| 基于MODIS数据的北疆积雪黑碳和雪粒径反演及时空变化分析 |
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| 引用本文： | 魏亚瑞,郝晓华,王建,李弘毅,赵宏宇,高扬,邵东航,钟歆玥,李红星.基于MODIS数据的北疆积雪黑碳和雪粒径反演及时空变化分析[J].冰川冻土,2019,41(5):1192-1204. |
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| 作者姓名： | 魏亚瑞 郝晓华 王建 李弘毅 赵宏宇 高扬 邵东航 钟歆玥 李红星 |
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| 作者单位： | 兰州交通大学 测绘与地理信息学院,甘肃 兰州 730070;中国科学院 西北生态环境资源研究院,甘肃 兰州 730000;地理国情监测技术应用国家地方联合工程研究中心,甘肃 兰州 730070;甘肃省地理国情监测工程实验室,甘肃 兰州 730070;中国科学院 西北生态环境资源研究院,甘肃 兰州 730000;中国科学院 西北生态环境资源研究院,甘肃 兰州 730000;江苏省地理信息资源开发与利用协同创新中心,江苏 南京 210023;太原理工大学,山西 太原 030024;电子科技大学,四川 成都 611731 |
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| 基金项目： | 国家自然科学基金项目（41971325）；科技基础资源调查专项（2017FY100502）；受兰州交通大学优秀平台支持（201806）资助 |
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| 摘 要： | 积雪是地球上反射率较高的自然表面，对于中高纬度地区的水文和能量收支平衡发挥着重要作用。表层积雪中的黑碳和雪粒径变化可以显著影响积雪反照率，造成积雪对太阳辐射吸收的变化，进而对区域气候变化和水文循环产生反馈作用。利用遥感技术对季节性积雪表层黑碳和雪粒径进行定量评估，可以获取时空上连续系统的雪表黑碳浓度和雪粒径变化情况，这也是许多气候和水文模型的输入因子。以中国主要季节性积雪区北疆为研究区，基于MODIS（Moderate Resolution Imaging Spectroradiometer）数据的3（0.47 μm）、2（0.86 μm）和5（1.24 μm）波段，采用SGSP（Snow Grain Size and Pollution Amount）算法反演2000-2018年积雪期的雪表黑碳浓度和雪粒径，并结合地面观测数据对于反演结果进行了精度验证，综合分析北疆雪表黑碳浓度和雪粒径时空变化趋势。结果显示，SGSP算法能够同时反演雪表黑碳浓度和雪粒径，并且验证结果表明纯雪像元上反演结果具有较好的精度；2000-2018年北疆雪表年均黑碳浓度和年均雪粒径都随时间变化呈现微弱下降趋势；受地理位置和局部污染源的影响，北疆积雪黑碳浓度空间分布复杂，天山北坡经济带平均黑碳浓度最高，伊犁地区平均黑碳浓度最低，雪粒径的空间分布显示塔城地区平均雪粒径最大，伊犁地区最小。
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| 关 键 词： | MODIS 黑碳 雪粒径 SGSP 时空变化分析 |
| 收稿时间： | 2019-06-22 |
| 修稿时间： | 2019-09-28 |
Retrieval and analysis of spatiotemporal variation of snow black carbon and snow grain size in Northern Xinjiang based on MODIS data |
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| WEI Yarui,HAO Xiaohua,WANG Jian,LI Hongyi,ZHAO Hongyu,GAO Yang,SHAO Donghang,ZHONG Xinyue,LI Hongxing.Retrieval and analysis of spatiotemporal variation of snow black carbon and snow grain size in Northern Xinjiang based on MODIS data[J].Journal of Glaciology and Geocryology,2019,41(5):1192-1204. |
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| Authors: | WEI Yarui HAO Xiaohua WANG Jian LI Hongyi ZHAO Hongyu GAO Yang SHAO Donghang ZHONG Xinyue LI Hongxing |
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| Abstract: | Snow is the natural surface with high reflectivity on the earth, which plays an important role in the hydrological and energy balance in the middle and high latitudes. The change of black carbon and snow grain size in surface snow can significantly affect the albedo of snow, resulting in the change of solar radiation absorption by snow, and then produce feedback on regional climate change and hydrological cycle. Using remote sensing technology to quantitatively evaluate the black carbon and snow grain size of seasonal snow surface can obtain the variation of snow surface black carbon concentration and snow grain size in continuous system in time and space, which is also the input factor of many climate and hydrological models. In this paper, taking the northern Xinjiang of the main seasonal snow accumulation areas in China as the study area, based on the 3 (0.47 μm), 2(0.86 μm) and 5 (1.24 μm) bands of MODIS (Moderate Resolution Imaging Spectroradiometer) data, the snow surface black carbon concentration and snow grain size during the snow accumulation period from 2000 to 2018 are inversed by SGSP (Snow Grain Size and Pollution Amount) algorithm, and the accuracy of the inversion results is verified by the ground observation data. The temporal and spatial variation trend of snow surface black carbon concentration and snow grain size in northern Xinjiang was comprehensively analyzed. The results show that the SGSP algorithm can retrieve the black carbon concentration and snow grain size of snow surface at the same time, and the results show that the inversion results on pure snow pixels have good accuracy, and the average annual black carbon concentration and average annual snow grain size of snow surface in northern Xinjiang show a weak downward trend with the change of time from 2000 to 2018. Under the influence of geographical location and local pollution sources, the spatial distribution of snow black carbon concentration in northern Xinjiang is complex, the average black carbon concentration in the economic belt of the northern slope of Tianshan Mountain is the highest, the average black carbon concentration in Yili area is the lowest, the spatial distribution of snow grain size shows that the average snow grain size in Tacheng is the largest, and that in Yili is the smallest. |
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| Keywords: | MODIS black carbon snow grain size SGSP analysis of spatiotemporal variation |
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