Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in India
An optimal model was developed for accounting forest carbon stock from synergistic use of optical data from Landsat TM and synthetic aperture radar (SAR) data from COSMO-Skymed (X-band), Radarsat-2 (C-band) and ALOS PALSAR (L-band) sensors over a tropical deciduous heterogeneous forest of India. The...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2020-01-01
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| Series: | Carbon Management |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/17583004.2019.1686931 |
| _version_ | 1797678443487297536 |
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| author | Suman Sinha Shiv Mohan A. K. Das L. K. Sharma C. Jeganathan A. Santra S. Santra Mitra M. S. Nathawat |
| author_facet | Suman Sinha Shiv Mohan A. K. Das L. K. Sharma C. Jeganathan A. Santra S. Santra Mitra M. S. Nathawat |
| author_sort | Suman Sinha |
| collection | DOAJ |
| description | An optimal model was developed for accounting forest carbon stock from synergistic use of optical data from Landsat TM and synthetic aperture radar (SAR) data from COSMO-Skymed (X-band), Radarsat-2 (C-band) and ALOS PALSAR (L-band) sensors over a tropical deciduous heterogeneous forest of India. The best-fit integrated multiple linear regression model had a model accuracy of 83%, r2 = 0.96, root mean square error = 10.02 Mg/ha and Willmott’s index of agreement of 0.98. The model further validated using chi-squared and t-test. Results of models for calculating the aboveground biomass (AGB) were converted to C and CO2 using conversion factors. Average AGB, C and CO2 were 70.5, 35.26 and 130.89 Mg/ha, respectively. The synergistic use of optical and multi-frequency SAR data enhanced the AGB saturation threshold to about 150 Mg/ha for tropical deciduous mixed forests. Hence, the synergistic use of this data is suggested for large-scale AGB and C estimations for tropical forests. Optical remote sensing sensors are extensively used due to greater data availability despite their poor sensitivity toward forest parameters. In contrast, SAR signals are highly sensitive toward forest biophysical and structural parameters, providing a better alternative. This unique integrated approach provides valuable information regarding the spatial distribution and quantification of forest biomass and carbon. |
| first_indexed | 2024-03-11T22:59:52Z |
| format | Article |
| id | doaj.art-b780a97461444a459c528b64dc9184a9 |
| institution | Directory Open Access Journal |
| issn | 1758-3004 1758-3012 |
| language | English |
| last_indexed | 2024-03-11T22:59:52Z |
| publishDate | 2020-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Carbon Management |
| spelling | doaj.art-b780a97461444a459c528b64dc9184a92023-09-21T15:09:05ZengTaylor & Francis GroupCarbon Management1758-30041758-30122020-01-01111395510.1080/17583004.2019.16869311686931Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in IndiaSuman Sinha0Shiv Mohan1A. K. Das2L. K. Sharma3C. Jeganathan4A. Santra5S. Santra Mitra6M. S. Nathawat7Department of Geography, Amity Institute of Social Sciences, Amity University KolkataPLANEXGovernment of IndiaDepartment of Environmental Science, Central University of RajasthanBirla Institute of TechnologyHaldia Institute of TechnologyHaldia Institute of TechnologyIndira Gandhi National Open University (IGNOU)An optimal model was developed for accounting forest carbon stock from synergistic use of optical data from Landsat TM and synthetic aperture radar (SAR) data from COSMO-Skymed (X-band), Radarsat-2 (C-band) and ALOS PALSAR (L-band) sensors over a tropical deciduous heterogeneous forest of India. The best-fit integrated multiple linear regression model had a model accuracy of 83%, r2 = 0.96, root mean square error = 10.02 Mg/ha and Willmott’s index of agreement of 0.98. The model further validated using chi-squared and t-test. Results of models for calculating the aboveground biomass (AGB) were converted to C and CO2 using conversion factors. Average AGB, C and CO2 were 70.5, 35.26 and 130.89 Mg/ha, respectively. The synergistic use of optical and multi-frequency SAR data enhanced the AGB saturation threshold to about 150 Mg/ha for tropical deciduous mixed forests. Hence, the synergistic use of this data is suggested for large-scale AGB and C estimations for tropical forests. Optical remote sensing sensors are extensively used due to greater data availability despite their poor sensitivity toward forest parameters. In contrast, SAR signals are highly sensitive toward forest biophysical and structural parameters, providing a better alternative. This unique integrated approach provides valuable information regarding the spatial distribution and quantification of forest biomass and carbon.http://dx.doi.org/10.1080/17583004.2019.1686931alos palsarradarsat-2cosmo-skymedlandsatforest biomass |
| spellingShingle | Suman Sinha Shiv Mohan A. K. Das L. K. Sharma C. Jeganathan A. Santra S. Santra Mitra M. S. Nathawat Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in India Carbon Management alos palsar radarsat-2 cosmo-skymed landsat forest biomass |
| title | Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in India |
| title_full | Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in India |
| title_fullStr | Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in India |
| title_full_unstemmed | Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in India |
| title_short | Multi-sensor approach integrating optical and multi-frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in India |
| title_sort | multi sensor approach integrating optical and multi frequency synthetic aperture radar for carbon stock estimation over a tropical deciduous forest in india |
| topic | alos palsar radarsat-2 cosmo-skymed landsat forest biomass |
| url | http://dx.doi.org/10.1080/17583004.2019.1686931 |
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