Mapping dynamic peri-urban land use transitions across Canada using Landsat time series: Spatial and temporal trends and associations with socio-demographic factors
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Nicholas C. Coops | Michael A. Wulder | Joanne C. White | Txomin Hermosilla | Agatha Czekajlo | Matilda van den Bosch | N. Coops | M. Wulder | J. White | T. Hermosilla | M. Bosch | Agatha Czekajlo
[1] Juan Carlos Duque,et al. A review of regional science applications of satellite remote sensing in urban settings , 2013, Comput. Environ. Urban Syst..
[2] D. Goodin,et al. Mapping land cover and land use from object-based classification: an example from a complex agricultural landscape , 2015 .
[3] F. Creutzig,et al. Future urban land expansion and implications for global croplands , 2016, Proceedings of the National Academy of Sciences.
[4] Joanne C. White,et al. Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series , 2018 .
[5] José G. Siri,et al. Defining and advancing a systems approach for sustainable cities , 2016 .
[6] Erik Andersson,et al. Remote sensing in urban planning: Contributions towards ecologically sound policies? , 2020 .
[7] K. Seto,et al. A Meta-Analysis of Global Urban Land Expansion , 2011, PloS one.
[8] Linxin Ye,et al. What Is “Smart Growth?”—Really? , 2005 .
[9] J. Boardman. Automating spectral unmixing of AVIRIS data using convex geometry concepts , 1993 .
[10] M. Brauer,et al. Beyond the Normalized Difference Vegetation Index (NDVI): Developing a Natural Space Index for population‐level health research , 2017, Environmental research.
[11] M. McKinney,et al. Urbanization, Biodiversity, and Conservation , 2002 .
[12] Brian Curtiss,et al. A method for manual endmember selection and spectral unmixing , 1996 .
[13] Christian Fertner,et al. Urban sprawl and growth management – drivers, impacts and responses in selected European and US cities , 2016 .
[14] Karen C. Seto,et al. A systematic review and assessment of algorithms to detect, characterize, and monitor urban land change , 2020 .
[15] M. Helbich. Spatiotemporal Contextual Uncertainties in Green Space Exposure Measures: Exploring a Time Series of the Normalized Difference Vegetation Indices , 2019, International journal of environmental research and public health.
[16] J. Ottensmann. Urban Sprawl, Land Values and the Density of Development , 1977 .
[17] Md. Golam Mortoja,et al. What is the most suitable methodological approach to demarcate peri-urban areas? A systematic review of the literature , 2020, Land Use Policy.
[18] Dirk Pflugmacher,et al. Green growth? On the relation between population density, land use and vegetation cover fractions in a city using a 30-years Landsat time series , 2020 .
[19] M. Storper,et al. Behaviour, Preferences and Cities: Urban Theory and Urban Resurgence , 2006 .
[20] Lisa-Marie Hemerijckx,et al. Bridging the rural-urban dichotomy in land use science , 2020, Journal of Land Use Science.
[21] Kate E. Jones,et al. Mapping synergies and trade-offs between urban ecosystems and the sustainable development goals , 2019, Environmental Science & Policy.
[22] J. Boardman,et al. Mapping target signatures via partial unmixing of AVIRIS data: in Summaries , 1995 .
[23] Ruiliang Pu,et al. The impact of land development regulation on residential tree cover: An empirical evaluation using high-resolution IKONOS imagery , 2010 .
[24] Cayce J. Hook,et al. A meta-analysis of the relationship between socioeconomic status and executive function performance among children. , 2018, Developmental science.
[25] Di Yang,et al. Open land-use map: a regional land-use mapping strategy for incorporating OpenStreetMap with earth observations , 2017, Geo spatial Inf. Sci..
[26] Txomin Hermosilla,et al. Original papers: A feature extraction software tool for agricultural object-based image analysis , 2011 .
[27] Cristian Silva. Auckland’s Urban Sprawl, Policy Ambiguities and the Peri-Urbanisation to Pukekohe , 2018, Urban Science.
[28] Jing Zhang,et al. Agglomeration and diffusion of urban functions: An approach based on urban land use conversion , 2016 .
[29] Sérgio Freire,et al. Unveiling 25 Years of Planetary Urbanization with Remote Sensing: Perspectives from the Global Human Settlement Layer , 2018, Remote. Sens..
