| Title | Assessing plant senescence reflectance index-retrieved vegetation phenology and its spatiotemporal response to climate change in the Inner Mongolian Grassland |
| Authors | Ren, Shilong Chen, Xiaoqiu An, Shuai |
| Affiliation | Peking Univ, Coll Urban & Environm Sci, Lab Earth Surface Proc, Minist Educ, 5 Yiheyuan Rd,Yifuerlou Room 3352, Beijing 100871, Peoples R China. |
| Keywords | Grassland phenology Remote sensing Plant senescence reflectance index Temperature and precipitation Spatiotemporal response Spatiotemporal pattern GROWING-SEASON SATELLITE DATA SPRING PHENOLOGY AIR-TEMPERATURE NORTHERN CHINA TREE PHENOLOGY EASTERN CHINA TIME-SERIES MODIS DATA REGION |
| Issue Date | 2017 |
| Publisher | INTERNATIONAL JOURNAL OF BIOMETEOROLOGY |
| Citation | INTERNATIONAL JOURNAL OF BIOMETEOROLOGY.2017,61(4),601-612. |
| Abstract | Plant phenology is a key link for controlling interactions between climate change and biogeochemical cycles. Satellite-derived normalized difference vegetation index (NDVI) has been extensively used to detect plant phenology at regional scales. Here, we introduced a new vegetation index, plant senescence reflectance index (PSRI), and determined PSRI-derived start (SOS) and end (EOS) dates of the growing season using Moderate Resolution Imaging Spectroradiometer data from 2000 to 2011 in the Inner Mongolian Grassland. Then, we validated the reliability of PSRI-derived SOS and EOS dates using NDVI-derived SOS and EOS dates. Moreover, we conducted temporal and spatial correlation analyses between PSRI-derived SOS/EOS date and climatic factors and revealed spatiotemporal patterns of PSRI-derived SOS and EOS dates across the entire research region at pixel scales. Results show that PSRI has similar performance with NDVI in extracting SOS and EOS dates in the Inner Mongolian Grassland. Precipitation regime is the key climate driver of interannual variation of grassland phenology, while temperature and precipitation regimes are the crucial controlling factors of spatial differentiation of grassland phenology. Thus, PSRI-derived vegetation phenology can effectively reflect land surface vegetation dynamics and its response to climate change. Moreover, a significant linear trend of PSRI-derived SOS and EOS dates was detected only at small portions of pixels, which is consistent with that of greenup and brownoff dates of herbaceous plant species in the Inner Mongolian Grassland. Overall, PSRI is a useful and robust metric in addition to NDVI for monitoring land surface grassland phenology. |
| URI | http://hdl.handle.net/20.500.11897/493071 |
| ISSN | 0020-7128 |
| DOI | 10.1007/s00484-016-1236-6 |
| Indexed | SCI(E) PubMed |
| Appears in Collections: | 城市与环境学院 地表过程分析与模拟教育部重点实验室 |
