Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques
The relationship between the physic features of the Earth’s surface and its temperature has been significantly investigated for further soil moisture assessment. In this study, the spatiotemporal impacts of surface properties on land surface temperature (<i>LST</i>) were examined by usin...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/9/1667 |
| _version_ | 1797536379724365824 |
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| author | Mai Son Le Yuei-An Liou |
| author_facet | Mai Son Le Yuei-An Liou |
| author_sort | Mai Son Le |
| collection | DOAJ |
| description | The relationship between the physic features of the Earth’s surface and its temperature has been significantly investigated for further soil moisture assessment. In this study, the spatiotemporal impacts of surface properties on land surface temperature (<i>LST</i>) were examined by using Landsat-8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) and meteorological data. The significant distinctions were observed during a crop growing season through the contrast in the correlation between different multi-spectral satellite indices and <i>LST</i>, in which the highest correlation of −0.65 was found when the Normalized Difference Latent heat Index (<i>NDLI</i>) was used. A new index, named as Temperature-soil Moisture Dryness Index (<i>TMDI</i>), is accordingly proposed to assess surface moisture and evapotranspiration (ET) variability. It is based on a triangle space where <i>NDLI</i> is set as a reference basis for examining surface water availability and the variation of <i>LST</i> is an indicator as a consequence of the cooling effect by ET. <i>TMDI</i> was evaluated against ET derived from the commonly-used model, namely Surface Energy Balance Algorithm for Land (SEBAL), as well as compared to the performance of Temperature Vegetation Dryness Index (<i>TVDI</i>). This study was conducted over five-time points for the 2014 winter crop growing season in southern Taiwan. Results indicated that <i>TMDI</i> exhibits significant sensitivity to surface moisture fluctuation by showing a strong correlation with SEBAL-derived ET with the highest correlation of −0.89 was found on 19 October. Moreover, <i>TMDI</i> revealed its superiority over <i>TVDI</i> in the response to a rapidly changing surface moisture due to water supply before the investigated time. It is suggested that <i>TMDI</i> is a proper and sensitive indicator to characterize the surface moisture and ET rate. Further exploitation of the usefulness of the <i>TMDI</i> in a variety of applications would be interesting. |
| first_indexed | 2024-03-10T11:59:49Z |
| format | Article |
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| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T11:59:49Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-594abb36993a481080de9be5bf71de1e2023-11-21T17:01:57ZengMDPI AGRemote Sensing2072-42922021-04-01139166710.3390/rs13091667Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing TechniquesMai Son Le0Yuei-An Liou1Space Technology Institute, Vietnam Academy of Science and Technology, Hanoi 10000, VietnamCenter for Space and Remote Sensing Research, National Central University, Taoyuan 320317, TaiwanThe relationship between the physic features of the Earth’s surface and its temperature has been significantly investigated for further soil moisture assessment. In this study, the spatiotemporal impacts of surface properties on land surface temperature (<i>LST</i>) were examined by using Landsat-8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) and meteorological data. The significant distinctions were observed during a crop growing season through the contrast in the correlation between different multi-spectral satellite indices and <i>LST</i>, in which the highest correlation of −0.65 was found when the Normalized Difference Latent heat Index (<i>NDLI</i>) was used. A new index, named as Temperature-soil Moisture Dryness Index (<i>TMDI</i>), is accordingly proposed to assess surface moisture and evapotranspiration (ET) variability. It is based on a triangle space where <i>NDLI</i> is set as a reference basis for examining surface water availability and the variation of <i>LST</i> is an indicator as a consequence of the cooling effect by ET. <i>TMDI</i> was evaluated against ET derived from the commonly-used model, namely Surface Energy Balance Algorithm for Land (SEBAL), as well as compared to the performance of Temperature Vegetation Dryness Index (<i>TVDI</i>). This study was conducted over five-time points for the 2014 winter crop growing season in southern Taiwan. Results indicated that <i>TMDI</i> exhibits significant sensitivity to surface moisture fluctuation by showing a strong correlation with SEBAL-derived ET with the highest correlation of −0.89 was found on 19 October. Moreover, <i>TMDI</i> revealed its superiority over <i>TVDI</i> in the response to a rapidly changing surface moisture due to water supply before the investigated time. It is suggested that <i>TMDI</i> is a proper and sensitive indicator to characterize the surface moisture and ET rate. Further exploitation of the usefulness of the <i>TMDI</i> in a variety of applications would be interesting.https://www.mdpi.com/2072-4292/13/9/1667land surface temperature (<i>LST</i>)normalized difference latent heat index (<i>NDLI</i>)temperature-soil moisture dryness index (<i>TMDI</i>)landsat-8 OLI/TIRS |
| spellingShingle | Mai Son Le Yuei-An Liou Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques Remote Sensing land surface temperature (<i>LST</i>) normalized difference latent heat index (<i>NDLI</i>) temperature-soil moisture dryness index (<i>TMDI</i>) landsat-8 OLI/TIRS |
| title | Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques |
| title_full | Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques |
| title_fullStr | Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques |
| title_full_unstemmed | Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques |
| title_short | Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques |
| title_sort | spatio temporal assessment of surface moisture and evapotranspiration variability using remote sensing techniques |
| topic | land surface temperature (<i>LST</i>) normalized difference latent heat index (<i>NDLI</i>) temperature-soil moisture dryness index (<i>TMDI</i>) landsat-8 OLI/TIRS |
| url | https://www.mdpi.com/2072-4292/13/9/1667 |
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