as whole systems that use dedicated databases and workstations hooked up to a network, or as simple as "off-the-shelf" desktop software. GISs play an important role in many organizations. For instance, police and fire departments may use GISs to locate landmarks and hazards, plot destinations, and design emergency routes. GISs may also be used by governments, research institutes or any other body that can't possibly handle the task of manually processing large amounts of geographical data.

geospatial data -- information that identifies the geographic location and characteristics of natural or constructed features and boundaries on the earth. This information may be derived from, among other things, remote sensing, mapping, and surveying technologies.

I 

Image data. Image data ranges from satellite images and aerial photographs to scanned maps (maps that have been converted from printed to digital format). Learn more.

K

Kriging - is a group of geostatistical techniques to interpolate the value of a random field (e.g., the elevation, z, of the landscape as a function of the geographic location) at an unobserved location from observations of its value at nearby locations. 

M

Map data. Map data contains the location and shape of geographic features. Maps use three basic shapes to present real-world features: points, lines, and areas (called polygons). Learn more.

Moderate Resolution Imaging Spectroradiometer (MODIS) – Instrument used for obtaining land surface thermal data.

R

Raster data model. Continuous numeric values, such as elevation, and continuous categories, such as vegetation types, are represented using the raster model. Learn more.

Remote Sensing - Remotely sensed observations, taken from sensors aboard aircraft or satellites in space, provide information about land surface properties over much broader areas than can be measured on the ground. These observations are often much more cost efficient than ground measurements in terms of price per unit area.

S

Satellite Temperature Measurements - The temperature of the atmosphere at various altitudes as well as sea and land surface temperatures can be inferred from satellite measurements. Weather satellites do not measure temperature directly but measure radiances in various wavelength bands. These measurements can be used to locate weather fronts, monitor the El Niño-Southern Oscillation, determine the strength of tropical cyclones, study urban heat islands and monitor the global climate. Wildfires, volcanos, and industrial hot spots can also be found via thermal imaging from weather satellites.

Spatial Analysis - Spatial analysis or spatial statistics includes any of the formal techniques which study entities using their topological, geometric, or geographic properties. The phrase properly refers to a variety of techniques, many still in their early development, using different analytic approaches and applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, to chip fabrication engineering, with its use of 'place and route' algorithms to build complex wiring structures. The phrase is often used in a more restricted sense to describe techniques applied to structures at the human scale, most notably in the analysis of geographic data. The phrase is even sometimes used to refer to a specific technique in a single area of research, for example, to describe geostatistics.

Spatial Data – Also known as geospatial data or geographic information it is the data or information that identifies the geographic location of features and boundaries on Earth, such as natural or constructed features, oceans, and more. Spatial data is usually stored as coordinates and topology, and is data that can be mapped. Spatial data is often accessed, manipulated or analyzed through Geographic Information Systems (GIS).

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Vector data model. Discrete features, such as customer locations and data summarized by area, are usually represented using the vector model. Learn more.