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We analyzed the 10-year record (1999-2009) of SeaWinds Ku-band microwave backscatter from humid tropical forest regions in South America, Africa, and Indonesia/Malaysia. While backscatter was relatively stable across much of the region, it declined by 1-2 dB in areas of known large-scale deforestation, and increased by up to 1-2 dB in areas of secondary forest or plantation forest growth and in major metropolitan areas. The reduction in backscatter over 142 18.5 km × 18.5 km blocks of tropical forest was correlated with gross forest cover loss (as determined from Landsat data analysis) (R = -0.78); this correlation improved when restricted to humid tropical forest blocks in South America with high initial forest cover (R = -0.93, n = 22). This study shows that scatterometer-based analyses can provide an important geophysical data record leading to robust identification of the spatial patterns and timing of large-scale change in tropical forests. The coarse spatial resolution of SeaWinds ( ~ 10 km) makes it unsuitable for mapping deforestation at the scale of land-use activity. However, due to a combination of instrument stability, sensitivity to canopy change and insensitivity to atmospheric effects, and straight-forward data processing, Ku-band scatterometery can provide a fully independent assessment of large-scale tropical forest canopy dynamics which may complement the interpretation of higher resolution optical remote sensing. [ABSTRACT FROM AUTHOR]

The availability of nitrogen represents a key constraint on carbon cycling in terrestrial ecosystems, and it is largely in this capacity that the role of N in the Earth's climate system has been considered. Despite this, few studies have included continuous variation in plant N status as a driver of broad-scale carbon cycle analyses. This is partly because of uncertainties in how leaf-level physiological relationships scale to whole ecosystems and because methods for regional to continental detection of plant N concentrations have yet to be developed. Here, we show that ecosystem CO[sub2] uptake capacity in temperate and boreal forests scales directly with whole-canopy N concentrations, mirroring a leaf-level trend that has been observed for woody plants worldwide. We further show that both CO[sub2] uptake capacity and canopy N concentration are strongly and positively correlated with shortwave surface albedo. These results suggest that N plays an additional, and overlooked, role in the climate system via its influence on vegetation reflectivity and shortwave surface energy exchange. We also demonstrate that much of the spatial variation in canopy N can be detected by using broad-band satellite sensors, offering a means through which these findings can be applied toward improved application of coupled carbon cycle-climate models. [ABSTRACT FROM AUTHOR]

In this landscape-scale study we explored the potential for multitemporal 10-day composite data from the Vegetation sensor to characterize land cover types, in combination with Landsat TM image and agricultural census data. The study area (175 km by 165 km) is located in eastern Jiangsu Province, China. The Normalized Difference Vegetation Index (NDVI ) and the Normalized Difference Water Index (NDWI ) were calculated for seven 10-day composite (VGT-S10) data from 11 March to 20 May 1999. Multi-temporal NDVI and NDWI were visually examined and used for unsupervised classification. The resultant VGT classification map at 1 km resolution was compared to the TM classification map derived from unsupervised classification of a Landsat 5 TM image acquired on 26 April 1996 at 30 m resolution to quantify percent fraction of cropland within a 1 km VGT pixel; resulting in a mean of 60% for pixels classified as cropland, and 47% for pixels classified as cropland/natural vegetation mosaic. The estimates of cropland area from VGT data and TM image were also aggregated to county-level, using an administrative county map, and then compared to the 1995 county-level agricultural census data. This landscape-scale analysis incorporated image classification (e.g. coarse-resolution VGT data, fineresolution TM data), statistical census data (e.g. county-level agricultural census data) and a geographical information system (e.g. an administrative county map), and demonstrated the potential of multi-temporal VGT data for mapping of croplands across various spatial scales from landscape to region. This analysis also illustrated some of the limitations of per-pixel classification at the 1 km resolution for a heterogeneous landscape. [ABSTRACT FROM AUTHOR]

The seasonal transition of the boreal forest between frozen and non-frozen conditions affects a number of ecosystem processes that cycle between winter dormant and summer active states. The relatively short Ku-band wavelength (2.14 cm) of the space-borne NASA scatterometer (NSCAT) is sensitive to changes in dielectric properties, associated with large-scale changes in the relative abundance and phase (frozen or thawed) of canopy and surface water. We used a temporal change detection analysis of NSCAT daily radar backscatter measurements to characterize the 1997 seasonal spring thaw transition period across the 106 km2 BOREAS study region of central Canada. In the spring, air temperature transitions from frozen to non-frozen conditions and surface observations of seasonal snow cover depletion were generally coincident with decreases in radar backscatter of more than 2.9 dB, regardless of regional landcover characteristics. We used a temporal classification of NSCAT daily differences from 5-day smoothed backscatter values to derive three simple indices describing the initiation, primary event and completion of the spring thaw transition period. Several factors had a negative impact on the relative accuracy of NSCAT-based results, including periodic gaps in NSCAT daily time-series information and a large (i.e., >2 cm day−1) spring rainfall event. However, these results were generally successful in capturing the seasonal transition of the region from frozen to non-frozen conditions, based on comparisons with regional weather station network information. These results illustrate the potential for improved assessment of springtime phenology and associated ecosystem dynamics across high latitude regions, where field based and optical remote-sensing methods are substantially degraded by frequent cloud cover, low solar illumination and sparse surface weather station networks. [Copyright &y& Elsevier]