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Remote Sensing for Land & Resources    2018, Vol. 30 Issue (2) : 214-222     DOI: 10.6046/gtzyyg.2018.02.29
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Generation of daily cloudless snow cover product in the past 15 years in Xinjiang and accuracy validation
Xiaogang HOU1(), Zhaojun ZHENG2(), Shuai LI3, Xuehua CHEN4, Yu CUI3
1. Institute of Network Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
2. National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
3. Insitute of Desert Meteorology, China Meteorological Administration, Urumqi 830002, China
4. Xinjiang Academy of Surveying and Mapping, Urumqi 830002, China
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Abstract  

MODIS snow product data constitute one of the most common data in the real-time monitoring and the research on snow cover; nevertheless, the cloud is the biggest factor affecting the application of MODIS snow cover products (MOD10A1 and MYD10A1) to real-time monitoring and researching daily snow cover in Xinjiang region. By introducing such data as the interactive multi-sensor snow ice mapping system (IMS) data and the meteorological station observation data and combining the existent cloud removal methods based on temporal filter method, spatial filter method and multi-sensor data fusion method, the authors established a new cloud removal method based on multi-source remote sensing data, with which the 15-year-long daily snow cover product in clear air of the study area from 2002 to 2016 was generated. In addition, the accuracy of the cloud removed product was evaluated with field experiment data. The results show that the overall monitoring accuracy of the new product after cloud removal reaches 90.61% in the study area, which is close to the overall monitoring accuracy (93.3%) of the MODIS clear air snow cover product before cloud removal in the study area.
Keywords daily cloudless snow product      multi-source remote sensing data      cloud removal method      Xinjiang     
:  TP79  
Corresponding Authors: Zhaojun ZHENG     E-mail: hxg510487306@qq.com;zhengzj@cma.gov.cn
Issue Date: 30 May 2018
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Xiaogang HOU
Zhaojun ZHENG
Shuai LI
Xuehua CHEN
Yu CUI
Cite this article:   
Xiaogang HOU,Zhaojun ZHENG,Shuai LI, et al. Generation of daily cloudless snow cover product in the past 15 years in Xinjiang and accuracy validation[J]. Remote Sensing for Land & Resources, 2018, 30(2): 214-222.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2018.02.29     OR     https://www.gtzyyg.com/EN/Y2018/V30/I2/214
MODIS标准产品编码及意义 重新编码及意义
编码 意义 编码 意义
0 数据丢失
1 无法判识
11 夜间 50 云
254 探测器饱和
50 云
255 填充数据 255 填充数据
37 内陆水体或湖泊
37
湖与湖冰
100 湖冰
39 海洋 39 海洋
25 无雪覆盖陆地 25 无雪覆盖陆地
200 积雪 200 积雪
Tab.1  MODIS standardized snow cover product classes and reclassification rules
Fig.1  Study area and position of meteorological stations
Fig.2  Flow chart of cloud-removing algorithm
类型 第d-1日 第d日 第d+1日
雪 无雪 云 云 雪 无雪 云
1 √ 判识为有雪 √
2 √ — √
3 √ — √
4 √ 判识为有雪 √
5 √ 判识为无雪 √
6 √ — √
7 √ 判识为有雪 √
8 √ — √
9 √ — √
Tab.2  Cloud removal judgement by combination of before and after day
Fig.3  Pixel types in filtering window
Fig.4  Cloud removal process images of MODIS snow cover product of study area
Fig.5  Daily average cloud cover proportion by different cloud removal methods during recent 15 years in study area
Fig.6  Space distribution of snow cover in clear sky in study area
Fig.7  Daily average snow cover proportion by different cloud removal methods from 2002 to 2016 in study area
类别 遥感—积雪 遥感—陆地 合计
站点—积雪 52 767
(占比91.5%)		 4 902
(占比8.5%)		 57 669
站点—陆地 11 303
(占比4.9%)		 219 376
(占比95.1%)		 230 679
合计 64 070 224 278 288 348
Tab.3  Error matrix of MODIS data before cloud removal and in-situ observation data at meteorological station
类别 遥感—积雪 遥感—陆地 合计
站点—积雪 41 436
(占比88.12%)		 5 586
(占比11.88%)		 47 022
站点—陆地 12 959
(占比6.89%)		 175 129
(占比93.11%)		 188 089
合计 54 395 180 716 235 111
Tab.4  Error matrix of MODIS data after cloud removal and in-situ observation data at meteorological station
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