Sentence examples for estimate landscape from inspiring English sources

Following the approach of Vassilev et al. [1] we propose to estimate landscape properties from random walks using the variation operator of the search heuristic.

To estimate landscape CO2 fluxes, the measurements from the individual fields are weighted according to their areal contribution.

One of the reasons circuit theory is appealing as a model of gene flow and individual movement is that the incorporation of random walkers on networks to estimate landscape resistance allows resistance to decrease with increasing connectivity, path width, and path redundancy [11], [14].

We used circuit theory to estimate landscape resistance to organism movement and gene flow, and compared the output across several scenarios: a habitat-quality map with artificial boundaries and no buffer, a map with a buffer composed of randomized habitat quality data, and a map with a buffer composed of the true habitat quality data.

Over the 10-year period, the researchers estimate landscape fire smoke killed an average 339,000 people per year, with a high percentage of deaths occurring in low-income areas.

Airborne lidar data were collected in 2005 and 2012 in Blue Earth County, Minnesota (1980 km2) and the occurrence of an extreme flood in 2010 produced geomorphic change clearly observed in the field, providing an opportunity to estimate landscape-scale geomorphic change.

This is not only confusing [ 119, 118], but also frustrates any attempt to estimate landscapes from empirical data.

Estimating landscape surface roughness using radar helps in modeling of the land surface.

For each catchment we estimated landscape variables as the proportion of five land-cover units and eight topographic properties.

For atlas based richness estimates, landscape attributes played more important role than climate while for expert-drawn range based richness estimates climatic variables were more important (for the ectothermic amphibians and reptiles).

We developed a regional (Mississippi, Louisiana, eastern Texas, Arkansas, and Missouri, USA) model estimating landscape resistance to movement using GIS-based features considered to affect black bear space use: land cover type, distance to major rivers, road density, and highway presence.