Sentence examples for model for vegetation from inspiring English sources

Based on extensive experimental study, a two-dimensional numerical model for vegetation fire spread was developed to simulate laboratory-scale fires.

Radiative transfer models for vegetation serve as a basis for extracting vegetation variables using directional/spectral data from modern-borne sensors (e.g., MODIS, MISR, POLDER, SeaWiFS).

These results are comparable to many other models for vegetation properties based on Landsat data, where model %RMSE values were in the range of 21 50 % [13, 28, 67, 69].

In the control simulations, the standard type-8 (shrubs with ground-cover) data typically used by general circulation models for vegetation in the Sahel produce more than 50% underestimation of average latent heat flux and 100% overestimation of average sensible heat flux.

These aspects have not yet been adequately incorporated in the model for all vegetation structure types.

We propose a grid model for the vegetation in bands, with special emphasis on those comprising the tiger bush in the Sahel.

Here we develop and employ a Markov model of vegetation dynamics for the sagebrush steppe ecosystem to predict vegetation change and management costs under different intensities and types of post-fire revegetation.

Looking at all models, two variables (temperature the previous year and SINDVI the previous year) show the same directional output for both the model of SINDVI for all vegetation types together and the individual models for each vegetation type (Table 2).

We assess multivariate QUEST DTs with unbiased classification rules and linear discriminant node models for integrated vegetation mapping and change detection.

We present a set of models for simulating vegetation dynamics in disturbance-prone ecosystems with different complexity levels, integrated in a modelling environment for generating landscapes and analysing landscape patterns and simulation results (Lass).

Our model for percent total vegetation cover accounted for significant random effects and showed that vegetation cover increased with soil strength and dripline (Table 2).