Understanding an urbanizing planet: Strategic directions for remote sensing

[1]  P. Ohadike Urbanization , 1968, Encyclopedia of the UN Sustainable Development Goals.

[2]  Zhiqiang Yang,et al.  Continuous monitoring of land disturbance based on Landsat time series , 2020, Remote Sensing of Environment.

[3]  Eleanor C. Stokes,et al.  Satellite-based assessment of electricity restoration efforts in Puerto Rico after Hurricane Maria , 2019, PloS one.

[4]  Chun Liu,et al.  Automatic extraction of built-up area from ZY3 multi-view satellite imagery: Analysis of 45 global cities , 2019, Remote Sensing of Environment.

[5]  Zhe Zhu,et al.  Current status of Landsat program, science, and applications , 2019, Remote Sensing of Environment.

[6]  P. Strobl,et al.  Benefits of the free and open Landsat data policy , 2019, Remote Sensing of Environment.

[7]  Eleanor C. Stokes,et al.  Characterizing and measuring urban landscapes for sustainability , 2019, Environmental Research Letters.

[8]  Yuyu Zhou,et al.  Characterizing the relationship between satellite phenology and pollen season: A case study of birch , 2019, Remote Sensing of Environment.

[9]  Michael Jendryke,et al.  A preliminary investigation of Luojia-1 night-time light imagery , 2019, Remote Sensing Letters.

[10]  S. Pickett,et al.  From feedbacks to coproduction: toward an integrated conceptual framework for urban ecosystems , 2018, Urban Ecosystems.

[11]  Yuyu Zhou,et al.  A global record of annual urban dynamics (1992–2013) from nighttime lights , 2018, Remote Sensing of Environment.

[12]  Markus Amann,et al.  The 2018 report of the Lancet Countdown on health and climate change: shaping the health of nations for centuries to come , 2018, The Lancet.

[13]  Hannes Taubenböck,et al.  Six fundamental aspects for conceptualizing multidimensional urban form: A spatial mapping perspective , 2018, Landscape and Urban Planning.

[14]  Jianping Wu,et al.  NPP-VIIRS DNB Daily Data in Natural Disaster Assessment: Evidence from Selected Case Studies , 2018, Remote. Sens..

[15]  Bo Huang,et al.  Urban land-use mapping using a deep convolutional neural network with high spatial resolution multispectral remote sensing imagery , 2018, Remote Sensing of Environment.

[16]  S. Pickett,et al.  The smart growth of Chinese cities: Opportunities offered by vacant land , 2018, Land Degradation & Development.

[17]  Peijun Du,et al.  SAR-Based Urban Extents Extraction: From ENVISAT to Sentinel-1 , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[18]  Hannes Taubenböck,et al.  Capturing the Urban Divide in Nighttime Light Images From the International Space Station , 2018, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[19]  Xiao Xiang Zhu,et al.  Classification of Settlement Types from Tweets Using LDA and LSTM , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[20]  B. McGrath Intersecting disciplinary frameworks: the architecture and ecology of the city , 2018, Ecosystem Health and Sustainability.

[21]  C. Scavuzzo,et al.  Urban environmental clustering to assess the spatial dynamics of Aedes aegypti breeding sites. , 2018, Geospatial health.

[22]  Yan Song,et al.  Examining the impacts of urban form on air pollutant emissions: Evidence from China. , 2018, Journal of environmental management.

[23]  S. LaDeau,et al.  Primary blood-hosts of mosquitoes are influenced by social and ecological conditions in a complex urban landscape , 2018, Parasites & Vectors.

[24]  Yun-ya Yang,et al.  Nutrients in Urban Stormwater Runoff: Current State of the Science and Potential Mitigation Options , 2018, Current Pollution Reports.

[25]  Eleanor C. Stokes,et al.  NASA's Black Marble nighttime lights product suite , 2018, Remote Sensing of Environment.

[26]  R. Azzam,et al.  Impact of urbanization on groundwater recharge and urban water balance for the city of Hyderabad, India , 2018, International Soil and Water Conservation Research.

[27]  Yunyan Du,et al.  An integrated model for generating hourly Landsat-like land surface temperatures over heterogeneous landscapes , 2018 .

[28]  H. Taubenböck,et al.  The morphology of the Arrival City - A global categorization based on literature surveys and remotely sensed data , 2018 .

[29]  A. Preti,et al.  Coping with the New Era: Noise and Light Pollution, Hperactivity and Steroid Hormones. Towards an Evolutionary View of Bipolar Disorders , 2018, Clinical practice and epidemiology in mental health : CP & EMH.

[30]  R. Corstanje,et al.  Linking ecosystem services, urban form and green space configuration using multivariate landscape metric analysis , 2018, Landscape Ecology.

[31]  H. Taubenböck,et al.  Detecting social groups from space – Assessment of remote sensing-based mapped morphological slums using income data , 2018 .

[32]  Thomas Esch,et al.  Exploiting big earth data from space – first experiences with the timescan processing chain , 2018 .

