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1.
We modeled net primary productivity (NPP) at high spatial resolution using an advanced spaceborne thermal emission and reflection radiometer (ASTER) image of a Qilian Mountain study area using the boreal ecosystem productivity simulator (BEPS). Two key driving variables of the model, leaf area index (LAI) and land cover type, were derived from ASTER and moderate resolution imaging spectroradiometer (MODIS) data. Other spatially explicit inputs included daily meteorological data (radiation, precipitation, temperature, humidity), available soil water holding capacity (AWC), and forest biomass. NPP was estimated for coniferous forests and other land cover types in the study area. The result showed that NPP of coniferous forests in the study area was about 4.4 tCha(-1)y(-1). The correlation coefficient between the modeled NPP and ground measurements was 0.84, with a mean relative error of about 13.9%.  相似文献   

2.
LAI inversion algorithm based on directional reflectance kernels   总被引:3,自引:0,他引:3  
Leaf area index (LAI) is an important ecological and environmental parameter. A new LAI algorithm is developed using the principles of ground LAI measurements based on canopy gap fraction. First, the relationship between LAI and gap fraction at various zenith angles is derived from the definition of LAI. Then, the directional gap fraction is acquired from a remote sensing bidirectional reflectance distribution function (BRDF) product. This acquisition is obtained by using a kernel driven model and a large-scale directional gap fraction algorithm. The algorithm has been applied to estimate a LAI distribution in China in mid-July 2002. The ground data acquired from two field experiments in Changbai Mountain and Qilian Mountain were used to validate the algorithm. To resolve the scale discrepancy between high resolution ground observations and low resolution remote sensing data, two TM images with a resolution approaching the size of ground plots were used to relate the coarse resolution LAI map to ground measurements. First, an empirical relationship between the measured LAI and a vegetation index was established. Next, a high resolution LAI map was generated using the relationship. The LAI value of a low resolution pixel was calculated from the area-weighted sum of high resolution LAIs composing the low resolution pixel. The results of this comparison showed that the inversion algorithm has an accuracy of 82%. Factors that may influence the accuracy are also discussed in this paper.  相似文献   

3.
Aboveground biomass (AGB) of forests is an important component of the global carbon cycle. In this study, Landsat ETM(+) images and field forest inventory data were used to estimate AGB of forests in Liping County, Guizhou Province, China. Three different vegetation indices, including simple ratio (SR), reduced simple ratio (RSR), and normalized difference vegetation index (NDVI), were calculated from atmospherically corrected ETM(+) reflectance images. A leaf area index (LAI) map was produced from the RSR map using a regression model based on measured LAI and RSR. The LAI map was then used to develop an initial AGB map, from which forest stand age was deduced. Vegetation indices, LAI, and forest stand age were together used to develop AGB estimation models for different forest types through a stepwise regression analysis. Significant predictors of AGB changed with forest types. LAI and NDVI were significant predictors of AGB for Chinese fir (R(2)=0.93). The model using LAI and stand age as predictors explained 94% of the AGB variance for coniferous forests. Stand age captured 79% of the AGB variance for broadleaved forests (R(2)=0.792). AGB of mixed forests was predicted well by LAI and SR (R(2)=0.931). Without differentiating among forest types, the model with SR and LAI as predictors was able to explain 90% of AGB variances of all forests. In Liping County, AGB shows a strong gradient that increases from northeast to southwest. About 64% of the forests have AGB in the range from 90 to 180 t ha(-1).  相似文献   

4.
Large scale process-based modeling is a useful approach to estimate distributions of global net primary productivity (NPP). In this paper, in order to validate an existing NPP model with observed data at site level, field experiments were conducted at three sites in northern China. One site is located in Qilian Mountain in Gansu Province, and the other two sites are in Changbaishan Natural Reserve and Dunhua County in Jilin Province. Detailed field experiments are discussed and field data are used to validate the simulated NPP. Remotely sensed images including Landsat Enhanced Thematic Mapper plus (ETM+, 30 m spatial resolution in visible and near infrared bands) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER, 15m spatial resolution in visible and near infrared bands) are used to derive maps of land cover, leaf area index, and biomass. Based on these maps, field measured data, soil texture and daily meteorological data, NPP of these sites are simulated for year 2001 with the boreal ecosystem productivity simulator (BEPS). The NPP in these sites ranges from 80 to 800 gCm(-2)a(-1). The observed NPP agrees well with the modeled NPP. This study suggests that BEPS can be used to estimate NPP in northern China if remotely sensed images of high spatial resolution are available.  相似文献   

5.
Wetlands in the Sanjiang Plain are rich in biodiversity and natural resources in the northeast of China. However, this wetland area has decreased in size and deteriorated in quality owing to expanded agricultural activities since the 1950s. Converting farmlands to wetlands is necessary to improve these conditions. Using Remote Sensing (RS) and Geographic Information Systems (GIS) technologies, we derived farmland productivity data and hydrology data for the Sanjiang Plain. The farmland productivity data were derived from land use and net primary productivity (NPP) data of the MODIS products. We obtained three productivity farmland classes (low, medium, and high) through the NPP anomaly percentage method. We were only concerned with the low-productivity farmland. Hydrology data were modeled with a wetness index, which was derived from Digital Elevation Model (DEM) data. Based on these two data layers, we identified and prioritized sites for the conversion of farmlands to wetlands. The areas with low farmland productivity and medium or high wetness values have potential to support the conversion of farmlands to wetlands. Potential sites were prioritized in terms of patch size and proximity to natural wetlands and water bodies. We obtained three priority classes, among which the high-priority class would be used as the areas for the recent conversion of farmlands to wetlands. The area of this class was 75,888 ha and accounted for 1.3% of the total farmland area.  相似文献   

