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}
}
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.
Długoński, Andrzej; Wellmann, Thilo; Haase, Dagmar
Old-Growth Forests in Urban Nature Reserves: Balancing Risks for Visitors and Biodiversity Protection in Warsaw, Poland Journal Article
In: Land, vol. 12, no. 2, 2023, ISSN: 2073-445X.
Abstract | Links | BibTeX | Tags: Biodiversity, Urban forest, Urban nature reserve, Vegetation management, Warsaw
@article{land12020275,
title = {Old-Growth Forests in Urban Nature Reserves: Balancing Risks for Visitors and Biodiversity Protection in Warsaw, Poland},
author = {Andrzej Długoński and Thilo Wellmann and Dagmar Haase},
url = {https://www.mdpi.com/2073-445X/12/2/275},
doi = {10.3390/land12020275},
issn = {2073-445X},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {Land},
volume = {12},
number = {2},
abstract = {Urban nature reserves in Poland are precious relics of ancient nature with preserved biodiversity. They consist of valuable trees several 100 years old, are biodiverse, and are valuable recreational spaces right in and around cities. It is therefore critical to manage tradeoffs between visitor safety due to, e.g., falling dead branches and the need for old-grown trees for biodiversity conservation. This study aimed to determine whether airborne laser scanning data (LiDAR) can confirm that trees exhibiting the worst crown defoliation are the first to be damaged in storms. Our results show that during Storm Eunice in 2022, the detected defoliated trees, in fact, were damaged the most. Despite such evidence available to the city, no targeted changes to the management of the reserves were taken after the storm. One of the forests was completely closed to visitors; in the other forest, areas with damaged trees were fenced off, and then, the remaining branches and fallen trees were removed to make the forest available for recreation. Using available evidence such as LiDAR data, we propose more targeted and nuanced forms of managing biodiversity conservation in conjunction with visitor safety. This includes the establishment of priority areas, visitor information, and visitor management. This way, airborne laser scanning and Geographic Information Systems can be used to balance management needs accounting for both biodiverse old-grown forest structures while at the same time providing added safety for visitors.},
keywords = {Biodiversity, Urban forest, Urban nature reserve, Vegetation management, Warsaw},
pubstate = {published},
tppubtype = {article}
}
Urban nature reserves in Poland are precious relics of ancient nature with preserved biodiversity. They consist of valuable trees several 100 years old, are biodiverse, and are valuable recreational spaces right in and around cities. It is therefore critical to manage tradeoffs between visitor safety due to, e.g., falling dead branches and the need for old-grown trees for biodiversity conservation. This study aimed to determine whether airborne laser scanning data (LiDAR) can confirm that trees exhibiting the worst crown defoliation are the first to be damaged in storms. Our results show that during Storm Eunice in 2022, the detected defoliated trees, in fact, were damaged the most. Despite such evidence available to the city, no targeted changes to the management of the reserves were taken after the storm. One of the forests was completely closed to visitors; in the other forest, areas with damaged trees were fenced off, and then, the remaining branches and fallen trees were removed to make the forest available for recreation. Using available evidence such as LiDAR data, we propose more targeted and nuanced forms of managing biodiversity conservation in conjunction with visitor safety. This includes the establishment of priority areas, visitor information, and visitor management. This way, airborne laser scanning and Geographic Information Systems can be used to balance management needs accounting for both biodiverse old-grown forest structures while at the same time providing added safety for visitors.
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{XIE2023158608b,
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}
}
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.