[33]  K. Seto,et al.  Building a global urban science , 2018, Nature Sustainability.

[34]  Zhenhui Sun,et al.  Characterizing spatial and temporal trends of surface urban heat island effect in an urban main built-up area: A 12-year case study in Beijing, China , 2018 .

[35]  Yuyu Zhou,et al.  The surface urban heat island response to urban expansion: A panel analysis for the conterminous United States. , 2017, The Science of the total environment.

[36]  Michael Dixon,et al.  Google Earth Engine: Planetary-scale geospatial analysis for everyone , 2017 .

[37]  Yong Suk Lee,et al.  International Isolation and Regional Inequality: Evidence from Sanctions on North Korea , 2017 .

[38]  Zhe Zhu,et al.  Subpixel urban impervious surface mapping: the impact of input Landsat images , 2017 .

[39]  Xiao Xiang Zhu,et al.  Deep learning in remote sensing: a review , 2017, ArXiv.

[40]  Ingunn Burud,et al.  High-resolution spectral mapping of urban thermal properties with Unmanned Aerial Vehicles , 2017 .

[41]  Karen C. Seto,et al.  Sustainability in an urbanizing planet , 2017, Proceedings of the National Academy of Sciences.

[42]  Zhe Zhu,et al.  Change detection using landsat time series: A review of frequencies, preprocessing, algorithms, and applications , 2017 .

[43]  Eleanor C. Stokes,et al.  Supplemental Material Associations between Greenness , Impervious Surface Area , and Nighttime Lights on Biomarkers of Vascular Aging in Chennai , India , 2017 .

[44]  A. Soliman,et al.  Social sensing of urban land use based on analysis of Twitter users’ mobility patterns , 2017, PloS one.

[45]  D. Rybski,et al.  The role of city size and urban form in the surface urban heat island , 2017, Scientific Reports.

[46]  Hannes Taubenböck,et al.  Measuring morphological polycentricity - A comparative analysis of urban mass concentrations using remote sensing data , 2017, Comput. Environ. Urban Syst..

[47]  Erin B. Wetherley,et al.  Mapping spectrally similar urban materials at sub-pixel scales , 2017 .

[48]  Hannes Taubenböck,et al.  Slum mapping in polarimetric SAR data using spatial features , 2017 .

[49]  Michael Wurm,et al.  Oliveira, Vítor (2016): Urban Morphology. An Introduction to the Study of the Physical Form of Cities , 2017 .

[50]  Zhe Zhu,et al.  Monitoring urban expansion using time series of night-time light data: a case study in Wuhan, China , 2017, Remote Sensing of Night-time Light.

[51]  Min Liu,et al.  Air quality and its response to satellite-derived urban form in the Yangtze River Delta, China , 2017 .

[52]  Hannes Taubenböck,et al.  Towards large-area morphologic characterization of urban environments using the TanDEM-X mission and Sentinel-2 , 2017, 2017 Joint Urban Remote Sensing Event (JURSE).

[53]  Hannes Taubenböck,et al.  Regions Set in Stone - Delimiting and Categorizing Regions in Europe by Settlement Patterns Derived from EO-Data , 2017, ISPRS Int. J. Geo Inf..

[54]  P. Patel,et al.  Global scenarios of urban density and its impacts on building energy use through 2050 , 2017, Proceedings of the National Academy of Sciences.

[55]  Nancy B. Grimm,et al.  Does the ecological concept of disturbance have utility in urban social–ecological–technological systems? , 2017 .

[56]  Daniel Krewski,et al.  Comparing the Health Effects of Ambient Particulate Matter Estimated Using Ground-Based versus Remote Sensing Exposure Estimates , 2016, Environmental health perspectives.

[57]  Xiaoping Liu,et al.  Examining the impacts of socioeconomic factors, urban form, and transportation networks on CO2 emissions in China’s megacities , 2017 .

[58]  Masaru Yoshioka,et al.  Global and regional trends in particulate air pollution and attributable health burden over the past 50 years , 2017 .

[59]  Corinne Le Quéré,et al.  Urban infrastructure choices structure climate solutions , 2016 .

[60]  John R. Schott,et al.  The impact of improved signal-to-noise ratios on algorithm performance: Case studies for Landsat class instruments , 2016 .

[61]  Christopher E. Holden,et al.  Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014) , 2016 .

[62]  David P. Roy,et al.  The global Landsat archive: Status, consolidation, and direction , 2016 .

[63]  J. Gulliver,et al.  Effective impervious area for runoff in urban watersheds , 2016 .

[64]  Sang Michael Xie,et al.  Combining satellite imagery and machine learning to predict poverty , 2016, Science.

[65]  Catherine Linard,et al.  Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam , 2016, International Journal of Health Geographics.

[66]  Christophe Sannier,et al.  Monitoring Urban Areas with Sentinel-2A Data: Application to the Update of the Copernicus High Resolution Layer Imperviousness Degree , 2016, Remote. Sens..

