Establishment and Application of Spatial Distribution Model of Roof Greening Based on GIS Technology

The stage from the beginning of the 21st century to now is the stage of the scale development of roof greening(RG) in China. With the continuous progress of urban construction, on the one hand, the ecological environment is deteriorating, on the other hand, the available green space in the urban center area becomes more and more scarce. The development of this contradiction promotes the rapid development of RG. RG plays an important role in enriching urban landscape, increasing urban green quantity, reducing urban heat island effect, conserving rainwater and reducing temperature, and creating a new green space for the city, including leisure, entertainment and ecology, and improving urban ecological landscape. This paper mainly studies the establishment and application of spatial distribution(SD) model of RG Based on GIS technology. Through understanding the SD design of RG, the paper investigates and analyzes the status quo of green space of roof, macro layout and the integration of multiple functional spaces. This paper studies and establishes a multiobjective optimization model of SD of RG, and analyzes the purification effect of RG on rainwater pollutants and the overall performance of ecosystem service equity. The results show that 26.31% of the people think that the degree of RG is insufficient, and 5.14% think that RG is scarce. In the cognition of the status of RG space, 12.41% of people don't care about RG, 8.69% think it is face engineering, and even 9.31% think it is waste of resources, which indicates that the promotion of RG needs to be improved

Rainwater Harvesting for Agricultural Irrigation: An Analysis of Global Research

Within a context of scarce water resources for agriculture, rainwater harvesting constitutes a promising alternative that has been studied by different disciplines in recent years. This article analyses the dynamics of global research on rainwater harvesting for agricultural irrigation over the last two decades. To do this, qualitative systematic analysis and quantitative bibliometric analysis have been carried out. The results reveal that this line of research is becoming increasingly important within research on irrigation. Environmental sciences and agricultural and biological sciences are the most relevant subject areas. Agricultural Water Management, Physics and Chemistry of the Earth, and Irrigation and Drainage are the journals that have published the most articles on the subject. India, China, the United States (USA), South Africa, and the Netherlands are the countries that lead this line of research. Although significant progress has been made in this subject area, it is necessary to increase the number of studies on the capacity of rainwater harvesting systems to cover irrigation needs in different farming contexts, the factors that determine their adoption by farmers, the economic and financial feasibility of their implementation, and their contribution to mitigating global climate change

Ambon City Portrait of Flood Vulnerabilities: Spatial Analysis and Identification of Causing Factors

Ambon City is one of the cities with a relatively high flood disaster intensity. This study aims to analyze the factors that cause flooding and determine the vulnerability of flooding. The method is based on a geographic information system (GIS) by integrating secondary and primary data. Parameters analyzed include elevation, rainfall, slope, soil type, and land use. Study results show that the factors causing flooding in Ambon City include relatively high-intensity rains, land use patterns dominated by mixed gardens, slopes in lowland areas, low elevations, and soil types easily inundated with water. The flood hazard zone is divided into three classes, namely high, medium, and low hazard zones. Areas with high vulnerability are 2,251.3 ha (6.99%) of the total area of the study area. For this reason, the community and the Ambon City government need to pay attention to this area in dealing with flood disasters

An integrated framework to assess compound flood risks for interdependent critical infrastructure in a coastal environment

