Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application
The current Polish Agricultural Drought Monitoring System (ADMS) adopted Climatic Water Balance (<i>CWB</i>) as the main indicator of crop losses caused by drought conditions. All meteorological data needed for <i>CWB</i> assessment are provided by the ground meteorological s...
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MDPI AG
2020-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/20/3411 |
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| author | Kamil Szewczak Helena Łoś Rafał Pudełko Andrzej Doroszewski Łukasz Gluba Mateusz Łukowski Anna Rafalska-Przysucha Jan Słomiński Bogusław Usowicz |
| author_facet | Kamil Szewczak Helena Łoś Rafał Pudełko Andrzej Doroszewski Łukasz Gluba Mateusz Łukowski Anna Rafalska-Przysucha Jan Słomiński Bogusław Usowicz |
| author_sort | Kamil Szewczak |
| collection | DOAJ |
| description | The current Polish Agricultural Drought Monitoring System (ADMS) adopted Climatic Water Balance (<i>CWB</i>) as the main indicator of crop losses caused by drought conditions. All meteorological data needed for <i>CWB</i> assessment are provided by the ground meteorological stations network. In 2018, the network consisted of 665 stations, among which in only 58 stations full weather parameters were registered. Therefore, only these stations offered a possibility to estimate the exact values of potential evapotranspiration, which is a component of the <i>CWB</i> algorithm. This limitation affects the quality of <i>CWB</i> raster maps, interpolated on the basis of the meteorological stations network for the entire country. However, the interpolation process itself may introduce errors; therefore, the adaptation of satellite data (that are spatially continuous) should be taken into account, even if the lack of data due to cloudiness remains a serious problem. In this paper, we involved the remote sensing data from MODIS instrument and considered the ability to integrate those data with values determined by using ground measurements. The paper presents results of comparisons for the <i>CWB</i> index assessed using ground station data and those obtained from potential evapotranspiration as the product from Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing instrument. The comparisons of results were performed for specific points (locations of ground stations) and were expressed by differences in means values. Analysis of Pearson’s correlation coefficient (r), Mann–Kendal trend test (Z-index), mean absolute error (MAE) and root mean square error (RMSE) for ten years’ series were evaluated and are presented. In addition, the basic spatial interpretation of results has been proposed. The correlation test revealed the r coefficient in the range from 0.06 to 0.68. The results show good trend agreement in time between two types of <i>CWB</i> with constantly higher values of this index, which is estimated using ground measurement data. In results for 34 (from 43 analyzed) stations the Mann–Kendal test provide the consistent trend, and only nine trends were inconsistent. Analyses revealed that the disagreement between the two considered indices (determined in different ways) increased significantly in the warmer period with a significant break point between R7 and R8 that falls at the end of May for each examined year. The value of MAE varied from 80 mm to 135 mm. |
| first_indexed | 2024-03-10T15:32:33Z |
| format | Article |
| id | doaj.art-7df672d3cdc84f16a980984a049ff952 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T15:32:33Z |
| publishDate | 2020-10-01 |
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| series | Remote Sensing |
| spelling | doaj.art-7df672d3cdc84f16a980984a049ff9522023-11-20T17:29:31ZengMDPI AGRemote Sensing2072-42922020-10-011220341110.3390/rs12203411Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data ApplicationKamil Szewczak0Helena Łoś1Rafał Pudełko2Andrzej Doroszewski3Łukasz Gluba4Mateusz Łukowski5Anna Rafalska-Przysucha6Jan Słomiński7Bogusław Usowicz8Institute of Agrophysics, Polish Academy of Sciences (IA PAN), Doświadczalna 4, 20-290 Lublin, PolandDEIMOS Engenharia S.A, Av. D. Joao II 41, 1998-023 Lisbon, PortugalInstitute of Soil Science and Plant Cultivation—State Research Institute (IUNG-PIB), Czartoryskich 8, 24-100 Puławy, PolandInstitute of Soil Science and Plant Cultivation—State Research Institute (IUNG-PIB), Czartoryskich 8, 24-100 Puławy, PolandInstitute of Agrophysics, Polish Academy of Sciences (IA PAN), Doświadczalna 4, 20-290 Lublin, PolandInstitute of Agrophysics, Polish Academy of Sciences (IA PAN), Doświadczalna 4, 20-290 Lublin, PolandInstitute of Agrophysics, Polish Academy of Sciences (IA PAN), Doświadczalna 4, 20-290 Lublin, PolandSpace Research Centre, Polish Academy of Sciences (CBK PAN), Bartycka 18A, 00-716 Warsaw, PolandInstitute of Agrophysics, Polish Academy of Sciences (IA PAN), Doświadczalna 4, 20-290 Lublin, PolandThe current Polish Agricultural Drought Monitoring System (ADMS) adopted Climatic Water Balance (<i>CWB</i>) as the main indicator of crop losses caused by drought conditions. All meteorological data needed for <i>CWB</i> assessment are provided by the ground meteorological stations network. In 2018, the network consisted of 665 stations, among which in only 58 stations full weather parameters were registered. Therefore, only these stations offered a possibility to estimate the exact values of potential evapotranspiration, which is a component of the <i>CWB</i> algorithm. This limitation affects the quality of <i>CWB</i> raster maps, interpolated on the basis of the meteorological stations network for the entire country. However, the interpolation process itself may introduce errors; therefore, the adaptation of satellite data (that are spatially continuous) should be taken into account, even if the lack of data due to cloudiness remains a serious problem. In this paper, we involved the remote sensing data from MODIS instrument and considered the ability to integrate those data with values determined by using ground measurements. The paper presents results of comparisons for the <i>CWB</i> index assessed using ground station data and those obtained from potential evapotranspiration as the product from Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing instrument. The comparisons of results were performed for specific points (locations of ground stations) and were expressed by differences in means values. Analysis of Pearson’s correlation coefficient (r), Mann–Kendal trend test (Z-index), mean absolute error (MAE) and root mean square error (RMSE) for ten years’ series were evaluated and are presented. In addition, the basic spatial interpretation of results has been proposed. The correlation test revealed the r coefficient in the range from 0.06 to 0.68. The results show good trend agreement in time between two types of <i>CWB</i> with constantly higher values of this index, which is estimated using ground measurement data. In results for 34 (from 43 analyzed) stations the Mann–Kendal test provide the consistent trend, and only nine trends were inconsistent. Analyses revealed that the disagreement between the two considered indices (determined in different ways) increased significantly in the warmer period with a significant break point between R7 and R8 that falls at the end of May for each examined year. The value of MAE varied from 80 mm to 135 mm.https://www.mdpi.com/2072-4292/12/20/3411PETclimatic water balanceMODISMann–Kendall test |
| spellingShingle | Kamil Szewczak Helena Łoś Rafał Pudełko Andrzej Doroszewski Łukasz Gluba Mateusz Łukowski Anna Rafalska-Przysucha Jan Słomiński Bogusław Usowicz Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application Remote Sensing PET climatic water balance MODIS Mann–Kendall test |
| title | Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application |
| title_full | Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application |
| title_fullStr | Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application |
| title_full_unstemmed | Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application |
| title_short | Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application |
| title_sort | agricultural drought monitoring by modis potential evapotranspiration remote sensing data application |
| topic | PET climatic water balance MODIS Mann–Kendall test |
| url | https://www.mdpi.com/2072-4292/12/20/3411 |
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