[67]  C. Ford,et al.  Intersection of Living in a Rural Versus Urban Area and Race/Ethnicity in Explaining Access to Health Care in the United States. , 2016, American journal of public health.

[68]  G. McCord,et al.  Geographic determinants of China's urbanization , 2016 .

[69]  Peng Gong,et al.  Urban growth models: progress and perspective , 2016 .

[70]  Bo Du,et al.  Deep Learning for Remote Sensing Data: A Technical Tutorial on the State of the Art , 2016, IEEE Geoscience and Remote Sensing Magazine.

[71]  Hannes Taubenböck,et al.  How good is the map? A multi-scale cross-comparison framework for global settlement layers: Evidence from Central Europe , 2016 .

[72]  R. Davey,et al.  Physical activity in relation to urban environments in 14 cities worldwide: a cross-sectional study , 2016, The Lancet.

[73]  Monika Kuffer,et al.  Slums from Space - 15 Years of Slum Mapping Using Remote Sensing , 2016, Remote. Sens..

[74]  Karen C. Seto,et al.  Hidden linkages between urbanization and food systems , 2016, Science.

[75]  Patricia J. Culligan,et al.  Meta-principles for developing smart, sustainable, and healthy cities , 2016, Science.

[76]  Andrew Gonzalez,et al.  The impacts of urban sprawl on ecological connectivity in the Montreal Metropolitan Region , 2016 .

[77]  Jorge Rodríguez-Álvarez,et al.  Urban Energy Index for Buildings (UEIB): A new method to evaluate the effect of urban form on buildings’ energy demand , 2016 .

[78]  Pierre Soille,et al.  Assessment of the Added-Value of Sentinel-2 for Detecting Built-up Areas , 2016, Remote. Sens..

[79]  Qihao Weng,et al.  A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery , 2016 .

[80]  Qihao Weng,et al.  Annual dynamics of impervious surface in the Pearl River Delta, China, from 1988 to 2013, using time series Landsat imagery , 2016 .

[81]  L. Salvati,et al.  Soil sealing footprint as an indicator of dispersed urban growth: a multivariate statistics approach , 2016 .

[82]  Vítor Oliveira,et al.  Urban Morphology: An Introduction to the Study of the Physical Form of Cities , 2016 .

[83]  Julea Andreea Maria,et al.  Operating procedure for the production of the Global Human Settlement Layer from Landsat data of the epochs 1975, 1990, 2000, and 2014 , 2016 .

[84]  Gui-Song Xia,et al.  Deep Learning for Remote Sensing Image Understanding , 2016, J. Sensors.

[85]  William L. Stefanov,et al.  Micro-scale urban surface temperatures are related to land-cover features and residential heat related health impacts in Phoenix, AZ USA , 2015, Landscape Ecology.

[86]  N. Grimm,et al.  A broader framing of ecosystem services in cities , 2015 .

[87]  F. Creutzig,et al.  Energy and environment. Transport: A roadblock to climate change mitigation? , 2015, Science.

[88]  O. Barbosa,et al.  Bird Richness and Abundance in Response to Urban Form in a Latin American City: Valdivia, Chile as a Case Study , 2015, PloS one.

[89]  R. Green,et al.  An introduction to the NASA Hyperspectral InfraRed Imager (HyspIRI) mission and preparatory activities , 2015 .

[90]  P. Gong,et al.  A 30-year (1984–2013) record of annual urban dynamics of Beijing City derived from Landsat data , 2015 .

[91]  Michael Z Levy,et al.  The ecological foundations of transmission potential and vector-borne disease in urban landscapes. , 2015, Functional ecology.

[92]  A. Thomson,et al.  A global map of urban extent from nightlights , 2015 .

[93]  Land cover in single-family housing areas and how it correlates with urban form , 2015, Urban Ecosystems.

[94]  Jin Chen,et al.  Global land cover mapping at 30 m resolution: A POK-based operational approach , 2015 .

[95]  Tom J. Coulthard,et al.  Evaluating the importance of catchment hydrological parameters for urban surface water flood modelling using a simple hydro-inundation model , 2015 .

[96]  Weiqi Zhou,et al.  The New Global Urban Realm: Complex, Connected, Diffuse, and Diverse Social-Ecological Systems , 2015 .

[97]  Weixu Wang,et al.  Spatiotemporal and semantic information extraction from Web news reports about natural hazards , 2015, Comput. Environ. Urban Syst..

[98]  A. Tatem,et al.  Detecting Change in Urban Areas at Continental Scales with MODIS Data , 2015 .

[99]  Margareth Lara Capurro,et al.  São Paulo urban heat islands have a higher incidence of dengue than other urban areas , 2014, The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases.

[100]  W. Nordhaus,et al.  A sharper image? Estimates of the precision of nighttime lights as a proxy for economic statistics , 2015 .

[101]  Weiqi Zhou,et al.  Understanding the dynamic of greenspace in the urbanized area of Beijing based on high resolution satellite images , 2015 .

[102]  M. Ha-Duong,et al.  Climate change 2014 - Mitigation of climate change , 2015 .

