Message posté par : n314
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https://doi.org/10.1016/j.cageo.2005.11.008
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Citation :
Tomislav Hengl,
Finding the right pixel size,
Computers & Geosciences,
Volume 32, Issue 9,
2006,
Pages 1283-1298,
ISSN 0098-3004,
https://doi.org/10.1016/j.cageo.2005.11.008.
(
https://www.sciencedirect.com/science/article/pii/S0098300405002657)
Abstract: This paper discusses empirical and analytical rules to select a suitable grid
resolution for output maps and based on the inherent properties of the input data. The
choice of grid resolution was related with the cartographic and statistical concepts:
scale, computer processing power, positional accuracy, size of delineations, inspection
density, spatial autocorrelation structure and complexity of terrain. These were further
related with the concepts from the general statistics and information theory such as
Nyquist frequency concept from signal processing and equations to estimate the probability
density function. Selection of grid resolution was demonstrated using four datasets: (1)
GPS positioning data—the grid resolution was related to the area of circle described by
the error radius, (2) map of agricultural plots—the grid resolution was related to the
size of smallest and narrowest plots, (3) point dataset from soil mapping—the grid
resolution was related to the i
nspection density, nugget variation and range of spatial autocorrelation and (4) contour
map used for production of digital elevation model—the grid resolution was related with
the spacing between the contour lines i.e. complexity of terrain. It was concluded that no
ideal grid resolution exists, but rather a range of suitable resolutions. One should at
least try to avoid using resolutions that do not comply with the effective scale or
inherent properties of the input dataset. Three standard grid resolutions for output maps
were finally recommended: (a) the coarsest legible grid resolution—this is the largest
resolution that we should use in order to respect the scale of work and properties of a
dataset; (b) the finest legible grid resolution—this is the smallest grid resolution that
represents 95% of spatial objects or topography; and (c) recommended grid resolution—a
compromise between the two. Objective procedures to derive the true optimal grid
resolution that maximizes
the predictive capabilities or information content of a map are further discussed. This
methodology can now be integrated within a GIS package to help inexperienced users select
a suitable grid resolution without doing extensive data preprocessing.
Keywords: Grid resolution; Scale; Inspection density; Point pattern analysis; Variogram;
Terrain complexity
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