Search results for "kriging"

Estimating the phenological dynamics of irrigated rice leaf area index using the combination of PROSAIL and Gaussian Process Regression

2021

The growth of rice is a sequence of three different phenological phases. This sequence of change in rice phenology implies that the condition of the plant during the vegetative phase relates directly to the health of leaves functioning during the reproductive and ripening phases. As such, accurate monitoring is important towards understanding rice growth dynamics. Leaf Area Index (LAI) is an important indicator of rice yields and the availability of this information during key phenological phases can support more informed farming decisions. Satellite remote sensing has been adopted as a proxy to field measurements of LAI and with the launch of freely available high resolution Satellite imag…

Comparative analysis of different techniques for spatial interpolation of rainfall data to create a serially complete monthly time series of precipit…

2011

Abstract The availability of good and reliable rainfall data is fundamental for most hydrological analyses and for the design and management of water resources systems. However, in practice, precipitation records often suffer from missing data values mainly due to malfunctioning of raingauge for specific time periods. This is an important issue in practical hydrology because it affects the continuity of rainfall data and ultimately influences the results of hydrologic studies which use rainfall as input. Many methods to estimate missing rainfall data have been proposed in literature and, among these, most are based on spatial interpolation algorithms. In this paper different spatial interpo…

Modelling the presence of disease under spatial misalignment using Bayesian latent Gaussian models.

2015

Modelling patterns of the spatial incidence of diseases using local environmental factors has been a growing problem in the last few years. Geostatistical models have become popular lately because they allow estimating and predicting the underlying disease risk and relating it with possible risk factors. Our approach to these models is based on the fact that the presence/absence of a disease can be expressed with a hierarchical Bayesian spatial model that incorporates the information provided by the geographical and environmental characteristics of the region of interest. Nevertheless, our main interest here is to tackle the misalignment problem arising when information about possible covar…

Developing an erodibility triangle for soil textures in semi-arid regions, NW Iran

2016

Abstract There is a strong need to develop a simple method for rapid estimation of erodibility using readily available data. In this study, soil erodibility was measured using eleven soil textures at the plot scale (60 cm × 80 cm) on a slope of 9% in a semi-arid region. A total of 110 soil erosion experiments were conducted using ten simulated rainfalls (50 mm h− 1 for 30 min). A regression model was developed based on silt and clay content (R2 = 0.82, p

Rainfall erosivity over the Calabrian region

1997

Abstract Following the results of a study carried out for the neighbouring Sicilian region, this paper reports a study of the applicability of the annual value, Faj, of the Arnouldus index to represent the erosion risk in Calabrian region. Firstly, By using 214 values of the mean annual value of the erosivity index, FF, and a Kriging interpolation method, an isoerosivity map is plotted. Then, in order to predict the erosion risk for an event of any return period, the probability distribution of the Faj index is studied. An in situ statistical analysis, carried out by using candidate distributions with two parameters (Gauss, LN2, EV1 and Weibull distribution), showed that the EV1 and LN2 law…

SW—Soil and Water

2000

Abstract Recent research has directed attention to the properties of the eroded material because of its influence in deposition phenomena and in carrying capacity of pollutant materials. In this paper, the spatial distribution of the content of nitrogen, phosphorus and total organic carbon is firstly deduced using the measurements carried out in 129 soil samples well distributed over the Sicilian Sparacia Basin and a Kriging interpolation method. Then the load of each chemical was calculated at morphological unit and basin scale using the above-mentioned spatial distributions and sediment yield values calculated by a parametric approach such as the revised universal soil loss equation (RUSL…

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…

A comparison between three meta-modeling optimization approaches to design a tube hydroforming process

2012

Seasonal Mapping of Irrigated Winter Wheat Traits in Argentina with a Hybrid Retrieval Workflow Using Sentinel-2 Imagery

2022

Earth observation offers an unprecedented opportunity to monitor intensively cultivated areas providing key support to assess fertilizer needs and crop water uptake. Routinely, vegetation traits mapping can help farmers to monitor plant development along the crop’s phenological cycle, which is particularly relevant for irrigated agricultural areas. The high spatial and temporal resolution of the Sentinel-2 (S2) multispectral instrument leverages the possibility to estimate leaf area index (LAI), canopy chlorophyll content (CCC), and vegetation water content (VWC) from space. Therefore, our study presents a hybrid retrieval workflow combining a physically-based strategy with a machine learni…

Mapping Ash CaCO3, pH, and Extractable Elements Using Principal Component Analysis

2017

Abstract Ash cover in fire-affected areas is an important factor in the reduction of soil erosion and increased availability of soil nutrients. Thus it is important to understand the spatial distribution of ash and its capacity for soil protection and to provide nutrients to the underlying soil. In this work, we aimed to map ash CaCO3, pH, and select extractable elements using a principal component analysis (PCA). Four days after a medium to severe wildfire, we established a grid in a 9 ×27 m area on a west facing slope and took ash samples every 3 m for a total of 40 sampling points. The PCA carried out retained five different factors. Factor 1 had high positive loadings for ash with elect…