[103]  Karen C. Seto,et al.  Chapter 12 - Human settlements, infrastructure and spatial planning , 2014 .

[104]  Michael Batty,et al.  Detecting the dynamics of urban structure through spatial network analysis , 2014, Int. J. Geogr. Inf. Sci..

[105]  H. Ho,et al.  Mapping maximum urban air temperature on hot summer days , 2014 .

[106]  A. Tatem,et al.  Dynamic population mapping using mobile phone data , 2014, Proceedings of the National Academy of Sciences.

[107]  Kwawu Mensan Gaba,et al.  Tracking Electrification in Vietnam Using Nighttime Lights , 2014, Remote. Sens..

[108]  Michael P. Johnson,et al.  Maintain, demolish, re-purpose: Policy design for vacant land management using decision models , 2014 .

[109]  Dagmar Haase,et al.  Applying a novel urban structure classification to compare the relationships of urban structure and surface temperature in Berlin and New York City , 2014 .

[110]  Hannes Taubenböck,et al.  Investigating the Applicability of Cartosat-1 DEMs and Topographic Maps to Localize Large-Area Urban Mass Concentrations , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[111]  Hong S. He,et al.  Effects of spatial pattern of greenspace on urban cooling in a large metropolitan area of eastern China , 2014 .

[112]  Edward A. Cook,et al.  Influence of urban form on landscape pattern and connectivity in metropolitan regions: a comparative case study of Phoenix, AZ, USA, and Izmir, Turkey , 2014, Environmental Monitoring and Assessment.

[113]  D. Roberts,et al.  Urban tree species mapping using hyperspectral and lidar data fusion , 2014 .

[114]  F. Steiner Frontiers in urban ecological design and planning research , 2014 .

[115]  Karen C. Seto,et al.  Supporting Global Environmental Change Research: A Review of Trends and Knowledge Gaps in Urban Remote Sensing , 2014, Remote. Sens..

[116]  Martha C. Anderson,et al.  Landsat-8: Science and Product Vision for Terrestrial Global Change Research , 2014 .

[117]  H. Taubenböck,et al.  The physical face of slums: a structural comparison of slums in Mumbai, India, based on remotely sensed data , 2014 .

[118]  Timothy R. Oke,et al.  Evaluation of the ‘local climate zone’ scheme using temperature observations and model simulations , 2014 .

[119]  S. Guhathakurta,et al.  Impact of urban form and design on mid-afternoon microclimate in Phoenix Local Climate Zones , 2014 .

[120]  Stefan Kohler,et al.  Urbanization and health in developing countries: a systematic review. , 2014, World health & population.

[121]  E. Andersson,et al.  Understanding how built urban form influences biodiversity , 2014 .

[122]  Marcello de Michele,et al.  High nonlinear urban ground motion in Manila (Philippines) from 1993 to 2010 observed by DInSAR: Implications for sea-level measurement , 2013 .

[123]  Kwawu Mensan Gaba,et al.  Detection of rural electrification in Africa using DMSP-OLS night lights imagery , 2013 .

[124]  Alexander J. Felson,et al.  Promoting Earth Stewardship through urban design experiments , 2013 .

[125]  C. Deng,et al.  A spatially adaptive spectral mixture analysis for mapping subpixel urban impervious surface distribution , 2013 .

[126]  R. Winston,et al.  A Comparison of Runoff Quality and Quantity from a Urban Commercial Infill Low Impact Development and a Conventional Development , 2013 .

[127]  Aixue Hu,et al.  Energy consumption and the unexplained winter warming over northern Asia and North America , 2013 .

[128]  Changshan Wu,et al.  Examining the impacts of urban biophysical compositions on surface urban heat island: A spectral unmixing and thermal mixing approach , 2013 .

[129]  S. Frolking,et al.  A global fingerprint of macro-scale changes in urban structure from 1999 to 2009 , 2013 .

[130]  David W. S. Wong,et al.  An approach to differentiate informal settlements using spectral, texture, geomorphology and road accessibility metrics , 2013 .

[131]  J. Townshend,et al.  Urban growth of the Washington, D.C.–Baltimore, MD metropolitan region from 1984 to 2010 by annual, Landsat-based estimates of impervious cover , 2013 .

[132]  K. Seto,et al.  The Vegetation Adjusted NTL Urban Index: A new approach to reduce saturation and increase variation in nighttime luminosity , 2013 .

[133]  S. Michalopoulos,et al.  National Institutions and Subnational Development in Africa , 2012, The quarterly journal of economics.

[134]  Peter J. Marcotullio,et al.  What Is a City? An Essential Definition for Sustainability , 2013 .

[135]  T. Oke,et al.  Local Climate Zones for Urban Temperature Studies , 2012 .

[136]  C. Woodcock,et al.  Continuous change detection and classification of land cover using all available Landsat data , 2014 .

[137]  Jin Chen,et al.  Mapping impervious surface expansion using medium-resolution satellite image time series: a case study in the Yangtze River Delta, China , 2012 .

