A crop height model (CHM) can be an important element of the decision making process in agriculture, because it relates well with many agronomic parameters, e.g., crop height, plant biomass or crop yield. Today, CHMs can be inexpensively obtained from overlapping imagery captured from unmanned aerial vehicle (UAV) platforms or from proximal sensors attached to ground-based vehicles used for reg...

Whenever simulation requires much computer time, interpolation is needed. There are several interpolation techniques in use (for example, linear regression), but this paper focuses on Kriging. This technique was originally developed in geostatistics by D. G. Krige, and has recently been widely applied in deterministic simulation. This paper, however, focuses on random or stochastic simulation. ...

Annually much agricultural productions are lost by natural hazards such as flooding, extreme temperature, and drought. In this research we present a procedure to identify such hazards for rice cropping from remote sensing imagery. Extreme temperature is investigated by comparing actual temperatures with tolerance temperatures during the growing stage. Drought is investigated using the evapotran...

This paper outlines the application of the multi-layer perceptron artificial neural network (ANN), ordinary kriging (OK), and inverse distance weighting (IDW) models in the estimation of local scour depth around bridge piers. As part of this study, bridge piers were installed with bed sills at the bed of an experimental flume. Experimental tests were conducted under different flow conditions an...

This article reviews Kriging (also called spatial correlation modeling). It presents the basic Kriging assumptions and formulas—contrasting Kriging and classic linear regression metamodels. Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor. Besides classic one-shot statistical designs such as Latin Hypercube Sampl...

In this study, a spatiotemporal estimation method based on Funk singular value decomposition (F-SVD) that considers the correlation of rainfall is proposed to improve estimations from gauge observations. Hourly data several flood events are selected verify by comparing with Inverse Distance Weighting (IDW) and Ordinary Kriging (OK) in Hanjiang basin, China. The results show (1) F-SVD has best p...

In light of the unavailability traffic volume data for all road segments, scientific literature proposes estimating this variable using spatial interpolators. However, most methods found use Euclidean distance between database points as a proximity measure, in addition to ignoring anisotropy phenomenon. Thus, objective present study was apply Ordinary Kriging (OK) with network distances and ani...

abstract guilan is a famous province in growing rice in iran. recently, due to shortage of water, farmers' desire to use groundwater in order to grow rice in northern part of iran has been increasing rapidly. the fact that rice is sensitive to water quality, caused concern about rice cultivation sustainability in the area, especially in drought years. this study was done to investigate the spat...

Estimating the spatial distribution of precipitation is an important and challenging task in hydrology, climatology, ecology, and environmental science. In order to generate a highly accurate distribution map of average annual precipitation for the Loess Plateau in China, multiple linear regression Kriging (MLRK) and geographically weighted regression Kriging (GWRK) methods were employed using ...

Terrain attributes derived from digital elevation models have been used widely for mapping soil organic matter (SOM). Among these attributes, the topographic wetness index (TWI), an index for quantitatively indicating the balance between water accumulation and drainage conditions at the local scale, has been shown to correlate with SOM. However, TWIs used in most studies are calculated using a ...