Variations in the biomass of Eucalyptus plantations at a regional scale in Southern China

We quantified deviations in regional forest biomass from simple extrapolation of plot data by the biomass expansion factor method（BEF） versus estimates obtained from a local biomass model,based on large-scale empirical field inventory sampling data.The sources and relative contributions of deviations between the two models were analyzed by the boosted regression trees method.Relative to the local model,BEF overestimated accumulative biomass by 22.12%.The predominant sources of the total deviation （70.94%） were stand-structure variables.Stand age and diameter at breast height are the major factors.Compared with biotic variables,abiotic variables had a smaller overall contribution （29.06%）,with elevation and soil depth being the most important among the examined abiotic factors.Large deviations in regional forest biomass and carbon stock estimates are likely to be obtained with BEF relative to estimates based on local data.To minimize deviations,stand age and elevation should be included in regional forest-biomass estimation.

Understanding the effects of the impervious surfaces pattern on land surface temperature in an urban area

It is well known that urban impervious surface （IS） has a warming effect on urban land surface temperature （LST）. However, the influence of an IS＇s structure, components, and spatial distribution on LST has rarely been quantitatively studied within strictly urban areas. Using ETM＋ remote sensing images from the downtown area of Shanghai, China in 2010, this study characterized and quantified the influence of the IS spatial pattern on LST by selecting the percent cover of each IS cover feature and ten configuration metrics. The IS fraction was estimated by linear spectral mixture analysis （LSMA）, and LST was retrieved using a mono-window algorithm. The results indicate that high fraction IS cover features account for the majority of the study area. The high fraction IS cover features are widely distributed and concentrated in groups, which is similar with that of high temperature zones. Both the percent composition and the configuration of IS cover features greatly affect the magnitude of LST, but the percent composition is a more important factor in determining LST than the configuration of those features. The significances and effects of the given configuration variables on LST vary greatly among IS cover features.

Uncertainty analysis of cross-calibration for HJ-1 CCD camera

Radiometric calibration of sensor is the basis of quantitative remote sensing,and uncertainty analysis is critical to ensure the accuracy of cross-calibration.Therefore,firstly,cross-calibration formulas were improved by redefining calibration coefficient and spectral band matching factor.In these formulas,cci was redefined as the calibration coefficient of normalized apparent reflectance,and spectral band matching factor as the ratio of normalized apparent reflectance.Secondly,based on the contrast of ideal and actual conditions in cross-calibration,8 sources of cross-calibration uncertainty were proposed:calibration uncertainty of standard sensor;pixel matching uncertainty;spectral band matching factor uncertainty caused by site altitude setting error,atmospheric parameters setting error,surface spectrum source,surface bidirectional reflectance characteristic,and error of atmospheric radiative transfer model;and uncertainty caused by other factors which were not considered.Finally,the contribution of each uncertainty was further analyzed and discussed for the HJ-1 CCD camera.The results provide many valuable references for evaluating the feasibility of alternative cross-calibration measurements.

Long-range cross-correlation between urban impervious surfaces and land surface temperatures

The thermal effect of urban impervious surfaces （UIS） is a complex problem. It is thus necessary to study the relationship between UIS and land surface temperatures （LST） using complexity science theory and methods. This paper investigates the long-range cross- correlation between UIS and LST with detrended cross- correlation analysis and multifractal detrended cross- correlation analysis, utilizing data from downtown Shanghai, China. UIS estimates were obtained from linear spectral mixture analysis, and LST was retrieved through application of the mono-window algorithm, using Landsat Thematic Mapper and Enhanced Thematic Mapper Plus data for 1997-2010. These results highlight a positive long-range cross-correlation between UIS and LST across People＇s Square in Shanghai. LST has a long memory for a certain spatial range of UIS values, such that a large increment in UIS is likely to be followed by a large increment in LST. While the multifractal long-range cross- correlation between UIS and LST was observed over a longer time period in the W-E direction （2002-2010） than in the N-S （2007-2010）, these observed correlations show a weakening during the study period as urbanization increased.