New remote sensing technologies have emerged to quantitatively assess submersed aquatic vegetation abundance and distribution. We evaluated a hydroacoustics global positioning system to map the percent of the water column occupied by submersed vegetation (referred to here as biovolume) in three Minnesota (USA) lakes. We evaluated the relative accuracy and precision of digital biovolume maps pro...

This paper focuses on possibilities for using a simple scoring technique to make estimates of millet yield. Estimates are intended to be used for de®ning application rates of manure in the context of low-tech precision agriculture. Yields from 1995 and 1996 at three locations were related to scoring, soil data and elevation. Kriging was used to interpolate point data to areas. Several procedure...

The cone penetration test (CPT) has been the de facto field exploration method in geotechnical engineering for decades. Variations of CPT can measure parameters seismic, environmental, and hydrological applications. Analyzing response often requires properties areas that have little or no data. Therefore, given limited data, it is critical to understand how accurately estimate soil at unsampled...

The super-resolution of depth images is a research hotspot. In this study, the classical Kriging algorithm applied to spatial interpolation images, together with fractional-order differential method for edge recognition, realise reconstruction images. resulting model improves performance by harnessing superior characteristics recognition and effectively solving blurring problem in Experimental ...

As being an essential tool for estimating spatial continuous data, interpolation methods have been applied to various disciplines concerned with the Earth’s surface. In the paper, six spatial interpolation algorithms, including an internationally popular ANUDEM method and five other commonly used interpolation methods, were applied in three different landform regions, that is, hills, mountains ...

Accurately quantifying soil organic carbon (SOC) stocks in soils is considered necessary and important for studying the soil quality and productivity, modeling the global carbon cycle, and assessing the global climate change. The objectives of this chapter are (1) to evaluate the effects of sampling density and interpolation methods on spatial distribution of SOC density (SOCD) and (2) to estim...

This work falls within the context of predicting the value of a real function at some input locations given a limited number of observations of this function. The Kriging interpolation technique (or Gaussian process regression) is often considered to tackle such a problem but the method suffers from its computational burden when the number of observation points is large. We introduce in this ar...

In this paper we introduce a new interpolation method, known as kernel interpolation (KI), for modeling the output from expensive deterministic computer experiments. We construct it by repeating a generalized version of the classic Nadaraya-Watson kernel regression an infinite number of times. Although this development is numerical, we are able to provide a statistical framework for KI using a ...

Filtering is one of the core post-processing steps for airborne LiDAR point cloud. In recent years, the morphology-based filtering algorithms have proven to be a powerful and efficient tool for filtering airborne LiDAR point cloud. However, most traditional morphology-based algorithms have difficulties in preserving abrupt terrain features, especially when using larger filtering windows. In ord...