Laboratory for Remote Sensing and Geoinformatics


Directed by  Dr. Hongjie Xie , Professor


MODIS and AMSR-E Snow Products Validation and Applications


Snow cover pattern has a significant impact on climate processes, surface hydrological cycles and ecological processes (Simpson et al., 1998; Simic et al., 2004). Frequent and long term snow observation and accurate snow cover (SC) mappings and snow water equivalent (SWE) estimates are critical for snowmelt-runoff prediction, operational flood control, water supply planning, and water resource management in snow cover-dominated basins (Gutzler & Rosen, 1992; Brown, 2000; Dressler et al., 2006; Pulliainen2006). Conventional ground snow monitoring is normally based on point measurements. However, sparse point observation networks can not provide accurate data on regional and global scales, due to their low density even no existence especially at inaccessible mountainous or high latitude regions (Derksen et al., 2005). Satellite images are readily available and provide spatio-temporal characteristics needed for snow monitoring and snow cover mapping. Satellite data from visible and infrared spectrum as well as from passive microwaves provide important sources of information on snow cover. Since the middle of the 1960¨s, a number of satellite-derived snow products have been available, with a few available in near-real time through Internet (Bitner et al, 2002).

Space-board passive microwave radiometer, such as SMMR (Scanning Multichannel Microwave Radiometer), SSM/I (Special Sensor Microwave/Imager), and AMSR-E (Advanced Microwave Scanning Radiometer-Earth Observing System), can penetrate clouds to detect microwave energy emitted by snow and ice and provide information on SWE or snow depth and thus estimating runoff (Pulliainen & Hallikainen2001; Wulder et al., 2000). Since the 1970s, SWE retrieval from space-borne passive microwave has been investigated (Pulliainen, 2006; Derksen et al., 2005). Space-borne passive microwave data are well suited to snow cover monitoring because of characteristics such as all weather imaging, a wide swath width with frequent overpass times, and a long available time series (Derksen et al., 2004). But the coarse spatial resolution (25 km of AMSR-E is the best available now) hinders their application in operational hydrological modeling and snow-caused disasters monitoring (kelly et al., 2003; Dressler, et al. 2006; Pulliainen2006). Optical sensors such as AVHRR (Advanced Very High Resolution Radiometer), MODIS (Moderate Resolution Imaging Spectraradiometer), SPOT and Landsat have been well developed to produce snow cover maps with high spatial resolution (Salonmonson & Appel, 2004; Brown et al., 2007; Dozier&Painter, 2004). But due to the inherent limitation, optical sensors cannot see the earth surface when cloud is present. High cloud blockage becomes the biggest problem in applying snow products from optical sensor (Klein & Barnett, 2003; Zhou et al., 2005; Tekeli et al., 2005; Ault et al., 2006; Liang et al. 2008 a, b; Wang et al., 2008a, b; Wang and Xie 2008;).


The goals of the LRSG group for the MODIS and AMSR-E snow products study, supported by DoEd, USGS, and Chinese NSF, are to:

(1) validate the MODIS and AMSR-E snow products,

(2) develop algorithms to general advanced daily and/or multi-day MODIS/Terra and Aqua and AMSR-E/Aqua snow cover and SWE products, with a purpose of reducing cloud contamination and increase spatial resolution of SWE product,

(3) use the new products to generate image-based snow cover onset date, snow melt onset date, snow cover duration date, and snow cover index to better study the snow cover spatial and temporal variations, and their climate connection, and

(4) perform snow-runoff modeling and predict the water availability for regions depending on snow pack.  