Compound flooding refers to flood events caused by multiple factors, including marine processes (e.g. storm tides and waves), hydrometeorological signals (e.g. rainfall and river flows) among others. Saint Lucia is a tropical island in eastern Caribbean Sea, which is frequently affected by weather-related extreme events such as tropical storms and the associated risks are exacerbated due to its mountainous topography and high concentrations of infrastructure and human communities close to the coast. At the southern coast of Saint Lucia, significant infrastructures such as Hewanorra International Airport and Vieux Fort Seaport, and human settlements such as towns of Vieux Fort and La Tourney are located at low-lying areas and are at risk of compound flooding. A hydrologic model (i.e. HYdrological MODel) and a two-dimensional hydrodynamic model (i.e. LISFLOOD-FP) are set up and calibrated to investigate the combined effects of storm tides, wave run-up, rainfall, and river flows on flood risks in Saint Lucia. Results indicate the necessity to consider multiple contributing factors as well as to characterize the effects of uncertain boundary conditions. In flood-prone areas, there are infrastructures supporting major services in the study area, and by extension, the economy of the Island. A network-based model, which considers direct and indirect connections between infrastructures, is set up to explore risks of assets in conditions of non-flooding and flooding. Modelling results reveal the fundamental importance of various components including electricity distribution, flood control, information and communication services, transportation, housing and human settlements, tourism, and particularly the normal operations of Hewanorra International Airport. Prioritization of risks is critical for developing effective mitigation methods for infrastructure networks

Urban and river flooding: Comparison of flood risk management approaches in the UK and China and an assessment of future knowledge needs

Increased urbanisation, economic growth, and long-term climate variability have made both the UK and China more susceptible to urban and river flooding, putting people and property at increased risk. This paper presents a review of the current flooding challenges that are affecting the UK and China and the actions that each country is undertaking to tackle these problems. Particular emphases in this paper are laid on (1) learning from previous flooding events in the UK and China, and (2) which management methodologies are commonly used to reduce flood risk. The paper concludes with a strategic research plan suggested by the authors, together with proposed ways to overcome identified knowledge gaps in flood management. Recommendations briefly comprise the engagement of all stakeholders to ensure a proactive approach to land use planning, early warning systems, and water-sensitive urban design or redesign through more effective policy, multi-level flood models, and data driven models of water quantity and quality

Laserkeilausaineiston ja katunäkymäkuvien hyödyntäminen tieympäristön seurannassa

