An Adjacency-Effect-Based Approach for Accuracy Improvement in Satellite Land Surface Temperature Disaggregation
One of the key parameters that affects the accuracy of land surface temperature (LST) disaggregation is the environmental variables that are fed to the disaggregation model. The aim of this article is to present a new strategy for the disaggregation of LST based on adjacency effects. To do this, a d...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10288054/ |
| _version_ | 1827585390997929984 |
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| author | Mohammad Karimi Firozjaei Majid Kiavarz Seyed Kazem Alavipanah |
| author_facet | Mohammad Karimi Firozjaei Majid Kiavarz Seyed Kazem Alavipanah |
| author_sort | Mohammad Karimi Firozjaei |
| collection | DOAJ |
| description | One of the key parameters that affects the accuracy of land surface temperature (LST) disaggregation is the environmental variables that are fed to the disaggregation model. The aim of this article is to present a new strategy for the disaggregation of LST based on adjacency effects. To do this, a dataset obtained from satellite images and auxiliary information from five European cities was used. First, maps of environmental variables that affect LST were collected. Second, a map of effective environmental variables was produced by calculating and applying the influence of the adjacency effects of each environmental variable based on the proposed weighted inverse distance kernel. Finally, the datasets of environmental variables and effective environmental variables were used separately in the disaggregation process to convert LST at 990 m to disaggregated LST (DLST) at 90 m. The mean RMSEs between LST and DLST obtained without considering the adjacency effects approach for the built-up, agricultural, pasture, forest, and water lands in the cold (warm) season were 0.85 (1.55), 0.72 (1.31), 0.98 (1.63), 0.59 (1.2), and 0.40 (1.12) K, respectively. Taking into account the adjacency effects, the mean RMSE between LST and DLST on built-up, agricultural, pasture, forest, and water lands used in the cold season decreased by 0.35, 0.17, 0.13, 0.09, and 0.03 K, respectively. These values were 0.54, 0.36, 0.33, 0.34, and 0.07 K for the warm season, respectively. The result showed that considering adjacency effects increases the accuracy of LST disaggregation. |
| first_indexed | 2024-03-08T23:44:54Z |
| format | Article |
| id | doaj.art-991b4999533149af9f5bed773546646e |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-03-08T23:44:54Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-991b4999533149af9f5bed773546646e2023-12-14T00:00:51ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352024-01-01171066108310.1109/JSTARS.2023.332592010288054An Adjacency-Effect-Based Approach for Accuracy Improvement in Satellite Land Surface Temperature DisaggregationMohammad Karimi Firozjaei0https://orcid.org/0000-0002-3060-9162Majid Kiavarz1https://orcid.org/0000-0003-0335-3795Seyed Kazem Alavipanah2https://orcid.org/0000-0002-3554-111XDepartment of Remote Sensing and GIS, University of Tehran, Tehran, IranDepartment of Remote Sensing and GIS, University of Tehran, Tehran, IranDepartment of Remote Sensing and GIS, University of Tehran, Tehran, IranOne of the key parameters that affects the accuracy of land surface temperature (LST) disaggregation is the environmental variables that are fed to the disaggregation model. The aim of this article is to present a new strategy for the disaggregation of LST based on adjacency effects. To do this, a dataset obtained from satellite images and auxiliary information from five European cities was used. First, maps of environmental variables that affect LST were collected. Second, a map of effective environmental variables was produced by calculating and applying the influence of the adjacency effects of each environmental variable based on the proposed weighted inverse distance kernel. Finally, the datasets of environmental variables and effective environmental variables were used separately in the disaggregation process to convert LST at 990 m to disaggregated LST (DLST) at 90 m. The mean RMSEs between LST and DLST obtained without considering the adjacency effects approach for the built-up, agricultural, pasture, forest, and water lands in the cold (warm) season were 0.85 (1.55), 0.72 (1.31), 0.98 (1.63), 0.59 (1.2), and 0.40 (1.12) K, respectively. Taking into account the adjacency effects, the mean RMSE between LST and DLST on built-up, agricultural, pasture, forest, and water lands used in the cold season decreased by 0.35, 0.17, 0.13, 0.09, and 0.03 K, respectively. These values were 0.54, 0.36, 0.33, 0.34, and 0.07 K for the warm season, respectively. The result showed that considering adjacency effects increases the accuracy of LST disaggregation.https://ieeexplore.ieee.org/document/10288054/Accuracyadjacency effectsdisaggregationenvironmental variablesland surface temperature (LST) |
| spellingShingle | Mohammad Karimi Firozjaei Majid Kiavarz Seyed Kazem Alavipanah An Adjacency-Effect-Based Approach for Accuracy Improvement in Satellite Land Surface Temperature Disaggregation IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Accuracy adjacency effects disaggregation environmental variables land surface temperature (LST) |
| title | An Adjacency-Effect-Based Approach for Accuracy Improvement in Satellite Land Surface Temperature Disaggregation |
| title_full | An Adjacency-Effect-Based Approach for Accuracy Improvement in Satellite Land Surface Temperature Disaggregation |
| title_fullStr | An Adjacency-Effect-Based Approach for Accuracy Improvement in Satellite Land Surface Temperature Disaggregation |
| title_full_unstemmed | An Adjacency-Effect-Based Approach for Accuracy Improvement in Satellite Land Surface Temperature Disaggregation |
| title_short | An Adjacency-Effect-Based Approach for Accuracy Improvement in Satellite Land Surface Temperature Disaggregation |
| title_sort | adjacency effect based approach for accuracy improvement in satellite land surface temperature disaggregation |
| topic | Accuracy adjacency effects disaggregation environmental variables land surface temperature (LST) |
| url | https://ieeexplore.ieee.org/document/10288054/ |
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