Zobrazeno 1 - 10
of 33
pro vyhledávání: '"Dani Arribas-Bel"'
Autor:
Gladys Elizabeth Kenyon, Dani Arribas-Bel, Caitlin Robinson, Olga Gkountouna, Pelayo Arbués, David Rey-Blanco
Publikováno v:
npj Urban Sustainability, Vol 4, Iss 1, Pp 1-10 (2024)
Abstract In this paper we explore the temporal dynamics of spatial inequality in housing prices for Madrid, the capital city of Spain. Spatial inequalities are a concerning feature of urban areas across the globe. It has been suggested that within ci
Externí odkaz:
https://doaj.org/article/71759a24d023438ea6806b4f982962d0
Publikováno v:
Land, Vol 13, Iss 5, p 575 (2024)
The following paper proposes a novel machine learning approach to the segmentation of urban housing markets. We extract features from globally available satellite imagery using an unsupervised machine learning model called MOSAIKS, and apply a k-mean
Externí odkaz:
https://doaj.org/article/2eecd332faa848f4a6ae1be1285b3301
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 9, Iss 4, p 264 (2020)
Urban environments play a crucial role in the design, planning, and management of cities. Recently, as the urban population expands, the ways in which humans interact with their surroundings has evolved, presenting a dynamic distribution in space and
Externí odkaz:
https://doaj.org/article/3cef6db118d94fc7bda8286e2e4d92cd
Publikováno v:
Remote Sensing, Vol 11, Iss 12, p 1395 (2019)
We develop a method based on computer vision and a hierarchical multilevel model to derive an Urban Street Tree Vegetation Index which aims to quantify the amount of vegetation visible from the point of view of a pedestrian. Our approach unfolds in t
Externí odkaz:
https://doaj.org/article/bd8d8815b8cb4659af19c0bdc1892b84
Publikováno v:
Geographic Data Science with Python ISBN: 9780429292507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ae4edf494026ab314c5f2654df64defa
https://doi.org/10.1201/9780429292507-8
https://doi.org/10.1201/9780429292507-8
Publikováno v:
Geographic Data Science with Python ISBN: 9780429292507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0fa483d39082c4d9188e36b7d36dea53
https://doi.org/10.1201/9780429292507-3
https://doi.org/10.1201/9780429292507-3
Publikováno v:
Geographic Data Science with Python ISBN: 9780429292507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c11490dfc6ffd5dba033a4069ace25e3
https://doi.org/10.1201/9780429292507-13
https://doi.org/10.1201/9780429292507-13
Publikováno v:
Geographic Data Science with Python ISBN: 9780429292507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::881f9995c458de7d9cf34d7e74127c8a
https://doi.org/10.1201/9780429292507-7
https://doi.org/10.1201/9780429292507-7
Publikováno v:
Geographic Data Science with Python ISBN: 9780429292507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::930ae94bad8a9167cf16ad26f6bfd959
https://doi.org/10.1201/9780429292507-12
https://doi.org/10.1201/9780429292507-12
Publikováno v:
Geographic Data Science with Python ISBN: 9780429292507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::292625efff4d20592c3cc740117792fa
https://doi.org/10.1201/9780429292507-9
https://doi.org/10.1201/9780429292507-9