The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-3
https://doi.org/10.5194/isprs-archives-XLII-3-1453-2018
https://doi.org/10.5194/isprs-archives-XLII-3-1453-2018
30 Apr 2018
 | 30 Apr 2018

SPATIO-TEMPORAL CHANGES OF NET PRIMARY PRODUCTIVITY AND ITS RESPONSE TO PHENOLOGY IN NORTHEAST CHINA DURING 2000–2015

Y. Qiu, L. Zhang, and D. Fan

Keywords: Northeast China, NDVI, Net Primary Productivity, Phenology, Spatio-temporal Changes

Abstract. The relationship between net primary productivity (NPP) and phenological changes is of great significance to the study of regional ecosystem processes. In this study, firstly, NPP was estimated with the remote sensing model based on the SPOT-VGT NDVI dataset (2000–2015), meteorological data and the vegetation map in Northeast China. Then, using NDVI time series data which was reconstructed by polynomial fitting, phenology was extracted with the dynamic threshold method. Finally, the relationship between NPP and phenology was analyzed. The results showed that NPP mainly increased in the cropland, grassland, forestland and shrubland; however, vegetation NPP decreased in the ecotone among cropland, grassland and forestland. Correlation analysis suggested that the relationships between NPP and phenological metrics (i.e., the start of the growing season (SOS), the end of the growing season (EOS), the length of the growing season (LOS)) were different due to geographical location. On the whole, there was a positive correlation between NPP and the LOS in the forestland, and negative in the cropland and grassland, indicating that extended LOS can promote the accumulation of forestland NPP. By analyzing the monthly NDVI data during the vigorous growth period, the increase of NPP in the grassland and cropland was mainly due to the better growth from June to August, and shortened LOS did not lead to reduce the NPP. Generally, the response of NPP to phenology in Northeast China were more complex, showing obvious difference of vegetation types and spatial variability, we need to consider topography, community structure and other factors in the further studies.