Case study of soil moisture effect on land surface temperature retrieval

Land surface temperature (LST) is an important element of the climate system. Remote sensing methods for estimating LST have been developed in the past and several of them have been implemented at large-scales. Geostationary satellites are of particular interest because they depict the diurnal cycle. Soil moisture has a strong effect on the magnitude of surface temperature via its influence on emissivity; yet, information on soil moisture at large scales is meager. It is of interest to estimate what effect soil moisture has on the retrieval accuracy of surface temperature by methods of remote sensing. In this study, newly developed algorithms to estimate land surface temperature (LST) from geostationary satellites will be applied to GOES-8 observations during the Southern Great Plains 1997 Hydrology Experiment (SGP-97) when surface observations of both soil moisture and surface temperature were made. The ground observations were used to first demonstrate the influence of soil moisture on the diurnal cycle of the surface temperature, its amplitude and the lag in LST maxima. Subsequently, it was established that errors in LST as derived from GOES-8 measurements have a negative correlation with soil moisture, namely, increasing with the decrease of soil moisture.

[1]  V. Caselles,et al.  A split‐window algorithm for land surface temperature from advanced very high resolution radiometer data: Validation and algorithm comparison , 1997 .

[2]  W. Kustas,et al.  A verification of the 'triangle' method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface e , 1997 .

[3]  A. Prata.  Land surface temperatures derived from the advanced very high resolution radiometer and the along‐track scanning radiometer: 1. Theory , 1993 .

[4]  S. Running,et al.  Developing Satellite-derived Estimates of Surface Moisture Status , 1993 .

[5]  Venkat Lakshmi,et al.  Observations of land surface temperature and its relationship to soil moisture during SGP99 , 2000, IGARSS 2000. IEEE 2000 International Geoscience and Remote Sensing Symposium. Taking the Pulse of the Planet: The Role of Remote Sensing in Managing the Environment. Proceedings (Cat. No.00CH37120).

[6]  Fran Li,et al.  Surface temperature and emissivity at various scales: Definition, measurement and related problems , 1995 .

[7]  Rachel T. Pinker,et al.  Estimation of land surface temperature diurnal cycle from Geostationary Operational Environmental Satellite (GOES-8) and application to the polar orbiting imager NOAA/AVHRR , 2003, SPIE Asia-Pacific Remote Sensing.

[8]  T. Carlson,et al.  A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover , 1994 .

[9]  W. C. Snyder,et al.  Classification-based emissivity for land surface temperature measurement from space , 1998 .

[10]  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 .

[11]  A. Dalcher,et al.  A Simple Biosphere Model (SIB) for Use within General Circulation Models , 1986 .

[12]  A. Berk.  MODTRAN : A moderate resolution model for LOWTRAN7 , 1989 .

[13]  Zhao-Liang Li,et al.  Improvements in the split-window technique for land surface temperature determination , 1994, IEEE Trans. Geosci. Remote. Sens..

[14]  Z. Wan.  MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD) , 1999 .

[15]  Andrew Shepherd,et al.  Land surface temperature derived from the Along Track Scanning Radiometer , 1999 .

[16]  Donglian Sun,et al.  Estimation of land surface temperature from a Geostationary Operational Environmental Satellite (GOES‐8) , 2003 .

[17]  C. Francois,et al.  Atmospheric corrections in the thermal infrared: global and water vapor dependent split-window algorithms-applications to ATSR and AVHRR data , 1996, IEEE Trans. Geosci. Remote. Sens..

[18]  Richard H. Moss,et al.  Relating land use and global land-cover change , 1993 .