Estimating Net Primary Productivity Using Chinese GF-1 Remote Sensing Data for Regional Grassland

doi:10.12068/j.issn.1005-3026.2016.10.018

Journal of Northeastern University Natural Science ›› 2016, Vol. 37 ›› Issue (10): 1450-1454.DOI: 10.12068/j.issn.1005-3026.2016.10.018

• Resources & Civil Engineering • Previous Articles Next Articles

Estimating Net Primary Productivity Using Chinese GF-1 Remote Sensing Data for Regional Grassland

BAO Ni-sha¹， WU Li-xin²， YE Bao-ying³， ZHAO Fei-fei¹

1. School of Resources & Civil Engineering， Northeastern University， Shenyang 110819， China； 2. School of Environment Science and Spatial Informatics， China University of Mining and Technology， Xuzhou 221116， China； 3. Institute of Geological Survey， China University of Geosciences

Received:2015-06-20 Revised:2015-06-20 Online:2016-10-15 Published:2016-10-14
Contact: BAO Ni-sha
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Abstract

Abstract: The ability of net primary production (NPP) was estimated by using the Chinese GF-1 remote sensing data. The specified land surface parameters such as vegetation indices， light efficiency and water indices were modified to establish Carnegie-Ames-Stanford approach (CASA) model for NPP modeling by using the Chinese GF-1 satellite data. The field observation data was used to valid the accuracy of simulated NPP from CASA model. There is a good correlation between the simulated NPP and field observed NPP with correlation coefficient of 0.94， and RMSE is 20.59gC/(m²·a). Furthermore， the NPP results were compared with similar study over semi-arid grassland zone. The results showed that the CASA model performs well at regional scale grassland monitoring. The Chinese satellite data has potential to be further applied on the semi-arid grassland， particular on coal mine environment monitoring over this region.

Key words: Chinese GF-1 satellite data, NPP (net primary productivity), semi-arid grassland, coal mine area； CASA model

CLC Number:

BAO Ni-sha， WU Li-xin， YE Bao-ying， ZHAO Fei-fei. Estimating Net Primary Productivity Using Chinese GF-1 Remote Sensing Data for Regional Grassland[J]. Journal of Northeastern University Natural Science, 2016, 37(10): 1450-1454.

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Estimating Net Primary Productivity Using Chinese GF-1 Remote Sensing Data for Regional Grassland

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