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Above Ground Biomass Estimation of Dalbergia sissoo Forest Plantation from Dual-Polarized ALOS-2 PALSAR Data

Authors :
Shahbaz Baig
Waqas A. Qazi
Aqeela Mobeen Akhtar
Mirza Muhammad Waqar
Ahmad Ammar
Hammad Gilani
Syed Amer Mehmood
Source :
Canadian Journal of Remote Sensing, Vol 43, Iss 3, Pp 297-308 (2017)
Publication Year :
2017
Publisher :
Taylor & Francis Group, 2017.

Abstract

In this study, ALOS-2 PALSAR L-band dual-pol (HH and HV) synthetic aperture radar (SAR) images were used for above ground biomass (AGB) estimation of Shisham (Dalbergia sissoo) tree species in the managed forest of Chichawatni Irrigated Plantation, Sahiwal District, Punjab, Pakistan. A total of 15 plots were surveyed during the field campaign and locally developed tree species-specific allometric equation was used for AGB calculation. The SAR images were pre-processed and calibrated to sigma nought (dB) for statistical AGB modeling. Nonlinear regression models between field-based AGB (ton/ha) and SAR backscatter sigma nought (dB) values give R2 (0.47 and 0.55) and RMSE (1.18 and 1.87) values for HH and HV-pol data, respectively. AGB maps generated through these regression models from both HH and HV-pol data show similar AGB values and spatial patterns. Due to a small number of sample plots, the Leave-One-Out Cross-Validation (LOOCV) proxy validation method was used for model validation, between estimated and predicted backscatter sigma nought (dB) values. The validation R2 values are small; however, outliers are identifiable in the validation scatterplots. The AGB maps from this study are useful as a first estimate of AGB values from remote sensing in the study region, especially in the context of the REDD+ program.

Details

Language :
English, French
ISSN :
17127971 and 07038992
Volume :
43
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Canadian Journal of Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.3a4ad3cca49448bc8331a5fda37e8706
Document Type :
article
Full Text :
https://doi.org/10.1080/07038992.2017.1330143