scholarly journals How Do Urban Parks Provide Bird Habitats and Birdwatching Service? Evidence from Beijing, China

2020 ◽  
Vol 12 (19) ◽  
pp. 3166
Author(s):  
Zhengkai Zhang ◽  
Ganlin Huang
Keyword(s):  
Green Infrastructure ◽  
Complex Dynamics ◽  
Remote Sensing Data ◽  
Entropy Method ◽  
Landscape Patterns ◽  
Bird Survey ◽  
Bird Habitat ◽  
Bird Census ◽  
Patch Density ◽  
Beijing China

Parks are an important green infrastructure. Besides other benefits for human and animals, parks provide important bird habitats and accommodate most human-bird interactions in cities. Understanding the complex dynamics among park characteristics, bird habitats and park attractiveness to birdwatchers will inform park designers and managers. However, previous studies often examined factors influencing bird habitats and birdwatching activities separately. To fill this gap, we aim to study the whole picture of “parks, birds and birdwatchers” in Beijing, China for its spatial patterns and possible factors which influence bird habitat areas and birdwatching services. We conducted a three-month bird census in at 159 sites and mapped bird habitat areas in parks of Beijing through the maximum entropy method based on results of the bird survey as well as high-resolution remote sensing data. We derived the number of birdwatching records to describe birdwatching activities from the China Birdwatching Record Center website. We used correlation analysis, regression and analysis of variance to investigate factors that may influence areas of bird habitats and the number of birdwatching records for each park. Our results showed that among the 102 parks, 61 provide habitats to breeding birds with an average of 17 ha, and 26 parks generated a total of 330 birdwatching records. Park size, age, proportion of pavement, landscape connectedness, pavement largest patch index and woodland patch density explained 95% of the variation in habitat areas altogether. Bird habitat area alone explained 65% of the variation in the number of birdwatching records. Furthermore, parks with birdwatching records are significantly larger, older, closer to the city center and more accessible than those have no reported birdwatching. These findings have important implications for park management. While park size or age cannot be easily changed, modifying landscape patterns can increase bird habitats in parks, and improving accessibility may attract more birdwatchers to parks that already have considerable bird habitats.

Geosystems of Middle Siberia southern part: mapping methodology and results

2021 ◽  
Vol 970 (4) ◽  
pp. 35-44
Author(s):  
G.I. Lysanova ◽  
Ju.M. Semenov ◽  
A.A. Sorokovoi ◽  
I.V. Balyazin
Keyword(s):  
Landscape Structure ◽  
Remote Sensing Data ◽  
Landscape Patterns ◽  
Mountain Areas ◽  
Space Images ◽  
Earth Remote Sensing ◽  
Horizontal Structure ◽  
Composition And Structure ◽  
Geographical Regionalization ◽  
Middle Siberia

The сlassification of geosystem used in mapping is based on a system-hierarchic approach to detecting the co-involvement of landscape taxons. At the same time, we took into account the positioning of individual territories in the system of physical- geographical regionalization. The complexity of the landscape structure of the studied territory is due to its location at the junction of high- and lowland regions belonging to four physical-geographical areas. In the area under study, we identified and described more than 200 groups of fairies, which were then typed into classes of facies, geomes, and groups of geomes. Geoinformation mapping is performed using vector topographic basis and Earth remote sensing data. The decryption of synthesized space images was carried out manually and was based on field landscape surveys data. Digitization and indexing of landscape contours, creation, design and layout of the map were carried out in GIS MapInfo Professional. The cartographical analysis revealed regional differences in the complexity of landscape horizontal structures of high- and lowland regions, as well as the composition and structure of typological spectra of regional geosystems. Lowland geosystems mostly have a fairly uniform horizontal structure and large areas of landscape patterns. At the same time, mountain areas are characterized by considerable complexity and contrast of landscape structure.

scholarly journals Green Infrastructure, Urbanization, and Ecosystem Services: The Main Challenges for Russia’s Largest Cities

Land ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1292
Author(s):  
Oxana Klimanova ◽  
Olga Illarionova ◽  
Karsten Grunewald ◽  
Elena Bukvareva
Keyword(s):  
Ecosystem Services ◽  
Green Infrastructure ◽  
Remote Sensing Data ◽  
Well Being ◽  
Climate Conditions ◽  
Planning Policy ◽  
Current State ◽  
Decision Making Processes ◽  
Process Of Urbanization ◽  
High Level

