Name
Abstract | ||
|---|---|---|
Land surface temperature (LST) is a critical parameter in land surface process. The Moderate Resolution Imaging Spectroradiometer (MODIS) can be used to generate various LST data products, and these data have been widely applied in many studies. Unfortunately, cloud contamination brings about numerous missing or abnormal values, which negatively affect the application of LST data. To reconstruct missing values and improve data quality, this paper proposes an integrated method for reconstructing LST data under two conditions: Clear sky and cloudy sky. For the clear-sky condition, the MODIS eight-day LST (MOD11A2) product is used to be interpolated into the low-quality daily LST dataset using the harmonic analysis of time series (HANTS) algorithm. And then the linear regression algorithm is implemented on the original good-quality pixels of the MODIS daily LST (MOD11A1) product. After that, seamless processing on the reconstructed low-quality daily LST dataset is carried using the Poisson image editing method, and finally the high-quality daily LST dataset under clear-sky condition are then obtained. For the cloudy-sky conditions, the revised neighboring-pixel (NP) algorithm that originates from the surface energy balance theory is used to reconstruct the real LST data. To evaluate the reconstruction performance under clear-sky condition, a simulated dataset is generated from simulated missing pixels with good quality that are randomly chosen from 98 available LST images in the year 2010. Meanwhile, the real LST measurements collected from ground sites are used to assess the reconstructed results under cloudy-sky condition. Satisfactory validation results show that the proposed integrated method effectively reconstructs the missing information and low-quality pixels caused by cloud cover and other factors. The filled data can seamlessly preserve the temporal and spatial consistence of the daily LST data, which do promote the practical utility of the MODIS LST product. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JSTARS.2019.2896455 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Keywords | Field | DocType |
Land surface temperature,Clouds,MODIS,Image reconstruction,Land surface,Surface reconstruction,Remote sensing | Poisson image editing,Iterative reconstruction,Moderate-resolution imaging spectroradiometer,Data quality,Remote sensing,Interpolation,Pixel,Missing data,Cloud cover,Mathematics | Journal |
Volume | Issue | ISSN |
12 | 3 | 1939-1404 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gang Yang | 1 | 16 | 3.33 |
| Weiwei Sun | 2 | 94 | 20.80 |
| Huanfeng Shen | 3 | 1394 | 84.63 |
| Xiangchao Meng | 4 | 10 | 5.20 |
| Jialin Li | 5 | 247 | 18.58 |