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A mixed model for forest policy formulation is discussed.
This is intended to serve as a model for forest management to restore biodiversity in this region.
This study was designed to identify the most precise model for forest managers to predict the 300 Index based on data from remote sensing and auxiliary data.
We develop an agent-based model for forest harvesting to study how interactions between neighboring land parcels and the degree of information flow among landowners influence harvesting patterns.
Wooldridge et al. (2001) worked to regionalize the parameters of a simple model for forest and non-forest classification and different climate regions for predicting the impact of landuse/land cover change on the hydrologic response of a catchment.
We develop a decision model for forest use under social learning to explore whether social learning is efficient to improve landowners' decisions and can lead to effective forest management.
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We could only compare our allometric models for forest lands with previous published allometric equations due to the lack of allometric equations for cropland, grassland and settlements.
Some studies on propagation models for forest environments have been presented in the literature since the 1960s until today [6, 21, 27, 28, 38].
Finally, I discuss the stand and landscape level implications of the reviewed conceptual models for forest restoration and ecosystem-based management.
IWCM based modeling for forest AGB retrieval showed R2 value of 0.5, RMSE of 62.73 (t ha−1) and a percent accuracy of 51%.
We therefore compared only the models for forest land and the generic model with results from Brown [67], Chave et al. [22], Chave et al. [3] and de Jose [45].
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CEO of Professional Science Editing for Scientists @ prosciediting.com