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Satellite Image Classification with Deep Learning Survey

Roshni Rajendran, Liji Samuel
2020 Zenodo  
It has achieved success in image understanding by means that of convolutional neural networks. The problem of object and facility recognition in satellite imagery is considered.  ...  Because the geographic area to be covered is very large and the analysts available to conduct the searches are few, thus an automation is required.  ...  [7] discuss about the challenge of land use and land cover classification using Sentinel-2 satellite images. The key contributions are as follows.  ... 
doi:10.5281/zenodo.3854918 fatcat:lmyotz4ryrdrzi3rmbj537at6i

Identification of land cover alterations in the Alta Murgia National Park (Italy) with VHR satellite imagery

M. Caprioli, E. Tarantino
2006 International Journal of Sustainable Development and Planning  
The advent of recent satellite imagery has increased the possibility to investigate large-scale areas in great detail.  ...  Land cover exerts a great influence on many basic environmental processes and consequently any transformation in it may have a marked impact on the environment from the local to the global scales.  ...  Synoptic view: satellite images are 'big-picture' views of large areas of the surface.  ... 
doi:10.2495/sdp-v1-n3-261-270 fatcat:rhyfq46vlfhrpo6kg4wbl4xtwi

Satellite Imagery Classification Based On Deep Convolution Network

Zhong Ma, Zhuping Wang, Congxin Liu, Xiangzeng Liu
2016 Zenodo  
The contributions of this paper are twofold — First, to cope with the large-scale variance in the satellite image, we introduced the inception module, which has multiple filters with different size at  ...  The results of the proposed hyper-parameters search method show it will guide the search towards better regions of the parameter space.  ...  ACKNOWLEDGMENT The authors thank Tang Lei from Xi'an Microelectronics Technology Institute for his valuable comments to improve the quality of this paper.  ... 
doi:10.5281/zenodo.1125018 fatcat:tky2xdnbf5auzlcgjm3vfta7ue

Observing the Natural World with Flickr

Jingya Wang, Mohammed Korayem, David J. Crandall
2013 2013 IEEE International Conference on Computer Vision Workshops  
In this paper, we study the feasibility of observing the state of the natural world by recognizing specific types of scenes and objects in large-scale social image collections.  ...  Snow recognition turns out to be a surprisingly difficult and under-studied problem, so we test a variety of modern scene recognition techniques on this problem and introduce a large-scale, realistic dataset  ...  Gretchen LeBuhn and biology students at San Francisco State University for labeling the poppy images.  ... 
doi:10.1109/iccvw.2013.66 dblp:conf/iccvw/WangKC13 fatcat:2shgucyhcrecznapj572qdvzcq

Land Cover Classification of Resources Survey Remote Sensing Images Based on Segmentation Model

Zhenyu Fan, Tao Zhan, Zhichao Gao, Rui Li, Yao Liu, Lianzhi Zhang, Zixiang Jin, Supeng Xu
2022 IEEE Access  
Besides, the conclusion of this study can provide a demonstration for large-scale land cover resources investigation using low and medium resolution RS images.  ...  With the increasingly prominent problems of population, resources, and environment, there is an urgent need for a fast and accurate classification method of large-scale land use and land cover based on  ...  Based on the above, these methods are not practicable for large-scale land cover resources surveys.  ... 
doi:10.1109/access.2022.3175978 fatcat:wjlcm7q6vjhp5nj73mn5clxw4u

Large scale mosaicing and compositing of Proba-V satellite images

Tatjana Veljanovski, Klemen Čotar, Aleš Marsetič
2019 Geodetski Glasnik  
The paper deals with the production of large scale vegetation products derived from PROBA-V 100 m satellite images.  ...  Image compositing and mosaicking are needed to create seamless products on a global or continental scale. In the study, we have analysed and compared two compositing methods.  ...  Large scale mosaicing and compositing of PROBA-V satellite images. Geodetski glasnik, 50, 5-18.  ... 
doaj:b7f2694a054d48bc95db677ca12e440e fatcat:jmcgveix2ba3vddituilgrbtki

3D Dynamic Representation for Urban Sprawl Modelling: Example of India's Delhi-Mumbai corridor

Sébastien Gadal, Stéphane Fournier, Emeric Prouteau
2010 SAPIENS  
They facilitate understanding of the process of urbanisation and the resulting transformations of land use.  ...  3D dynamic geo-visualisation models reflect changes in urban land areas and make a new contribution to the spatiotemporal representation of land use processes and the production of geographic knowledge  ...  areas of land on regional and local scale in the form of geographic images or a spatial model of developing urbanisation.  ... 
doaj:2b2a516790194686ba8c586fb182476c fatcat:acbfr4x5tzat3c2k2niwsp4d54

