2019 Joint Urban Remote Sensing Event (JURSE)最新文献

Mapping slums and model population density using earth observation data and open source solutions 利用地球观测数据和开源解决方案绘制贫民窟和模拟人口密度

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-08-22 DOI: 10.1109/JURSE.2019.8808934

T. Grippa, S. Georganos, S. Vanhuysse, M. Lennert, Nicholus Mboga, E. Wolff

引用次数: 4

Detection of Informal Graveyards in Lima using Fully Convolutional Network with VHR Images 利用VHR图像的全卷积网络检测利马的非正式墓地

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-24 DOI: 10.1109/JURSE.2019.8808983

H. Debray, M. Kuffer, C. Persello, C. Klaufus, K. Pfeffer

{"title":"Detection of Informal Graveyards in Lima using Fully Convolutional Network with VHR Images","authors":"H. Debray, M. Kuffer, C. Persello, C. Klaufus, K. Pfeffer","doi":"10.1109/JURSE.2019.8808983","DOIUrl":"https://doi.org/10.1109/JURSE.2019.8808983","url":null,"abstract":"Lima is facing rapid urban growth, including a rapid expansion of informal areas, mainly taking place within three peripheral cones. Most of the studies on that subject focused in general on informal settlements. Yet in this paper, we focus on two different informal types, graveyards and housing. They are experiencing complex, intertwined development dynamics due to a lack of land for housing and burials, causing social and public health problems. Housing invasions on burial grounds have never been systematically investigated. Yet, while challenging due to their morphological similarity, the detection of boundaries between graveyards and neighbouring and sometimes invading informal housing is essential, e.g., to prevent the spread of diseases. This study aims to distinguish those similar urban structures of which the visual features are very alike (e.g., rectangular shapes, same colours, organic organization). We used state-of-the-art Fully Convolutional Networks (FCNs) with dilated convolution of increasing spatial kernels to acquire features of deep level of abstraction on Pleiades satellites images. We found that such neural networks can reach a good level in mapping both informal developments with a F1-score of 0.819. Effective monitoring of such developments is important to inform planning and decision-making processes to allow interventions at critical locations.","PeriodicalId":299183,"journal":{"name":"2019 Joint Urban Remote Sensing Event (JURSE)","volume":"13 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116638978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Online Random Forests for Urban Area Classification from Polarimetric SAR Images 基于极化SAR图像的城市区域在线随机森林分类

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-22 DOI: 10.1109/JURSE.2019.8808964

R. Hänsch, O. Hellwich

引用次数: 0

Using remote sensing data and cluster algorithms to structure cities 利用遥感数据和聚类算法构建城市

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-22 DOI: 10.1109/JURSE.2019.8808973

Thomas Tiessen, John Friesen, Lea Rausch, P. Pelz

引用次数: 2

The ‘urban’ component of the French Land Data and Services Centre (THEIA) 法国土地数据和服务中心(THEIA)的“城市”部分

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-22 DOI: 10.1109/JURSE.2019.8808998

A. Puissant, A. Sellé, N. Baghdadi, V. Thierion, A. L. Bris, J. Roujean

引用次数: 1

Slum Mapping in Imbalanced Remote Sensing Datasets Using Transfer Learned Deep Features 基于迁移学习深度特征的不平衡遥感数据贫民窟映射

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-22 DOI: 10.1109/JURSE.2019.8808965

Thomas Stark, M. Wurm, H. Taubenböck, Xiaoxiang Zhu

引用次数: 10

Novelty detection in very high resolution urban scenes with Density Forests 具有密度森林的高分辨率城市场景的新颖性检测

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-22 DOI: 10.1109/JURSE.2019.8808974

C. Wendl, Diego Marcos, D. Tuia

{"title":"Novelty detection in very high resolution urban scenes with Density Forests","authors":"C. Wendl, Diego Marcos, D. Tuia","doi":"10.1109/JURSE.2019.8808974","DOIUrl":"https://doi.org/10.1109/JURSE.2019.8808974","url":null,"abstract":"Uncertainty in deep learning has recently received a lot of attention. While deep neural networks have shown better accuracy than other competing methods in many benchmarks, it has been shown that they may yield wrong predictions with unreasonably high confidence. This has increased the interest in methods that help providing better confidence estimates in neural networks, some using specifically designed architectures with probabilistic building blocks, and others using a standard architecture with an additional confidence estimation step based on its output. This work proposes a confidence estimation method for Convolutional Neural Networks based on fitting a forest of randomized density estimation decision trees to the network activations before the final classification layer and compares it to other confidence estimation methods based on standard architectures. The methods are compared on a semantic labelling dataset with very high resolution satellite imagery. Our results show that methods based on intermediate network activations lead to better confidence estimates in novelty detection, i.e., in the discovery of classes that are not present in the training set.","PeriodicalId":299183,"journal":{"name":"2019 Joint Urban Remote Sensing Event (JURSE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124370518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Multi-label Aerial Image Classification using A Bidirectional Class-wise Attention Network 基于双向分类关注网络的多标签航空图像分类

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-22 DOI: 10.1109/JURSE.2019.8808940

Yuansheng Hua, Lichao Mou, Xiaoxiang Zhu

引用次数: 9

Synthetic Aperture Radar Tomography for Change Detection Applications 变化检测应用的合成孔径雷达层析成像

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-22 DOI: 10.1109/JURSE.2019.8808937

E. M. Domínguez, D. Small, D. Henke

引用次数: 1

A multidimensional urban land cover change analysis in Tempe, AZ 亚利桑那州坦佩市多维城市土地覆盖变化分析

2019 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2019-05-22 DOI: 10.1109/JURSE.2019.8808957

Qunshan Zhao, Ryan Reynolds, Chuyuan Wang, E. Wentz

引用次数: 1