Abstract
Net Primary Productivity (NPP) is one of the important biophysical variables of vegetation activity, and it plays an important role in studying global carbon cycle, carbon source and sink of ecosystem, and spatial and temporal distribution of CO2. Remote sensing can provide broad view quickly, timely and multi-temporally, which makes it an attractive and powerful tool for studying ecosystem primary productivity, at scales ranging from local to global. This paper aims to use Moderate Resolution Imaging Spectroradiometer (MODIS) data to estimate and analyze spatial and temporal distribution of NPP of the northern Hebei Province in 2001 based on Carnegie-Ames-Stanford Approach (CASA) model. The spatial distribution of Absorbed Photosynthetically Active Radiation (APAR) of vegetation and light use efficiency in three geographical subregions, that is, Bashang Plateau Region, Basin Region in the northwestern Hebei Province and Yanshan Mountainous Region in the Northern Hebei Province were analyzed, and total NPP spatial distribution of the study area in 2001 was discussed. Based on 16-day MODIS Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) product, 16-day composite NPP dynamics were calculated using CASA model; the seasonal dynamics of vegetation NPP in three subregions were also analyzed. Result reveals that the total NPP of the study area in 2001 was 25.1877 × 106gC/(m2·a), and NPP in 2001 ranged from 2 to 608gC/(m2·a), with an average of 337.516gC/(m2·a). NPP of the study area in 2001 accumulated mainly from May to September (DOY 129–272), high NPP values appeared from June to August (DOY 177–204), and the maximum NPP appeared from late July to mid-August (DOY 209–224).
Similar content being viewed by others
References
Ahl D E, Gower S T, Mackay D S et al., 2004. Heterogeneity of light use efficiency in a northern Wisconsin forest: implications for modeling net primary production with remote sensing. Remote Sensing of Environment, 93: 168–178. DOI: 10.1016/j.rse.2004.07.003.
Allen R G, Pereira L S, Raes D et al., 1998. Crop evapotranspiration-Guidelines for computing crop water requirements. FAO irrigation and drainage paper 56. Rome: Food and Agriculture Organization of the United Nations, 13–25, 38–56.
Barton C V M, North P R J, 2001. Remote sensing of canopy light use efficiency using the photochemical reflectance index model and sensitivity analysis. Remote Sensing of Environment, 78(3): 264–273.
Field C B, Randerson J T, Malmstrom C M, 1995. Global net primary production: combining ecology and remote sensing. Remote Sensing of Environment, 51(1): 74–88.
Li Guicai, 2004. Estimation of Chinese terrestrial net primary production using LUE model and MODIS data. Ph.D. Dissertation. Bei**g: Institute of Remote Sensing Applications, Chinese Academy of Sciences. (in Chinese)
Lin Zhonghui, Mo **ngguo, Li Hongxuan et al., 2002. Comparison of three spatial interpolation methods for climate variables in China. Acta Geographtca Sinica, 57(1): 47–56. (in Chinese)
Monteith J L, 1972. Solar radiation and productivity in tropical ecosystems. Journal of Applied Ecology, 9: 744–766.
Monteith J L, 1977. Climate and the efficiency of crop production in Britain. Philosoph. Royal Soci., B28: 277–294.
Patenaude G, Milne R, Dawson T P, 2005. Synthesis of remote sensing approaches for forest carbon estimation: reporting to the Kyoto Protocol. Environmental Science & Policy, 8(2): 161–178. DOI: 10.1016/j.envsci.2004.12.010.
Potter C S, Randerson J T, Field C B et al., 1993. Terrestrial ecosystem production: a process model based on global satellite and surface data. Global Biogeochemical Cycles, 7(4): 811–841.
Rahman A F, Gamon J A, Fuentes D A et al., 2001. Modeling spatially distributed ecosystem flux of boreal forest using hyperspectral indices from AVIRIS imagery. Journal of Geophysical Research, 16(D24): 33579–33591.
Rahman A F, Cordova V D, Gamon J A et al., 2004. Potential of MODIS ocean bands for estimating CO2 flux from terrestrial vegetation: A novel approach. Geophysical Research Letters, 31(10): 1–4. DOI: 10.1029/2004GL019778.
Running S W, Nemani R-R, Heinsch F A et al., 2004. A continuous satellite-derived measure of global terrestrial primary production. Bioscience, 54: 547–560.
Running S W, Thornton P E, Nemani R, 2000. Global terrestrial gross and net primary productivity from the earth observing system. In: Sala et al. (eds.). Methods in Ecosystem Science. New York: Springer-Verlag, 44–57.
Zhao Dengzhong, Zhang Wanchang, Liu Sanchao, 2004. Interpolation of meteorological data based on DEM using PRISM Model. Scientia Geographica Sinica, 24(2): 205–211. (in Chinese)
Author information
Authors and Affiliations
Additional information
Foundation item: Under the auspices of the National Natural Science Foundation of China (No. 40571117), the Knowledge Innovation Program of Chinese Academy of Sciences (No. KZCX3-SW-338), Research foundation of the State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing Applications, Chinese Academy of Sciences (KQ060006)
Biography: YUAN **guo (1972–), female, a native of Gucheng in Hebei Province, associate professor, Ph.D. candidate, specialized in global change remote sensing.
Rights and permissions
About this article
Cite this article
Yuan, J., Niu, Z. & Wang, C. Vegetation NPP distribution based on MODIS data and CASA model—A case study of northern Hebei Province. Chin. Geograph.Sc. 16, 334–341 (2006). https://doi.org/10.1007/s11769-006-0334-5
Received:
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/s11769-006-0334-5