Project Title Funding Source
Dynamic monitoring and evaluation between grassland ecological environment and snow/ice and lakes on Tibetan Plateau National Science Foundation of China/Chinese Oversea Collaborative Fund
Remote sensing monitoring and early warning system on snow-caused disasters for the pastoral agriculture area in Tibetan Plateau, China Chinese Department of Education and Lanzhou University
Developing an algorithm for automatically producing multi-day MODIS Terra and Aqua snow cover composite for its better utilities USGS/TexasView Remote Sensing Consortium
MODIS and AMSR-E based monitoring and early warning system on snow-caused disasters for the pastoral agriculture area in Northern Xinjiang Province, China Chinese NSF
Minority Opportunities for Research Experience in Earth Science at the University of Texas at San Antonio (MORE Science at UTSA) U.S. Department of Education




(*first author student, **first author postdoc/visiting professor)


Yu, J., G. Zhang, T. Yao, H. Xie, H. Zhang, C. Ke, and R. Yao, 2015. Developing daily cloud-free snow composite products from MODIS Terra-Aqua and IMS for the Tibetan Plateau. IEEE Trans. on Geoscience and Remote Sensing (accepted).

*Bi, Y., H. Xie, C. Huang, and C. Ke, 2015. Snow cover variations and controlling factors at Upper Heihe River Basin, Northwestern China. Remote Sensing, 7: 6741-6762, doi:10.3390/rs70606741 (link).

Xie, H., T. Liang, X. Wang, and G. Zhang, 2015. Remote sensing mapping and modeling of snow cover parameters and applications (Chapter 10). Remote Sensing Handbook Volume III: Water Resources, Disasters, and Urban Monitoring, Modeling, and Mapping, edited by P.S. Thenkabail, Taylor & Francis Group Press (to appear in Sept 2015).

Wang, W., X. Huang, J. Deng, H. Xie, and T. Liang, 2015. Spatio-Temporal Change of Snow Cover and Its Response to Climate over the Tibetan Plateau Based on an Improved Daily Cloud-Free Snow Cover Product. Remote Sensing, 2015, 7(1):169-194 (link)

Zhang G., H. Xie, T. Yao, H. Li, and S. Duan, 2014. Quantitative water resources assessment of Qinghai Lake basin using snowmelt runoff model (SRM). J. of Hydrology, doi: 10.1016/j.jhydrol.2014.08.022 (link).

Chen, S., Q. Yang, H. Xie, C. Zhou, and P. Lu, 2014. Time series snow cover data of Northeast China (HY2004-HY2013). ACTA Geographica SINICA, vol.69, doi: 10.11821/dlxb2014S015. Data can be downloaded from (link).

Xie, H. C. Huang, and T. Liang, 2014. Special Section Guest Editorial: Progress in Snow Remote Sensing, Journal of Applied Remote Sensing, 8(1), 084601, doi:10.1117/1.JRS.8.084601 (link).

Chen, S., Q. Yang, H. Xie, H. Zhang, P. Lu, and C. Zhou, 2014. Spatio-temporal variations of snow cover in Northeast China based on flexible multiday combinations of MODIS snow cover products. Journal of Applied Remote Sensing, 8(1), 084685, doi:10.1117/1.JRS.8.084685 (link)

Chen, S., T. Liang, H. Xie, Q. Feng, X. Huang, and H. Yu, 2014. Interrelation among climate factors, snow cover, grassland, vegetation, and lake in the Nam Co basin of the Tibetan Plateau. Journal of Applied Remote Sensing, 8(1), 084694, doi:10.1117/1.JRS.8.084694 (link)

Chu, D., H. Xie, P. Wang, J. La, J. Guo, Y. Qiu, and Z. Zheng, 2014. Snow cover variation over the Tibetan Plateau from MODIS and comparison with ground observations. Journal of Applied Remote Sensing, 8(1), 084690, doi:10.1117/1.JRS.8.084690 (link)

Zhang, G., T. Yao, H. Xie, K. Zhang, and F. Zhu, 2014. The state and abundance of lakes across the Tibetan Plateau. Chinese Science Bulletin. doi: 10.1007/s11434-014-0258-x (link)

Wang, X., H. Xie and T. Liang. 2014. Spatiotemporal variation of snow cover from space in Northern Xinjiang. Book Chapter 6 of Water Resources Research in Northwest China, Editor: Yaning Chen. Springer, doi:10.1007/978-94-017-8017-9 (link).

