A robust and unified land surface phenology algorithm for diverse biomes and growth cycles in China by using harmonized Landsat and Sentinel-2 imagery
文献类型：期刊论文
| 作者 | Yang, Jilin; Dong, Jinwei; Liu, Luo; Zhao, Miaomiao; Zhang, Xiaoyang; Li, Xuecao; Dai, Junhu; Wang, Huanjiong; Wu, Chaoyang; You, Nanshan |
| 刊名 | ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
 |
| 出版日期 | 2023-08-01 |
| 卷号 | 202页码:610-636 |
| ISSN号 | 0924-2716 |
| 关键词 | Land surface phenology Vegetation indices Harmonized Landsat and Sentinel-2 30 m phenology product China |
| DOI | 10.1016/j.isprsjprs.2023.07.017 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | Land surface phenology (LSP) is beneficial to understand ecosystem response to climate change, vegetation and crop type discrimination, and ecological modeling. However, the existing efforts based on coarse resolution data (& GE;500 m) cannot perform well in regions with higher spatial heterogeneity and multi-cropping system, such as China. Given that the majority of 10 m/30 m-based phenological research has focused on North America and Europe, developing spatiotemporally explicit LSP data in China is imperative. More importantly, the existing 30 m LSP products are mainly suitable for vegetation types with a single vegetation cycle, but cannot work well for biomes with complex seasonality (e.g., multiple growth cycles). Here we first harmonized three vegetation indices, i.e., the normalized difference vegetation index (NDVI), two-band enhanced vegetation index (EVI2), and land surface water index (LSWI) from Landsat-7/8 and Sentinel-2 imagery on the Google Earth Engine (GEE) platform. We then developed a new 30 m LSP algorithm that unified different phenological cycle-seeking processes per vegetation type and improved the existing algorithm. Furthermore, we used the algorithm to estimate the LSP product (LSP30CHN) for 2016-2019 across China, suitable for all vegetation types. The validation results showed a reasonably high accuracy (R2 > 0.6, RMSE < 15 days, mostly) of the LSP30CHN data against multisources in-situ observational (e.g., PhenoCam) and satellite-retrieved vegetation phenology data. Moreover, LSP30CHN data showed a consistent pattern but finer spatial details with the 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) phenology product (MCD12Q2) at the homogenous area. We also found that phenological differences between LSP30CHN and MCD12Q2 increased with surface fragmentation, suggesting the potential of LSP30CHN to delineate phenological information on more fragmented landscapes. In contrast, the 500 m LSP data cannot provide such details in the regions with mixed cropping structures (e.g., corn, rice, and soybean) and multiple cropping index (e.g., single- and double-cropping systems). This study offers high accuracy of the LSP map for China, valuable for finer phenology-based services such as field-level crop management and agricultural phenology monitoring. It opens up new insights about exploring large-scale refined agricultural management and ecological assessment for other regions with complicated, fragmented landscapes and vegetation seasonality. |
| WOS关键词 | NORTH-AMERICAN TEMPERATE ; PADDY RICE AGRICULTURE ; TIME-SERIES ; INTERANNUAL VARIATION ; VEGETATION PHENOLOGY ; SPRING PHENOLOGY ; CLIMATE-CHANGE ; DATASET ; CLOUD ; VIIRS |
| WOS研究方向 | Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| 出版者 | ELSEVIER |
| WOS记录号 | WOS:001046716800001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/194527]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 作者单位 | 1.Research Institute of Forest Resources Information Technique, CAF 2.Institute of Geographic Sciences & Natural Resources Research, CAS 3.China Agricultural University 4.University of Oklahoma System 5.China University of Geosciences 6.University of Oklahoma - Norman 7.Chinese Academy of Meteorological Sciences (CAMS) 8.South Dakota State University 9.South China Agricultural University 10.Chinese Academy of Sciences |
| 推荐引用方式 GB/T 7714 | Yang, Jilin,Dong, Jinwei,Liu, Luo,et al. A robust and unified land surface phenology algorithm for diverse biomes and growth cycles in China by using harmonized Landsat and Sentinel-2 imagery[J]. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,2023,202:610-636. |
| APA | Yang, Jilin.,Dong, Jinwei.,Liu, Luo.,Zhao, Miaomiao.,Zhang, Xiaoyang.,...&Ge, Quansheng.(2023).A robust and unified land surface phenology algorithm for diverse biomes and growth cycles in China by using harmonized Landsat and Sentinel-2 imagery.ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING,202,610-636. |
| MLA | Yang, Jilin,et al."A robust and unified land surface phenology algorithm for diverse biomes and growth cycles in China by using harmonized Landsat and Sentinel-2 imagery".ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 202(2023):610-636. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。