Utilization of laser scanning has increased during the past few years in many fields of applications, for example, in road environment monitoring. Mild winters, increasing rainfalls and frost are deteriorating the surface and structure of the road causing road damages. The road environment and its condition can be examined for example with laser scanning and street view images. Utilization of laser scanning data and street view images in road environment monitoring was studied in this thesis. The main focus was on the road damages and drainage. Also individual trees were detected nearby road scenes. TerraModeler and TerraScan software were used for investigations. Five different lidar datasets were used to detect road damages and drainage. Both mobile and helicopter-based lidar data were available from Jakomäki area. In Rauma case, there were two datasets collected from the helicopter but the point densities were different. In addition, to helicopter-based lidar data, there were also street view images available from BlomSTREET service in Hyvinkää case. The results between the datasets were compared. Aim was to investigate if same damages can be found from the several datasets that have different point densities. Lidar data for individual tree detection was collected by helicopter from Korppoo area. Tree locations were also measured with a tachymeter to get reference data for automatic detection. Heights of the trees were manually determined from the point cloud. Manually measured heights and locations were compared with automatically detected ones. Detection of rut depths, slopes and drainage is possible from the high point density datasets. From lower point density datasets it is not possible to detect for example rut depths. Point cloud is possible to color by slopes, which may give some information about rut locations even from lower point density datasets. Obtaining slopes and drainage accurately is also possible from lower point density data. With TerraModeler water gathering points can be obtained. Panorama pictures from BlomSTREET can be utilized for ensuring if there is a rainwater outlet or if water will gather as a puddle. Tree locations were detected in a meter accuracy with automatic method. Successful detection of tree heights and locations is dependent on many things. Successful classification of the data and creation of tree models are the most important parameters.Laserkeilaus on yleistynyt ja sitä hyödynnetään useissa eri sovelluksissa kuten esimerkiksi tiesovelluksissa. Leudot ja sateiset talvet sekä routa kuluttavat tien pintaa ja rakennetta aiheuttaen tievaurioita, jotka voivat olla vaaraksi liikenteelle. Tienkuntoa ja sen ympäristöä voidaan tarkastella esimerkiksi laserkeilausaineistojen sekä katunäkymäkuvien avulla. Työssä tutkittiin kuinka laserkeilausaineistoa ja katunäkymäkuvia voidaan hyödyntää tieympäristön seurannassa. Tutkimuksessa keskityttiin tarkastelemaan tievaurioita ja kuivatusta sekä tiealueiden läheisyydessä sijaitsevien puiden tunnistusta. Tutkimuksessa käytettiin TerraModeler ja TerraScan ohjelmistoja. Tievaurioita ja kuivatusta tutkittiin viidestä eri aineistosta kolmelta eri alueelta. Jakomäen alueelta tien ominaisuuksia tutkittiin sekä mobiili- että helikopterilaserkeilausaineistosta ja Rauman alueelta vaurioita kartoitettiin kahdesta eri helikopterilla kerätystä pistetiheyden aineistosta. Hyvinkäältä helikopterilla kerätyn laserkeilausaineiston lisäksi oli saatavilla katunäkymäkuvia BlomSTREET palvelusta. Aineistoista saatuja tuloksia vertailtiin keskenään ja tutkittiin, onko niistä mahdollista havaita samankaltaisia tuloksia. Yksittäisen puun tunnistukseen käytettiin helikopterilla kerättyä laserkeilausaineistoa Korppoon alueelta ja referenssinä aineistolle toimi maastossa mitatut puiden sijainnit. Automaattisesti määritettyjen puiden sijaintia verrattiin maastossa mitattuihin sijainteihin. Myös puiden korkeus määritettiin pistepilvestä manuaalisesti ja tätä verrattiin automaattiseen korkeuden määritykseen. Korkean pistetiheyden laserkeilausaineistoilla on mahdollista tutkia tien urautumista, tien kaltevuuksia ja kuivatusta. Matalamman pistetiheyden aineistoista ei pystytä määrittämään esimerkiksi urasyvyyksiä. Pistepilvi on mahdollista värjätä kaltevuuksien mukaan, minkä avulla urautumista voidaan havaita jossain määrin myös matalampien pistetiheyksien aineistoista. Tien kaltevuuksia ja kuivatusta pystytään havaitsemaan tarkasti jopa alhaisista pistetiheyden aineistoista. TerraModelerin avulla voidaan määrittää alueet, johon sadevesi kasautuu. BlomSTREET 360 panoraamakuvien avulla pystytään tarkastamaan onko kohdassa sadevesikaivo vai kerääntyykö vesi lammikoiksi. Yksittäisten puiden sijainnin määrittäminen onnistui noin metrin tarkkuudella, mutta sijainnin ja korkeuden määrittämisen onnistuminen on riippuvainen monesta tekijästä. Pistepilven luokittelun onnistumisen lisäksi yksi tärkeä tekijä on puiden muodoista tehdyt mallit, joiden avulla TerraScan ohjelmisto etsii yksittäisiä puita

MAPPING OF FLOOD SUSCEPTIBILITY IN CAMPINA GRANDE COUNTY – PB: A SPATIAL MULTICRITERIA APPROACH

The social and economic impacts caused by floods in urban areas are diverse and increase as the land becomes gradually impervious. Due to the increasing urbanization of cities, it is necessary to implement a better planning process and optimize the urban spaces management and occupation. Thus, the government needs to gather reliable and useful data for the decision-making process. Therefore, the GIS plays an important role among urban planning instruments. Given the current situation in Campina Grande County, Paraiba State, Brazil - an area continually facing disturbances caused by occasional and concentrated rainfalls - the current study aims to map the areas seen as the most susceptible to floods, by using a MCDA GIS-based model (Multi-Criteria Decision Analysis). There are five quantitative criteria considered in the analysis: slope, altitude, roads with drainage infrastructure, distance from water bodies and land use. It is a pixel by pixel analysis based on predetermined assumptions. Fuzzy functions were developed and overlay operations were performed. The results were consistent with historical records and with previous studies about the county, thus adding reliability to the model, which can be considered a potential management instrument for the case study area, as well as for cities facing similar issues