[138]  C. Deng,et al.  BCI: A biophysical composition index for remote sensing of urban environments , 2012 .

[139]  K. Seto,et al.  Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools , 2012, Proceedings of the National Academy of Sciences.

[140]  Víctor Soto,et al.  Characterizing Urban Landscapes Using Geolocated Tweets , 2012, 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing.

[141]  R. Pu,et al.  A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species , 2012 .

[142]  Paul D. Bates,et al.  Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: A case study , 2012 .

[143]  M. Herold,et al.  Near real-time disturbance detection using satellite image time series , 2012 .

[144]  Michael A. Wulder,et al.  Opening the archive: How free data has enabled the science and monitoring promise of Landsat , 2012 .

[145]  Gavin Pereira,et al.  The association between neighborhood greenness and cardiovascular disease: an observational study , 2012, BMC Public Health.

[146]  Lishan Xiao,et al.  Urbanisation and human health in China: spatial features and a systemic perspective , 2012, Environmental Science and Pollution Research.

[147]  Lu Liang,et al.  China’s urban expansion from 1990 to 2010 determined with satellite remote sensing , 2012 .

[148]  C. Donlon,et al.  The Global Monitoring for Environment and Security (GMES) Sentinel-3 mission , 2012 .

[149]  Josef Aschbacher,et al.  The European Earth monitoring (GMES) programme: Status and perspectives , 2012 .

[150]  Matthias Drusch,et al.  Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services , 2012 .

[151]  Tim Gulden,et al.  Global Metropolis: Assessing Economic Activity in Urban Centers Based on Nighttime Satellite Images , 2012 .

[152]  Daniel Hoornweg,et al.  What a waste? : a global review of solid waste management , 2012 .

[153]  X. Tong,et al.  Building-damage detection using pre- and post-seismic high-resolution satellite stereo imagery: A case study of the May 2008 Wenchuan earthquake , 2012 .

[154]  Alfred Stein,et al.  An ontology of slums for image-based classification , 2012, Comput. Environ. Urban Syst..

[155]  T. Esch,et al.  Monitoring urbanization in mega cities from space , 2012 .

[156]  Qihao Weng,et al.  Enhancing temporal resolution of satellite imagery for public health studies: A case study of West Nile Virus outbreak in Los Angeles in 2007 , 2012 .

[157]  Simon J. Hook,et al.  Synergies Between VSWIR and TIR Data for the Urban Environment: An Evaluation of the Potential for the Hyperspectral Infrared Imager (HyspIRI) , 2012 .

[158]  C. Woodcock,et al.  Assessment of spectral, polarimetric, temporal, and spatial dimensions for urban and peri-urban land cover classification using Landsat and SAR data , 2012 .

[159]  Qihao Weng,et al.  Remote sensing of impervious surfaces in the urban areas: Requirements, methods, and trends , 2012 .

[160]  A. Cohen,et al.  Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution. , 2012, Environmental science & technology.

[161]  Hannes Taubenböck,et al.  TanDEM-X mission—new perspectives for the inventory and monitoring of global settlement patterns , 2012 .

[162]  Yuyu Zhou,et al.  Estimation of the relationship between remotely sensed anthropogenic heat discharge and building energy use , 2012 .

[163]  Nina Schwarz,et al.  Exploring indicators for quantifying surface urban heat islands of European cities with MODIS land surface temperatures , 2011 .

[164]  Conghe Song,et al.  Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China , 2011 .

[165]  R. F. Grais,et al.  Explaining Seasonal Fluctuations of Measles in Niger Using Nighttime Lights Imagery , 2011, Science.

[166]  Kyle A. Hartfield,et al.  Fusion of High Resolution Aerial Multispectral and LiDAR Data: Land Cover in the Context of Urban Mosquito Habitat , 2011, Remote. Sens..

[167]  J. Schwartz,et al.  Assessing temporally and spatially resolved PM2.5 exposures for epidemiological studies using satellite aerosol optical depth measurements , 2011 .

[168]  P. Bates,et al.  The accuracy of sequential aerial photography and SAR data for observing urban flood dynamics, a case study of the UK summer 2007 floods , 2011 .

[169]  Brenda K. Jones,et al.  USGS remote sensing coordination for the 2010 Haiti earthquake , 2011 .

[170]  K. Seto,et al.  A Meta-Analysis of Global Urban Land Expansion , 2011, PloS one.

[171]  M. Cadenasso,et al.  Does spatial configuration matter? Understanding the effects of land cover pattern on land surface temperature in urban landscapes , 2011 .

[172]  Irwan Gumilar,et al.  Land subsidence of Jakarta (Indonesia) and its relation with urban development , 2011 .

[173]  R. Sinha,et al.  The Indus flood of 2010 in Pakistan: a perspective analysis using remote sensing data , 2011 .

[174]  W. Nordhaus,et al.  Using luminosity data as a proxy for economic statistics , 2011, Proceedings of the National Academy of Sciences.

[175]  Patricia Gober,et al.  Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery , 2011, Remote Sensing of Environment.