*Mazari, N., A.Tekeli, H.Xie, H. Sharif, and A. Hassan, 2013. Assessment of IMS and MODIS snow cover maps over Colorado Plateau. Journal of Applied Remote Sensing. Vol 7, 073540-1, doi:10.1117/I.JRS.7.07.073540 (link).

Wang, W., T. Liang, X. Huang, Q. Feng, H. Xie, X. Liu, M. Chen, and X. Wang, 2013. Early warning of snow-caused disasters in pastoral areas on Tibetan Plateau. Natural Hazards and Earth System Sciences. Vol 13(6): 1411-1425 (link).

*Zhang, G., H. Xie, T. Yao, T. Liang, and S. Kang. Snow cover dynamics of four lake basins over Tibetan Plateau using time series MODIS data (2001-2010). Water Resources Research. 48, W10529, doi:10.1029/2012WR011971 (link). This paper was among The Most Accessed/Viewed Articles in all WRR papers in 2012.

Yu, H., X. Zhang, T. Liang, H. Xie, X. Wang, Q. Feng, and Q. Chen, 2012. A new approach of dynamic monitoring of 5-day snow cover extent and snow depth based on MODIS and AMSR-E data from Northern Xinjiang region. Hydrological Processes. Vol.26(20):3052-3061, doi:10.1002/hyp.8253 (link)

*Gao, Y., H. Xie, and T. Yao, 2011. Developing snow cover parameters maps from MODIS, AMSR-E and blended snow products. Photogrammetric Engineering and Remote Sensing. Vol 77(4):351-361 (link)

*Gao, Y., H. Xie, T. Yao, and C. Xue, 2010. Integrated assessment on multi-temporal and multi-sensor combination for reducing cloud obscuration of MODIS snow cover products at the Pacific Northwestern USA. Remote Sensing of Environment, Vol 114(8): 1662-1675. doi:10.1016/j.rse.2010.02.017 (link).

*Gao, Y., H. Xie, N. Lu, T. Yao, and T. Liang, 2010. Toward advanced daily cloud-free snow cover and snow water equivalent products from Terra-Aqua MODIS & Aqua AMSR-E measurements. Journal of Hydrology, doi:10.1016/j.jhydrol.2010.01.022 (link).

Xie, H., X. Wang, and T. Liang, 2009. Development and assessment of combined Terra and Aqua snow cover products in Colorado Plateau, USA and northern Xinjiang, China. Journal of Applied Remote Sensing, Vol 3, 033559, doi:10.1117/1.3265996  (link)

*Wang, X. and H. Xie, 2009. New methods for studying the spatiotemporal variation of snow cover based on combination products of MOIDS Terra and Aqua. Journal of Hydrology, Vol 371 (192-200). doi:10.1016/j.jhydrol.2009.03.028 (link).

*Wang, X., H. Xie, T. Liang, X. Huang, 2009. Comparison and Validation of MODIS Standard and New Combination of Terra and Aqua Snow Cover Products in Northern Xinjiang, China. Hydrological Processes, Vol.23 (3): 419-429. doi: 10.1002/hyp.7151 (link)

Liang, T., X. Zhang, H. Xie, C. Wu, Q. Feng, X. Huang, and Q. Chen, 2008. Toward improved daily snow cover mapping with advanced combination of MODIS and AMSR-E measurements. Remote Sensing of Environment, Vol 112(10): 3750-3761, doi:10.1016/j.rse.2008.05.010 (pdf)

*Wang, X., H. Xie, and T. Liang, 2008. Evaluation of MODIS snow cover and cloud mask and its applications in northern Xinjiang, China. Remote Sensing of Environment, doi:10.1016/j.rse.2007.05.016, Vol 112(4): 1497-1513 (pdf).

Liang, T., X. Huang, C. Wu, X. Liu, W. Li, Z. Guo, and J. Ren. (2007). Application of  MODIS data on snow cover monitoring in pastoral area: A case study in the Northern Xinjiang, China. Remote Sensing of Environment, DOI: 10.1016/j.rse.2007.06.001, Vol 112(4): 1514-1526 (link)

Zhou, X., H. Xie, J. Hendrickx, 2005, Statistical evaluation of MODIS snow cover products with constraints from streamflow and  SNOTEL measurement. Remote Sensing of Environment, Vol.94 (2), pp214-231 (pdf).