Globally, the process of urbanization is transforming land use and, as a consequence, reducing the efficiency of ecosystem services (ESs), which ensure a healthy and comfortable urban environment. In cities, green infrastructure (GI) is a key source of urban ESs. Russia is a highly urbanized country: 70% of its population live in towns or cities. As cities continue to expand, they are swallowing unsealed lands that support ESs. In this paper, we present the results of an analysis of the current state and recent changes in urban GI in Russia’s 16 largest cities, including a biophysical evaluation of key urban ESs, using remote sensing data and freely available statistics. Our analysis identifies a weak correlation between GI area, ES volume, and favorable climate conditions as well as a stronger correlation between ESs and the increasing rate of urbanization. Considering Russia’s high level of urbanization, the key importance of ESs for the well-being of citizens, and ongoing reductions of urban GI, major revisions to urban planning policy are required. Indicators of urban biodiversity, GI, and ESs should be incorporated into decision-making processes. In particular, it is vital that the accounting and monitoring of GI and ESs are established in all of Russia’s larger cities.

scholarly journals Green infrastructure indicators for urban planning: applying the integrated approach for Russian largest cities

2020 ◽  
Vol 13 (1) ◽  
pp. 251-259
Author(s):  
Oxana A. Klimanova ◽  
Olga I. Illarionova
Keyword(s):  
Urban Planning ◽  
Green Infrastructure ◽  
Remote Sensing Data ◽  
Integrated Approach ◽  
Steppe Zone ◽  
Integrated Network ◽  
Ecosystem Integrity ◽  
Saint Petersburg ◽  
The One

Modern approaches to urban planning assume the dualistic nature of urban green infrastructure (GI). On the one hand, green infrastructure is as an integrated network of natural and semi-natural areas, featuring a delivery of various benefits to humans. On the other hand, GI is multifunctional and provides the residents by complex of ecosystem services to be user-oriented. Most official reports and programs use common indicators that do not characterize distribution, dynamics or state of GI. In our research, we assessed the quality of GI in 15 largest Russian cities by using an integrated assessment of 13 indicators that make up three groups: the ones 1) characterizing general GI availability; 2) supporting a comfortable urban environment («recreational indicators»); and 3) forming a stable ecosystem («integrity indicators»). The cities were ranked by values of every indicator from 1 to 15 and then the results were summed and normalized to get a total mark (max. 100). To assess the development of GI elements of each group, we also ranked cities separately by values of different groups indicators. Thus, our study revealed that satisfactory marks for both recreational and integrity indicators have Ufa, Nizhny Novgorod, Kazan, Ekaterinburg, Perm and Voronezh. In contrast, Saint Petersburg, being a densely built-up city in an auspicious natural zone, got the worst result. According to the final assessment, the quality of green infrastructure in Krasnoyarsk, a large industrial city, and four cities from the steppe zone (Rostov-on-Don, Samara, Omsk, Novosibirsk) is also unsatisfactory. Our method does not cover all GI aspects (like vegetation health) and since it is based solely on remote sensing data and statistics data, there is definitely a room for improvement. However, this method, while being relatively quick and simple to accomplish, allows to assess not only general availability of GI, but its quality and distribution as well, which are essential for urban spatial planning.

scholarly journals Effects of Urbanization on Landscape Patterns in a Mountainous Area: A Case Study in the Mentougou District, Beijing, China

2016 ◽  
Vol 8 (11) ◽  
pp. 1190 ◽  
Author(s):  
Yang Yi ◽  
Yuanyuan Zhao ◽  
Guodong Ding ◽  
Guanglei Gao ◽  
Mingchang Shi ◽  
...  
Keyword(s):  
Landscape Patterns ◽  
Mountainous Area ◽  
Beijing China

scholarly journals Urban Residential Land Suitability Analysis Combining Remote Sensing and Social Sensing Data: A Case Study in Beijing, China

2019 ◽  
Vol 11 (8) ◽  
pp. 2255 ◽  
Author(s):  
Huiping Huang ◽  
Qiangzi Li ◽  
Yuan Zhang
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Suitability ◽  
Residential Land ◽  
Social Sensing ◽  
Sensing Data ◽  
Beijing China

With the degradation of the environment and the acceleration of urbanization, urban residential land has been undergoing rapid changes and has attracted great attention worldwide. Meanwhile, the quantitative evaluation of the suitability of urban residential land is essential for a better and more powerful understanding of urban residential land planning and improvement. Most urban land suitability studies rely solely on remote sensing data and GIS data to evaluate natural suitability, and few studies have focused on urban land suitability from a socioeconomic perspective. Consequently, this paper integrates remote sensing data (GaoFen-2 satellite image) and social sensing data (Tencent User Density data, Point-of-interest data and OpenStreetMap data) to establish an evaluation framework for analyzing the suitability of urban residential land in the Haidian District, Beijing, China, in which, ecological comfortability, locational livability and overall suitability were evaluated according to five attributes extracted from urban residential land via the factor analysis method. The evaluation results of this case study show that, compared with the suburban area in the northwest, the urban area tends to have lower ecological comfortability and higher locational livability. The overall suitability increases from southeast to northwest, consistent with the spatial distribution of ecological comfortability. This framework can potentially assist with the sustainable development of residential lands and urban land use planning.

