Assessing soil carbon stocks under pastures through orbital remote sensing
The growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniq...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Universidade de São Paulo
2011-10-01
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| Series: | Scientia Agricola |
| Subjects: | |
| Online Access: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162011000500010 |
| _version_ | 1819020638324523008 |
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| author | Gabor Gyula Julius Szakács Carlos Clemente Cerri Uwe Herpin Martial Bernoux |
| author_facet | Gabor Gyula Julius Szakács Carlos Clemente Cerri Uwe Herpin Martial Bernoux |
| author_sort | Gabor Gyula Julius Szakács |
| collection | DOAJ |
| description | The growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. This article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon (SOC) stocks in degraded pastures, using remote sensing techniques. Four pastures on sandy soils under Brazilian Cerrado vegetation in São Paulo state were chosen due to their SOC sequestration potential, which was characterized for the soil depth 0-50 cm. Subsequently, a linear regression analysis was performed between SOC and Leaf Area Index (LAI) measured in the field (LAIfield) and derived by satellite (LAIsatellite) as well as SOC and pasture reflectance in six spectra from 450 nm - 2350 nm, using the Enhanced Thematic Mapper (ETM+) sensor of satellite Landsat 7. A high correlation between SOC and LAIfield (R² = 0.9804) and LAIsatellite (R² = 0.9812) was verified. The suitability of satellite derived LAI for SOC determination leads to the assumption, that orbital remote sensing is a very promising SOC estimation technique from regional to global scale. |
| first_indexed | 2024-12-21T03:54:23Z |
| format | Article |
| id | doaj.art-cae6904ccb6f46ac904471cf09dca1e5 |
| institution | Directory Open Access Journal |
| issn | 0103-9016 1678-992X |
| language | English |
| last_indexed | 2024-12-21T03:54:23Z |
| publishDate | 2011-10-01 |
| publisher | Universidade de São Paulo |
| record_format | Article |
| series | Scientia Agricola |
| spelling | doaj.art-cae6904ccb6f46ac904471cf09dca1e52022-12-21T19:16:53ZengUniversidade de São PauloScientia Agricola0103-90161678-992X2011-10-0168557458110.1590/S0103-90162011000500010Assessing soil carbon stocks under pastures through orbital remote sensingGabor Gyula Julius SzakácsCarlos Clemente CerriUwe HerpinMartial BernouxThe growing demand of world food and energy supply increases the threat of global warming due to higher greenhouse gas emissions by agricultural activity. Therefore, it is widely admitted that agriculture must establish a new paradigm in terms of environmental sustainability that incorporate techniques for mitigation of greenhouse gas emissions. This article addresses to the scientific demand to estimate in a fast and inexpensive manner current and potential soil organic carbon (SOC) stocks in degraded pastures, using remote sensing techniques. Four pastures on sandy soils under Brazilian Cerrado vegetation in São Paulo state were chosen due to their SOC sequestration potential, which was characterized for the soil depth 0-50 cm. Subsequently, a linear regression analysis was performed between SOC and Leaf Area Index (LAI) measured in the field (LAIfield) and derived by satellite (LAIsatellite) as well as SOC and pasture reflectance in six spectra from 450 nm - 2350 nm, using the Enhanced Thematic Mapper (ETM+) sensor of satellite Landsat 7. A high correlation between SOC and LAIfield (R² = 0.9804) and LAIsatellite (R² = 0.9812) was verified. The suitability of satellite derived LAI for SOC determination leads to the assumption, that orbital remote sensing is a very promising SOC estimation technique from regional to global scale.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162011000500010Brazilleaf Area Indexsoil organic carbonpasture degradationspectral reflectanceclimate change |
| spellingShingle | Gabor Gyula Julius Szakács Carlos Clemente Cerri Uwe Herpin Martial Bernoux Assessing soil carbon stocks under pastures through orbital remote sensing Scientia Agricola Brazil leaf Area Index soil organic carbon pasture degradation spectral reflectance climate change |
| title | Assessing soil carbon stocks under pastures through orbital remote sensing |
| title_full | Assessing soil carbon stocks under pastures through orbital remote sensing |
| title_fullStr | Assessing soil carbon stocks under pastures through orbital remote sensing |
| title_full_unstemmed | Assessing soil carbon stocks under pastures through orbital remote sensing |
| title_short | Assessing soil carbon stocks under pastures through orbital remote sensing |
| title_sort | assessing soil carbon stocks under pastures through orbital remote sensing |
| topic | Brazil leaf Area Index soil organic carbon pasture degradation spectral reflectance climate change |
| url | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162011000500010 |
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