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Forest biomass estimation using remote sensing and field inventory: a case study of Tripura, India
- Source :
- Environmental Monitoring and Assessment. 191
- Publication Year :
- 2019
- Publisher :
- Springer Science and Business Media LLC, 2019.
-
Abstract
- Forests are the potential source for managing carbon sequestration, regulating climate variations and balancing universal carbon equilibrium between sources and sinks. Further, assessment of biomass, carbon stock, and its spatial distribution is prerequisite for monitoring the health of forest ecosystem. Moreover, vegetation field inventories are valuable source of data for estimating aboveground biomass (AGB), density, and the carbon stored in biomass of forest vegetation. In view of the importance of biomass, the present study makes an attempt to estimate temporal AGB of Tripura State, India, using Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), leaf area index (LAI) and the field inventory data through geospatial techniques. A model was developed for establishing the relationship between biomass, LAI, and NDVI in the selected study site. The study also aimed to improve method for quantifying and verifying inventory-based biomass stock estimation. The results demonstrate the correlation value obtained between LAI and NDVI were 0.87 and 0.53 for the years 2011 and 2014, respectively. The correlation value between estimated AGB with LAI were found as 0.66 and 0.69, while with NDVI, the values were obtained as 0.64 and 0.94 for the years 2011 and 2014, respectively. The regression model of measured biomass with MODIS NDVI and LAI was developed for the data obtained during the period 2011–2014. The developed model was used to estimate the spatial distribution of biomass and its relationship between LAI and NDVI. The R2 values obtained were 0.832 for estimated and the measured AGB during the training and 0.826 for the validation. The results indicate that the methodology adopted in this study can help in selecting best fit model for analyzing relationship between AGB and NDVI/LAI and for estimating biomass using allometric equation at various spatial scales. The developed output thematic map showed an average biomass distribution of 32–94 Mg ha−1. The highest biomass values (72–95 Mg ha −1) was confined to the dense region of the forest while the lowest biomass values (32–46 Mg ha−1) was identified in the outer regions of the study site.
- Subjects :
- Satellite Imagery
010504 meteorology & atmospheric sciences
India
Forests
010501 environmental sciences
Management, Monitoring, Policy and Law
Carbon sequestration
Spatial distribution
Atmospheric sciences
01 natural sciences
Normalized Difference Vegetation Index
Forest ecology
Biomass
Leaf area index
0105 earth and related environmental sciences
General Environmental Science
Spatial Analysis
Regression analysis
General Medicine
Plants
Pollution
Plant Leaves
Thematic map
Remote Sensing Technology
Environmental science
Moderate-resolution imaging spectroradiometer
Environmental Monitoring
Subjects
Details
- ISSN :
- 15732959 and 01676369
- Volume :
- 191
- Database :
- OpenAIRE
- Journal :
- Environmental Monitoring and Assessment
- Accession number :
- edsair.doi.dedup.....0f9854fe765f4e64202f55a690efd69f