[176]  J. Henderson,et al.  A Bright Idea for Measuring Economic Growth. , 2011, The American economic review.

[177]  G. Myers,et al.  African Cities: Alternative Visions of Urban Theory and Practice , 2011 .

[178]  Guoqing Sun,et al.  ICESat GLAS Data for Urban Environment Monitoring , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[179]  Elena Mauri,et al.  Satellite monitoring of summer heat waves in the Paris metropolitan area , 2011 .

[180]  Z Vojinovic,et al.  Effects of model schematisation, geometry and parameter values on urban flood modelling. , 2011, Water science and technology : a journal of the International Association on Water Pollution Research.

[181]  J. Weiner,et al.  An evaluation of access to health care services along the rural-urban continuum in Canada , 2011, BMC health services research.

[182]  Jianping Wu,et al.  Automated derivation of urban building density information using airborne LiDAR data and object-based method , 2010 .

[183]  M. Lazar Shedding Light on the Global Distribution of Economic Activity , 2010 .

[184]  P. Sutton,et al.  Shedding Light on the Global Distribution of Economic Activity , 2010 .

[185]  S. Bhaskaran,et al.  Per-pixel and object-oriented classification methods for mapping urban features using Ikonos satellite data , 2010 .

[186]  Xiaolin Zhu,et al.  An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions , 2010 .

[187]  Christopher Doll,et al.  Estimating rural populations without access to electricity in developing countries through night-time light satellite imagery , 2010 .

[188]  P. McIntyre,et al.  Global threats to human water security and river biodiversity , 2010, Nature.

[189]  V. Machault,et al.  Spatial heterogeneity and temporal evolution of malaria transmission risk in Dakar, Senegal, according to remotely sensed environmental data , 2010, Malaria Journal.

[190]  C. Homer,et al.  Updating the 2001 National Land Cover Database Impervious Surface Products to 2006 using Landsat Imagery Change Detection Methods , 2010 .

[191]  I. Kloog,et al.  Nighttime light level co-distributes with breast cancer incidence worldwide , 2010, Cancer Causes & Control.

[192]  Charles E Matthews,et al.  The built environment and location-based physical activity. , 2010, American journal of preventive medicine.

[193]  M. Brauer,et al.  Global Estimates of Ambient Fine Particulate Matter Concentrations from Satellite-Based Aerosol Optical Depth: Development and Application , 2010, Environmental health perspectives.

[194]  L. Bounoua,et al.  Remote sensing of the urban heat island effect across biomes in the continental USA , 2010 .

[195]  Thomas A Glass,et al.  The built environment and obesity: a systematic review of the epidemiologic evidence. , 2010, Health & place.

[196]  Mark A. Goddard,et al.  Scaling up from gardens: biodiversity conservation in urban environments. , 2010, Trends in ecology & evolution.

[197]  Qihao Weng,et al.  Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran. , 2009 .

[198]  P. Shi,et al.  Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach , 2009 .

[199]  Xinjun Wang,et al.  Remote sensing evaluation of urban heat island and its spatial pattern of the Shanghai metropolitan area, China , 2009 .

[200]  M. Friedl,et al.  A new map of global urban extent from MODIS satellite data , 2009 .

[201]  Janet E. Nichol,et al.  Urban heat island diagnosis using ASTER satellite images and 'in situ' air temperature , 2009 .

[202]  Qihao Weng,et al.  Spatio‐temporal modelling and analysis of urban heat islands by using Landsat TM and ETM+ imagery , 2009 .

[203]  Qihao Weng Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends , 2009 .

[204]  Elisabeth M. Hamin,et al.  Urban form and climate change: Balancing adaptation and mitigation in the U.S. and Australia , 2009 .

[205]  Qihao Weng,et al.  Urban heat island monitoring and analysis using a non-parametric model: A case study of Indianapolis , 2009 .

[206]  B. Sanders,et al.  Unstructured mesh generation and landcover-based resistance for hydrodynamic modeling of urban flooding , 2008 .

[207]  S. Kark,et al.  Accurate prediction of bird species richness patterns in an urban environment using Landsat‐derived NDVI and spectral unmixing , 2008 .

[208]  Martha C. Anderson,et al.  Free Access to Landsat Imagery , 2008, Science.

[209]  M. Tiangco,et al.  ASTER‐based study of the night‐time urban heat island effect in Metro Manila , 2008 .

[210]  Jeremy F. Wallace,et al.  Monitoring an invasive perennial at the landscape scale with remote sensing , 2008 .

[211]  D. Haase Urban Ecology of Shrinking Cities: An Unrecognized Opportunity? , 2008 .

[212]  N. Grimm,et al.  Global Change and the Ecology of Cities , 2008, Science.

[213]  M. Dear,et al.  Urban Politics and the Los Angeles School of Urbanism , 2008 .

[214]  Frédéric Achard,et al.  GLOBCOVER : The most detailed portrait of Earth , 2008 .

