Estimating aboveground biomass and carbon stocks in periurban Andean secondary forests using very high resolution imagery

Periurban forests are key to offsetting anthropogenic carbon emissions, but they are under constant threat from urbanization. In particular, secondary Neotropical forest types in Andean periurban areas have a high potential to store carbon, but are currently poorly characterized. To address this lack of information, we developed a method to estimate periurban aboveground biomass (AGB)—a proxy for multiple ecosystem services—of secondary Andean forests near Bogota, Colombia, based on very high resolution (VHR) GeoEye-1, Pleiades-1A imagery and field-measured plot data. Specifically, we tested a series of different pre-processing workflows to derive six vegetation indices that were regressed against in situ estimates of AGB. Overall, the coupling of linear models and the Ratio Vegetation Index produced the most satisfactory results. Atmospheric and topographic correction proved to be key in improving model fit, especially in high aerosol and rugged terrain such as the Andes. Methods and findings provide baseline AGB and carbon stock information for little studied periurban Andean secondary forests. The methodological approach can also be used for integrating limited forest monitoring plot AGB data with very high resolution imagery for cost-effective modelling of ecosystem service provision from forests, monitoring reforestation and forest cover change, and for carbon offset assessments.

[1]  Above-ground biomass and carbon stocks in a secondary forest in comparison with adjacent primary forest on limestone in Seram, the Moluccas, Indonesia , 2014 .

[2]  Susan G. Letcher,et al.  Biomass resilience of Neotropical secondary forests , 2016, Nature.

[3]  Dave Kendal,et al.  Multiple ecosystem services and disservices of the urban forest establishing their connections with landscape structure and sociodemographics , 2014 .

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

[5]  Renata Ribeiro do Valle Gonçalves,et al.  Coffee Crop's Biomass and Carbon Stock Estimation With Usage of High Resolution Satellites Images , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[6]  Steven M. Manson,et al.  A comparison of illumination geometry-based methods for topographic correction of QuickBird images of an undulant area , 2008 .

[7]  Andrés Etter,et al.  Land Cover Change in Colombia: Surprising Forest Recovery Trends between 2001 and 2010 , 2012, PloS one.

[8]  A. Huete,et al.  A review of vegetation indices , 1995 .

[9]  A. Chao,et al.  Resilience of tropical rain forests: tree community reassembly in secondary forests. , 2009, Ecology letters.

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

[11]  J. Grace Understanding and managing the global carbon cycle , 2004 .

[12]  Giles M. Foody,et al.  The relationship between the biomass of Cameroonian tropical forests and radiation reflected in middle infrared wavelengths (3.0-5.0 mu m) , 1999 .

[13]  Anand M. Osuri,et al.  Spatio-temporal variation in forest cover and biomass across sacred groves in a human-modified landscape of India's Western Ghats , 2014 .

[14]  C. Perry,et al.  Functional equivalence of spectral vegetation indices , 1984 .

[15]  B. Griscom,et al.  Biomass estimations and carbon stock calculations in the oil palm plantations of African derived savannas using IKONOS data , 2004 .

[16]  B. Markham,et al.  Summary of Current Radiometric Calibration Coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI Sensors , 2009 .

[17]  Jun Zhao,et al.  Quantification of aboveground forest biomass using Quickbird imagery, topographic variables, and field data , 2013 .

[18]  D. Jupp,et al.  A physics-based atmospheric and BRDF correction for Landsat data over mountainous terrain , 2012 .

[19]  G. Daily Nature's services: societal dependence on natural ecosystems. , 1998 .

[20]  M. Ashton,et al.  Growth of native tree species planted in montane reforestation projects in the Colombian and Ecuadorian Andes differs among site and species , 2016, New Forests.

[21]  L. D. Miller,et al.  Remote mapping of standing crop biomass for estimation of the productivity of the shortgrass prairie, Pawnee National Grasslands, Colorado , 1972 .

[22]  A. Gentry Seasonally Dry Tropical Forests: Diversity and floristic composition of neotropical dry forests , 1995 .

[23]  Marie-Françoise Courel,et al.  Utilisation des bandes spectrales du vert et du rouge pour une meilleure évaluation des formations végétales actives , 1991 .

[24]  Sean C. Thomas,et al.  Carbon Content of Tree Tissues: A Synthesis , 2012 .

[25]  A. Lugo,et al.  The Potential for Species Conservation in Tropical Secondary Forests , 2009, Conservation biology : the journal of the Society for Conservation Biology.

[26]  Warren B. Cohen,et al.  Estimation of crown biomass of Pinus pinaster stands and shrubland above-ground biomass using forest inventory data, remotely sensed imagery and spatial prediction models , 2012 .

[27]  M. D. Craig,et al.  Analysis of aircraft spectrometer data with logarithmic residuals , 1985 .

[28]  P. Chavez An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data , 1988 .

[29]  M. Harmon,et al.  Total carbon stocks in a tropical forest landscape of the Porce region, Colombia , 2007 .

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

[31]  R. Fournier,et al.  A comparison of four methods to map biomass from Landsat-TM and inventory data in western Newfoundland , 2006 .

[32]  P. Teillet,et al.  On the Slope-Aspect Correction of Multispectral Scanner Data , 1982 .

[33]  Onder Kayadibi,et al.  Evaluation of imaging spectroscopy and atmospheric correction of multispectral images (Aster and LandsaT 7 ETM+) , 2011, Proceedings of 5th International Conference on Recent Advances in Space Technologies - RAST2011.

[34]  R. Etter,et al.  Multitemporal analysis (1940-1996) of land cover changes in the southwestern Bogotá highplain (Colombia) , 2002 .

