干旱区生态环境知识资源中心(Arid): Uncertainty of Vegetation Green-Up Date Estimated from Vegetation Indices Due to Snowmelt at Northern Middle and High Latitudes

Arid

DOI	10.3390/rs12010190
	Uncertainty of Vegetation Green-Up Date Estimated from Vegetation Indices Due to Snowmelt at Northern Middle and High Latitudes
	Cao, Ruyin 1; Feng, Yan 1; Liu, Xilong 1; Shen, Miaogen 2; Zhou, Ji 1
通讯作者	Cao, Ruyin
来源期刊	REMOTE SENSING
EISSN	2072-4292
出版年	2020
卷号	12 期号:1
英文摘要	Vegetation green-up date (GUD), an important phenological characteristic, is usually estimated from time-series of satellite-based normalized difference vegetation index (NDVI) data at regional and global scales. However, GUD estimates in seasonally snow-covered areas suffer from the effect of spring snowmelt on the NDVI signal, hampering our realistic understanding of phenological responses to climate change. Recently, two snow-free vegetation indices were developed for GUD detection: the normalized difference phenology index (NDPI) and normalized difference greenness index (NDGI). Both were found to improve GUD detection in the presence of spring snowmelt. However, these indices were tested at several field phenological camera sites and carbon flux sites, and a detailed evaluation on their performances at the large spatial scale is still lacking, which limits their applications globally. In this study, we employed NDVI, NDPI, and NDGI to estimate GUD at northern middle and high latitudes (north of 40 degrees N) and quantified the snowmelt-induced uncertainty of GUD estimations from the three vegetation indices (VIs) by considering the changes in VI values caused by snowmelt. Results showed that compared with NDVI, both NDPI and NDGI improve the accuracy of GUD estimation with smaller GUD uncertainty in the areas below 55 degrees N, but at higher latitudes (55 degrees N-70 degrees N), all three indices exhibit substantially larger GUD uncertainty. Furthermore, selecting which vegetation index to use for GUD estimation depends on vegetation types. All three indices performed much better for deciduous forests, and NDPI performed especially well (5.1 days for GUD uncertainty). In the arid and semi-arid grasslands, GUD estimations from NDGI are more reliable (i.e., smaller uncertainty) than NDP-based GUD (e.g., GUD uncertainty values for NDGI vs. NDPI are 4.3 d vs. 7.2 d in Mongolia grassland and 6.7 d vs. 9.8 d in Central Asia grassland), whereas in American prairie, NDPI performs slightly better than NDGI (GUD uncertainty for NDPI vs. NDGI is 3.8 d vs. 4.7 d). In central and western Europe, reliable GUD estimations from NDPI and NDGI were acquired only in those years without snowfall before green-up. This study provides important insights into the application of, and uncertainty in, snow-free vegetation indices for GUD estimation at large spatial scales, particularly in areas with seasonal snow cover.
英文关键词	land-surface phenology NDPI NDGI Snow-free vegetation index vegetation spring phenology
类型	Article
语种	英语
国家	Peoples R China
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000515391700190
WOS关键词	LAND-SURFACE PHENOLOGY ; SPRING PHENOLOGY ; PLANT PHENOLOGY ; TIBETAN PLATEAU ; BOREAL REGIONS ; MODIS ; COVER ; RESPONSES ; TEMPERATURE ; AVHRR
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
来源机构	中国科学院青藏高原研究所
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/315407
作者单位	1.Univ Elect Sci & Technol China, Sch Resources & Environm, 2006 Xiyuan Ave, Chengdu 611731, Peoples R China; 2.Chinese Acad Sci, Key Lab Alpine Ecol, Inst Tibetan Plateau Res, CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Cao, Ruyin,Feng, Yan,Liu, Xilong,et al. Uncertainty of Vegetation Green-Up Date Estimated from Vegetation Indices Due to Snowmelt at Northern Middle and High Latitudes[J]. 中国科学院青藏高原研究所,2020,12(1).
APA	Cao, Ruyin,Feng, Yan,Liu, Xilong,Shen, Miaogen,&Zhou, Ji.(2020).Uncertainty of Vegetation Green-Up Date Estimated from Vegetation Indices Due to Snowmelt at Northern Middle and High Latitudes.REMOTE SENSING,12(1).
MLA	Cao, Ruyin,et al."Uncertainty of Vegetation Green-Up Date Estimated from Vegetation Indices Due to Snowmelt at Northern Middle and High Latitudes".REMOTE SENSING 12.1(2020).