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

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.

[1]  Dirk Tiede,et al.  ESP: a tool to estimate scale parameter for multiresolution image segmentation of remotely sensed data , 2010, Int. J. Geogr. Inf. Sci..

[2]  D. Bui,et al.  A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape. , 2015 .

[3]  Na Yin,et al.  Estimating Forest Aboveground Biomass by Combining ALOS PALSAR and WorldView-2 Data: A Case Study at Purple Mountain National Park, Nanjing, China , 2014, Remote. Sens..

[4]  J. Swenson,et al.  Reference scenarios for deforestation and forest degradation in support of REDD: a review of data and methods , 2008 .

[5]  T. Maraseni,et al.  Carbon stock dynamics in different vegetation dominated community forests under REDD+: A case from Nepal , 2014 .

[6]  Sandra A. Brown,et al.  Monitoring and estimating tropical forest carbon stocks: making REDD a reality , 2007 .

[7]  G. Foody,et al.  Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions , 2003 .

[8]  David B. Clark,et al.  APPLICATION OF 1-M AND 4-M RESOLUTION SATELLITE DATA TO ECOLOGICAL STUDIES OF TROPICAL RAIN FORESTS , 2004 .

[9]  I. Woodhouse,et al.  Using satellite radar backscatter to predict above‐ground woody biomass: A consistent relationship across four different African landscapes , 2009 .

[10]  Johannes Breidenbach,et al.  The Influence of DEM Quality on Mapping Accuracy of Coniferous- and Deciduous-Dominated Forest Using TerraSAR-X Images , 2012, Remote. Sens..

[11]  J. Chambers,et al.  Tree allometry and improved estimation of carbon stocks and balance in tropical forests , 2005, Oecologia.

[12]  D. Leckie,et al.  The Individual Tree Crown Approach Applied to Ikonos Images of a Coniferous Plantation Area , 2006 .

[13]  I. Mohd Hasmadi,et al.  Combination of SPOT-5 and ALOS PALSAR images in estimating aboveground biomass of lowland Dipterocarp forest , 2014 .

[14]  M. Fernandez,et al.  Polarimetric Data for Tropical Forest Monitoring. Studies at the Colombian Amazon , 2002 .

[15]  Nandin-Erdene Tsendbazar,et al.  Evaluation of object-based image analysis techniques on very high-resolution satellite image for biomass estimation in a watershed of hilly forest of Nepal , 2014 .

[16]  João Roberto dos Santos,et al.  Savanna and tropical rainforest biomass estimation and spatialization using JERS-1 data , 2002 .

[17]  Lindi J. Quackenbush,et al.  A comparison of three methods for automatic tree crown detection and delineation from high spatial resolution imagery , 2011 .

[18]  Dirk Tiede,et al.  Transferability of a Tree-Crown Delineation Approach Using Region-specific Segmentation , 2007 .

[19]  R. Houghton,et al.  Aboveground Forest Biomass and the Global Carbon Balance , 2005 .

[20]  K. A. Rahman,et al.  REMOTELY SENSED L-BAND SAR DATA FOR TROPICAL FOREST BIOMASS ESTIMATION , 2011 .

[21]  Paulo Mesquita,et al.  Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia , 2015 .

[22]  R. Rutt,et al.  Social and Environmental Tensions: Affirmative Measures Under REDD + Carbon Payment Initiatives in Nepal , 2014 .

[23]  Maurizio Santoro,et al.  Mapping forest aboveground biomass in the Northeastern United States with ALOS PALSAR dual-polarization L-band , 2012 .

[24]  B. Karky,et al.  Gender Equality Challenges to the REDD+ Initiative in Nepal , 2014 .

[25]  J. Kong,et al.  Retrieval of forest biomass from SAR data , 1994 .

[26]  Mahendra Singh Nathawat,et al.  A review of radar remote sensing for biomass estimation , 2015, International Journal of Environmental Science and Technology.

[27]  Jianping Guo,et al.  Estimation of forest above-ground biomass using multi-parameter remote sensing data over a cold and arid area , 2012, Int. J. Appl. Earth Obs. Geoinformation.

[28]  W. Walker,et al.  Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR/InSAR, ETM+, Quickbird) synergy , 2006 .

[29]  T. Maraseni,et al.  An assessment of the impacts of the REDD+ pilot project on community forests user groups (CFUGs) and their community forests in Nepal. , 2014, Journal of environmental management.

[30]  T. Schoennagel,et al.  An object-oriented approach to assessing changes in tree cover in the Colorado Front Range 1938–1999 , 2009 .

[31]  Joanne C. White,et al.  Segment-constrained regression tree estimation of forest stand height from very high spatial resolution panchromatic imagery over a boreal environment , 2010 .

[32]  M. Sahebi,et al.  A review on biomass estimation methods using synthetic aperture radar data. , 2011 .

