Agata Cieszewska, 2019, Green belts. Zielone pierścienie wielkich miast, Warszawa, Wydawnictwo Akademickie SEDNO, 296 stron, DOI 10.26343/9788379630868, recenzja książki

-

Exploring the Influencing Factors of the Recreational Utilization and Evaluation of Urban Ecological Protection Green Belts for Urban Renewal: A Case Study in Shanghai

With the continuous expansion of urban construction land, the green belts aiming for ecological protection have ensured a sustainable and effective function of regional ecosystem services. At the same time, these ecological green belts are expected to develop their compound service potentials with the development of cities. In order to meet the increasing demand of urban residents for the recreational utilization of urban green space, the primary function of the ecological green belts has transformed from being purely ecological to a combination of being ecological and recreational. Based on social media data, which has the characteristics of a large amount of accessible geographic information, this study used multiple regression models to analyze the recreational utilization intensity of ecological protection green belts with a case study in the green belt of Shanghai, China. The research results showed that the internal elements (total external area, water area, etc.) of the Shanghai green belt have positive correlations with its recreational utilization. The impact of external factors was inconclusive on the recreational utilization of the outer forest belt (the number of subway stations in accessibility factors was negatively correlated; the number of cultural facilities and the number of restaurants in the surrounding service facilities were positively related). Combined with the “Shanghai City Master Plan (2017–2035)”, this study suggests potential zones for the recreational transformation of the Shanghai green belt, provides a theoretical and practical basis for improving the recreational utilization of an urban ecological protection green belt and contributes to the sustainable development of ecological protection green belts in high-density cities.

Reconsidering green belts, green wedges and greenways

Facing accelerated urbanization and landscape alteration, cities expand on the territory showing better or worse relationships between built environment and green spaces. Based on recent literature review, this article discusses the green wedges, green belts and greenway planning models in order to evaluate their capability in answering contemporary ecological and social issues. The article presents a conceptual overview of the selected planning models through a recent literature review, looking at the fundamental concepts of green infrastructure; then, it enlightens the connections between the spatial forms and the functions derived of these forms. These three models are connected infrastructures, varying between the ring, the star or linear forms. What differs the most is the capacity to encompass existing patches like forests or other valuable areas and the proximity and distribution of green spaces throughout the city. Whilst green belts, for their fringe condition, distance itself from the majority of inner-city dwellers, both green wedges and greenways can cross the urban fabric, and reach a greater number of neighborhoods, although the simple existence of these features does not guarantee their social functions. These findings have significant implications for the design of city expansions and can help to configure better neighborhoods in growing cities.

Deep Vision Based Surveillance System to Prevent Train-Elephant Collisions

Animal conservation is imperative, and a lot of technology has been used in different ways. The endangered species like tiger and elephant has raised the need for such efforts. Human-Elephant Collision (HEC) has been an active area of research but still, the optimum solution is not found. As trains are widely used transportation medium in Asian countries, the rail track is even laid down through forest areas and hence intervene the wildlife. Elephants due to their bulky size often become victims of trains. Such tragedy is common especially in green belts in southern zones of India. To rectify the problem, we have proposed a deep vision-based model to identify the elephant near-site using implanted video cameras. Four different models are proposed for the identification of elephants in image/video. One novel lightweight CNN based model is proposed. Three Transfer Learning (TL) models, i.e., ResNet50, MobileNet, Inception V3 have been experimented and tuned for elephant detection. These highly accurate and precise models can alarm the trains hence it can save a precious life.

Green belt’s effect on fine particle matter (PM2.5) in residential cluster: based on CFD simulation

In the area of residential green belt planning, most planners pay attention to the landscape function of green belts, while few researchers consider the impact of green belt on the concentration of fine particulate matter in the air. Based on site investigation, information about plants, buildings and weather in the selected area were collected, combined with air pollution measurement, four CFD models with different green belt composition were built and simulated. The results showed that at the residential cluster scale, green belts had two effects on fine particles: blocking and agglomeration. Under the two effects, the role of green belts in reducing fine particulate pollution was not always positive, improper green belts could even aggravate air pollution. This study discussed the impact of different greenbelt composition on PM2.5 concentration in residential clusters by CFD simulation, providing theoretical and methodological support for green belt planning and healthy city planning.