Deep Aggregation Net for Land Cover Classification

Tzu-Sheng Kuo, Keng-Sen Tseng, Jia-Wei Yan, Yen-Cheng Liu, Yu-Chiang Frank Wang
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
Land cover classification aims at classifying each pixel in a satellite image into a particular land cover category, which can be regarded as a multi-class semantic segmentation task.  ...  of our proposed network architecture.  ...  Proposed Method Given pairs of RGB satellite images and land cover masks {X, Y }, we aim at training a model to produce land cover segmentation prediction Ỹ .  ... 
doi:10.1109/cvprw.2018.00046 dblp:conf/cvpr/KuoTYLW18 fatcat:kitsgx5dljgzbpvh6ofhlkyw5q

EuroSAT: A Novel Dataset and Deep Learning Benchmark for Land Use and Land Cover Classification

Patrick Helber, Benjamin Bischke, Andreas Dengel, Damian Borth
2019 IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing  
In this paper, we present a patch-based land use and land cover classification approach using Sentinel-2 satellite images.  ...  We present a novel dataset, based on these images that covers 13 spectral bands and is comprised of ten classes with a total of 27 000 labeled and geo-referenced images.  ...  In this paper, we make the following contributions: 1) We introduce the first large-scale patch-based land use and land cover classification dataset based on Sentinel-2 satellite images.  ... 
doi:10.1109/jstars.2019.2918242 fatcat:dkkraiq5bzf7np6tey5g73begm

A Comprehensive Study on Peri-Urban Regions of Visakhapatnam Smart City

Ramoji Rao. J
2020 International Journal for Research in Applied Science and Engineering Technology  
The classification of various existing parameters of the study area developed on 1:50,000 scale and a minimum delineation unit of sentinel 10 m resolution satellite image employed for better visualization  ...  The study aims to develop map layers at local and regional scales for an area where the rapid urbanization leads to degradation of it's surrounding land resources.  ...  The satellite image was geometrically corrected using UTM-WGS84 projection and applied coordinates with the help of Survey of India (SOI) published topographical maps (scale 1:50,000).  ... 
doi:10.22214/ijraset.2020.32015 fatcat:2b2qnmcdz5h63b5ekooeofhd4i

An Ecological Land Cover Sampling Reclassification Model for Safety Estimation of Shoreline Systems from a Flood Defense Perspective Using Optical Satellite Remote Sensing Imaging

2018 Water  
information from an optical satellite RS data interpretation of land cover on both side of the shoreline.  ...  With the development of remote sensing (RS) techniques, high spatial-spectral resolution and quick-revolution satellite images are now available and widely used in environment monitoring and management  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/w10030285 fatcat:t7v6gtnhyvepzo4smd5qhvjogi

Land Cover Classification using Machine Learning Techniques - A Survey

Vandana Singh, BIT Mesra
2020 International Journal of Engineering Research and  
The aim of this research is the review of literature for classification of land cover features using machine learning techniques.  ...  Land resources must be monitored, evaluated, and managed. Land cover classification based on remote sensing imagery is an important means to enable this.  ...  The use of remote sensing images for land cover classification is an important means to detect, evaluate, and manage land resources.  ... 
doi:10.17577/ijertv9is060881 fatcat:i4d7xu7cwfgz7nrbyzu6tdr544

Representative-Discriminative Learning for Open-set Land Cover Classification of Satellite Imagery [article]

Razieh Kaviani Baghbaderani, Ying Qu, Hairong Qi, Craig Stutts
2020 arXiv   pre-print
Land cover classification of satellite imagery is an important step toward analyzing the Earth's surface.  ...  However, due to the unique characteristics of satellite imagery with an extremely vast area of versatile cover materials, the training data are bound to be non-representative.  ...  Ablation Study Conclusions We studied the challenging problem of open-set land cover recognition in satellite images.  ... 
arXiv:2007.10891v1 fatcat:sdrxjtjnzbfj7dbmkevxx3w5ci

Large Scale High-Resolution Land Cover Mapping With Multi-Resolution Data

Caleb Robinson, Le Hou, Kolya Malkin, Rachel Soobitsky, Jacob Czawlytko, Bistra Dilkina, Nebojsa Jojic
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
The land cover mapping problem, at country-level scales, is challenging for common deep learning methods due to the scarcity of high-resolution labels, as well as variation in geography and quality of  ...  input images.  ...  C.R. was partially supported by the NSF grant CCF-1522054 (COMPUST-NET: Expanding Horizons of Computational Sustainability).  ... 
doi:10.1109/cvpr.2019.01301 dblp:conf/cvpr/RobinsonHMSCDJ19 fatcat:hj7qgrk3urajtfbxrmnagkly4a

A Coordinated Yield Suggestion System for Effective Cultivation

Nirmala C R
2020 International Journal for Research in Applied Science and Engineering Technology  
India has 159.7 million hectares of agriculture land and second largest agriculture land in world.  ...  So here our concern is effective utilization of agriculture land and train the farmers with the help of agriculture and forest department guidance and support.  ...  Satellite Image Processing for Land Use and Land Cover Mapping In this paper, urban growth of Bangalore region is analysed and discussed by using multi-temporal and multi-spectral Landsat satellite images  ... 
doi:10.22214/ijraset.2020.31288 fatcat:xdkfh54cfveudn263og5k3mk6y
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