2015 Joint Urban Remote Sensing Event (JURSE)最新文献_第2页

Urban monitoring in support of sustainable cities 支持可持续城市的城市监测

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120493

M. Marconcini, A. Metz, J. Zeidler, T. Esch

{"title":"Urban monitoring in support of sustainable cities","authors":"M. Marconcini, A. Metz, J. Zeidler, T. Esch","doi":"10.1109/JURSE.2015.7120493","DOIUrl":"https://doi.org/10.1109/JURSE.2015.7120493","url":null,"abstract":"Nowadays, there is a clear evidence that climate change poses serious challenges to urban areas and their growing population, e.g. increasing occurrence of heat waves, drought, heavy precipitation, cyclones and extreme high sea level events. These changes will affect physical infrastructure, water supply, energy provision, transport and industrial production, hence resulting in a variety of ripple effects across different sectors of the city life. In this context, Earth observation (EO) has proven to be an effective tool for supporting decision makers in facing climate change; nevertheless, gaps still exist between the current state-of-the-art and the users' requirements. The FP7 DECUMANUS project aims at bridging this gap also by a direct strong engagement of city users. In particular, DECUMANUS has a principal objective to develop and consolidate a set of sustainable services that allows city managers to incorporate EO-based geo-spatial products and geo-information services in their climate and environmental change strategies to support the sustainable management of the cities in Europe. In this paper, we present three advanced products generated in the framework of the DECUMANUS land monitoring services, namely spatiotemporal urbanization mapping, imperviousness estimation and settlement patterns analysis. In particular, all of them have been generated according with the requirements of the project users' community and will allow supporting their environmental change adaptation strategies at the district level.","PeriodicalId":207233,"journal":{"name":"2015 Joint Urban Remote Sensing Event (JURSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126435414","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: 13

Evaluation on the natural suitability of urban human settlement environment using multisource data 基于多源数据的城市人居环境自然适宜性评价

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120455

Jieqiong Luo, Peijun Du, A. Samat, Li Feng

引用次数: 4

Modeling of Chlorophyll-a concentration for the coastal waters of Hong Kong 香港沿岸水域叶绿素-a浓度的模拟

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120460

M. Nazeer, J. Nichol

{"title":"Modeling of Chlorophyll-a concentration for the coastal waters of Hong Kong","authors":"M. Nazeer, J. Nichol","doi":"10.1109/JURSE.2015.7120460","DOIUrl":"https://doi.org/10.1109/JURSE.2015.7120460","url":null,"abstract":"In coastal waters, accurate remote sensing retrieval of Chlorophyll-a (Chl-a) is challenging. In a spatially complex urban coastal region like Hong Kong, the development of a single Chl-a estimation algorithm over whole region is unrealistic. In such case the best strategy will be to develop an individual algorithm for each water type to precisely estimate Chl-a concentration. Therefore, to define the effective water zones in the region, Fuzzy c-Means (FCM) clustering was applied to surface reflectance derived from the first four bands of the Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) and HJ-1 A/B Charge Couple Device (CCD) sensors for 76 Hong Kong Environmental Protection Department (EPD) water monitoring stations. The FCM clustering results suggested the existence of five optically different water types in the region. Cluster specific algorithms were then developed for the retrieval of Chl-a concentrations using Neural Network (NN) and Regression Modeling (RM) techniques. Twenty seven Landsat TM/ETM+ (January 2000-December 2012) and thirty HJ-1 A/B CCD (September 2008-December 2012) cloud free images paired with in situ Chl-a data were used for development and validation of the NNs and RMs. The performance of the cluster specific NNs and RMs suggested that NN can efficiently estimate and map Chl-a concentrations with greater confidence as compared to band ratio algorithms developed using regression modeling. Overall, the validation results showed a correlation of 0.63 to 0.85 between the NN estimated and in situ measured Chl-a concentrations compared to a correlation of 0.26 to 0.54 between the RM estimated and in situ measured Chl-a concentrations.","PeriodicalId":207233,"journal":{"name":"2015 Joint Urban Remote Sensing Event (JURSE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121823090","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: 2

A novel application of Kalman Filter: 3D Reconstruction of urban areas from InSAR data 卡尔曼滤波的新应用:基于InSAR数据的城市区域三维重建

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120468

R. Ambrosino, F. Baselice, G. Ferraioli, Gilda Schirinzi

引用次数: 1

Integration of multi-seasonal Landsat 8 and TerraSAR-X data for urban mapping: An assessment 整合多季节Landsat 8和TerraSAR-X数据用于城市制图:评估

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120474

P. Villa, G. Fontanelli, A. Crema

引用次数: 3

The URBIS project: Vacant urban area classification and detection of changes URBIS项目:空置城市区域分类和变化检测

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120532

G. Moser, V. Krylov, M. Martino, S. Serpico

引用次数: 6

Classification of urban structural types with multisource data and structured models 基于多源数据和结构化模型的城市结构类型分类

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120489

Arnaud Poncet Montanges, G. Moser, H. Taubenböck, M. Wurm, D. Tuia

引用次数: 25

Three-dimensional reconstruction of urban areas by multi-aspect TomoSAR data fusion 基于多向TomoSAR数据融合的城市区域三维重建

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120478

M. Schmitt

引用次数: 8

Using Web-enabled Landsat Data time series to analyze the impacts of urban areas on remotely sensed vegetation dynamics 利用基于web的Landsat数据时间序列分析城市地区对遥感植被动态的影响

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120469

C. Krehbiel, T. Jackson, G. Henebry

{"title":"Using Web-enabled Landsat Data time series to analyze the impacts of urban areas on remotely sensed vegetation dynamics","authors":"C. Krehbiel, T. Jackson, G. Henebry","doi":"10.1109/JURSE.2015.7120469","DOIUrl":"https://doi.org/10.1109/JURSE.2015.7120469","url":null,"abstract":"Earth is currently experiencing rapid urban growth with >50% of global population living in urban areas. Urbanization occurs as cities expand to meet the demands of increasing populations and socioeconomic growth. Consequently, there is a need for remote sensing research to detect, quantify, and monitor urbanization and subsequent impacts on the environment. Here we used Normalized Difference Vegetation Index (NDVI) data products derived from the Web-enabled Landsat Data (WELD) project to (1) characterize the response of vegetation to urban land cover change and (2) analyze the impacts of urban areas on land surface phenology across rural to urban gradients for two cities located on the United States Great Plains. Here we fit the decade (2003-2012) of NDVI observations as a quadratic function of thermal time to calculate land surface phenology (LSP) metrics and characterize vegetation dynamics on an urban-rural gradient. We found croplands to exhibit greater variation in NDVI at half thermal time to peak compared to forest and developed land cover types. We found a linear relationship between modeled peak height NDVI and NDVI at half thermal time to peak in forest and developed pixels, as well as pixels that experienced a land cover change from cropland to developed. In general, duration of season decreased with distance from the city center in deciduous forest pixels for both cities. Developed pixels had lower modeled peak height NDVI, longer duration of season and greater variation compared to forest pixels.","PeriodicalId":207233,"journal":{"name":"2015 Joint Urban Remote Sensing Event (JURSE)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127648483","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

Object-based urban change detection using high resolution SAR images 基于目标的高分辨率SAR图像城市变化检测

2015 Joint Urban Remote Sensing Event (JURSE) Pub Date : 2015-06-11 DOI: 10.1109/JURSE.2015.7120502

Osama Yousif, Y. Ban

引用次数: 6