Nexus Between Urban Green Streets and the Sustainability: Case on Khulna City Corporation (KCC) Area, Bangladesh

Rapid Urbanization in Bangladesh has created a negative impact on the ecosystem and it’s resulting a change in the climate. In this research, Khulna City Corporation (KCC) is chosen to be the study area. The main objective of this study is to propose feasible models of green streets to reduce environmnetal pollution. Then it proposes green belts to alleviate the effect of harmful gases while maintaining ecological balance to achieve Sustainable Development Goals (SDGs) 11th goal. The study is completed in three phases. Firstly, Land Use Land Cover (LULC) detection and public opinion survey was conducted considering the existing scenario. Secondly, green street system was proposed in different intersection points, highways and neighborhoods of Khulna city on the basis of some successful cases and finally a conceptual framework for achieving SDG’s 11th goal is shown. This research shows that about 5% vegetation has decreased over the last 20 years. Also it shows the total amount of carbon-di-oxide (CO2) that can be consumed by big trees after 10 years is approximately 32,340 kg per year. The total amount of CO2 that can be consumed by shrubs is 34,810 kg per year. According to user satisfaction survey more than 90% people like the idea of green street and more than 60% people thinks that using the streets will be more convenient after its implementation. The successful adoption of green streets will help to achieve livable and healthy communities and also it will push the urban area towards sustainability by achieving SDG’s 11th goal.

Sebaran Mangrove di Desa Bumiharjo Kecamatan Keling Kabupaten Jepara

Kabupaten Jepara memiliki potensi wilayah pesisir dengan panjang garis pantai 81,6 km. Mangrove sebagai sabuk pantai hijau memiliki sebaran di setiap kecamatan pesisir. Salah satu lokasi sebaran mangrove di pesisir Jepara berada di desa Bumiharjo Kecamatan Keling. Identifikasi potensi luasan lahan serta sebaran mangrove adalah salah upaya mengetahui potensi sumberdaya pesisir. Metode penelitian yang digunakan adalah overlay peta RBI dan peta satelit landsat 8 guna mengetahui lokasi serta luasan sebaran mangrove di lokasi penelitian.Selanjutnya dilakukan investigasi ekologi mangrove dengan Survei Lapang guna mengetahui distribusi dan kelimpahan mangrove. Hasil penelitian menunjukan bahwa hutan mangrove dilokasi penelitian adalah seluas 4,75 Ha. Hasil identifikasi komposisi jenis mangrove ditemukan sebanyak 6 spesies mangrove yaitu: Avicennia marina, Rhizophora apiculata, Rhizophora stylosa, Rhizophora mucronata, Soneratia alba, serta Soneratia muconata. Kerapatan rata-rata vegetasi mangrove berkisar antara 4000 – 10.000 individu/ha. Tegakan mangrove memiliki tinggi batang 5-6 meter, diameter batang berkisara antara 4,3- 5,0 cm. Kerapatan mangrove didominasi oleh Rhizophora mucronata. dengan kerapatan paling dominan adalah semai (Sapling). Hal ini menunjukan bahwa mangrove yang ada di desa Bumiharjo Kecamatan Keling kabupaten Jepara adalah dominan mangrove hasil replant. Jepara Regency has a potential coastal area with a coastline length of 81.6 km. Mangroves as coastal green belts have distribution in each coastal district. One of the mangrove distribution locations on the coast of Jepara is in the village of Bumiharjo, Keling district. Identification of the potential land area and the distribution of mangroves is an effort to determine the potential of coastal resources. The research method used is an overlay RBI map and satellite map Landsat 8 to determine the location and extent of the distribution of mangroves in research locations. Subsequently carried out an investigation of mangrove ecology with a Field Survey (Ground Truth) to determine the distribution and abundance of mangroves. The results showed that the mangrove forest in the study area was 4.75 Ha. The results of the identification of the composition of mangrove species were found as many as 6 species of mangroves, namely: Avicennia marina, Rhizophora apiculata, Rhizophora stylosa, Rhizophora mucronata, Soneratia alba, and Soneratia muconata. the average density of mangrove vegetation ranges between 4000 - 10,000 individuals/ha. Mangrove stand has a stem height of 5-6 meters. the diameter of the stem is between 4.3 - 5.0 cm. Mangrove density is dominated by Rizophora mucronata. with the most dominant density is the seedling (Sapling). This shows that the mangroves on the coast of the Jepara district are replanted mangrove species. (rehabilitation).