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SENSING URBAN LAND-USE PATTERNS BY INTEGRATING GOOGLE TENSORFLOW AND SCENE-CLASSIFICATION MODELS

Y. Yao, H. Liang, X. Li, J. Zhang, J. He
2017 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features.  ...  Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs).  ...  Only a small number of studies have focused on fusing remote-sensing image data with multi-source social media data to classify urban land use (Liu et al., 2017; Yao et al., 2016) .  ... 
doi:10.5194/isprs-archives-xlii-2-w7-981-2017 fatcat:mmjfjp36wveknpoomgq5t5uu7u

Sensing Urban Land-Use Patterns By Integrating Google Tensorflow And Scene-Classification Models [article]

Yao Yao, Haolin Liang, Xia Li, Jinbao Zhang, Jialv He
2017 arXiv   pre-print
To take advantage of the deep-learning method in detecting urban land-use patterns, we applied a transfer-learning-based remote-sensing image approach to extract and classify features.  ...  Then, a random-forest-based classifier was constructed and trained on these generated vectors to classify the actual urban land-use pattern on the scale of traffic analysis zones (TAZs).  ...  Only a small number of studies have focused on fusing remote-sensing image data with multi-source social media data to classify urban land use (Liu et al., 2017; Yao et al., 2016) .  ... 
arXiv:1708.01580v1 fatcat:roc2h6ape5c3dbcjv35qmlrtwm

An Ensemble Learning Approach for Urban Land Use Mapping Based on Remote Sensing Imagery and Social Sensing Data

Zhou Huang, Houji Qi, Chaogui Kang, Yuelong Su, Yu Liu
2020 Remote Sensing  
(POIs) and social media check-ins for the urban land use mapping task.  ...  Yet, the major challenge lies in the lack of a universal and reliable approach for the extraction and combination of physical and socioeconomic features derived from remote sensing imagery and social sensing  ...  To fill the research gap, this article proposes an ensemble-learning-approach-based solution of integrating rich features in remote sensing and social sensing data for urban land use mapping tasks.  ... 
doi:10.3390/rs12193254 fatcat:37co74t7jvbrljqyyvrnii2y4a

Social Sensing for Urban Land Use Identification

Adindha Surya Anugraha, Hone-Jay Chu, Muhammad Zeeshan Ali
2020 ISPRS International Journal of Geo-Information  
The accuracy assessment of land use classified maps shows that the integration of remote and social sensing, using the decision tree and random forest methods, yields accuracies of 83% and 86%, respectively  ...  This data mining approach is related to data cleaning/outlier removal and machine learning, and is used to achieve land use classification from remote and social sensing data.  ...  Urban Land Use Map The land use classified map is generated in three ways, namely, using remote sensing data only, using integration of remote sensing and social sensing data without data cleaning, and  ... 
doi:10.3390/ijgi9090550 fatcat:svdowtrthbabbdgl7cfl7ggp7y

Distributed Fusion of Heterogeneous Remote Sensing and Social Media Data: A Review and New Developments

Jun Li, Zhenjie Liu, Xinya Lei, Lizhe Wang
2021 Proceedings of the IEEE  
A new distributed fusion framework that can accelerate the fusion of heterogeneous remote sensing and social media data is proposed by decomposing large data sets into small ones and processing them in  ...  social media data).  ...  and demographic characteristics of urban land, thereby contributing to accurate remote sensing land-use mapping in complex urban systems [82] .  ... 
doi:10.1109/jproc.2021.3079176 fatcat:gk2xqgsipjfr7kfanauymtk724

Portraying Urban Functional Zones by Coupling Remote Sensing Imagery and Human Sensing Data

Wei Tu, Zhongwen Hu, Lefei Li, Jinzhou Cao, Jincheng Jiang, Qiuping Li, Qingquan Li
2018 Remote Sensing  
Remote sensing is another fast and efficient approach to capture land cover and land use data to facilitate related studies.  ...  Massive human sensing data are available, such as vehicle GPS data [32] [33] [34] , mobile phone records [35] [36] [37] [38] [39] [40] and social media data [41] [42] [43] [44] .  ...  The founding sponsors had no role in the design of the study; in the collection, analysis or interpretation of data; in the writing of the manuscript; nor in the decision to publish the results.  ... 
doi:10.3390/rs10010141 fatcat:kgxgbcjvwfahfh2v2akt4depgy

Urban Land Use and Land Cover Classification Using Multisource Remote Sensing Images and Social Media Data

Shi, Qi, Liu, Niu, Zhang
2019 Remote Sensing  
This study examined the capability of combined multisource remote sensing images and social media data in urban LULC classification.  ...  Social media data, "marks" left by people using mobile phones, have great potential to overcome this semantic gap.  ...  Acknowledgments: We would like to gratefully thank the anonymous reviewers for their insightful and helpful comments to improve the manuscript.  ... 
doi:10.3390/rs11222719 fatcat:uo2verzynratvc2udnho6ufc6q

Social Sensing: A New Approach to Understanding Our Socioeconomic Environments

Yu Liu, Xi Liu, Song Gao, Li Gong, Chaogui Kang, Ye Zhi, Guanghua Chi, Li Shi
2015 Annals of the Association of American Geographers  
In the coming big data era, GIScientists should investigate theories in using social sensing data, such as data representativeness and quality, and develop new tools to deal with social sensing data.  ...  This article conceptually bridges social sensing with remote sensing and points out the major issues when applying social sensing data and associated analytics.  ...  Such a limitation can be compensated for by integrating remote sensing data with social sensing data. A number of issues should be paid attention to when using social sensing data, however.  ... 
doi:10.1080/00045608.2015.1018773 fatcat:cuul5c75ifah3k35gjfbmybata

