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The source codes of Time-series-based Reflectance Adjustment (TRA) approach (Windows C/C++ and MATLAB version)

TRA 최신버젼 다운로드

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# TRA
This repository shows the source codes of the Time-series-based Reflectance Adjustment (TRA) approach. It includes two versions: one is ***MATLAB*** version ([versionMATLAB directory](https://github.com/GERSL/TRA/tree/master/versionMATLAB)); and the other is ***Windows C/C++*** version, which is based on Windows 10 and Microsoft Visual Studio 2017 (or higher).

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## Windows C/C++ version
This version requires the installation of the ***HDF library*** (version 4.2.11) for reading the HLS product (HDF format). When you open ***TRA.sln***, you need to check the configuration. Choose ***Release*** and ***x64***, and then make sure:

(1) Use ***MFC in a Shared DLL***;

(2) Use ***Multi-Bytes Character Set***;

(3) Add the ***include and library directories*** of HDF;

(4) Add ***_CTR_SECURE_NO_WARMINGs*** into preprocessor.

More details about how to use this code are given in the [How to use.PDF](https://github.com/GERSL/TRA/blob/master/How%20to%20use.pdf).

There are ***two functions for running TRA***: one is for a ***single pixel*** and the other is for the ***MGRS tile***.

(1) When running a single pixel, you need to define the ***path of L30 and S30 point*** data (CSV format) and the ***output path*** of fitted parameters (TXT format). The CSV file should be organized as nine columns (***Year, DOY, Blue, Green, Red, NIR, SWIR1, SWIR2, and ClearFlag***). The ClearFlag labeled as 1 means the clear-sky observation.

(2) When running an MGRS tile, you need to create the TXT file for ***all paths of the HLS L30 or S30*** files (use the command: ***dir *S30*.hdf /s/b >pathS30.txt***), and then define the paths of two TXT files and the output path of the HDF file with the fitted parameters.

## MATLAB verison
This version currently can only run TRA for a single pixel. The script ***mainTRAtest*** shows an example of using the TRA functions (e.g. ***TRAmatch***, ***TRAregression***, ***TRAadjust***). Notice that the remaining clouds removal in this version (***TimeSeiresNoiseFilter***) is different from that in Windows C/C++ version, which can provide better results.

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If using this code, please cite the following paper:

Shang, R., Zhu, Z., 2019. [Harmonizing Landsat 8 and Sentinel-2: A time-series-based reflectance adjustment approach](https://www.sciencedirect.com/science/article/pii/S0034425719304584). *Remote Sensing of Environment*. 235, 111439.

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