Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran
The leaf area index (LAI) is an important vegetation biophysical index that provides broad information on the dynamic behavior of an ecosystem’s productivity and related climate, topography, and edaphic impacts. The spatiotemporal changes of LAI were assessed throughout Ardabil Province—a host of re...
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MDPI AG
2021-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/15/2879 |
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| author | Lida Andalibi Ardavan Ghorbani Mehdi Moameri Zeinab Hazbavi Arne Nothdurft Reza Jafari Farid Dadjou |
| author_facet | Lida Andalibi Ardavan Ghorbani Mehdi Moameri Zeinab Hazbavi Arne Nothdurft Reza Jafari Farid Dadjou |
| author_sort | Lida Andalibi |
| collection | DOAJ |
| description | The leaf area index (LAI) is an important vegetation biophysical index that provides broad information on the dynamic behavior of an ecosystem’s productivity and related climate, topography, and edaphic impacts. The spatiotemporal changes of LAI were assessed throughout Ardabil Province—a host of relevant plant communities within the critical ecoregion of a semi-arid climate. In a comparative study, novel data from Google Earth Engine (GEE) was tested against traditional ENVI measures to provide LAI estimations. Moreover, it is of important practical significance for institutional networks to quantitatively and accurately estimate LAI, at large areas in a short time, and using appropriate baseline vegetation indices. Therefore, LAI was characterized for ecoregions of Ardabil Province using remote sensing indices extracted from Landsat 8 Operational Land Imager (OLI), including the Enhanced Vegetation Index calculated in GEE (EVI<sub>G</sub>) and ENVI5.3 software (EVI<sub>E</sub>), as well as the Normalized Difference Vegetation Index estimated in ENVI5.3 software (NDVI<sub>E</sub>). Moreover, a new field measurement method, i.e., the LaiPen LP 100 portable device (LP 100), was used to evaluate the accuracy of the derived indices. Accordingly, the LAI was measured in June and July 2020, in 822 ground points distributed in 16 different ecoregions-sub ecoregions having various plant functional types (PFTs) of the shrub, bush, and tree. The analyses revealed heterogeneous spatial and temporal variability in vegetation indices and LAIs within and between ecoregions. The mean (standard deviation) value of EVI<sub>G</sub>, EVI<sub>E</sub>, and NDVI<sub>E</sub> at a province scale yielded 1.1 (0.41), 2.20 (0.78), and 3.00 (1.01), respectively in June, and 0.67 (0.37), 0.80 (0.63), and 1.88 (1.23), respectively, in July. The highest mean values of EVI<sub>G</sub>-LAI, EVI<sub>E</sub>-LAI, and NDVI<sub>E</sub>-LAI in June are found in Meshginshahr (1.40), Meshginshahr (2.80), and Hir (4.33) ecoregions and in July are found in Andabil ecoregion respectively with values of 1.23, 1.5, and 3.64. The lowest mean values of EVI<sub>G</sub>-LAI, EVI<sub>E</sub>-LAI, and NDVI<sub>E</sub>-LAI in June were observed for Kowsar (0.67), Meshginshahr (1.8), and Neur (2.70) ecoregions, and in July, the Bilesavar ecoregion, respectively, with values of 0.31, 0.31, and 0.81. High correlation and determination coefficients (r > 0.83 and R<sup>2</sup> > 0.68) between LP 100 and remote sensing derived LAI were observed in all three PFTs (except for NDVI<sub>E</sub>-LAI in June with r = 0.56 and R<sup>2</sup> = 0.31). On average, all three examined LAI measures tended to underestimate compared to LP 100-LAI (r > 0.42). The findings of the present study could be promising for effective monitoring and proper management of vegetation and land use in the Ardabil Province and other similar areas. |
| first_indexed | 2024-03-10T09:09:52Z |
| format | Article |
