Abstract
The article describes the assessment of the areas and spatial distribution of adjoining green spaces as one of the most vulnerable and low studied kind of green spaces in cities. Usually gardening near the residential houses is not legally regulated is being destroyed during the implementation of urban renovation projects. The characteristics of adjoining green spaces were assessed for the city of Nur-Sultan, where, on the one hand, natural properties make green spaces vulnerable, and on the other hand, the acquisition of capital functions increases the value for the urban environment. A large-scale assessment, carried out using unmanned aerial vehicles, has demonstrated its high efficiency in assessing the vertical and horizontal structure of adjacent green spaces and other elements of the city. As a result of aerial imagery sessions for representative key points, a series of orthophotomaps with the horizontal resolution of 3–4 cm and digital terrain models with a horizontal resolution of 3 cm and a vertical resolution of about 4 cm were obtained. These products provided possibility to identify 12 historically established morphotypes of urban buildings, characterized by different levels and types of adjacent landscaping. Using a three-dimensional model of green cover, the average size of the biomass and the density of biomass per 1 m2 of the area in the selected morphotypes of the building were calculated. Territorial differences of adjoining green spaces in the different morphotypes depend on the period of construction, distance from the river, types of the building and urban planning standards typical for the period of the morphotype forming. Losses of the adjoining green spaces during the implementation of the renovation program according to the modern General Plan, excluding restoration, for the city of Nur-Sultan, will be mor than 11.5 % (+/-3.5 %) of the city’s tree cover.
Highlights
The article describes the assessment of the areas
The characteristics of adjoining green spaces were assessed for the city of Nur-Sultan
the acquisition of capital functions increases the value for the urban environment
Summary
Разметка территории в приложении DroneDeploy (для того, чтобы определить примерное время полета БПЛА и количество необходимых аккумуляторов). Съемка проводилась в осеннее время года, так как желтая листва намного легче дешифрируется, чем зеленая, при автоматическом дешифрировании. Положение камеры в момент съемки определяется элементами внутреннего и внешнего ориентирования. Элементы внутреннего ориентирования включают фокусное расстояние камеры, координаты главной точки снимка и коэффициенты дисторсии объектива. В результате процесса выравнивания определяются элементы внешнего ориентирования камеры и уточняются элементы внутреннего ориентирования. Программа вычисляет карты глубины для каждой камеры, основываясь на их рассчитанных положениях. А затем на основании карт глубины строят плотное облако точек. Полученное облако используется для построения карты высот 3. Облако точек (на примере одного из репрезентативных ключевых участков) Fig. 3.
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