Putting people in the picture: Combining big location-based social media data and remote sensing imagery for enhanced contextual urban information in Shanghai

Michael Jendryke, Timo Balz, Stephen C McClure, Mingsheng Liao
2017 Computers, Environment and Urban Systems  
A combination of remotely sensed and social media data is a step towards a more granular analysis of urbanization processes than is possible from either data source alone.  ...  Microwave remote sensing images are used to identify urban built-up areas and changes within those areas in an objective way, while geocoded mobile social media messages deliver valuable information about  ...  Acknowledgements This work is financially supported by the National Natural Science Foundation of China (grant no. 61331016 and 41174120), and the German Academic Exchange Service (DAAD).  ... 
doi:10.1016/j.compenvurbsys.2016.10.004 fatcat:vl3kekspnratbokbyabzr7of24

Supporting Global Environmental Change Research: A Review of Trends and Knowledge Gaps in Urban Remote Sensing

Elizabeth Wentz, Sharolyn Anderson, Michail Fragkias, Maik Netzband, Victor Mesev, Soe Myint, Dale Quattrochi, Atiqur Rahman, Karen Seto
2014 Remote Sensing  
This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change.  ...  For mapping we describe the data sources, methods, and limitations of mapping urban boundaries, land use and land cover, population, temperature, and air quality.  ...  Unexplored or underutilized data sources that could be integrated with satellite sensor data include social media, cell phone tracking, and volunteered geographic information [163] .  ... 
doi:10.3390/rs6053879 fatcat:vv4fd5icarbsdo52sycj4nwsle

LAND USE CLASSIFICATION FROM COMBINED USE OF REMOTE SENSING AND SOCIAL SENSING DATA

A. S. Anugraha, H.-J. Chu
2018 The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
This research aims to sense and analyze the patterns of human behavior and to classify land use from the combination of remote sensing data and social sensing data.  ...  The accuracy assessment shows that the combination of remote sensing data and social sensing data facilitates accurate urban land use classification.</p>  ...  This study integrates remote sensing and social sensing information to classify land use on the basis of a decision tree.  ... 
doi:10.5194/isprs-archives-xlii-4-33-2018 fatcat:nuaqwfx5izfq3iqpr2xu5lv7xe

Urban Residential Land Suitability Analysis Combining Remote Sensing and Social Sensing Data: A Case Study in Beijing, China

Huiping Huang, Qiangzi Li, Yuan Zhang
2019 Sustainability  
Consequently, this paper integrates remote sensing data (GaoFen-2 satellite image) and social sensing data (Tencent User Density data, Point-of-interest data and OpenStreetMap data) to establish an evaluation  ...  Most urban land suitability studies rely solely on remote sensing data and GIS data to evaluate natural suitability, and few studies have focused on urban land suitability from a socioeconomic perspective  ...  This study perceives POI data and TUD data as important social sensing data sources to integrate socioeconomic characteristics into urban land-use suitability analyses.  ... 
doi:10.3390/su11082255 fatcat:ad5lwfyeuzg7jn3es7q3mkv3um

Exploring Impact of Spatial Unit on Urban Land Use Mapping with Multisource Data

Xuanyan Dong, Yue Xu, Leping Huang, Zhigang Liu, Yi Xu, Kangyong Zhang, Zhongwen Hu, Guofeng Wu
2020 Remote Sensing  
In recent years, remote sensing images and social sensing data have been frequently used for urban land use mapping.  ...  The aim of this study is to explore the impact of spatial units on urban land use mapping, with remote sensing images and social sensing data of Shenzhen City, China.  ...  case of combining remote sensing and social sensing data.  ... 
doi:10.3390/rs12213597 fatcat:t7txbw7e55enthwedj2tkliaau

A New Remote Sensing Images and Point-of-Interest Fused (RPF) Model for Sensing Urban Functional Regions

Shengyu Xu, Linbo Qing, Longmei Han, Mei Liu, Yonghong Peng, Lifang Shen
2020 Remote Sensing  
However, the existing methods developed in the literature for identifying urban functional regions have mainly been focused on single remote sensing image data or social sensing data.  ...  To sense urban functional regions comprehensively and accurately, we developed a multi-mode framework through the integration of spatial geographic characteristics of remote sensing images and the functional  ...  And we thank the suggestion and support of Chengdu Institute of Urban Planning and Design. Conflicts of Interest: The authors declare no conflicts of interest.  ... 
doi:10.3390/rs12061032 fatcat:5q3gxlvorfdbxjtdxuxhv52dua

The Combined Use of Remote Sensing and Social Sensing Data in Fine-Grained Urban Land Use Mapping: A Case Study in Beijing, China

2017 Remote Sensing  
High-resolution remote sensing imagery and multi-source social sensing data were used to provide both physical and socioeconomic information.  ...  While using solely remote sensing data or social sensing data can achieve equally high overall accuracy, their importance varies in terms of the classification of individual classes.  ...  Author Contributions: Y.Z. conducted the data analysis and wrote the manuscript; Y.Z., Q.L., and H.H. developed the methodology; W.W. contributed to the land cover classification; X.D. and H.W. provided  ... 
doi:10.3390/rs9090865 fatcat:dkpevbme3jhzzifx42ifrq6s44
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