Search results for "Variogram"
showing 10 items of 13 documents
SAR Image Classification Combining Structural and Statistical Methods
2011
The main objective of this paper is to develop a new technique of SAR image classification. This technique combines structural parameters, including the Sill, the slope, the fractal dimension and the range, with statistical methods in a supervised image classification. Thanks to the range parameter, we define the suitable size of the image window used in the proposed approach of supervised image classification. This approach is based on a new way of characterising different classes identified on the image. The first step consists in determining relevant area of interest. The second step consists in characterising each area identified, by a matrix. The last step consists in automating the pr…
Evaluating field-scale sampling methods for the estimation of mean plant densities of weeds
2000
The weed flora (comprising seven species) of a field continuously grown with soyabean was simulated for 4 years, using semivariograms established from previous field observations. Various sampling methods were applied and compared for accurately estimating mean plant densities, for differing weed species and years. The tested methods were based on (a) random selection wherein samples were chosen either entirely randomly, randomly with at least 10 or 20 m between samples, or randomly after stratifying the field; (b) systematic selection where samples were placed along diagonals or along zig-zagged lines across the field; (c) predicted Setaria viridis (L.) P. Beaux seedling maps which were us…
Spatial and temporal stability of weed populations over five years
2000
Abstract The size, location, and variation in time of weed patches within an arable field were analyzed with the ultimate goal of simplifying weed mapping. Annual and perennial weeds were sampled yearly from 1993 to 1997 at 410 permanent grid points in a 1.3-ha no-till field sown to row crops each year. Geostatistical techniques were used to examine the data as follows: (1) spatial structure within years; (2) relationships of spatial structure to literature-derived population parameters, such as seed production and seed longevity; and (3) stability of weed patches across years. Within years, densities were more variable across crop rows and patches were elongated along rows. Aggregation of …
Distributed Clustering Algorithm for Spatial Field Reconstruction in Wireless Sensor Networks
2015
En este trabajo, consideramos el problema de la estimación espacial distribuida para la reconstrucción del campo radio en redes de sensores inalámbricos. Para estimar el campo, se utiliza una técnica geoestadística llamada kriging. La estimación espacial centralizada con un gran número de sensores conllevan un elevado coste computacional y gasto de energía. Presentamos un novedoso algoritmo de clustering distribuido para estimar mapas de interferencia espacial, que son esenciales para las operaciones y la gestión de las futuras redes inalámbricas. En este algoritmo, los clústeres de sensores se forman de forma adaptativa mediante la minimización de la varianza de kriging. El cálculo del sem…
REGEOTOP: New climatic data fields for East Asia based on localized relief information and geostatistical methods
2004
Climate data fields represent essential tools for climate, biogeographical and agricultural research to run models and to provide observational data for the verification of global climate models (GCM). Climate data fields are generated through interpolation of observations taken at meteorological stations. Most current interpolation procedures try to describe the influence of topography on spatial climatic variations by relating them directly to absolute elevation or by introducing simple relief variables such as exposure. In both cases this may not properly describe spatial climatic variations, particularly not those of precipitation. This paper describes a regionalization procedure (REGEO…
Geostatistical Microscale Study of Magnetic Susceptibility in Soil Profile and Magnetic Indicators of Potential Soil Pollution
2015
Directional variograms, along the soil profile, can be useful and precise tool that can be used to increase the precision of the assessment of soil pollution. The detail analysis of spatial variability in the soil profile can be also an important part of the standardization of soil magnetometry as a screening method for an assessment of soil pollution related to the dust deposition. The goal of this study was to investigate the correlation between basic parameters of spatial correlations of magnetic susceptibility in the soil profile, such as a range of correlation and a sill, and selected magnetometric indicators of soil pollution. Magnetic indicators were an area under the curve of magnet…
Promoting mathematical skills using the instructive program Kriging
2011
Geostatistics was developed in mining for the grade estimation problems of ore deposits, nowadays; it is the most popular method for the interpolation and estimation problems. Methodological consideration about its interpolator, the Kriging, is presented in this paper. For geosciences engineering and other students in general is important to take in advance interpolation methods. This methodology is coming from natural phenomenon, where it is very difficult or even impossible to build deterministic models, only it is possible to describing the behavior from fragmented information of the problem studied. The characterization of the spatial variables using geostatistics has, in general, two m…
Orientational analysis of planar fibre systems observed as a Poisson shot-noise process
2007
Summary We consider two-dimensional fibrous materials observed as a digital greyscale image. The problem addressed is to estimate the orientation distribution of unobservable thin fibres from a greyscale image modelled by a planar Poisson shot-noise process. The classical stereological approach is not straightforward, because the point intensities of thin fibres along sampling lines may not be observable. For such cases, Karkkainen et al. (2001) suggested the use of scaled variograms determined from grey values along sampling lines in several directions. Their method is based on the assumption that the proportion between the scaled variograms and point intensities in all directions of sampl…
A geostatistical approach to map near-surface soil moisture through hyperspatial resolution thermal inertia.
2021
Thermal inertia has been applied to map soil water content exploiting remote sensing data in the short and long wave regions of the electromagnetic spectrum. Over the last years, optical and thermal cameras were sufficiently miniaturized to be loaded onboard of unmanned aerial systems (UASs), which provide unprecedented potentials to derive hyperspatial resolution thermal inertia for soil water content mapping. In this study, we apply a simplification of thermal inertia, the apparent thermal inertia (ATI), over pixels where underlying thermal inertia hypotheses are fulfilled (unshaded bare soil). Then, a kriging algorithm is used to spatialize the ATI to get a soil water content map. The pr…
Optimizing the Sampling Area across an Old-Growth Forest via UAV-Borne Laser Scanning, GNSS, and Radial Surveying
2022
Aboveground biomass, volume, and basal area are among the most important structural attributes in forestry. Direct measurements are cost-intensive and time-consuming, especially for old-growth forests exhibiting a complex structure over a rugged topography. We defined a methodology to optimize the plot size and the (total) sampling area, allowing for structural attributes with a tolerable error to be estimated. The plot size was assessed by analyzing the semivariogram of a CHM model derived via UAV laser scanning, while the sampling area was based on the calculation of the absolute relative error as a function of allometric relationships. The allometric relationships allowed the structural …