[215]  G. Leeuw,et al.  Exploring the relation between aerosol optical depth and PM 2.5 at Cabauw, the Netherlands , 2008 .

[216]  R. G. Davies,et al.  Urban form, biodiversity potential and ecosystem services , 2007 .

[217]  M. Goodchild Citizens as sensors: the world of volunteered geography , 2007 .

[218]  Kathleen M. Bergen,et al.  Increasing Gross Primary Production (GPP) in the Urbanizing Landscapes of Southeastern Michigan , 2007 .

[219]  Y. Yamaguchi,et al.  Estimation of storage heat flux in an urban area using ASTER data , 2007 .

[220]  Naresh Kumar,et al.  An empirical relationship between PM(2.5) and aerosol optical depth in Delhi Metropolitan. , 2007, Atmospheric environment.

[221]  Stefan Voigt,et al.  Satellite Image Analysis for Disaster and Crisis-Management Support , 2007, IEEE Transactions on Geoscience and Remote Sensing.

[222]  M. Bauer,et al.  Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery , 2007 .

[223]  Hua Zheng,et al.  Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China. , 2007, Journal of environmental sciences.

[224]  D. Roberts,et al.  Sub-pixel mapping of urban land cover using multiple endmember spectral mixture analysis: Manaus, Brazil , 2007 .

[225]  S. Goetz,et al.  Laser remote sensing of canopy habitat heterogeneity as a predictor of bird species richness in an eastern temperate forest, USA , 2006 .

[226]  Alexandre Boucher,et al.  A Novel Method for Mapping Land Cover Changes: Incorporating Time and Space With Geostatistics , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[227]  D. Quattrochi,et al.  A multi-scale approach to urban thermal analysis , 2006 .

[228]  Xiaoling Chen,et al.  Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes , 2006 .

[229]  Mathew R. Schwaller,et al.  On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[230]  H. Overman,et al.  Causes of Sprawl: A Portrait from Space , 2006 .

[231]  N. Grimm,et al.  A distinct urban biogeochemistry? , 2006, Trends in ecology & evolution.

[232]  Eric F. Lambin,et al.  Introduction: Local Processes with Global Impacts , 2006 .

[233]  M. Bauer,et al.  Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing , 2005 .

[234]  J. M. Shepherd,et al.  A Review of Current Investigations of Urban-Induced Rainfall and Recommendations for the Future , 2005 .

[235]  C. Elvidge,et al.  Spatial analysis of global urban extent from DMSP-OLS night lights , 2005 .

[236]  P. Vitousek,et al.  Remote analysis of biological invasion and biogeochemical change. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[237]  Gilberto Câmara,et al.  Estimating population and energy consumption in Brazilian Amazonia using DMSP night-time satellite data , 2005, Comput. Environ. Urban Syst..

[238]  S. Ustin,et al.  Using AVIRIS data and multiple-masking techniques to map urban forest tree species , 2004 .

[239]  Marcel Tanner,et al.  Integrated urban malaria control: a case study in dar es salaam, Tanzania. , 2004, The American journal of tropical medicine and hygiene.

[240]  A. Strahler,et al.  The footprint of urban climates on vegetation phenology , 2004 .

[241]  Basil W. Coutant,et al.  Qualitative and quantitative evaluation of MODIS satellite sensor data for regional and urban scale air quality , 2004 .

[242]  Taylor H. Ricketts,et al.  The consequences of urban land transformation on net primary productivity in the United States , 2004 .

[243]  D. Lu,et al.  Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies , 2004 .

[244]  Jun Wang,et al.  Intercomparison between satellite‐derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies , 2003 .

[245]  T. Oke,et al.  Thermal remote sensing of urban climates , 2003 .

[246]  S. Running,et al.  Assessing the impact of urban land development on net primary productivity in the southeastern United States , 2003 .

[247]  M. Crosetto,et al.  Urban Subsidence Monitoring Using Radar Interferometry: Algorithms and Validation , 2003 .

[248]  M. Fladeland,et al.  Remote sensing for biodiversity science and conservation , 2003 .

[249]  D. Streutker,et al.  Satellite-measured growth of the urban heat island of Houston, Texas , 2003 .

[250]  J. Sallis,et al.  Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures , 2003, Annals of behavioral medicine : a publication of the Society of Behavioral Medicine.

[251]  Jay Gao,et al.  Use of normalized difference built-up index in automatically mapping urban areas from TM imagery , 2003 .

[252]  Limin Yang,et al.  An approach for mapping large-area impervious surfaces: synergistic use of Landsat-7 ETM+ and high spatial resolution imagery , 2003 .

[253]  Alan H. Strahler,et al.  Global land cover mapping from MODIS: algorithms and early results , 2002 .

[254]  P. Sutton,et al.  SPECIAL ISSUE: The Dynamics and Value of Ecosystem Services: Integrating Economic and Ecological Perspectives Global estimates of market and non-market values derived from nighttime satellite imagery, land cover, and ecosystem service valuation , 2002 .

[255]  D. Streutker A remote sensing study of the urban heat island of Houston, Texas , 2002 .