[30] Nicholas C. Coops,et al. The urban greenness score: A satellite-based metric for multi-decadal characterization of urban land dynamics , 2020, Int. J. Appl. Earth Obs. Geoinformation.
[31] G. Tiwari,et al. Land use, transport, and population health: estimating the health benefits of compact cities , 2016, The Lancet.
[32] K. Seto,et al. Time series analysis of satellite data to characterize multiple land use transitions: a case study of urban growth and agricultural land loss in India , 2018 .
[33] Mark Nieuwenhuijsen,et al. No time to lose - Green the cities now. , 2017, Environment international.
[34] Zhe Zhu,et al. Understanding an urbanizing planet: Strategic directions for remote sensing , 2019, Remote Sensing of Environment.
[35] Suming Jin,et al. Completion of the 2011 National Land Cover Database for the Conterminous United States – Representing a Decade of Land Cover Change Information , 2015 .
[36] Nicholas C. Coops,et al. Regional assessment of pan-Pacific urban environments over 25 years using annual gap free Landsat data , 2016, Int. J. Appl. Earth Obs. Geoinformation.
[37] Jian Yang,et al. Automated mapping of impervious surfaces in urban and suburban areas: Linear spectral unmixing of high spatial resolution imagery , 2017, Int. J. Appl. Earth Obs. Geoinformation.
[38] L. Kubzansky,et al. It's not easy assessing greenness: A comparison of NDVI datasets and neighborhood types and their associations with self‐rated health in New York City , 2018, Health & place.
[39] Bert Guindon,et al. Landsat urban mapping based on a combined spectral–spatial methodology , 2004 .
[40] Hongwei Dong,et al. Smart growth in two contrastive metropolitan areas: A comparison between Portland and Los Angeles , 2015 .
[41] I. Helbrecht,et al. Housing Vancouver, 1972–2017: A personal urban geography and a professional response , 2020 .
[42] Xin Pan,et al. An object-based convolutional neural network (OCNN) for urban land use classification , 2018, Remote Sensing of Environment.
[43] Josep Maria Haro,et al. The role of socio-economic status in depression: results from the COURAGE (aging survey in Europe) , 2016, BMC Public Health.
[44] Xiaojing Tang,et al. Characterizing urban landscapes using fuzzy sets , 2016, Comput. Environ. Urban Syst..
[45] Li Tian,et al. Coupled dynamics of urban landscape pattern and socioeconomic drivers in Shenzhen, China , 2014, Landscape Ecology.
[46] Nicholas C. Coops,et al. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring , 2016, Int. J. Digit. Earth.
[47] P. Switzer,et al. A transformation for ordering multispectral data in terms of image quality with implications for noise removal , 1988 .
[48] K. Seto,et al. Trends in urban land expansion, density, and land transitions from 1970 to 2010: a global synthesis , 2020, Environmental Research Letters.
[49] P. Sen. Estimates of the Regression Coefficient Based on Kendall's Tau , 1968 .
[50] B. Guindon,et al. Concepts and application of the Canadian Urban Land Use Survey , 2010 .
[51] Mohsen Gholoobi,et al. Using object-based hierarchical classification to extract land use land cover classes from high-resolution satellite imagery in a complex urban area , 2015 .
[52] H. B. Mann. Nonparametric Tests Against Trend , 1945 .
[53] Joanne C. White,et al. Pixel-Based Image Compositing for Large-Area Dense Time Series Applications and Science , 2014 .
[54] P. Sutton,et al. The ecological economics of land degradation: impacts on ecosystem service values. , 2016 .
[55] Lawrence N Hudson,et al. Global patterns of terrestrial assemblage turnover within and among land uses , 2016 .
[56] José I. Barredo,et al. Are European Cities Becoming Dispersed? A Comparative Analysis of 15 European Urban Areas , 2006 .
[57] Michael A. Wulder,et al. Opening the archive: How free data has enabled the science and monitoring promise of Landsat , 2012 .
[58] L. Alonso,et al. Urban natural environments and motor development in early life. , 2019, Environmental research.
[59] M. Jerrett,et al. Development of a Canadian socioeconomic status index for the study of health outcomes related to environmental pollution , 2015, BMC Public Health.
[60] Jianping Wu,et al. Monitoring urban expansion and land use/land cover changes of Shanghai metropolitan area during the transitional economy (1979–2009) in China , 2011, Environmental monitoring and assessment.