Mapping and estimating the total living biomass and carbon in low-biomass woodlands using Landsat 8 CDR data
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Terje Gobakken | Erik Næsset | Ole Martin Bollandsås | Johannes Breidenbach | Eliakimu Zahabu | Svein Solberg | Belachew Gizachew | Ernest William Mauya | E. Næsset | S. Solberg | O. Bollandsås | T. Gobakken | J. Breidenbach | Belachew Gizachew | E. Mauya | Eliakimu Zahabu | E. Zahabu
[1] W. Schroeder,et al. Active fire detection using Landsat-8/OLI data , 2016 .
[2] M. Herold,et al. An integrated pan‐tropical biomass map using multiple reference datasets , 2016, Global change biology.
[3] Terje Gobakken,et al. Mapping and estimating forest area and aboveground biomass in miombo woodlands in Tanzania using data from airborne laser scanning, TanDEM-X, RapidEye, and global forest maps: A comparison of estimated precision , 2016 .
[4] Liviu Theodor Ene,et al. Modelling aboveground forest biomass using airborne laser scanner data in the miombo woodlands of Tanzania , 2015, Carbon Balance and Management.
[5] Ø. Dick,et al. Spatial distribution of temporal dynamics in anthropogenic fires in miombo savanna woodlands of Tanzania , 2015, Carbon Balance and Management.
[6] Tarquinio Mateus Magalhães. Allometric equations for estimating belowground biomass of Androstachys johnsonii Prain , 2015, Carbon Balance and Management.
[7] R. Valentini,et al. Uncertainty of remotely sensed aboveground biomass over an African tropical forest: Propagating errors from trees to plots to pixels , 2015 .
[8] Xiaolin Zhu,et al. Improving forest aboveground biomass estimation using seasonal Landsat NDVI time-series , 2015 .
[9] O. Mutanga,et al. Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa , 2015 .
[10] L. Amekudzi,et al. Carbon dioxide fluxes from contrasting ecosystems in the Sudanian Savanna in West Africa , 2015, Carbon Balance and Management.
[11] Y. Ngaga,et al. Management, Growth, and Carbon Storage in Miombo Woodlands of Tanzania , 2014 .
[12] Jason C. Neff,et al. Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery , 2014, Remote. Sens..
[13] Michael A. Wulder,et al. Historical forest biomass dynamics modelled with Landsat spectral trajectories , 2014 .
[14] E. Tomppo,et al. A sampling design for a large area forest inventory: case Tanzania , 2014 .
[15] Martha C. Anderson,et al. Landsat-8: Science and Product Vision for Terrestrial Global Change Research , 2014 .
[16] Ole Martin Bollandsås,et al. Allometric models for prediction of above- and belowground biomass of trees in the miombo woodlands of Tanzania , 2013 .
[17] Pavel Propastin,et al. Large-scale mapping of aboveground biomass of tropical rainforest in Sulawesi, Indonesia, using Landsat ETM+ and MODIS data , 2013 .
[18] O. Bollandsås,et al. Relationships between diameter and height of trees in natural tropical forest in Tanzania , 2013 .
[19] C. Justice,et al. High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.
[20] N. Ribeiro,et al. Monitoring vegetation dynamics and carbon stock density in miombo woodlands , 2013, Carbon Balance and Management.
[21] S. Goetz,et al. Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps , 2013, Carbon Balance and Management.
[22] Feng Gao,et al. LEDAPS Calibration, Reflectance, Atmospheric Correction Preprocessing Code, Version 2 , 2013 .
[23] Julia A. Barsi,et al. The next Landsat satellite: The Landsat Data Continuity Mission , 2012 .
[24] Lammert Kooistra,et al. Assessing capacities of non-Annex I countries for national forest monitoring in the context of REDD+ , 2012 .
[25] David Saah,et al. Aboveground Forest Biomass Estimation with Landsat and LiDAR Data and Uncertainty Analysis of the Estimates , 2012 .
[26] S. Goetz,et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps , 2012 .
[27] A. Baccini,et al. Capabilities and limitations of Landsat and land cover data for aboveground woody biomass estimation of Uganda , 2012 .
[28] A. Marshall,et al. Carbon storage, structure and composition of miombo woodlands in Tanzania's Eastern Arc Mountains , 2011 .
[29] W. Salas,et al. Benchmark map of forest carbon stocks in tropical regions across three continents , 2011, Proceedings of the National Academy of Sciences.
[30] Haydee Karszenbaum,et al. Assessing multi-temporal Landsat 7 ETM+ images for estimating above-ground biomass in subtropical dry forests of Argentina , 2010 .
[31] 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 .
[32] Sassan Saatchi,et al. Aboveground biomass and leaf area index (LAI) mapping for Niassa Reserve, northern Mozambique , 2008 .
[33] Jay D. Miller,et al. Quantifying burn severity in a heterogeneous landscape with a relative version of the delta Normalized Burn Ratio (dNBR) , 2007 .
[34] Marguerite Madden,et al. A linear mixed-effects model of biomass and volume of trees using Landsat ETM+ images , 2007 .
