2023
Xie, Chenghan; Wang, Jingxia; Haase, Dagmar; Wellmann, Thilo; Lausch, Angela
In: Science of The Total Environment, vol. 855, pp. 158608, 2023, ISSN: 0048-9697.
Abstract | Links | BibTeX | Tags: Internal orderliness, RapidEye data, Spatial heterogeneity, Urban green space, Urban planning, Vegetation management
@article{XIE2023158608,
title = {Measuring spatio-temporal heterogeneity and interior characteristics of green spaces in urban neighborhoods: A new approach using gray level co-occurrence matrix},
author = {Chenghan Xie and Jingxia Wang and Dagmar Haase and Thilo Wellmann and Angela Lausch},
url = {https://www.sciencedirect.com/science/article/pii/S0048969722057072},
doi = {https://doi.org/10.1016/j.scitotenv.2022.158608},
issn = {0048-9697},
year = {2023},
date = {2023-01-01},
journal = {Science of The Total Environment},
volume = {855},
pages = {158608},
abstract = {Urban green space (UGS) is a complex and highly dynamic interface between people and nature. The existing methods of quantifying and evaluating UGS are mainly implemented on the surface features at a landscape scale, and most of them are insufficient to thoroughly reflect the spatial-temporal relationships, especially the internal characteristics changes at a small scale and the neighborhood spatial relationship of UGS. This paper thus proposes a method to evaluate the internal dynamics and neighborhood heterogeneity of different types of UGS in Leipzig using the gray level co-occurrence matrix (GLCM) index. We choose GLCM variance, contrast, and entropy to analyze five main types of UGS through a holistic description of their vegetation growth, spatial heterogeneity, and internal orderliness. The results show that different types of UGS have distinct characteristics due to the changes of surrounding buildings and the distance to the built-up area. Within a one-year period, seasonal changes in UGS far away from built-up areas are more obvious. As for the larger and dense urban forests, they have the lowest spatial heterogeneity and internal order. On the contrary, the garden areas present the highest heterogeneity. In this study, the GLCM index depicts the seasonal alternation of UGS on the temporal scale and shows the spatial form of each UGS, being in line with local urban planning contexts. The correlation analysis of indices also proves that each type of UGS has its distinct temporal and spatial characteristics. The GLCM is valid in assessing the internal characteristics and relationships of various UGS at the neighborhood scales, and using the methodology developed in our study, more studies and field experiments could be fulfilled to investigate the assessment accuracy of our GLCM index approach and to further enhance the scientific understanding on the internal features and ecological functions of UGS.},
keywords = {Internal orderliness, RapidEye data, Spatial heterogeneity, Urban green space, Urban planning, Vegetation management},
pubstate = {published},
tppubtype = {article}
}
2021
Lessel, Tilia; Wellmann, Thilo
Umweltgerechtigkeit aus bürgerschaftlicher Perspektive: Handlungsempfehlung am Beispiel Berlin-Schöneberg Journal Article
In: Stadt+Grün, vol. 01, 2021.
Abstract | Links | BibTeX | Tags: Berlin, Climate Change, Climate Change Adaptation, Environmental justice, Urban development, Urban green infrastructure, Urban planning
@article{Thilo_Wellmann_107218183,
title = {Umweltgerechtigkeit aus bürgerschaftlicher Perspektive: Handlungsempfehlung am Beispiel Berlin-Schöneberg},
author = {Tilia Lessel and Thilo Wellmann},
url = {https://stadtundgruen.de/artikel/umweltgerechtigkeit-aus-buergerschaftlicher-perspektive-15076.html},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Stadt+Grün},
volume = {01},
abstract = {Städte sind für die Umsetzung von Umweltgerechtigkeit von zentraler Bedeutung. Rund drei Viertel der EuropäerInnen leben in urbanen Räumen, so dass Fragen von Gerechtigkeit und Zugang zu Umweltqualitäten besonders hier entschieden werden. Zudem schaffen Städte durch ihre Baumasse Wärme- und Trockeninseln und damit ein besonders extremes, umwelt- und gesundheitsbelastendes Lokalklima. Vor diesem Hintergrund ist absehbar, dass die Effekte des Klimawandels die Städte besonders betreffen.},
keywords = {Berlin, Climate Change, Climate Change Adaptation, Environmental justice, Urban development, Urban green infrastructure, Urban planning},
pubstate = {published},
tppubtype = {article}
}
2020
Castillo-Cabrera, Fernando; Wellmann, Thilo; Haase, Dagmar
Urban Green Fabric Analysis Promoting Sustainable Planning in Guatemala City Journal Article
In: Land, 2020.
