Estimation of the stand ages of tropical secondary forests after shifting cultivation based on the combination of WorldView-2 and time-series Landsat images
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[1] Jonathan P. Dash,et al. Characterising forest structure using combinations of airborne laser scanning data, RapidEye satellite imagery and environmental variables , 2016 .
[2] O. Mutanga,et al. Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas , 2015 .
[3] Jin Chen,et al. Global land cover mapping at 30 m resolution: A POK-based operational approach , 2015 .
[4] 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 .
[5] F. Achard,et al. Remote sensing of forest degradation in Southeast Asia—Aiming for a regional view through 5–30 m satellite data , 2014 .
[6] Holmes Finch,et al. A Comparison of Methods for Group Prediction with High Dimensional Data , 2014 .
[7] D. Sheil,et al. Four Decades of Forest Persistence, Clearance and Logging on Borneo , 2014, PloS one.
[8] F. Achard,et al. Determination of tropical deforestation rates and related carbon losses from 1990 to 2010 , 2014, Global change biology.
[9] J. Powers,et al. Stand age and soils as drivers of plant functional traits and aboveground biomass in secondary tropical dry forest , 2014 .
[10] Ignacio Melendez-Pastor,et al. Remotely sensed biomass over steep slopes: An evaluation among successional stands of the Atlantic Forest, Brazil , 2014 .
[11] Thomas Blaschke,et al. Geographic Object-Based Image Analysis – Towards a new paradigm , 2014, ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing.
[12] C. Justice,et al. High-Resolution Global Maps of 21st-Century Forest Cover Change , 2013, Science.
[13] M. Hansen,et al. Reconciling Forest Conservation and Logging in Indonesian Borneo , 2013, PloS one.
[14] Frédéric Achard,et al. Change in tropical forest cover of Southeast Asia from 1990 to 2010 , 2013 .
[15] L. Durieux,et al. Advances in Geographic Object-Based Image Analysis with ontologies: A review of main contributions and limitations from a remote sensing perspective , 2013 .
[16] Ali Shamsoddini,et al. Pine plantation structure mapping using WorldView-2 multispectral image , 2013 .
[17] Dongmei Chen,et al. Change detection from remotely sensed images: From pixel-based to object-based approaches , 2013 .
[18] Frédéric Achard,et al. Combining Landsat TM/ETM+ and ALOS AVNIR-2 Satellite Data for Tropical Forest Cover Change Detection , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[19] T. A. Black,et al. Influence of stand age on the magnitude and seasonality of carbon fluxes in Canadian forests , 2012 .
[20] K. T. Vashum,et al. Methods to Estimate Above-Ground Biomass and Carbon Stock in Natural Forests - A Review , 2012 .
[21] Richard A. Birdsey,et al. Relationships between net primary productivity and forest stand age in U.S. forests , 2012 .
[22] Thomas R. Loveland,et al. A review of large area monitoring of land cover change using Landsat data , 2012 .
[23] Sandra Eckert,et al. Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data , 2012, Remote. Sens..
[24] Ben Somers,et al. Assessing post-fire vegetation recovery using red-near infrared vegetation indices: Accounting for background and vegetation variability , 2012 .
[25] Frédéric Achard,et al. An automated approach for segmenting and classifying a large sample of multi-date Landsat imagery for pan-tropical forest monitoring , 2011 .
[26] Arnon Karnieli,et al. redicting forest structural parameters using the image texture derived from orldView-2 multispectral imagery in a dryland forest , Israel , 2011 .
[27] J. Nichol,et al. Improved forest biomass estimates using ALOS AVNIR-2 texture indices , 2011 .
[28] Jing M. Chen,et al. ormalized algorithm for mapping and dating forest disturbances and regrowth or the United States , 2011 .
[29] Stephen V. Stehman,et al. International Journal of Applied Earth Observation and Geoinformation: Time-Series Analysis of Multi-Resolution Optical Imagery for Quantifying Forest Cover Loss in Sumatra and Kalimantan, Indonesia , 2011 .
[30] Weiliang Fan,et al. Estimation of aboveground carbon stock of Moso bamboo (Phyllostachys heterocycla var. pubescens) forest with a Landsat Thematic Mapper image , 2011 .
[31] Janet E. Nichol,et al. Improved Biomass Estimation Using the Texture Parameters of Two High-Resolution Optical Sensors , 2011, IEEE Transactions on Geoscience and Remote Sensing.
[32] J. Dupuy,et al. Influence of landscape structure and stand age on species density and biomass of a tropical dry forest across spatial scales , 2011, Landscape Ecology.
[33] J. J. Kendawang,et al. Changes in above- and belowground biomass in early successional tropical secondary forests after shifting cultivation in Sarawak, Malaysia. , 2010 .