[35]  R. B. Jackson,et al.  A Large and Persistent Carbon Sink in the World’s Forests , 2011, Science.

[36]  Mark O. Kimberley,et al.  Allometric Equations for Estimating Carbon Stocks in Natural Forest in New Zealand , 2012 .

[37]  Yadvinder Malhi,et al.  Fingerprinting the impacts of global change on tropical forests. , 2004, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[38]  J. V. Soares,et al.  Distribution of aboveground live biomass in the Amazon basin , 2007 .

[39]  David Edwards,et al.  Cheap carbon and biodiversity co-benefits from forest regeneration in a hotspot of endemism , 2014 .

[40]  P. Stevenson,et al.  Live aboveground carbon stocks in natural forests of Colombia , 2016 .

[41]  Hongxing Liu,et al.  Retrieval of Mangrove Aboveground Biomass at the Individual Species Level with WorldView-2 Images , 2015, Remote. Sens..

[42]  John A. Richards,et al.  Remote Sensing Digital Image Analysis , 1986 .

[43]  Sean T. O'Brien Nature's Services: Societal Dependence on Natural Ecosystems , 1998 .

[44]  A. McGuire,et al.  Global climate change and terrestrial net primary production , 1993, Nature.

[45]  Jun Yang,et al.  Quantifying the Impact of Different Ways to Delimit Study Areas on the Assessment of Species Diversity of an Urban Forest , 2016 .

[46]  S. Sandmeier,et al.  Radiometric corrections of topographically induced effects on Landsat TM data in an alpine environment , 1993 .

[47]  David P. Miller,et al.  Status of atmospheric correction using a MODTRAN4-based algorithm , 2000, SPIE Defense + Commercial Sensing.

[48]  A. Baccini,et al.  Capabilities and limitations of Landsat and land cover data for aboveground woody biomass estimation of Uganda , 2012 .

[49]  M. Clark,et al.  Deforestation and Reforestation of Latin America and the Caribbean (2001–2010) , 2013 .

[50]  D. C. Robertson,et al.  MODTRAN cloud and multiple scattering upgrades with application to AVIRIS , 1998 .

[51]  R. Dickinson,et al.  Couplings between changes in the climate system and biogeochemistry , 2007 .

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

[53]  Craig A. Coburn,et al.  SCS+C: a modified Sun-canopy-sensor topographic correction in forested terrain , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[54]  D. Roberts,et al.  Comparison of various techniques for calibration of AIS data , 1986 .

[55]  M. Keller,et al.  Estimation of biomass and carbon stocks: the case of the Atlantic Forest , 2008 .

[56]  L. S. Galvão,et al.  Investigation of terrain illumination effects on vegetation indices and VI-derived phenological metrics in subtropical deciduous forests , 2016 .

[57]  J. Terborgh,et al.  The regional variation of aboveground live biomass in old‐growth Amazonian forests , 2006 .

[58]  Christina L. Staudhammer,et al.  "Socio-ecological dynamics and inequality in Bogotá, Colombia's public urban forests and their ecosystem services" , 2015 .

[59]  L. Ji Performance evaluation of spectral vegetation indices using a statistical sensitivity function , 2017 .

[60]  Chi Zhang,et al.  The spatiotemporal patterns of vegetation coverage and biomass of the temperate deserts in Central Asia and their relationships with climate controls , 2016 .

[61]  K. Shadan,et al.  Available online: , 2012 .

[62]  Bernard J. Lewis,et al.  An Application of Remote Sensing Data in Mapping Landscape-Level Forest Biomass for Monitoring the Effectiveness of Forest Policies in Northeastern China , 2013, Environmental Management.

[63]  Bo Wu,et al.  Estimating aboveground biomass in Mu Us Sandy Land using Landsat spectral derived vegetation indices over the past 30 years , 2013, Journal of Arid Land.

[64]  S. Goetz,et al.  Radiometric rectification - Toward a common radiometric response among multidate, multisensor images , 1991 .

[65]  Graham D. Farquhar,et al.  Carbon Dioxide and Vegetation , 1997, Science.

[66]  Emilio Chuvieco,et al.  Aboveground biomass assessment in Colombia: a remote sensing approach. , 2009 .

[67]  Bunkei Matsushita,et al.  Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to Topographic Effects: A Case Study in High-Density Cypress Forest , 2007, Sensors.

[68]  L. Volkova,et al.  Empirical Estimates of Aboveground Carbon in Open Eucalyptus Forests of South-Eastern Australia and Its Potential Implication for National Carbon Accounting , 2015 .

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

[70]  J. Cuatrecasas Aspectos de la vegetacion natural de Colombia , 1958 .

[71]  R. Dirzo,et al.  Seasonally dry tropical forests: ecology and conservation. , 2011 .

[72]  Moreno Gamboa,et al.  Herramientas para el mejoramiento de la actividad del Grupo de Relaciones Internacionales y Cooperación Técnica - GRICT- del Departamento Administrativo Nacional de Estadística – DANE , 2010 .

[73]  H. Grau,et al.  Guest Editorial, part of a Special Feature on The influence of human demography and agriculture on natural systems in the Neotropics Globalization and Land-Use Transitions in Latin America , 2008 .

[74]  John R. Schott,et al.  Ground truth-based variability analysis of atmospheric inversion in the presence of clouds , 2006, SPIE Optics + Photonics.

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

[76]  Kenneth B. Pierce,et al.  Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches , 2010 .

[77]  Huaqiang Du,et al.  Moso bamboo forest extraction and aboveground carbon storage estimation based on multi-source remotely sensed images , 2013 .

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

[79]  Thomas R. Crow,et al.  Estimating aboveground biomass using Landsat 7 ETM+ data across a managed landscape in northern Wisconsin, USA , 2004 .