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Ruderal A “weedy” plant species that tends to colonize disturbed lands.
Scale (noun) Level of observation, including spatial, temporal, spectral, and biological. Can also refer to the extent and grain of observation units.
Scale (verb) to change the resolution of a dataset. Upscaling involves extrapolation to larger areas (increasing extent), for example, through data aggregation or
forward modeling; downscaling interpolates values or inverts a model to create
a higher-resolution dataset or to infer component contributions at finer scales
(increasing grain size). From a biological perspective, upscaling might involve
considering emergent properties, whereas downscaling might involve looking at
underlying mechanisms or properties.
Scale dimensions The different types of scale (e.g., spatial, temporal, spectral,
biological).
Scaling The act of examining a phenomenon at multiple levels, usually referring
to transcending spatial scales, as in “upscaling” (increasing extent by extrapolation from fine-scale data to a coarser, usually spatially broader scale) or “downscaling” (interpreting the variation in underlying patterns or mechanisms from
coarse-scale data to finer resolution patterns or grain size).
Scattering (scatter, scattered) in remote sensing, reflecting and transmitting
radiation. Radiation that is not absorbed is scattered either backward (reflected)
or forward (transmitted).
Scattering phase height center The approximate height above the ground within
a vegetation canopy where most of a radar signal interacts with scattering elements (leaves, branches) and is backscattered to the sensor.
Sclerophyllous having a hard, leathery texture, as in “sclerophyllous” leaf characteristic of Mediterranean or desert climates to maximize water retention.
Secondary metabolites Plant metabolites not directly associated with primary
metabolism (e.g., photosynthesis or respiration) tied to plant growth, development, or reproduction, often associated with plant defense or signaling.
Semantic web An effort to make the World Wide Web machine readable by
encoding semantics with data (e.g., through provision of metadata).
Semivariogram A plot of semivariance in some property vs. lag (distance between
sampling points), used in geostatistics to compare similarity between sampling
points and evaluate the scale dependence of features in a landscape.
Senescence The process of tissue or plant death.
Shortwave infrared (SWIR) The range of the electromagnetic spectrum between
1100 and 3000 nm.
Signal-to-noise ratio A ratio comparing the desired signal to the background
noise of the sensor; sometimes calculated as the mean signal value divided by
the standard deviation of the noise.
Simpson Index One of multiple metrics of alpha diversity that combines species
richness and evenness (relative abundance).
Singular value decomposition (SVD) Matrix factorization; decomposes a matrix
into an orthonormal basis transformation multiplied by a diagonal matrix followed by another orthonormal change of bases. Contrast with principal components analysis (PCA), which finds a new representation for a dataset in terms of a
(typically lower rank) orthogonal basis that preserves the variance of the original
Glossary
Ruderal A “weedy” plant species that tends to colonize disturbed lands.
Scale (noun) Level of observation, including spatial, temporal, spectral, and biological. Can also refer to the extent and grain of observation units.
Scale (verb) to change the resolution of a dataset. Upscaling involves extrapolation to larger areas (increasing extent), for example, through data aggregation or
forward modeling; downscaling interpolates values or inverts a model to create
a higher-resolution dataset or to infer component contributions at finer scales
(increasing grain size). From a biological perspective, upscaling might involve
considering emergent properties, whereas downscaling might involve looking at
underlying mechanisms or properties.
Scale dimensions The different types of scale (e.g., spatial, temporal, spectral,
biological).
Scaling The act of examining a phenomenon at multiple levels, usually referring
to transcending spatial scales, as in “upscaling” (increasing extent by extrapolation from fine-scale data to a coarser, usually spatially broader scale) or “downscaling” (interpreting the variation in underlying patterns or mechanisms from
coarse-scale data to finer resolution patterns or grain size).
Scattering (scatter, scattered) in remote sensing, reflecting and transmitting
radiation. Radiation that is not absorbed is scattered either backward (reflected)
or forward (transmitted).
Scattering phase height center The approximate height above the ground within
a vegetation canopy where most of a radar signal interacts with scattering elements (leaves, branches) and is backscattered to the sensor.
Sclerophyllous having a hard, leathery texture, as in “sclerophyllous” leaf characteristic of Mediterranean or desert climates to maximize water retention.
Secondary metabolites Plant metabolites not directly associated with primary
metabolism (e.g., photosynthesis or respiration) tied to plant growth, development, or reproduction, often associated with plant defense or signaling.
Semantic web An effort to make the World Wide Web machine readable by
encoding semantics with data (e.g., through provision of metadata).
Semivariogram A plot of semivariance in some property vs. lag (distance between
sampling points), used in geostatistics to compare similarity between sampling
points and evaluate the scale dependence of features in a landscape.
Senescence The process of tissue or plant death.
Shortwave infrared (SWIR) The range of the electromagnetic spectrum between
1100 and 3000 nm.
Signal-to-noise ratio A ratio comparing the desired signal to the background
noise of the sensor; sometimes calculated as the mean signal value divided by
the standard deviation of the noise.
Simpson Index One of multiple metrics of alpha diversity that combines species
richness and evenness (relative abundance).
Singular value decomposition (SVD) Matrix factorization; decomposes a matrix
into an orthonormal basis transformation multiplied by a diagonal matrix followed by another orthonormal change of bases. Contrast with principal components analysis (PCA), which finds a new representation for a dataset in terms of a
(typically lower rank) orthogonal basis that preserves the variance of the original
Glossary