[34] Craig A. Coburn,et al. Estimating aboveground forest biomass from canopy reflectance model inversion in mountainous terrain , 2010 .
[35] Jungho Im,et al. Synergistic use of QuickBird multispectral imagery and LIDAR data for object-based forest species classification , 2010 .
[36] S. Goward,et al. An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks , 2010 .
[37] A. Huth,et al. The impact of fragmentation and density regulation on forest succession in the Atlantic rain forest , 2009 .
[38] J. Vogelmann,et al. Monitoring forest changes in the southwestern United States using multitemporal Landsat data , 2009 .
[39] Matthew C. Hansen,et al. Quantifying changes in the rates of forest clearing in Indonesia from 1990 to 2005 using remotely sensed data sets , 2009 .
[40] R. Pu. Broadleaf species recognition with in situ hyperspectral data , 2009 .
[41] Walter C. Bausch,et al. Quickbird satellite and ground-based multispectral data correlations with agronomic parameters of irrigated maize grown in small plots , 2008 .
[42] J. Townshend,et al. Humid tropical forest clearing from 2000 to 2005 quantified by using multitemporal and multiresolution remotely sensed data , 2008, Proceedings of the National Academy of Sciences.
[43] W. Cohen,et al. North American forest disturbance mapped from a decadal Landsat record , 2008 .
[44] W. Ju,et al. Combining remote sensing imagery and forest age inventory for biomass mapping. , 2007, Journal of environmental management.
[45] Warren B. Cohen,et al. Trajectory-based change detection for automated characterization of forest disturbance dynamics , 2007 .
[46] S. Sarkar,et al. Systematic conservation planning , 2000, Nature.
[47] J. J. Kendawang,et al. Effects of burning strength in shifting cultivation on the early stage of secondary succession in Sarawak, Malaysia , 2007 .
[48] C. Burnett,et al. Assessing the mire conservation status of a raised bog site in Salzburg using object-based monitoring and structural analysis , 2007 .
[49] Tatiana Mora Kuplich,et al. Classifying regenerating forest stages in Amazônia using remotely sensed images and a neural network , 2006 .
[50] Carl J. Huberty,et al. Applied MANOVA and discriminant analysis , 2006 .
[51] M. Jepsen. Above-ground carbon stocks in tropical fallows, Sarawak, Malaysia , 2006 .
[52] D. Lu. The potential and challenge of remote sensing‐based biomass estimation , 2006 .
[53] D. Lindenmayer,et al. Biodiversity, ecosystem function, and resilience: ten guiding principles for commodity production landscapes , 2006 .
[54] R. DeFries,et al. A global overview of the conservation status of tropical dry forests , 2006 .
[55] J. Gamon,et al. Research Priorities for Neotropical Dry Forests 1 , 2005 .
[56] P. Atkinson,et al. Relating SAR image texture to the biomass of regenerating tropical forests , 2005 .
[57] N. Pettorelli,et al. Using the satellite-derived NDVI to assess ecological responses to environmental change. , 2005, Trends in ecology & evolution.
[58] D. Roberts,et al. Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales , 2005 .
[59] Sari C. Saunders,et al. Edge Influence on Forest Structure and Composition in Fragmented Landscapes , 2005 .
[60] G. Daily,et al. COUNTRYSIDE BIOGEOGRAPHY OF NEOTROPICAL HERBACEOUS AND SHRUBBY PLANTS , 2005 .
[61] David B. Lindenmayer,et al. Making the matrix matter: challenges in Australian grazing landscapes , 2005, Biodiversity & Conservation.
[62] J. Tenhunen,et al. On the relationship of NDVI with leaf area index in a deciduous forest site , 2005 .
[63] T. Ricketts,et al. Confronting a biome crisis: global disparities of habitat loss and protection , 2004 .
[64] Leslie Ries,et al. Ecological Responses to Habitat Edges: Mechanisms, Models, and Variability Explained , 2004 .
[65] B. Devereux,et al. An efficient image segmentation algorithm for landscape analysis , 2004 .
[66] A. Rango,et al. Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico , 2004 .
[67] James T. Cronin,et al. THE MATRIX ENHANCES THE EFFECTIVENESS OF CORRIDORS AND STEPPING STONES , 2004 .
[68] N. Coops,et al. High Spatial Resolution Remotely Sensed Data for Ecosystem Characterization , 2004 .
[69] Matthew E. Watts,et al. Effectiveness of the global protected area network in representing species diversity , 2004, Nature.
[70] E. Davidson,et al. Classifying successional forests using Landsat spectral properties and ecological characteristics in eastern Amazônia , 2003 .
[71] C. Burnett,et al. A multi-scale segmentation/object relationship modelling methodology for landscape analysis , 2003 .
