The use of topographic airborne LiDAR data has become an essential part archaeological prospection, and the need for archaeology-specific processing workflow is well established. However, interpolation, important step in which digital elevation model derived from classified point cloud, received little attention archaeologists. This a direct impact on accuracy visual performance model, but rema...

Information about the distribution and abundance of the habitat-forming sessile organisms in marine ecosystems is of great importance for conservation and natural resource managers. Spatial interpolation methodologies can be useful to generate this information from in situ sampling points, especially in circumstances where remote sensing methodologies cannot be applied due to small-scale spatia...

Precipitation is a significant input variable required in hydrological models such as the Soil & Water Assessment Tool (SWAT). The utilization of inaccurate precipitation data can result poor representation true hydrologic conditions catchment. SWAT utilizes conventional nearest neighbor method assigning weather parameters for each subbasin; representing spatial variations over large area, ...

BACKGROUND Physical inactivity, ambient air pollution and obesity are modifiable risk factors for non-communicable diseases, with the first accounting for 10% of premature deaths worldwide. Although community level interventions may target each simultaneously, research on the relationship between these risk factors is lacking. OBJECTIVES After comparing spatial interpolation methods to determ...

[1] Inverse weighted distance and regression nonexact techniques were evaluated for interpolating methods snow water equivalent (SWE) across the entire Colorado River Basin of the western United States. A 1-km spacing was used for the gridding of snow telemetry (SNOTEL) measurements for the years 1993, 1998, and 1999, which on average, represented higher than average, average, and lower than av...

Improving the quality of atmospheric precipitation measurements is crucial in view minimizing uncertainty weather forecasting, climate change impact assessment, water resource assessment and management, drought flood prediction. Remote sensing technology has considerably improved spatio-temporal precipitation. Despite advancement remote technology, there a need to investigate robust approach to...

Few studies empirically estimate the effects of metropolitan growth on nonmetropolitan communities at a national scale. This paper estimates the growth effects of 276 MSAs on population in 1,988 nonmetropolitan communities in the United States from 2000 to 2007. We estimate the distance for growth spillovers from MSAs to nonmetropolitan communities and test the assumption that a single MSA infl...

Spatial interpolation (SI) is currently one of the most common ways to estimate wind speed (Ws). However, classic SI models either ignore the complex geography [e.g. inverse distance weighting (IDW)], or demand high computational resources (e.g. cokriging). This study aimed to develop a simple yet effective SI model for estimating Ws in Eastern Thrace of Turkey. This new method, named MIDW(Ws),...

The dispersion of air pollutants and the spatial representation meteorological variables are subject to complex atmospheric local parameters. To reduce impact particulate matter (PM2.5) on human health, it is great significance know its concentration at high resolution. In order monitor effects an exposed population, geostatistical analysis offers potential obtain high-quality mapping PM2.5 var...

Sensible heat flux (H) plays an important role in characterizations of land surface water and heat balance. There are various types of H measurement methods that depend on observation scale, from local-area-scale eddy covariance (EC) to regional-scale large aperture scintillometer (LAS) and remote sensing (RS) products. However, methods of converting one H scale to another to validate RS produc...