(Presentations or proceedings)


Xie, H. Y. Gao, T. Yao, T. Liang, 2009. Estimating snow cover onset date, end date, and duration from MODIS, AMSR-E, and blended snow cover products. AGU Fall meeting, San Francisco, CA, December 14-18

Xie, H. and Y. Gao, 2009. Multi-temporal and multi-sensor combined approaches for snow cover mapping. ASPRS/MAPPS Fall Conference, Nov 16-19, San Antonio, TX

Xie, H., Y. Gao, X. Huang, and T. Liang, 2009. MODIS and ICESat-based snow cover and glacier changes across three rivers headstream region of Tibetan Plateau International Workshop on Environmental Change, Glacial and Hydrological Processes, and Related Consequence in the Third Pole Region, August 15-20, 2009, Beijing-Lhasa, China

Xie, H., X. Wang, and T. Liang, 2009. MODIS/Terra-Aqua snow cover products, validation, and applications (invited), SPIE Optics+Photonics: Remote Sensing and Modeling of Ecosystems for Sustainability 2-6 August 2009. San Diego, CA

Xie, H. and Y. Gao, 2008. Snow cover spatial and temporal variability across three rivers headstream region of Tibetan Plateau based on MODIS and AMSR-E data (2000-2008). AGU Fall meeting, San Francisco, CA, December 15-19.

*Gao, Y., H. Xie, N. Lu, T. Liang, C. Xue, 2008. Advanced new daily products of cloud-free snow cover area and snow water equivalent from MODIS/Terra-Aqua & AMSR-E measurements. AGU Fall meeting, San Francisco, CA, December 15-19.

Xie, H., X. Wang, T. Liang, X. Huang, B. Yu, 2008. MODIS Terra and Aqua snow cover products, validations, and applications. 2008 International Workshop on Earth Observation and Remote Sensing Applications. Beijing, China, June 30-July 2.

*Wang, X. and H. Xie, 2008. Mapping spatiotemporal variation of snow cover from combination of MODIS terra and Aqua observations in the Central Tianshan Mountains. 2008 AAG Annual Meeting, Boston, MA (link)

*Wang, X. and H. Xie, 2007. New multi-day snow cover products from combination of Terra and Aqua MODIS daily snow cover data. AGU Fall meeting, San Francisco, CA, December 10-14. (link)

*Yu, B., X. Wang, and H. Xie, 2007. MODIS-based snow cover variability of the Upper Rio Grande Basin. AGU Fall meeting, San Francisco, CA, December 10-14. (link)

*Wang, X. and H. Xie, 2007. An automatic approach to generate multi-day snow cover composite from combination of daily Terra and Aqua MODIS snow cover data. SWAAG/Mid-South ASPRS 2007 annual meeting, College Station, TX, November 1-3.

*Wang, X., H. Xie, and T. Liang, 2007. Assessing spatiotemporal distribution and variability of snow cover and SWE based on MOIDS and AMSR-E, and their applications on water source management in Yili River watershed in Xinjiang, China. ASPRS Annual conference, Tampa, FL, May 7-11.

Xie, H., X. Wang, and T. Liang, 2006. Spatiotemporal distribution and variability of snow cover and snow water equivalent based on MODIS and AMSR-E and their implications on snow-related disasters in Northern Xinjiang Uygur Autonomous region, China. WPGM, Beijing, China, July 24-27. (link)

Xie, H., X. Zhou, and J. Hendrickx, 2004, Evaluation of MODIS snow-cover products with constraints from streamflow and SNOTEL data, AGU Fall Meeting, December 13-17, San Francisco, California.

Zhou, X., H. Xie, and J. Hendrickx, 2004, Statistical evaluation of MODIS daily and 8-day snow products, EOS Snow and Ice Products workshop, November 16-17, Landover, Maryland.


Last Updated: October, 2013