MODIS-derived atmospheric water vapor (AWV) content and its correlation to land use and land cover in Northeast China

Atmospheric water vapor (AWV) content is closely related to precipitation that in turn has effects on the productivity of agricultural, forestry and range land. MODIS images have been used for AWV retrieval, and the method uses either two (0.841-0.876 μm and 0.915-0.965 μm) or three (0.841-0.876, 0.915-0.965 and 1.230-0-1.250 μm) MODIS channel ratios. We applied both methods to the MODIS data over Northeast China acquired from June to August, 2008 to retrieve AWV content, and the results were validated on ground observed data from 10 radio sonde stations characterized by various land cover. The bulk results indicate that the two-channel ratio outperformed the three-channel ratio based on the coefficient of determination R2 = 0.81 vs. 0.78. The validation results for individual land cover types also support this observation with R2 = 0.92 vs. 0.84 for woodland, 0.82 vs. 0.79 for cropland, 0.90 vs. 0.86 for grassland and 0.673 vs. 0.669 for urban areas. The spatial distribution of AWV derived using the two-channel ratio method was correlated to land-use classification data, and a high correlation was evident when other conditions were similar. With the exception of dry cropland, the amount of average water vapor content over different land use types demonstrates a consistent order: water-body > paddy-field > woodland > grassland > barren for the analyzed multi-temporal MODIS data. This order partially matches the evapotranspiration pattern of underlying surface, and future work is required for analyzing the association of the landscape pattern with AWV in the region.

[1]  Robert Frouin,et al.  Determination from Space of Atmospheric Total Water Vapor Amounts by Differential Absorption near 940 nm: Theory and Airborne Verification , 1990 .

[2]  F. Giorgi,et al.  Land use effects on climate in China as simulated by a regional climate model , 2007 .

[3]  C. Justice,et al.  Atmospheric correction of MODIS data in the visible to middle infrared: first results , 2002 .

[4]  Mei Zhao,et al.  The relative impact of regional scale land cover change and increasing CO2 over China , 2005 .

[5]  V. Salomonson,et al.  MODIS: advanced facility instrument for studies of the Earth as a system , 1989 .

[6]  Jin Chen,et al.  A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter , 2004 .

[7]  A. Goetz,et al.  Column atmospheric water vapor and vegetation liquid water retrievals from Airborne Imaging Spectrometer data , 1990 .

[8]  Helin Wei,et al.  Study of the sensitivity of a regional model in response to land cover change over northern China , 1998 .

[9]  Jan-Peter Muller,et al.  Comparison of precipitable water vapor derived from radiosonde, GPS, and Moderate‐Resolution Imaging Spectroradiometer measurements , 2003 .

[10]  W. Paul Menzel,et al.  Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS) , 1992, IEEE Trans. Geosci. Remote. Sens..

[11]  Yoram J. Kaufman,et al.  The MODIS Near-IR Water Vapor Algorithm , 1998 .

[12]  David P. Roy,et al.  MODIS land data storage, gridding, and compositing methodology: Level 2 grid , 1998, IEEE Trans. Geosci. Remote. Sens..

[13]  Changsheng Li,et al.  Mapping paddy rice agriculture in South and Southeast Asia using multi-temporal MODIS images , 2006 .

[14]  J. Susskind,et al.  Remote Sensing of Weather and Climate Parameters From , 1984 .

[15]  S. Adler-Golden,et al.  Atmospheric Correction for Short-wave Spectral Imagery Based on MODTRAN 4 , 2000 .

[16]  E. R. Stoner,et al.  Physiochemical, site, and bidirectional reflectance factor characteristics of uniformly moist soils. [Brazil, Spain and the United States of America] , 1980 .

[17]  Robert E. Wolfe,et al.  Key characteristics of MODIS data products , 1998, IEEE Trans. Geosci. Remote. Sens..

[18]  J. Townshend,et al.  Global land cover classi(cid:142) cation at 1 km spatial resolution using a classi(cid:142) cation tree approach , 2004 .

[19]  Jacinto F. Fabiosa,et al.  Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from Land-Use Change , 2008, Science.

[20]  Yoram J. Kaufman,et al.  Remote sensing of water vapor in the near IR from EOS/MODIS , 1992, IEEE Trans. Geosci. Remote. Sens..

[21]  E. Vermote,et al.  Absolute calibration of AVHRR visible and near-infrared channels using ocean and cloud views , 1995 .

[22]  Zhao-Liang Li,et al.  A new approach for retrieving precipitable water from ATSR2 split-window channel data over land area , 2003 .

[23]  H. Mooney,et al.  Modeling the Exchanges of Energy, Water, and Carbon Between Continents and the Atmosphere , 1997, Science.

[24]  F. X. Kneizys,et al.  Users Guide to LOWTRAN 7 , 1988 .

[25]  P. Bosch,et al.  Climate change 2007 - mitigation of climate change , 2007 .