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Tropical forest regrowth has been included implicitly in large scale estimations of land-use change [8], but there is renewed interested in separating it from deforestation emissions [6].

Tropical forest regrowth has been included implicitly in large scale estimations of land-use change [ 8], but there is renewed interested in separating it from deforestation emissions [ 6].

In the era prior to the large-scale estimation of sea-ice production from Tamura et al. (2008), the linkage between the ice production and AABW could not be discussed.

Most studies on the carbon balance of selectively logged forests have estimated pre- and post-logging carbon stocks with remote sensing methods [16], allowing large-scale estimation of logging extent and quantification of canopy damage [14, 17, 18].

Thus the biomass of herbs is easily overlooked in large-scale estimation of biomass but in the Gurbantunggut Desert the ecological significance (e.g. retaining ecosystem stability and species diversity, preventing sand diffusion, animal husbandry, soil nutrient cycling) of herbs, especially HSV, cannot be disregarded.

Large-scale estimation is in general more challenging than its small-scale counterpart.

The increasing availability of high-resolution remotely sensed information, including Light Detection and Ranging (LiDAR) (also referred to as airborne laser scanning (ALS)) sensors, is now routinely being coupled with geo-referenced inventory plot measurements to improve large- and small-scale estimation of forestry parameters (e.g. White et al. 2013).

This study was designed to a) assess the feasibility of large-scale kriging estimation of daily residential-level ambient PM concentrations, b) perform and compare cross-validations of different kriging models, c) determine and contrast the most appropriate kriging approaches, and d) calculate the SEs of the kriging estimations.

In this work we propose a new hybrid global method, based on the combination of an evolutionary search strategy with a local multiple-shooting approach, which offers a reliable and efficient alternative for the solution of large scale parameter estimation problems.

It is likely that a major application of these tests will be in large scale surveys for the estimation of infection prevalence.

In this paper, we demonstrate the efficiency and versatility of PGO with two different applications: (1) the parallelization of a large scale parameter estimation problem associated with modeling water flow in a heterogeneous deep vadose zone; (2) the parallelization of a complex simulation-optimization procedure for searching for an optimal groundwater remediation design.

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