A generalized split-window algorithm for retrieving land-surface temperature from space
نویسندگان
چکیده
We propose a generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must vary with the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (1t5.5" from nadir) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error over wide ranges of surface temperature and emissivity and atmospheric water vapor abundance and temperature. Simulations show that when atmospheric water vapor increases and viewing angle is larger than 45", it is necessary to optimize the split-window method by separating the ranges of the atmospheric water vapor, lower boundary temperature, and the surface temperature into tractable subranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range for the optimum coefficients of the split-window method. This new algorithm not only retrieves land-surface temperature more accurately, but is also less sensitive to uncertainty in emissivity and to instrument quantization error.
منابع مشابه
Comparison of Some Split-window Algorithms to Estimate Land Surface Temperature from AVHRR Data in Southeastern Tehran,
Land surface temperature (LST) is a significant parameter for many applications. Many studies have proposedvarious algorithms, such as the split-window method, for retrieving surface temperatures from two spectrallyadjacent thermal infrared bands of satellite data. Each algorithm is developed for a limited study area andapplication. In this paper, as part of developing an optimal split-window m...
متن کاملDevelopment a split window algorithm to estimate land surface temperature from Sentinel -3 satellite data
Land Surface Temperature (LST) is an important indicator of the study of energy balance models at the earthchr('39')s surface and the interactions between the Earth and the atmosphere on a regional and global scale. To date, different algorithms have been developed in the last few decades to determine the land surface temperature using various satellite images. In this study, a new split window...
متن کاملEstimating Land Surface Temperature in the Central Part of Isfahan Province Based on Landsat-8 Data Using Split- Window Algorithm
Land surface temperature (LST) is used as one of the key sources to study land surface processes such as evapotranspiration, development of indexes, air temperature modeling and climate change. Remote sensing data offer the possibility of estimating LST all over the world with high temporal and spatial resolution. Landsat-8, which has two thermal infrared channels, provides an opportunity for t...
متن کاملAn RM-NN algorithm for retrieving land surface temperature and emissivity from EOS/MODIS data
[1] Three radiative transfer equations are built for MODIS bands 29, 31, and 32, which involve six unknown parameters (average atmospheric temperature, land surface temperature (LST), three band emissivities, and water vapor content). The relationships between geophysical parameters have been analyzed in detail, which indicates that neural network is one of the best methods to resolve these ill...
متن کاملComparison of Split Window Algorithms for Retrieving Measurements of Sea Surface Temperature from MODIS Data in Near-Land Coastal Waters
Split window (SW) methods, which have been successfully used to retrieve measurements of land surface temperature (LST) and sea surface temperature (SST) from MODIS images, were exploited to evaluate the SST data of three sections of Italian coastal waters. For this purpose, sea surface emissivity (SSE) values were estimated by adding the effects of salinity and total suspended particulate matt...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- IEEE Trans. Geoscience and Remote Sensing
دوره 34 شماره
صفحات -
تاریخ انتشار 1996