[33]  K. T. Vashum,et al.  Methods to Estimate Above-Ground Biomass and Carbon Stock in Natural Forests - A Review , 2012 .

[34]  William J. Emery,et al.  Computing Ocean Surface Currents Over the Coastal California Current System Using 30-Min-Lag Sequential SAR Images , 2014, IEEE Transactions on Geoscience and Remote Sensing.

[35]  Masanobu Shimada,et al.  An Evaluation of the ALOS PALSAR L-Band Backscatter—Above Ground Biomass Relationship Queensland, Australia: Impacts of Surface Moisture Condition and Vegetation Structure , 2010, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[36]  Manfred Ehlers,et al.  Multi-sensor image fusion for pansharpening in remote sensing , 2010 .

[37]  D. A. King,et al.  Height-diameter allometry of tropical forest trees , 2010 .

[38]  Mark S. Seyfried,et al.  Effect of Digital Elevation Model resolution on topographic correction of airborne SAR , 1998 .

[39]  Q. Ketterings,et al.  Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests , 2001 .

[40]  Guoqing Sun,et al.  Forest biomass mapping from lidar and radar synergies , 2011 .

[41]  Lijuan Liu,et al.  A survey of remote sensing-based aboveground biomass estimation methods in forest ecosystems , 2016, Int. J. Digit. Earth.

[42]  Bhaskar Singh Karky,et al.  Case Study Report: REDD+ Pilot Project in Community Forests in Three Watersheds of Nepal , 2014 .

[43]  H. Baral,et al.  Payment for ecosystem services: possible instrument for managing ecosystem services in Nepal , 2014 .

[44]  Jussi Peuhkurinen,et al.  Robustness of model-based high-resolution prediction of forest biomass against different field plot designs , 2015, Carbon Balance and Management.

[45]  I. Woodhouse,et al.  Radar backscatter is not a \'direct measure\' of forest biomass , 2012 .

[46]  Eric A. Lehmann,et al.  SAR and optical remote sensing: Assessment of complementarity and interoperability in the context of a large-scale operational forest monitoring system , 2015 .

[47]  D. Lu.  Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon , 2005 .

[48]  S. Goetz,et al.  Mapping and monitoring carbon stocks with satellite observations: a comparison of methods , 2009, Carbon balance and management.

[49]  Werner A. Kurz,et al.  Carbon budget of the Canadian forest product sector , 1999 .

[50]  Lars M. H. Ulander,et al.  Radiometric slope correction of synthetic-aperture radar images , 1996, IEEE Trans. Geosci. Remote. Sens..

[51]  D. Lu.  The potential and challenge of remote sensing‐based biomass estimation , 2006 .

[52]  W. Salas,et al.  Secondary Forest Age and Tropical Forest Biomass Estimation Using Thematic Mapper Imagery , 2000 .

[53]  Dirk Tiede,et al.  Supervised and forest type-specific multi-scale segmentation for a one-level-representation of single trees , 2006 .

[54]  M. Murthy,et al.  Assessment of change in forest cover and biomass using geospatial techniques to support REDD+ activities in Nepal , 2015 .

[55]  Josaphat Tetuko Sri Sumantyo,et al.  Retrieval of tropical forest biomass information from ALOS PALSAR data , 2013 .

[56]  M. Weir,et al.  Quantification of carbon stock to understand two different forest management regimes in Kayar Khola watershed, Chitwan, Nepal , 2014, Journal of the Indian Society of Remote Sensing.

[57]  Fawwaz T. Ulaby,et al.  Toward consistent regional-to-global-scale vegetation characterization using orbital SAR systems , 1998, IEEE Trans. Geosci. Remote. Sens..

[58]  C. Proisy,et al.  Assessing aboveground tropical forest biomass using Google Earth canopy images. , 2012, Ecological applications : a publication of the Ecological Society of America.

[59]  Oliver Cartus,et al.  Mapping Canopy Height and Growing Stock Volume Using Airborne Lidar, ALOS PALSAR and Landsat ETM+ , 2012, Remote. Sens..

[60]  E. Nezry,et al.  Structure detection and statistical adaptive speckle filtering in SAR images , 1993 .

[61]  Xu Aigong,et al.  Integration of WorldView-2 and airborne LiDAR data for tree species level carbon stock mapping in Kayar Khola watershed, Nepal , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[62]  Kenneth Olofsson,et al.  Comparison of three individual tree crown detection methods , 2005, Machine Vision and Applications.

[63]  João Roberto dos Santos,et al.  Airborne P-band SAR applied to the aboveground biomass studies in the Brazilian tropical rainforest , 2003 .

[64]  Manabu Watanabe,et al.  Potential of high-resolution ALOS–PALSAR mosaic texture for aboveground forest carbon tracking in tropical region , 2015 .

[65]  D. Gritten,et al.  Predicting Future Conflict under REDD+ Implementation , 2013 .