Soil-landscape patterns and fractal parameters of deforestation: a case study of Continental Ecuador Biosphere Reserves.

2020 ◽  
Author(s):  
Andrea Urgilez-Clavijo ◽  
Ana Tarquis ◽  
David Rivas-Tabares ◽  
Juan de la Riva
Keyword(s):  
Land Cover ◽  
Agricultural Land ◽  
Complex Dynamics ◽  
Spatial Location ◽  
Landscape Patterns ◽  
Self Similarity ◽  
Biosphere Reserves ◽  
Classification Image ◽  
Structural Funds ◽  
Cross Classification

<p>The complex dynamics of changes in land use and land cover at different scales cause changes in the composition and configuration of the landscape. Deforestation, mainly caused by the transformation of forest to agricultural land, has been one of the most representative changes in recent years worldwide. In Ecuador, this transformation has occurred in different areas of the country, even in those areas declared by UNESCO as biosphere reserves (BRs), endangering the diversity of ecosystems and species existing within each of them. In this context, the identification of patterns, trajectories and magnitudes associated with the deforestation process in the BR areas is essential for the management, conservation and even evaluation of the protection effectiveness of these areas. We analyze the changes in land cover produced between 1990 and 2016 in the <em>Sumaco</em> and <em>Bosque Seco</em> BRs belonging to continental Ecuador, as well as the patterns associated with the deforestation process that occurred in that period. The quantification of land cover changes was performed using a cross-tabulation-table and their spatial location was done through a cross-classification image. The patterns were characterized using landscape ecology metrics and their nature described through multifractal analysis. In addition, the scales at which self-similarity characteristics are detected were identified by lacunarity analysis. The results show that there are three patterns associated with deforestation processes, (1) regrowth of preexisting patches without fusion of the adjacent patches, (2) Regrowth and fusion of preexisting patches and (3) the appearance of new deforested patches. In addition, the multifractal nature of the deforested structure was verified and characteristics of self-similarity at <em>parroquia</em> scale were identified.</p><p><strong>ACKNOWLEDGEMENTS</strong></p><p>This work was supported by the Program of University of Zaragoza-Santander for Ibero633 Americans in Doctorate studies. Second author acknowledges support from Project No. 634 PGC2018-093854-B-I00 of the Spanish Ministerio de Ciencia Innovación y Universidades of Spain and to the Comunidad de Madrid (Spain) and Structural Funds 2014–2020 (ERDF and ESF) project AGRISOST-CM S2018/BAA-4330. We are also grateful to University of Azuay and Ministry of Environment of Ecuador for providing data and resources for the development of this academic work.</p>

scholarly journals Mapping Functional Urban Green Types Using High Resolution Remote Sensing Data

2020 ◽  
Vol 12 (5) ◽  
pp. 2144
Author(s):  
Jeroen Degerickx ◽  
Martin Hermy ◽  
Ben Somers
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Green Infrastructure ◽  
Remote Sensing Data ◽  
Hyperspectral Data ◽  
Airborne Lidar ◽  
Green Spaces ◽  
Human Society ◽  
Urban Green ◽  
Sensing Data

Urban green spaces are known to provide ample benefits to human society and hence play a vital role in safeguarding the quality of life in our cities. In order to optimize the design and management of green spaces with regard to the provisioning of these ecosystem services, there is a clear need for uniform and spatially explicit datasets on the existing urban green infrastructure. Current mapping approaches, however, largely focus on large land use units (e.g., park, garden), or broad land cover classes (e.g., tree, grass), not providing sufficient thematic detail to model urban ecosystem service supply. We therefore proposed a functional urban green typology and explored the potential of both passive (2 m-hyperspectral and 0.5 m-multispectral optical imagery) and active (airborne LiDAR) remote sensing technology for mapping the proposed types using object-based image analysis and machine learning. Airborne LiDAR data was found to be the most valuable dataset overall, while fusion with hyperspectral data was essential for mapping the most detailed classes. High spectral similarities, along with adjacency and shadow effects still caused severe confusion, resulting in class-wise accuracies <50% for some detailed functional types. Further research should focus on the use of multi-temporal image analysis to fully unlock the potential of remote sensing data for detailed urban green mapping.

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