Remote Sensing Applications and Decision Support

Comparison of forest aboveground biomass estimates from passive and active remote sensing sensors over Kayar Khola watershed, Chitwan district, Nepal

[+] Author Affiliations
Waqas A. Qazi, Shahbaz Baig, Mirza Muhammad Waqar, Ahmad Ammar

Institute of Space Technology, Department of Space Science, Geospatial Research and Education Lab (GREL), Islamabad Highway, Islamabad, Pakistan

Hammad Gilani

University of Illinois, Department of Atmospheric Sciences, Urbana, Illinois, United States

International Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal

Ashwin Dhakal

Kathmandu University, Department of Civil and Geomatics Engineering, Dhulikhel Kavre, Nepal

J. Appl. Remote Sens. 11(2), 026038 (Jun 24, 2017). doi:10.1117/1.JRS.11.026038
History: Received February 17, 2017; Accepted June 7, 2017
Text Size: A A A

Abstract.  We use passive optical high-resolution GeoEye-1 imagery and active synthetic aperture radar (SAR) Advanced Land Observing Satellite (ALOS-1) phased array type L-band synthetic aperture radar (PALSAR) L-band horizontal–horizontal-polarization imagery to estimate forest aboveground biomass (AGB) of the tropical mountainous forest test site in Kayar Khola watershed, Chitwan district, Nepal. Object-based tools were used to delineate tree crowns from the orthorectified pan-sharpened GeoEye-1 optical imagery. AGB modeling with crown projection area extracted from the optical imagery shows a good linear relationship with R2=0.76. The terrain-corrected, radiometrically calibrated, and speckle-filtered ALOS-1 PALSAR backscatter image was utilized for AGB modeling; the nonlinear modeling of AGB with the SAR backscatter (dB) shows R2=0.52. The validation R2 values for AGB estimates from GeoEye-1 and ALOS-1 PALSAR are 0.83 and 0.44, respectively. The direct comparison of AGB estimates from both sensors is made possible by the utilization of the same set of ground survey points for both training and validation of the statistical models for both datasets. The final AGB output maps from both sensors show that the spatial patterns of AGB are in reasonable agreement at lower elevation, while SAR seems to underestimate AGB values as compared with optical-based estimates in the higher elevation zones.

Figures in this Article
© 2017 Society of Photo-Optical Instrumentation Engineers

Citation

Waqas A. Qazi ; Shahbaz Baig ; Hammad Gilani ; Mirza Muhammad Waqar ; Ashwin Dhakal, et al.
"Comparison of forest aboveground biomass estimates from passive and active remote sensing sensors over Kayar Khola watershed, Chitwan district, Nepal", J. Appl. Remote Sens. 11(2), 026038 (Jun 24, 2017). ; http://dx.doi.org/10.1117/1.JRS.11.026038


Tables

Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Proceedings Articles

Related Book Chapters

Topic Collections

Advertisement


 

  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.