Validation of the ESA CCI soil moisture product in China

环境科学 草原 含水量 产品(数学) 搭配(遥感) 水文学(农业) 地理 统计 数学 土壤科学 遥感 生态学 工程类 岩土工程 几何学 生物
作者
Ru An,Ling Zhang,Zhe Wang,Jonathan Arthur Quaye‐Ballard,You Jiajun,Xiaoji Shen,Wei Gao,Lijun Huang,Yinghui Zhao,Ke Zun-You
出处
期刊:International journal of applied earth observation and geoinformation [Elsevier BV]
卷期号:48: 28-36 被引量:83
标识
DOI:10.1016/j.jag.2015.09.009
摘要

The quality of a newly merged soil moisture product (ECV_SM v0.1) from active and passive microwave sensors has attracted widespread international attention. The performance evaluation of this product will benefit studies on climate, meteorology, agriculture, hydrology, ecology and the environment. In this study, meteorological station data and the Noah soil moisture product were used to validate the ECV_SM product in China. First, some conventional statistical measures, such as correlation coefficients, bias, root mean square difference (RMSD) and mean relative error (MRE), were computed to describe the level of agreement between the meteorological station data and ECV_SM values. The accuracy was moderately high (the correlation was significant at the 0.05 level), although the two datasets differed slightly for various types of land cover. Compared with cropland and urban and built-up areas, the performance of ECV_SM was best in grassland regions. Second, the triple collocation technique was used to assess the random error in the meteorological station data, Noah soil moisture product and ECV_SM product. The mean errors in these three datasets were 0.108, 0.079 and 0.075 m3 m−3, respectively, on July 8, 2010 and 0.099, 0.061 and 0.059 m3 m−3, respectively, on October 8, 2010. Only two days of data were used for the triple collocation test as a representative, but this cannot precisely indicate that the test results on any other day correspond with the test results on these two days. Additionally, a trend analysis of ECV_SM during 2003–2010 was carried out using the Mann–Kendall trend test.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
科研骏马完成签到 ,获得积分10
1秒前
yqhide完成签到,获得积分10
1秒前
筑梦之鱼完成签到,获得积分10
2秒前
十七完成签到 ,获得积分10
2秒前
贪玩的丹蝶完成签到,获得积分20
3秒前
3秒前
科研通AI6.4应助小太阳采纳,获得10
3秒前
lilian完成签到,获得积分10
4秒前
可靠老头给可靠老头的求助进行了留言
4秒前
lbma完成签到,获得积分10
6秒前
kk完成签到,获得积分10
7秒前
Cope完成签到 ,获得积分10
7秒前
小桓栀禾完成签到,获得积分10
9秒前
11秒前
美鹅完成签到 ,获得积分10
12秒前
614521完成签到,获得积分10
12秒前
胖墩儿驾到完成签到,获得积分10
12秒前
濮阳盼曼完成签到,获得积分10
12秒前
赵田完成签到 ,获得积分10
12秒前
肖之贤完成签到,获得积分10
12秒前
waswas完成签到,获得积分10
13秒前
13秒前
大猫不吃鱼完成签到,获得积分10
14秒前
欢喜小蚂蚁完成签到 ,获得积分10
15秒前
纯真惜芹完成签到,获得积分20
15秒前
chaoschen发布了新的文献求助30
16秒前
研友_nEjYyZ发布了新的文献求助30
16秒前
WnxIe发布了新的文献求助10
17秒前
黎藿完成签到,获得积分10
18秒前
程晓研完成签到 ,获得积分10
19秒前
立冬完成签到,获得积分10
20秒前
直率小霜完成签到,获得积分10
21秒前
22秒前
彪行天下完成签到,获得积分10
23秒前
YY完成签到 ,获得积分10
23秒前
偷看星星完成签到 ,获得积分10
24秒前
兰瓜瓜完成签到,获得积分10
24秒前
CharlieYue完成签到,获得积分10
26秒前
28秒前
29秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Römisch-Germanische Forschungen 1000
Social Psychology (第二版) 700
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7613062
求助须知:如何正确求助?哪些是违规求助? 9188409
关于积分的说明 19684085
捐赠科研通 7186276
什么是DOI,文献DOI怎么找? 3270770
关于科研通互助平台的介绍 2434319
邀请新用户注册赠送积分活动 2265669