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Improvement of Moderate Resolution Land Use and Land Cover Classification by Introducing Adjacent Region Features

Longlong Yu, Jinhe Su, Chun Li, Le Wang, Ze Luo, Baoping Yan
2018 Remote Sensing  
Landsat-like moderate resolution remote sensing images are widely used in land use and land cover (LULC) classification.  ...  The effects of the adjacent region features and the different feature set configurations on improving the LULC classification were evaluated by a series of well-controlled LULC classification experiments  ...  Figure 4 . 4 Overall accuracies of the land use and land cover (LULC) classifications with different feature set configurations.  ... 
doi:10.3390/rs10030414 fatcat:dmc2ouq2mfeincmjcosgvx2ixi


T. Mei, L. Zheng, S. Zhong
2012 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
This paper presents a joint pixel and region based multi-scale MRF model for high resolution image classification.  ...  The region shaped information is used to complement spectral signature for alleviating spectral signature ambiguity of different classes.  ...  Acknowledgements This work was supported by the National Natural Science Foundation of China, under Grant 40971219.  ... 
doi:10.5194/isprsarchives-xxxix-b3-237-2012 fatcat:m3gywvxpj5ez7ggte7cfsec6gy

Global Land Cover Heterogeneity Characteristics at Moderate Resolution for Mixed Pixel Modeling and Inversion

Wentao Yu, Jing Li, Qinhuo Liu, Yelu Zeng, Jing Zhao, Baodong Xu, Gaofei Yin
2018 Remote Sensing  
Global heterogeneity features at the 1-km scale are extracted from the 'GlobeLand30' land cover dataset with a spatial resolution of 30 m.  ...  This paper presents a parameterization scheme to describe land cover heterogeneity quantitatively by composition and boundary information based on high-resolution land cover products.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/rs10060856 fatcat:dwx5hnmvm5d6lasrrrvyqvlbdq

SAR Image Classification Using Fully Connected Conditional Random Fields Combined with Deep Learning and Superpixel Boundary Constraint

Zhensheng Sun, Miao Liu, Peng Liu, Juan Li, Tao Yu, Xingfa Gu, Jian Yang, Xiaofei Mi, Weijia Cao, Zhouwei Zhang
2021 Remote Sensing  
In the land cover classification experiments using the MSTAR, E-SAR and GF-3 datasets, the overall accuracy of our proposed method achieves 90.18 ± 0.37, 91.63 ± 0.27, and 90.91 ± 0.31, respectively.  ...  To mitigate some of the issues and to improve the pattern recognition of high-resolution SAR images, a ConvCRF model combined with superpixel boundary constraint is developed.  ...  Acknowledgments: The authors would like to thank the associate editor and anonymous reviewers for their helpful and constructive suggestions.  ... 
doi:10.3390/rs13020271 fatcat:f77fbdol6radxptnua7yrewlby

A Stratified Temporal Spectral Mixture Analysis Model for Mapping Cropland Distribution through MODIS Time-Series Data

Jinshui Zhang, Fenghua Wei, Peijun Sun, Yaozhong Pan, Zhoumiqi Yuan, Ya Yun
2015 Journal of Agricultural Science  
The proposed method used thematic map from MODIS classification as prior knowledge to determine the endmember set for each sub-region input into SMA model.  ...  The aim of study was to develop a stratified temporal spectral mixture analysis (STSMA) for cropland area estimation using MODIS time-series data to address the mixed pixel problem caused from coarse resolution  ...  Furthermore, thanks to the prior-knowledge introduced by classification, endmember colinearity which is evitable for conventional SMA could be solved at some degree using the strata to define the suitable  ... 
doi:10.5539/jas.v7n8p95 fatcat:5xuf7gc4enbrdpla5prho4kv4i

HOTEX: An approach for global mapping of human built-up and settlement extent

Panshi Wang, Chengquan Huang, James C. Tilton, Bin Tan, Eric C. Brown de Colstoun
2017 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)  
An innovative hierarchical object-based texture (HOTex) classification approach was designed to overcome spectral confusion between urban and nonurban land cover types.  ...  Using scene-level cross validation for results in Europe, we assessed the performance of HOTex and achieved a kappa coefficient of 0.91, compared to 0.74 from a baseline method using per-pixel classification  ...  HSeg combines the power of best merge region growing to delineate the boundaries between spatially adjacent region and spectral clustering to group spatially disjoint regions together.  ... 
doi:10.1109/igarss.2017.8127268 dblp:conf/igarss/WangHTTC17 fatcat:z7jk7eccqjhhfpttqdyvxpecr4

Index for the Consistent Measurement of Spatial Heterogeneity for Large-Scale Land Cover Datasets

Jing Yu, Shu Peng, Weiwei Zhang, Shun Kang
2020 ISPRS International Journal of Geo-Information  
Classification maps of land cover heterogeneity generated using the LCCI provide valuable insights and implications for regional conservation planning.  ...  One of the top research priorities is the quantification of land cover heterogeneity using effective landscape metrics.  ...  A recent study improved the land cover mapping accuracy by clustering the heterogeneity types of land cover, which helped to improve the classification accuracy of remote sensing-based land cover mapping  ... 
doi:10.3390/ijgi9080483 fatcat:sfvnduharbc63nbhgr7j74xhra

A Deep Convolution Neural Network Method for Land Cover Mapping: A Case Study of Qinhuangdao, China

