BackgroundCarbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing.ResultsWe compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (~20 returns m−2) data was highly accurate (mean signed error of 0.19 ± 0.97 m), while those derived from reduced-density datasets (8 m−2, 4 m−2, 2 m−2 and 1 m−2) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4 m−2, the bias in height estimates translated into errors of 80–125 Mg ha−1 in predicted aboveground biomass.ConclusionsGiven the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.Electronic supplementary materialThe online version of this article (doi:10.1186/s13021-015-0013-x) contains supplementary material, which is available to authorized users.
We have analysed monthly composites of normalized diVerence vegetation index (NDVI ) calculated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) for the Amazonian region of northern Brazil across a decade (August 1981 to June 1991 to ascertain if the dominant vegetation types could be diVerentiated, and to seek inter-annual climatic variation due to changing environmental conditions. The vegetation types observed included dense forest (submontana and terras baixas), open forest (submontana and terras baixas), transitional forest, seasonal forest (caatinga), and two types of savanna (cerrado). We found that monthly NDVI composites revealed seasonality in cerrado and especially in caatinga cover types, which can be used in their identi® cation, whilst the phenology of other forest cover types varies little throughout the year. Additionally, yearly composite NDVI values showed a clear and signi® cant reduction ( p>0´95) in dry years, such as those with El Nin Ä o Southern Oscillation events. These results indicate the potential use of multi-temporal NDVI data for the environmental characterization and identi® cation of forest ecosystems. Our research found NDVI images from NOAA AVHRR oVer a long-term data set that is unequalled for monitoring terrestrial land cover. However, these data have to be used with a degree of caution, especially in regards to atmospheric interference, such as cloud contamination and volcanic eruptions, and post-launch changes in calibration.
RESUMOA precipitação é um dos principais fatores que determina a dinâmica sazonal da vegetação na região de savanas tropicais, como é o caso do cerrado brasileiro. Neste trabalho foram analisadas as relações da precipitação sazonal, com o comportamento sazonal das classes de uso e cobertura da terra (UCT), principalmente as fisionomias de cerrado do Estado de Tocantins. Foi analisada a dinâmica sazonal do cerrado, incluindo áreas florestadas e não florestadas, a partir da análise de imagens do MODIS/TERRA IV (Índices de Vegetação) de janeiro a dezembro de 2004, bem como dados diários de precipitação de 2004 e uma série de precipitação diária do período de 1969 a 2005. Os resultados da análise de precipitação mostram que a área de estudo apresentou uma alta sazonalidade, com estação seca de maio a setembro. As análises dos IV mostram que a dinâmica sazonal das formações de cerrado é similar àquela das áreas convertidas para outros usos. O padrão sazonal das classes de UCT segue os padrões da precipitação, cujos menores valores foram registrados no mês de agosto de 2004, mês este que apresentou os menores valores dos IV. Diferentemente das demais classes de UCT, a formação florestal não se ajustou ao padrão de precipitação, apresentando valores de IV similares ao longo do ano com leve decréscimo no mês de setembro de 2004. Palavra chave: Uso e cobertura da terra, índices espectrais de vegetação, precipitação, vegetação sazonal do cerrado.
ABSTRACT: RELATIONSHIP BETWEEN VEGETATION SEASONAL PATTERN AND PRECIPITATION IN THE CERRADO REGION BY SPECTRAL VEGETATION INDEXES
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