6.
Decomposition of soil organic carbon (SOC) is a critical component of the global carbon cycle, and accurate estimates of SOC decomposition are important for forest carbon modeling and ultimately for decision making relative to carbon sequestration and mitigation of global climate change. We determined the major pools of SOC in four sites representing major forest types in China: temperate forests at Changbai Mountain (CBM) and Qilian Mountain (QLM), and sub-tropical forests at Yujiang (YJ) and Liping (LP) counties. A 90-day laboratory incubation was conducted to measure CO(2) evolution from forest soils from each site, and data from the incubation study were fitted to a three-pool first-order model that separated mineralizable soil organic carbon into active (C(a)), slow (C(s)) and resistant (C(r)) carbon pools. Results indicate that: (1) the rate of SOC decomposition in the sub-tropical zone was faster than that in the temperature zone, (2) The C(a) pool comprised approximately 1-3% of SOC with an average mean residence time (MRT) of 219 days. The C(s) pool comprised approximately 25-65% with an average MRT of 78 yr. The C(r) pool accounted for approximately 35-80% of SOC, (3) The YJ site in the sub-tropical zone had the greatest C(a) pool and the lowest MRT, while the QLM in the temperature zone had the greatest MRT for both the C(a) and C(s) pools. The results suggest a higher capacity for long-term C sequestration as SOC in temperature forests than in sub-tropical forests.  相似文献   

7.
Spatial scaling between leaf area index maps of different resolutions   总被引:1,自引:0,他引:1  
We developed algorithms for spatial scaling of leaf area index (LAI) using sub-pixel information. The study area is located near Liping County, Guizhou Province, in China. Methods for LAI spatial scaling were investigated on LAI images with 960 m resolution derived in two ways. LAI from distributed calculation (LAID) was derived using Landsat ETM+ data (30 m), and LAI from lumped calculation (LAIL) was obtained from the coarse (960 m) resolution data derived through resampling the ETM+ data. We found that lumped calculations can be considerably biased compared to the distributed (ETM+) case, suggesting that global and regional LAI maps can be biased if surface heterogeneity within the mapping resolution is ignored. Based on these results, we developed algorithms for removing the biases in lumped LAI maps using sub-pixel land cover-type information, and applied these to correct one coarse resolution LAI product which greatly improved its accuracy.  相似文献   

8.
Spatial distributions of the leaf area index (LAI) needed for carbon cycle modeling in Xingguo County, China were estimated based on correlations between the field-measurements and vegetation indices (VIs). After making geometric and atmospheric corrections to two Landsat ETM+ images, one in January 2000 and the other in May 2003, three VIs (SR, NDVI, and RSR) were derived, and their separate correlations with ground LAI measurements were established. The correlation with RSR was the highest among the three VIs. The retrieved LAI values for January 2000 were lower than those for May 2003 because of a small seasonal variation in the coniferous forests (predominantly masson pine) and the decrease in the understorey vegetation during winter.  相似文献   

9.
Semi-structured focus group interviews were employed to examine factors that affect the likelihood that resource managers in southern Africa will use information on vegetation fires provided by two satellite-derived products: an active fire product and a burned area product. The two products are updated regularly and aim to deliver the state-of-the-art in the global monitoring of fires from satellite remote-sensing. Both products are derived from data transmitted by the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors carried onboard NASA's Aqua and Terra satellites. The active fire product can be accessed for free via the internet and on media by users working anywhere in the world; the burned area product will be accessible in a similar manner in 2006. The MODIS fire products provide systematic, near-global coverage and are freely available; as such, they give resource managers new opportunities to obtain or supplement information they need to manage vegetation fires effectively. However, the availability of these products does not mean that resource managers will use them, and many other factors are involved. To understand factors that affect whether southern African resource managers will use the two products, two focus groups were held with members of the Southern African Fire Network (SAFNet) in Malawi, Africa, August 2004. Analysis of the group discussions reveals a number of factors that influence whether they will use the products. The qualitative, in depth nature of the group discussions revealed 12 main factors that influence product use; not least the low international internet bandwidths for African countries outside of South Africa. Analysis of the group discussions also suggests how the uptake of MODIS fire products by resource managers in southern Africa might be enhanced by affecting specific changes to how MODIS products are packaged and delivered.  相似文献   

10.
The integrated terrestrial ecosystem C-budget model (InTEC) developed by Chen and co-workers has been used successfully to predict carbon dynamics of forests in Canada. It was tested here for forest soil organic carbon (SOC) density of China's northern temperate zone and southern subtropical zone. The results show that the simulated SOC density is highly correlated and in broad agreement with observations in Liping and in Changbaishan, representing the southern subtropical zone and the northern temperate zone in China, respectively. SOC density ranged from 2.2 to 11.2 kg/m(2) in Liping and from 3.4 to 14.8 kg/m(2) in Changbaishan. The correlation coefficients (r(2)) are 0.63 (N=16) and 0.76 (N=14) between the simulated and measured data in Liping and Changbaishan, respectively. The SOC densities under different vegetation types in Liping decrease in the order of mixed forest, broadleaf forest, Chinese fir, couch grass, and Chinese redpine, and in Changbaishan in the order of mixed forest, silver fir, larch forest, and birch forest.  相似文献   

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