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Ellen Jasinski, Douglas Morton, Ruth DeFries, Yosio Shimabukuro, Liana Anderson, and Matthew Hansen

or absence of mechanized agriculture is set as the dependent variable such that a Y = 1 outcome refers to a pixel classified as cropland, and Y = 0 indicates a different land-cover class. Two logistic regressions were conducted. The first was a “snapshot” analysis for understanding how physical landscape characteristics are correlated with the general spatial distribution of mechanized agriculture as shown in the 2003 land-cover classification. The second was an analysis to examine how

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Jeffrey T. Morisette, Louis Giglio, Ivan Csiszar, Alberto Setzer, Wilfrid Schroeder, Douglas Morton, and Christopher O. Justice

provide detailed information with which to evaluate the two MODIS fire detection products. A quantitative comparison is accomplished through logistic regression and the application of accuracy assessment curves ( Morisette and Khorram 2000 ) applied to ASTER versus MODIS error matrices. We use the analysis to empirically quantify the detection envelope for the INPE and EOS algorithms with respect to fire size and spatial continuity as estimated by the ASTER fire maps. This paper goes beyond previous

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Andrew J. Elmore, Gregory P. Asner, and R. Flint Hughes

) were extracted and averaged from the nine MODIS pixels centered on each of the 23 sites. These monthly precipitation time series (February 2000 through December 2002) were compared against the MODIS land-cover time series using linear regression. Precipitation data from 2003 were not available at the time of this data analysis. Our work from other projects in Hawaii has built a substantial base of knowledge pertaining to land-use history, land-cover characteristics, and location of one recent large

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Tomas F. Domingues, Joseph A. Berry, Luiz A. Martinelli, Jean P. H. B. Ometto, and James R. Ehleringer

relationships among parameters evaluated. To assess effects of season or site, analysis of covariance was used to establish comparisons among the slopes derived from linear regressions. 3. Results 3.1. Canopy structure There was a significant relationship between cumulative LAI and canopy height ( Figure 1 and Table 3 ). LAI profiles from Flona-2.2 and Flona-1 had statistically different slopes ( F = 13.13, P = 0.001, n = 36), although no difference was detected between Flona-2.1 and Flona-1 ( F = 2

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Carlos M. Souza Jr., Dar A. Roberts, and AndréL. Monteiro

and Rocha 1992 ), supervised classification ( Stone and Lefebvre 1998 ), soil fraction images obtained through spectral mixture analysis ( Souza and Barreto 2000 ; Monteiro et al. 2003 ), contextual clustering ( Sgrenzaroli et al. 2002 ), and decision tree classification ( Souza et al. 2003 ). Additionally, efforts have been made to link forest biophysical properties of selectively logged forests with remotely sensed data ( Asner et al. 2002 ; Asner et al. 2004 ). Burned forests have also been

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Cuizhen Wang, Jiaguo Qi, and Mark Cochrane

extremely difficult to visualize these differences by simply comparing spectral values in medium-resolution remotely sensed imagery as Landsat Enhanced Thematic Mapper Plus (ETM+; Asner et al. 2004 ). Although texture analysis is a common method to detect spatial variation in remotely sensed imagery, when the gap fraction is less than 50%, the forest openings cannot be successfully detected ( Asner et al. 2004 ). A new measure is needed to quantitatively assess forest degradation by selective logging

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Ted R. Feldpausch, Susan J. Riha, Erick C. M. Fernandes, and Elisa V. Wandelli

using analysis of variance (ANOVA) and regression analysis, with LAI, canopy openness, basal area, biomass, DBH, and stem density as the response variables by time after pasture abandonment (midpoint of each age class). 3. Results 3.1. Plant community transition Across the successional sequence spanning more than a decade, the pioneering vegetation converted the abandoned pastures from a low biomass, grass–forb–shrub-dominated community with species from the genera Borreria (Rubiaceae

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Michael Keller, Ruth Varner, Jadson D. Dias, Hudson Silva, Patrick Crill, Raimundo Cosme de Oliveira Jr., and Gregory P. Asner

they did not drift ( Veldkamp and Keller 1997 ). Signals from the CO 2 and NO 2 analyzers and the mass flowmeter for the NO standard gas were recorded on a datalogger (Campbell CR10). Fluxes were calculated from the linear increase of concentration versus time adjusted for the ratio of chamber volume to area and the air density within the chamber. 2.4. Analysis of CH 4 and N 2 O We made static enclosure measurements for CH 4 and N 2 O fluxes using the same bases and vented caps ( Keller and

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