Mapping rubber tree growth in mainland Southeast Asia using time-series MODIS 250 m NDVI and statistical data
暂无分享,去创建一个
Jefferson Fox | J. Fox | Zhe Li | Zhe Li
[1] Alan H. Strahler,et al. Global land cover mapping from MODIS: algorithms and early results , 2002 .
[2] P. Hernandez,et al. Predicting species distributions in poorly-studied landscapes , 2008, Biodiversity and Conservation.
[3] Hong Jiang,et al. In‐Process Classification Assessment of Remotely Sensed Imagery , 2005 .
[4] G. M. Foody. The Continuum of Classification Fuzziness in Thematic Mapping , 1999 .
[5] R. Gil Pontius,et al. Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA , 2001 .
[6] Giles M. Foody,et al. Fully-fuzzy supervised classification of sub-urban land cover from remotely sensed imagery: Statistical and artificial neural network approaches , 2001 .
[7] Sithong Thongmanivong,et al. Agrarian Land Use Transformation in Northern Laos: from Swidden to Rubber( Land Use Changes in the Uplands of Southeast Asia: Proximate and Distant Causes) , 2009 .
[8] A. Belward,et al. GLC2000: a new approach to global land cover mapping from Earth observation data , 2005 .
[9] J. Ross Quinlan,et al. Induction of Decision Trees , 1986, Machine Learning.
[10] Charles C Mann,et al. Addicted to rubber. , 2009, Science.
[11] Zhe Li,et al. Commitment and typicality measures for the Self-Organizing Map , 2010 .
[12] F. Maselli,et al. Estimating inter-annual crop area variation using multi-resolution satellite sensor images , 2004 .
[13] Russell G. Congalton,et al. A review of assessing the accuracy of classifications of remotely sensed data , 1991 .
[14] B. Wardlow,et al. Large-area crop mapping using time-series MODIS 250 m NDVI data: An assessment for the U.S. Central Great Plains , 2008 .
[15] Matthew C. Hansen,et al. Corn and Soybean Mapping in the United States Using MODIS Time‐Series Data Sets , 2007 .
[16] Chi-Farn Chen,et al. Monitoring of soil moisture variability in relation to rice cropping systems in the Vietnamese Mekong Delta using MODIS data , 2011 .
[17] D. Roy,et al. A method for integrating MODIS and Landsat data for systematic monitoring of forest cover and change in the Congo Basin , 2008 .
[18] R. Jensen,et al. Human/Environment Interactions, Remote Sensing, and Artificial Neural Networks: Modeling Longleaf Pine Sandhill Leaf Area and Burn History in North-Central Florida , 2004 .
[19] Peter A. Troch,et al. Hydrologic effects of the expansion of rubber (Hevea brasiliensis) in a tropical catchment , 2010 .
[20] C. Brodley,et al. Decision tree classification of land cover from remotely sensed data , 1997 .
[21] N. Campbell,et al. Derivation and applications of probabilistic measures of class membership from the maximum-likelihood classification , 1992 .
[22] K. Jusoff,et al. New Approaches in Estimating Rubberwood Standing Volume Using Airborne Hyperspectral Sensing , 2009 .
[23] J. Settle,et al. Linear mixing and the estimation of ground cover proportions , 1993 .
[24] Zhe Li. Fuzzy ARTMAP Based Neurocomputational Spatial Uncertainty Measures , 2008 .
[25] Hongmei Li,et al. Past, present and future land-use in Xishuangbanna, China and the implications for carbon dynamics , 2008 .
[26] Philip H. Page,et al. Spatial simulation modelling of land use/land cover change scenarios in northeastern Thailand: a cellular automata approach , 2006 .
[27] Min Cao,et al. Demand for rubber is causing the loss of high diversity rain forest in SW China , 2007, Biodiversity and Conservation.
[28] R. Lunetta,et al. Land-cover change detection using multi-temporal MODIS NDVI data , 2006 .
[29] C. Lippitt,et al. Mapping Selective Logging in Mixed Deciduous Forest: A Comparison of Machine Learning Algorithms , 2008 .
[30] B. Wardlow,et al. Analysis of time-series MODIS 250 m vegetation index data for crop classification in the U.S. Central Great Plains , 2007 .
[31] Robert Gilmore Pontius,et al. Using the Relative Operating Characteristic to Quantify Certainty in Prediction of Location of Land Cover Change in India , 2003, Trans. GIS.
[32] T. Mitchell Aide,et al. A scalable approach to mapping annual land cover at 250 m using MODIS time series data: A case study in the Dry Chaco ecoregion of South America , 2010 .
[33] Giles M. Foody,et al. Hard and soft classifications by a neural network with a non-exhaustively defined set of classes , 2002 .
[34] Jefferson Fox,et al. Swidden Change in Southeast Asia: Understanding Causes and Consequences , 2009 .
[35] Nasser M. Nasrabadi,et al. Pattern Recognition and Machine Learning , 2006, Technometrics.
[36] J. Townshend,et al. Global land cover classi(cid:142) cation at 1 km spatial resolution using a classi(cid:142) cation tree approach , 2004 .
[37] John B. Vogler,et al. Simulating Land-Cover Change in Montane Mainland Southeast Asia , 2012, Environmental Management.
[38] Mustafa Turker,et al. Sequential masking classification of multi‐temporal Landsat7 ETM+ images for field‐based crop mapping in Karacabey, Turkey , 2005 .
[39] Andrew P. Bradley,et al. The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..
[40] R. DeFries,et al. Classification trees: an alternative to traditional land cover classifiers , 1996 .
[41] Zhe Li,et al. Integrating Mahalanobis typicalities with a neural network for rubber distribution mapping , 2011 .
[42] E. Van Ranst,et al. Application of fuzzy logic to land suitability for rubber production in peninsular Thailand , 1996 .
[43] R. Shrestha,et al. Relating plant diversity to biomass and soil erosion in a cultivated landscape of the eastern seaboard region of Thailand , 2010 .
[44] Kevin P. Price,et al. Multitemporal, Moderate-Spatial-Resolution Remote Sensing of Modern Agricultural Production and Land Modification in the Brazilian Amazon , 2007 .
[45] Felix Rembold,et al. Estimation of Inter-annual Crop Area Variation by the Application of Spectral Angle Mapping to Low Resolution Multitemporal NDVI Images , 2006 .
[46] Jane Qiu,et al. Where the rubber meets the garden , 2009, Nature.
[47] D. Roy,et al. The availability of cloud-free Landsat ETM+ data over the conterminous United States and globally , 2008 .
[48] John B. Vogler,et al. Land-Use and Land-Cover Change in Montane Mainland Southeast Asia , 2005, Environmental management.
[49] Jianchu Xu,et al. The Rubber Juggernaut , 2009, Science.
[50] J. Townshend,et al. Detection of land cover changes using MODIS 250 m data , 2002 .
[51] Min Cao,et al. Impact of land use and land cover changes on ecosystem services in Menglun, Xishuangbanna, Southwest China , 2008, Environmental monitoring and assessment.
[52] R. Lefroy,et al. Spatial identification by satellite imagery of the crop–fallow rotation cycle in northern Laos , 2009 .
[53] J. Eastman,et al. Bayesian Soft Classification for Sub-Pixel Analysis: A Critical Evaluation , 2002 .
[54] A. J. W. De Wit,et al. Efficiency and accuracy of per-field classification for operational crop mapping , 2004 .