Yunfeng Hu, Qianli Zhang, Yunzhi Zhang, Huimin Yan
2018 Remote Sensing  
This study used the new type of deep convolutional neural network to extract land cover information from Qinhuangdao City, Hebei Province, and compared the experimental results with those obtained by traditional  ...  This model performs the classification of multispectral and hyperspectral satellite images using deep neural networks, which improves the generalization ability of the model and simplifies the application  ...  Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/rs10122053 fatcat:hyl2sfxiercq3mrpx5cfguy5d4

Optimal Subset Selection of Time-Series MODIS Images and Sample Data Transfer with Random Forests for Supervised Classification Modelling

Fuqun Zhou, Aining Zhang
2016 Sensors  
The results of the case study of agricultural land cover classification at a regional scale show that using only about a half of the variables we can achieve land cover classification accuracy close to  ...  The variable importance feature is used to analyze and select optimal subsets of time-series MODIS imagery for efficient land cover mapping, and the outlier identification feature is utilized for transferring  ...  Acknowledgments: The authors would like to thank Junhua Li and Sylvain Leblanc, and the three anonymous reviewers for their valuable comments and suggestions for this improved manuscript.  ... 
doi:10.3390/s16111783 pmid:27792152 pmcid:PMC5134442 fatcat:bshuf4fkqnardplskix5jgi3by

Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions

Nathan C. Dadap, Alison M. Hoyt, Alexander R. Cobb, Doruk Oner, Mateusz Kozinski, Pascal V. Fua, Krishna Rao, Charles F. Harvey, Alexandra G. Konings
2021 AGU Advances  
Land use and subsidence data used in this study are available from Miettinen et al. (2016) and Hoyt et al. (2020)  ...  The code used to generate these maps are available at  ...  The non-drainage predictor features used were land use type and distance to peat edge (Text S2)-two features that were previously used to predict subsidence at regional scales -and VIIRS 375 m active fire  ... 
doi:10.1029/2020av000321 fatcat:6kauy2isujfjjgnma4vtk7j53m

A Combined Convolutional Neural Network for Urban Land-Use Classification with GIS Data

Jie Yu, Peng Zeng, Yaying Yu, Hongwei Yu, Liang Huang, Dongbo Zhou
2022 Remote Sensing  
Finally, land-use classification of high-resolution urban RSIs was achieved.  ...  The results indicated that the complex land-use types with heterogeneous features were more difficult to extract than the single-feature land-cover types.  ...  The Vaihingen and the Potsdam datasets were provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF).  ... 
doi:10.3390/rs14051128 fatcat:rechwr6tznd2ngobnrg7ndml7m

Hierarchical Remote Sensing Image Analysis via Graph Laplacian Energy

Zhang Huigang, Bai Xiao, Zheng Huaxin, Zhao Huijie, Zhou Jun, Cheng Jian, Lu Hanqing
2013 IEEE Geoscience and Remote Sensing Letters  
Such hierarchies can produce the state-of-the-art segmentations and can be used in the classification.  ...  In the classification stage, we apply local self-similarity feature to capture the internal geometric layouts of regions in an image.  ...  We also introduced the LSS for urban-area land-cover classification in remote sensing images.  ... 
doi:10.1109/lgrs.2012.2207087 fatcat:mnc2ac32yzbodjnhrgdfvu3gre

Land cover classification in multispectral imagery using clustering of sparse approximations over learned feature dictionaries

Daniela I. Moody, Steven P. Brumby, Joel C. Rowland, Garrett L. Altmann
2014 Journal of Applied Remote Sensing  
We learn our dictionaries from millions of overlapping multispectral image patches and then use a pursuit search to generate classification features.  ...  Land cover labels are automatically generated using unsupervised clustering of sparse approximations (CoSA).  ...  Application of the methodology and continued development is supported by DOE's Office of Science, Biological and Environmental Research (BER) Program, through the Next Generation Ecosystem Experiment (  ... 
doi:10.1117/1.jrs.8.084793 fatcat:spdxm3aa6fexfe5jpvafdnco4u

A Comprehensive Review on Pixel Oriented and Object Oriented Methods for Information Extraction from Remotely Sensed Satellite Images with a Special Emphasis on Cryospheric Applications

Shridhar D. Jawak, Prapti Devliyal, Alvarinho J. Luis
2015 Advances in Remote Sensing  
Information extraction in cryospheric regions is challenging, accounting to the very similar and conflicting spectral responses of the features present in the region.  ...  The present review focuses on the strengths and weaknesses of traditional pixel-based classification (PBC) and the advances of object-oriented classification (OOC) algorithms employed for the extraction  ...  Rajan, Director, NCAOR for his encouragement and motivation of this research. We acknowledge Dr. T. P. Singh (Director, SIT), Dr. Kanchan Khare (HOD, Department of Civil Engineering, SIT), S. D.  ... 
doi:10.4236/ars.2015.43015 fatcat:2buitjcwwbekrk6bcb7k6gljsq

Multisensor Microwave Sensitivity to Freeze/Thaw Dynamics Across a Complex Boreal Landscape

Erika Podest, Kyle C. McDonald, John S. Kimball
2014 IEEE Transactions on Geoscience and Remote Sensing  
Accurate characterization of these processes can improve regional assessment of seasonal carbon dynamics and climate feedbacks.  ...  We applied a change detection algorithm to the C-band and L-band data over both study areas and analyzed the FT classifications with land cover information.  ...  The classifier was trained, and results were validated based on a classification map of the region [47] , achieving 95% overall land cover classification accuracy.  ... 
doi:10.1109/tgrs.2014.2303635 fatcat:xvi3uys4mvco5exkgxmszrjnbm
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