| id | doaj.art-1edd81d09a5d40a8b20888f8fed51753 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T09:09:52Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-1edd81d09a5d40a8b20888f8fed517532023-11-22T06:05:31ZengMDPI AGRemote Sensing2072-42922021-07-011315287910.3390/rs13152879Leaf Area Index Variations in Ecoregions of Ardabil Province, IranLida Andalibi0Ardavan Ghorbani1Mehdi Moameri2Zeinab Hazbavi3Arne Nothdurft4Reza Jafari5Farid Dadjou6Department of Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, IranDepartment of Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili, Ardabil 56199-11367, IranDepartment of Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili, Ardabil 56199-11367, IranDepartment of Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili, Ardabil 56199-11367, IranDepartment of Forest and Soil Sciences, University of Natural Resources and Life Sciences (BOKU), 331180 Vienna, AustriaDepartment of Natural Resources, Isfahan University of Technology, Isfahan 84156-83111, IranDepartment of Natural Resources, University of Mohaghegh Ardabili, Ardabil 56199-11367, IranThe leaf area index (LAI) is an important vegetation biophysical index that provides broad information on the dynamic behavior of an ecosystem’s productivity and related climate, topography, and edaphic impacts. The spatiotemporal changes of LAI were assessed throughout Ardabil Province—a host of relevant plant communities within the critical ecoregion of a semi-arid climate. In a comparative study, novel data from Google Earth Engine (GEE) was tested against traditional ENVI measures to provide LAI estimations. Moreover, it is of important practical significance for institutional networks to quantitatively and accurately estimate LAI, at large areas in a short time, and using appropriate baseline vegetation indices. Therefore, LAI was characterized for ecoregions of Ardabil Province using remote sensing indices extracted from Landsat 8 Operational Land Imager (OLI), including the Enhanced Vegetation Index calculated in GEE (EVI<sub>G</sub>) and ENVI5.3 software (EVI<sub>E</sub>), as well as the Normalized Difference Vegetation Index estimated in ENVI5.3 software (NDVI<sub>E</sub>). Moreover, a new field measurement method, i.e., the LaiPen LP 100 portable device (LP 100), was used to evaluate the accuracy of the derived indices. Accordingly, the LAI was measured in June and July 2020, in 822 ground points distributed in 16 different ecoregions-sub ecoregions having various plant functional types (PFTs) of the shrub, bush, and tree. The analyses revealed heterogeneous spatial and temporal variability in vegetation indices and LAIs within and between ecoregions. The mean (standard deviation) value of EVI<sub>G</sub>, EVI<sub>E</sub>, and NDVI<sub>E</sub> at a province scale yielded 1.1 (0.41), 2.20 (0.78), and 3.00 (1.01), respectively in June, and 0.67 (0.37), 0.80 (0.63), and 1.88 (1.23), respectively, in July. The highest mean values of EVI<sub>G</sub>-LAI, EVI<sub>E</sub>-LAI, and NDVI<sub>E</sub>-LAI in June are found in Meshginshahr (1.40), Meshginshahr (2.80), and Hir (4.33) ecoregions and in July are found in Andabil ecoregion respectively with values of 1.23, 1.5, and 3.64. The lowest mean values of EVI<sub>G</sub>-LAI, EVI<sub>E</sub>-LAI, and NDVI<sub>E</sub>-LAI in June were observed for Kowsar (0.67), Meshginshahr (1.8), and Neur (2.70) ecoregions, and in July, the Bilesavar ecoregion, respectively, with values of 0.31, 0.31, and 0.81. High correlation and determination coefficients (r > 0.83 and R<sup>2</sup> > 0.68) between LP 100 and remote sensing derived LAI were observed in all three PFTs (except for NDVI<sub>E</sub>-LAI in June with r = 0.56 and R<sup>2</sup> = 0.31). On average, all three examined LAI measures tended to underestimate compared to LP 100-LAI (r > 0.42). The findings of the present study could be promising for effective monitoring and proper management of vegetation and land use in the Ardabil Province and other similar areas.https://www.mdpi.com/2072-4292/13/15/2879LaiPenmanagement toolsremote sensingvegetation indicesspatiotemporal changes |
| spellingShingle | Lida Andalibi Ardavan Ghorbani Mehdi Moameri Zeinab Hazbavi Arne Nothdurft Reza Jafari Farid Dadjou Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran Remote Sensing LaiPen management tools remote sensing vegetation indices spatiotemporal changes |
| title | Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran |
| title_full | Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran |
| title_fullStr | Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran |
| title_full_unstemmed | Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran |
| title_short | Leaf Area Index Variations in Ecoregions of Ardabil Province, Iran |
| title_sort | leaf area index variations in ecoregions of ardabil province iran |
| topic | LaiPen management tools remote sensing vegetation indices spatiotemporal changes |
| url | https://www.mdpi.com/2072-4292/13/15/2879 |
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