[35] S. Wulff. SAS for Mixed Models , 2007 .
[36] R. McRoberts. A model-based approach to estimating forest area , 2006 .
[37] R. Fournier,et al. A comparison of four methods to map biomass from Landsat-TM and inventory data in western Newfoundland , 2006 .
[38] R. Hall,et al. Modeling forest stand structure attributes using Landsat ETM+ data: Application to mapping of aboveground biomass and stand volume , 2006 .
[39] M. Duggin,et al. A temporal analysis of urban forest carbon storage using remote sensing , 2006 .
[40] J. Heiskanen. Estimating aboveground tree biomass and leaf area index in a mountain birch forest using ASTER satellite data , 2006 .
[41] J. Carreiras,et al. Estimation of tree canopy cover in evergreen oak woodlands using remote sensing , 2006 .
[42] D. Lu. Aboveground biomass estimation using Landsat TM data in the Brazilian Amazon , 2005 .
[43] Thomas R. Crow,et al. Estimating aboveground biomass using Landsat 7 ETM+ data across a managed landscape in northern Wisconsin, USA , 2004 .
[44] Kelly K. Caylor,et al. A simulation analysis of the detectability of understory burns in miombo woodlands , 2004 .
[45] R. Hall,et al. Empirical relations between Landsat TM spectral response and forest stands near Fort Simpson, Northwest Territories, Canada , 2002 .
[46] M. Steininger. Satellite estimation of tropical secondary forest above-ground biomass: Data from Brazil and Bolivia , 2000 .
[47] Xavier Pons,et al. On the applicability of Landsat TM images to Mediterranean forest inventories , 1998 .
[48] R. Lunetta,et al. A change detection experiment using vegetation indices. , 1998 .
[49] B. Everitt,et al. Analysis of longitudinal data , 1998, British Journal of Psychiatry.
[50] A. Huete,et al. A comparison of vegetation indices over a global set of TM images for EOS-MODIS , 1997 .
[51] B. Gao. NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .
[52] L. Skovgaard. NONLINEAR MODELS FOR REPEATED MEASUREMENT DATA. , 1996 .
[53] G. Rondeaux,et al. Optimization of soil-adjusted vegetation indices , 1996 .
[54] A. Huete,et al. A Modified Soil Adjusted Vegetation Index , 1994 .
[55] R. H. Haas,et al. Evaluating Landsat Thematic Mapper derived vegetation indices for estimating above-ground biomass on semiarid rangelands , 1993 .
[56] A. Huete. A soil-adjusted vegetation index (SAVI) , 1988 .
[57] S. Zeger,et al. Longitudinal data analysis using generalized linear models , 1986 .
[58] H. White. A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity , 1980 .
[59] S. Sohi. Agriculture, forestry and other land use , 2014 .
[60] T. Dokken,et al. Making REDD Work for Communities and Forest Conservation in Tanzania , 2014 .
[61] O. Edenhofer,et al. Climate change 2014 : mitigation of climate change , 2014 .
[62] E. Mtalo,et al. Multi-temporal assessment of forest cover, stocking parameters and above-ground tree biomass dynamics in Miombo Woodlands of Tanzania , 2013 .
[63] Eliakimu Zahabu,et al. Participatory Forest Carbon Assessment and REDD+: Learning from Tanzania , 2012 .
[64] easurements ei Ji,et al. stimating aboveground biomass in interior Alaska with Landsat data and field , 2012 .
[65] M. Kusaga. Participatory forest carbon assessment in Angai village land forest reserve in Liwale district, Lindi region, Tanzania , 2011 .
[66] Xuexia Chen,et al. Estimating aboveground forest biomass carbon and fire consumption in the U.S. Utah High Plateaus using data from the Forest Inventory and Analysis Program, Landsat, and LANDFIRE , 2011 .
[67] Michael A. Lefsky,et al. Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System , 2009 .
[68] Holly K. Gibbs,et al. New IPCC Tier-1 Global Biomass Carbon Map for the Year 2000 , 2008 .
[69] S. Goetz,et al. A first map of tropical Africa’s above-ground biomass derived from satellite imagery , 2008 .
[70] Pushpam Kumar. Agriculture (Chapter8) in IPCC, 2007: Climate change 2007: Mitigation of Climate Change. Contribution of Working Group III to the Fourth assessment Report of the Intergovernmental Panel on Climate Change , 2007 .
[71] M. Hill,et al. Spatial information for land use management , 2000 .
[72] S. Dondeyne,et al. No short cuts to sound forest management: experiences from a participatory survey in Angai forest, Tanzania , 1998 .
[73] B. Campbell. The miombo in transition: woodlands and welfare in Africa. , 1996 .
[74] B. Longest. Sampling techniques. , 1971, Hospitals.
[75] P. J. Huber. The behavior of maximum likelihood estimates under nonstandard conditions , 1967 .
[76] John Grace,et al. Edinburgh Research Explorer Above- and Belowground Carbon Stocks in a Miombo Woodland Landscape of Mozambique , 2022 .