Abstract | Links | BibTeX | Tags: Guatemala City, Remote Sensing, Urban green infrastructure, Urban planning, Urbanisation
@article{Thilo_Wellmann_85962105,
title = {Urban Green Fabric Analysis Promoting Sustainable Planning in Guatemala City},
author = {Fernando Castillo-Cabrera and Thilo Wellmann and Dagmar Haase},
url = {http://doi.org/10.3390/land10010018},
doi = {10.3390/land10010018},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Land},
abstract = {Urbanization rate in Central America is the second fastest worldwide and its major cities face challenges regarding urban sustainability. Urban Green Fabric (UGF) is an important material condition for the urban quality of life and, therefore, key to planning processes. We performed an analysis of the UGF of Guatemala City including the identification and classification of UGF, their spatial pattern analysis, construction of ensembles of districts (zones) and revealing citizen’s interactions with UGF. We used remote sensing and land use mapping techniques, spatial metrics and a questionnaire survey. Main results are the UGF map of Guatemala City and six ensembles of zones based on a set of indicators. We further revealed citizens’ recognition of green spaces, their perceptions about green space amount and availability as well as their support for UGF future interventions. Finally, we discuss the implications for planning promoted by our results and suggest three actions for UGF sustainability: Creation of new green spaces, protecting existing green spaces and enhancing the mosaic with different green spaces types. UGF is an essential decision support tool for a diversity of actors.},
keywords = {Guatemala City, Remote Sensing, Urban green infrastructure, Urban planning, Urbanisation},
pubstate = {published},
tppubtype = {article}
}
Wellmann, Thilo; Schug, Franz; Haase, Dagmar; Pflugmacher, Dirk; Linden, Sebastian
Green growth? On the relation between population density, land use and vegetation cover fractions in a city using a 30-years Landsat time series Journal Article
In: Landscape and Urban Planning, 2020, ISSN: 0169-2046.
Abstract | Links | BibTeX | Tags: Berlin, Compact vs. Dispersed developments, Earth observation, Greening City, Landsat, Machine learning, Unmixing, Urban planning
@article{Thilo_Wellmann_75416790,
title = {Green growth? On the relation between population density, land use and vegetation cover fractions in a city using a 30-years Landsat time series},
author = {Thilo Wellmann and Franz Schug and Dagmar Haase and Dirk Pflugmacher and Sebastian Linden},
url = {https://thilowellmann.de/wp/wp-content/uploads/2020/06/WellmannEtAl_GreenGrowth_AcceptedManuscript.pdf},
doi = {10.1016/j.landurbplan.2020.103857},
issn = {0169-2046},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Landscape and Urban Planning},
abstract = {Both compact and dispersed green cities are considered sustainable urban forms, yet some developments accompanied with these planning paradigms seem problematic in times of urban growth. A compact city might lose urban green spaces due to infill and a dispersed-green city might lose green in its outskirts through suburbanisation. To study these storylines, we introduce an operationalised concept of contrasting changes in population density (shrinkage or growth) with vegetation density (sealing or greening) over time. These trends are ascribed to different land use classes and single urban development projects, to quantify threads and pathways for urban green in a densifying city. We mapped the development in vegetation density over 30 years as subpixel fractions based on a Landsat remote sensing time series (for 2015: MAE 0.12). The case study city Berlin, Germany, developed into a city that is both gaining in vegetation–greening–and population–growing–in recent years but featured highly diverse trends for both compact and green city districts before that. Pathways to achieve a greening-growing scenario in a compact city include green roofs, brownfield and industrial revitalisation, and bioswales in predominantly green city districts. A threat for compact cities pose infill developments without greening measures. A threat for dispersed-green cities is microsealing in private residential gardens–gravel gardens–or car parking infrastructure. We conclude that neither a compact nor a dispersed-green city form concept logically leads to a development towards more environmental quality–here vegetation density–in times of densification but rather context specific urban planning.},
keywords = {Berlin, Compact vs. Dispersed developments, Earth observation, Greening City, Landsat, Machine learning, Unmixing, Urban planning},
pubstate = {published},
tppubtype = {article}
}