Tuesday, August 5, 2008 - 2:30 PM

COS 35-4: Estimating urban forest NPP based on forest inventory data and remote sensing

Min Zhao1, Wenpeng Lin2, and Jun Gao2. (1) 1 Shanghai Normal University 2 World Forestry Center, (2) Shanghai Normal University

Background/Question/Methods
The urban forest is one of the main components of terrestrial ecosystems and it plays an important role in terrestrial ecosystem carbon cycles. Under the background of global change, studying the urban forest carbon cycle is very imporant, yet there are few studies in this field, especially in Chinese urban forests. With 20 million residents, Shanghai is one of the largest cities in the world. This study estimated forest field inventory and remote sensing technology. Second, SPOT5 satellite imagery (after geometric correction and radiometric calibration) was used to adjust the soil vegetation index in order to minimize interference with soil, vegetation, and background factors. A regression model was created between leaf area index and SPOT5 modified soil adjusted vegetation index. Finally, using the NPP regression model and leaf area index estimation model, NPP was estimated at a regional scale for Shanghai.

Results/Conclusions

The results showed that Shanghai urban forest NPP was 3.24×105 t/ha/yr, and this was similar to the result of Shanghai urban forest NPP (2.92×105 t /yr) that was calculated using modified volume-derived method that was based on forest inventory data of China (FID). The range of NPP was 1.92~32.68 t/ha/yr. This research will not only provide a good method and theoretical base for rapid quantitative assessment of urban forest carbon storage, but it also provides a technology demonstration of the development of SPOT5 quantitative applications and the function of urban forest in the terrestrial carbon cycle