2020
Lausch, Angela; Schaepman, Michael E.; Skidmore, Andrew K.; Truckenbrodt, Sina C.; Hacker, Jörg M.; Baade, Jussi; Bannehr, Lutz; Borg, Erik; Bumberger, Jan; Dietrich, Peter; Gläßer, Cornelia; Haase, Dagmar; Heurich, Marco; Jagdhuber, Thomas; Jany, Sven; Krönert, Rudolf; Möller, Markus; Mollenhauer, Hannes; Montzka, Carsten; Pause, Marion; Rogass, Christian; Salepci, Nesrin; Schmullius, Christiane; Schrodt, Franziska; Schütze, Claudia; Schweitzer, Christian; Selsam, Peter; Spengler, Daniel; Vohland, Michael; Volk, Martin; Weber, Ute; Wellmann, Thilo; Werban, Ulrike; Zacharias, Steffen; Thiel, Christian
Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces Journal Article
In: Remote Sensing, vol. 12, no. 22, pp. 3690, 2020.
Abstract | Links | BibTeX | Tags: Earth observation, Geodiversity, Geomorphology, Monitoring, Remote Sensing, Spectral traits, Traits
@article{Lausch_2020,
title = {Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces},
author = {Angela Lausch and Michael E. Schaepman and Andrew K. Skidmore and Sina C. Truckenbrodt and Jörg M. Hacker and Jussi Baade and Lutz Bannehr and Erik Borg and Jan Bumberger and Peter Dietrich and Cornelia Gläßer and Dagmar Haase and Marco Heurich and Thomas Jagdhuber and Sven Jany and Rudolf Krönert and Markus Möller and Hannes Mollenhauer and Carsten Montzka and Marion Pause and Christian Rogass and Nesrin Salepci and Christiane Schmullius and Franziska Schrodt and Claudia Schütze and Christian Schweitzer and Peter Selsam and Daniel Spengler and Michael Vohland and Martin Volk and Ute Weber and Thilo Wellmann and Ulrike Werban and Steffen Zacharias and Christian Thiel},
url = {https://doi.org/10.3390%2Frs12223690},
doi = {10.3390/rs12223690},
year = {2020},
date = {2020-11-01},
urldate = {2020-11-01},
journal = {Remote Sensing},
volume = {12},
number = {22},
pages = {3690},
publisher = {MDPI AG},
abstract = {The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.},
keywords = {Earth observation, Geodiversity, Geomorphology, Monitoring, Remote Sensing, Spectral traits, Traits},
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}
}
Wellmann, Thilo; Lausch, Angela; Andersson, Erik; Knapp, Sonja; Cortinovis, Chiara; Jache, Jessica; Scheuer, Sebastian; Kremer, Peleg; Mascarenhas, André; Kraemer, Roland; Schug, Franz; Haase, Annegret; Haase, Dagmar
Remote sensing in urban planning: Contributions towards ecologically sound policies? Journal Article
In: Landscape and Urban Planning, vol. 204, pp. 103921, 2020.
Abstract | Links | BibTeX | Tags: Earth observation, Ecosystem services, Open science, Remote Sensing, Science policy interface, Systematic literature review, Urban ecology
@article{wellmann2020remote,
title = {Remote sensing in urban planning: Contributions towards ecologically sound policies?},
author = {Thilo Wellmann and Angela Lausch and Erik Andersson and Sonja Knapp and Chiara Cortinovis and Jessica Jache and Sebastian Scheuer and Peleg Kremer and André Mascarenhas and Roland Kraemer and Franz Schug and Annegret Haase and Dagmar Haase},
doi = {10.1016/j.landurbplan.2020.103921},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Landscape and Urban Planning},
volume = {204},
pages = {103921},
publisher = {Elsevier},
abstract = {Remote sensing has evolved to become a key tool for various fields of environmental analysis, thus actively informing policy across areas and domains. To evaluate the degree to which remote sensing is contributing to the science of ecologically-oriented urban planning, we carried out a systematic literature review using the SCOPUS database, searching for articles integrating knowledge in urban planning, remote sensing and ecology. We reviewed 186 articles, analysing various issues in urban environments worldwide. Key findings include that the level of integration between the three disciplines is limited, with only 12% of the papers fully integrating ecology, remote sensing and planning while 24% of the studies use specific methods from one domain only. The vast majority of studies is oriented towards contributing to the knowledge base or monitoring the impacts of existing policies. Few studies are directly policy relevant by either contributing to direct issues in planning and making specific design suggestions or evaluations. The accessibility of the scientific findings remains limited, as the majority of journal articles are not open access and proprietary software and data are frequently used. To overcome these issues, we suggest three future avenues for science as well as three potential entry points for remote sensing into applied urban planning. By doing so, remote sensing data could become a vital tool actively contributing to policies, civil engagement and concrete planning measures by providing independent and cost effective environmental analyses.},
keywords = {Earth observation, Ecosystem services, Open science, Remote Sensing, Science policy interface, Systematic literature review, Urban ecology},
pubstate = {published},
tppubtype = {article}
}