Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field Measurements
The accuracy assessment of the global leaf area index (LAI) products is an indispensable step before applications. Four popular LAI products, namely MCD15A2H, GLASS, GEOV2, and GLOBMAP, were assessed over croplands in China using field measurements. All of these four products were validated with ups...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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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/9525232/ |
| _version_ | 1831567574464200704 |
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| author | Bowen Song Liangyun Liu Jingjing Zhao Xidong Chen Helin Zhang Yuan Gao Xiao Zhang |
| author_facet | Bowen Song Liangyun Liu Jingjing Zhao Xidong Chen Helin Zhang Yuan Gao Xiao Zhang |
| author_sort | Bowen Song |
| collection | DOAJ |
| description | The accuracy assessment of the global leaf area index (LAI) products is an indispensable step before applications. Four popular LAI products, namely MCD15A2H, GLASS, GEOV2, and GLOBMAP, were assessed over croplands in China using field measurements. All of these four products were validated with upscaled reference LAI maps. The validation results revealed uncertainties in these products for crops with RMSE ranging from 0.49 to 1.37 over the validation sites in Beijing, in Zhoukou and Jiaozuo counties in Henan province, Youyi farm in Heilongjiang province, and in Longkang farm in Anhui province. GEOV2 gave the highest accuracy (<italic>R</italic><sup>2</sup> = 0.85, RMSE = 0.49, relative bias = −7.2%) compared to MCD15A2H (<italic>R</italic><sup>2</sup> = 0.54, RMSE = 0.91, and relative bias = −24.4%), GLASS (<italic>R</italic><sup>2</sup> = 0.80, RMSE = 0.73, and relative bias = −23.3%), and GLOBMAP (<italic>R</italic><sup>2</sup> = 0.25, RMSE = 1.37, and relative bias = −55.4%). The LAI products overestimated over the croplands with dark soil-backgrounds in Youyi farm while they underestimated over other validation sites. The seasonal variation of these products was assessed with continuous <italic>in situ</italic> measurements at Daman Station, Gansu province. All of these four products showed good temporal consistency at Daman Station, while GEOV2 showed the highest accuracy (<italic>R</italic><sup>2</sup> = 0.92, RMSE = 0.41, relative bias = −10.3%). The influence of scaling effect on the products’ accuracy was also investigated, and the scaling differences of these LAI products contributes overestimation at coarse-resolution for croplands with dark soil-backgrounds, while underestimation at coarse-resolution in other validation sties. |
| first_indexed | 2024-12-17T12:00:03Z |
| format | Article |
| id | doaj.art-3dc9487dacf74f42a1763f0d89a99759 |
| institution | Directory Open Access Journal |
| issn | 2151-1535 |
| language | English |
| last_indexed | 2024-12-17T12:00:03Z |
| publishDate | 2021-01-01 |
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| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj.art-3dc9487dacf74f42a1763f0d89a997592022-12-21T21:49:52ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing2151-15352021-01-01149372938210.1109/JSTARS.2021.31081729525232Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field MeasurementsBowen Song0https://orcid.org/0000-0003-1480-1637Liangyun Liu1https://orcid.org/0000-0002-4984-1623Jingjing Zhao2Xidong Chen3https://orcid.org/0000-0001-9102-2974Helin Zhang4Yuan Gao5Xiao Zhang6Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaState Information Center, Beijing, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaBeijing Engineering Research Center for Global Land Remote Sensing Products, Institute of Remote Sensing and Engineering, Faculty of Geographical Science, Beijing Normal University, Beijing, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing, ChinaThe accuracy assessment of the global leaf area index (LAI) products is an indispensable step before applications. Four popular LAI products, namely MCD15A2H, GLASS, GEOV2, and GLOBMAP, were assessed over croplands in China using field measurements. All of these four products were validated with upscaled reference LAI maps. The validation results revealed uncertainties in these products for crops with RMSE ranging from 0.49 to 1.37 over the validation sites in Beijing, in Zhoukou and Jiaozuo counties in Henan province, Youyi farm in Heilongjiang province, and in Longkang farm in Anhui province. GEOV2 gave the highest accuracy (<italic>R</italic><sup>2</sup> = 0.85, RMSE = 0.49, relative bias = −7.2%) compared to MCD15A2H (<italic>R</italic><sup>2</sup> = 0.54, RMSE = 0.91, and relative bias = −24.4%), GLASS (<italic>R</italic><sup>2</sup> = 0.80, RMSE = 0.73, and relative bias = −23.3%), and GLOBMAP (<italic>R</italic><sup>2</sup> = 0.25, RMSE = 1.37, and relative bias = −55.4%). The LAI products overestimated over the croplands with dark soil-backgrounds in Youyi farm while they underestimated over other validation sites. The seasonal variation of these products was assessed with continuous <italic>in situ</italic> measurements at Daman Station, Gansu province. All of these four products showed good temporal consistency at Daman Station, while GEOV2 showed the highest accuracy (<italic>R</italic><sup>2</sup> = 0.92, RMSE = 0.41, relative bias = −10.3%). The influence of scaling effect on the products’ accuracy was also investigated, and the scaling differences of these LAI products contributes overestimation at coarse-resolution for croplands with dark soil-backgrounds, while underestimation at coarse-resolution in other validation sties.https://ieeexplore.ieee.org/document/9525232/ChinacroplandLandsatleaf area index (LAI)validation |
| spellingShingle | Bowen Song Liangyun Liu Jingjing Zhao Xidong Chen Helin Zhang Yuan Gao Xiao Zhang Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field Measurements IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing China cropland Landsat leaf area index (LAI) validation |
| title | Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field Measurements |
| title_full | Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field Measurements |
| title_fullStr | Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field Measurements |
| title_full_unstemmed | Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field Measurements |
| title_short | Validation of Four Coarse-Resolution Leaf Area Index Products Over Croplands in China Using Field Measurements |
| title_sort | validation of four coarse resolution leaf area index products over croplands in china using field measurements |
| topic | China cropland Landsat leaf area index (LAI) validation |
| url | https://ieeexplore.ieee.org/document/9525232/ |
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