Mapping Forest Biomass Using Remote Sensing and National Forest Inventory in China

Abstract

Quantifying the spatial pattern of large-scale forest biomass can provide a general picture of the carbon stocks within a region and is of great scientific and political importance. The combination of the advantages of remote sensing data and field survey data can reduce uncertainty as well as demonstrate the spatial distribution of forest biomass. In this study, the seventh national forest inventory statistics (for the period [2004][2005][2006][2007][2008] and the spatially explicit MODIS Land Cover Type product (MCD12C1) were used together to quantitatively estimate the spatially-explicit distribution of forest biomass in China (with a resolution of 0.05°, ~5600 m). Our study demonstrated that the calibrated forest cover proportion maps allow proportionate downscaling of regional forest biomass statistics to forest cover pixels to produce a relatively fine-resolution biomass map. The total stock of forest biomass in China was 11.9 Pg with an average of 76.3 Mg ha −1 during the study period; the high values were located in mountain ranges in northeast, southwest and southeast China and were strongly correlated with forest age and forest density. OPEN ACCESSForests 2014, 5 1268

Quantifying Live Aboveground Biomass and Forest Disturbance of Mountainous Natural and Plantation Forests in Northern Guangdong, China, Based on Multi-Temporal Landsat, PALSAR and Field Plot Data

“…To date, Landsat images have been the most commonly used in AGB studies as multi-temporal medium-resolution data (30 m), leveraging the complete spatial coverage of imagery [14,17,25], while coarse resolution MODIS, AVHRR, SPOT-VGT are difficult to use because of the mismatch between field measurements and satellite observations [26,27]. However, previous studies have commonly used a single image per location [28][29][30] or multiple images but with one in each year in peak growing season to estimate AGB based on empirical models [14,17,31], which would lead to a saturation issue involving underestimation of high AGB values in complex and mature forests.…”

Biomass, Carbon and Nutrient Storage in a 30-Year-Old Chinese Cork Oak (Quercus Variabilis) Forest on the South Slope of the Qinling Mountains, China

“…However, most of these previous studies were mainly conducted on forest biomass C storage at the national and regional scales with different estimation methods and different forest resource data. Moreover, there are few precise studies concerning direct plot investigations for various forest types, C storage estimates that include understory, forest floor, and soil, and the relationship between climatic factors and forest types on regional scales [12][13][14][15][16]. An age-related study on C storage in a black locust forest ecosystem on the Loess Plateau showed that tree C storage increased from 5 to 38 years, but significantly decreased from 38 to 56 years owing to high tree mortality.…”

Measurement of Forest Above-Ground Biomass Using Active and Passive Remote Sensing at Large (Subnational to Global) Scales

“…The accuracy of predictions varied (e.g., r ranging from 0.31 to 0.73) and overall, the model over-and under-predicted in low and high AGB areas, respectively. For continental China, [63] spatially quantified forest AGB at 0.05°resolution using the MODIS land cover type product (MCD12C1) and national forest inventory data (R 2 =0.76). Total forest carbon stocks were estimated at 11.9 Pg, with an average of 76.3 Mg ha −1 .…”