[72] Magnus Nyström,et al. Reserves, Resilience and Dynamic Landscapes , 2003, Ambio.
[73] T. Benton,et al. Farmland biodiversity: is habitat heterogeneity the key? , 2003 .
[74] D. Lindenmayer,et al. Conserving Forest Biodiversity: A Comprehensive Multiscaled Approach , 2002 .
[75] J. Liu,et al. Ecological Degradation in Protected Areas: The Case of Wolong Nature Reserve for Giant Pandas , 2001, Science.
[76] G. Asner,et al. Cloud cover in Landsat observations of the Brazilian Amazon , 2001 .
[77] R. Dirzo,et al. Deforestation of seasonally dry tropical forest: a national and local analysis in Mexico , 2000 .
[78] Richard G. Oderwald,et al. Spectral Separability among Six Southern Tree Species , 2000 .
[79] W. Salas,et al. Secondary Forest Age and Tropical Forest Biomass Estimation Using Thematic Mapper Imagery , 2000 .
[80] J. Hyyppä,et al. Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes , 2000 .
[81] K. Kitayama,et al. Structure, composition and species diversity in an altitude-substrate matrix of rain forest tree communities on Mount Kinabalu, Borneo , 1999, Plant Ecology.
[82] Tung Fung,et al. Hyperspectral data analysis for subtropical tree species recognition , 1998, IGARSS '98. Sensing and Managing the Environment. 1998 IEEE International Geoscience and Remote Sensing. Symposium Proceedings. (Cat. No.98CH36174).
[83] P. Ranta,et al. The fragmented Atlantic rain forest of Brazil: size, shape and distribution of forest fragments , 1998, Biodiversity & Conservation.
[84] Ruiliang Pu,et al. Conifer species recognition: An exploratory analysis of in situ hyperspectral data , 1997 .
[85] D. H. Hoekman,et al. Radar monitoring system for sustainable forest management in Indonesia , 1997, IGARSS'97. 1997 IEEE International Geoscience and Remote Sensing Symposium Proceedings. Remote Sensing - A Scientific Vision for Sustainable Development.
[86] Didier Tanré,et al. Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview , 1997, IEEE Trans. Geosci. Remote. Sens..
[87] W. Salas,et al. Mapping deforestation and secondary growth in Rondonia, Brazil, using imaging radar and thematic mapper data☆ , 1997 .
[88] A. Gitelson,et al. Use of a green channel in remote sensing of global vegetation from EOS- MODIS , 1996 .
[89] R. Lucas,et al. Identifying terrestrial carbon sinks: Classification of successional stages in regenerating tropical forest from Landsat TM data , 1996 .
[90] Christopher O. Justice,et al. Spatial variability of images and the monitoring of changes in the Normalized Difference Vegetation Index , 1995 .
[91] Eduardo S. Brondizio,et al. INTEGRATING AMAZONIAN VEGETATION, LAND-USE, AND SATELLITE DATA , 1994 .
[92] K. Kitayama. An altitudinal transect study of the vegetation on Mount Kinabalu, Borneo , 1992, Vegetatio.
[93] W. Dulaney,et al. Normalized difference vegetation index measurements from the Advanced Very High Resolution Radiometer , 1991 .
[94] G. Birth,et al. Measuring the Color of Growing Turf with a Reflectance Spectrophotometer1 , 1968 .
[95] V. K. Dadhwal,et al. Potential of Envisat ASAR data for woody biomass assessment , 2010 .
[96] 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 .
[97] J. Beaman,et al. Mount Kinabalu: hotspot of plant diversity in Borneo. , 2005 .
[98] W. Salas,et al. Mapping secondary tropical forest and forest age from SPOT HRV data , 1999 .
[99] C. Goulding,et al. Adapting Finnish Multi-Source Forest Inventory Techniques to the New Zealand Preharvest Inventory , 1999 .
[100] K. P. Reese,et al. LANDSCAPE CHANGES WITHIN THE HISTORICAL DISTRIBUTION OF COLUMBIAN SHARP-TAILED GROUSE IN EASTERN WASHINGTON : IS THERE HOPE? , 1998 .
[101] S. Ekstrand,et al. Landsat TM-based forest damage assessment : correction for topographic effects , 1996 .
[102] R. Forman. Land Mosaics: The Ecology of Landscapes and Regions , 1995 .
[103] S. Alam,et al. Framework Convention on Climate Change , 1993 .
[104] G. H. Rosenfield,et al. A coefficient of agreement as a measure of thematic classification accuracy. , 1986 .
[105] B. Tabachnick,et al. Using Multivariate Statistics , 1983 .
[106] D. Deering. Measuring forage production of grazing units from Landsat MSS data , 1975 .