[256]  C. Woodcock,et al.  Monitoring land-use change in the Pearl River Delta using Landsat TM , 2002 .

[257]  W. Zipperer,et al.  Urban ecological systems: linking terrestrial ecological, physical, and socioeconomic components of metropolitan areas , 2001 .

[258]  Karen C. Seto,et al.  Change detection, accuracy, and bias in a sequential analysis of Landsat imagery in the Pearl River Delta, China: econometric techniques , 2001 .

[259]  Michael P. Conzen,et al.  The study of urban form in the United States , 2001, Urban Morphology.

[260]  C. Small Estimation of urban vegetation abundance by spectral mixture analysis , 2001 .

[261]  D. Roberts,et al.  Census from Heaven: An estimate of the global human population using night-time satellite imagery , 2001 .

[262]  Paul A. Longley,et al.  Remote Sensing and Urban Analysis : GISDATA 9 , 2000 .

[263]  J. Muller,et al.  Night-time Imagery as a Tool for Global Mapping of Socioeconomic Parameters and Greenhouse Gas Emissions , 2000 .

[264]  K. Gallo,et al.  Assessment of urban heat Islands: A multi‐sensor perspective for the Dallas‐Ft. worth, USA region , 1998 .

[265]  Eyal Ben-Dor,et al.  Airborne video thermal radiometry as a tool for monitoring microscale structures of the urban heat island , 1997 .

[266]  H. Mooney,et al.  Human Domination of Earth’s Ecosystems , 1997, Renewable Energy.

[267]  C. Elvidge,et al.  Mapping City Lights With Nighttime Data from the DMSP Operational Linescan System , 1997 .

[268]  C. Elvidge,et al.  Using nighttime DMSP/OLS images of city lights to estimate the impact of urban land use on soil resources in the United States , 1997 .

[269]  Jeff Dozier,et al.  A generalized split-window algorithm for retrieving land-surface temperature from space , 1996, IEEE Trans. Geosci. Remote. Sens..

[270]  M. Ridd Exploring a V-I-S (vegetation-impervious surface-soil) model for urban ecosystem analysis through remote sensing: comparative anatomy for cities , 1995 .

[271]  J. D. Tarpley,et al.  Assessment of urban heat islands: a satellite perspective , 1995 .

[272]  D. Schimel,et al.  Terrestrial biogeochemical cycles: Global estimates with remote sensing , 1995 .

[273]  C. Tucker,et al.  Tropical Deforestation and Habitat Fragmentation in the Amazon: Satellite Data from 1978 to 1988 , 1993, Science.

[274]  Hongsuk H. Kim Urban heat island , 1992 .

[275]  Philip J. Howarth,et al.  Land-use classification of SPOT HRV data using a cover-frequency method , 1992 .

[276]  Ingegärd Eliasson,et al.  Infrared thermography and urban temperature patterns , 1992 .

[277]  P. Gong,et al.  Frequency-based contextual classification and gray-level vector reduction for land-use identification , 1992 .

[278]  Terry McGee,et al.  The emergence of desakota regions in Asia: expanding a hypothesis , 1991 .

[279]  R. C. Larson,et al.  An analysis of an urban heat sink , 1990 .

[280]  P. Gong,et al.  The use of structural information for improving land-cover classification accuracies at the rural-urban fringe. , 1990 .

[281]  W. Emery,et al.  Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatology , 1989 .

[282]  Philip J. Howarth,et al.  Performance analyses of probabilistic relaxation methods for land-cover classification☆ , 1989 .

[283]  S. Kidder,et al.  A multispectral study of the St. Louis area under snow-covered conditions using NOAA-7 AVHRR data , 1987 .

[284]  D. Quattrochi An Initial Analysis of LANDSAT-4 Thematic Mapper Data for the Discrimination of Agricultural, Forested Wetland, and Urban Land Covers , 1984 .

[285]  B. Haack An analysis of thematic mapper simulator data for urban environments , 1983 .

[286]  Philip J. Howarth,et al.  Landsat digital enhancements for change detection in urban environments , 1983 .

[287]  T. Oke The energetic basis of the urban heat island , 1982 .

[288]  D. Toll,et al.  Preliminary results of mapping urban land cover with Seasat SAR imagery , 1980 .

[289]  C. Lo,et al.  CHINESE URBAN POPULATION ESTIMATES , 1977 .

[290]  M. Leonard Bryan Interpretation of an urban scene using multi-channel radar imagery , 1975 .

[291]  Steven P Kraus,et al.  Estimating population from photographically determined residential land use types , 1974 .

[292]  T. Oke City size and the urban heat island , 1973 .

[293]  Frank E. Horton,et al.  Urban-change detection systems: Remote-sensing inputs , 1972 .

[294]  Norman J. W. Thrower,et al.  ANNALS MAP SUPPLEMENT NUMBER TWELVE: LAND USE IN THE SOUTHWESTERN UNITED STATES—FROM GEMINI AND APOLLO‐IMAGERY , 1970 .