绿色开放空间分布模式,萨马林达市地区的温度

Muhammad Ari Saputra, Achmad Ghozali, Berly Gizela Putri Pramesti, Muhammad Qoirul Purwanto
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引用次数: 0

摘要

萨马林达城市的物理发展与建筑空间的存在和绿色开放空间的分布不协调,影响了城市小气候的变化。这些变化发生在小气候要素中,如温度、湿度、阳光和风的强度。如果小气候要素发生变化,恐怕会朝着不符合人体舒适状况的方向发生变化。那么,萨马林达市区域温度与绿地开放空间分布的关系如何就成为了本研究的一个问题。为实现研究目标,开展的目标是分析萨马林达城市区域的温度分布,分析萨马林达城市绿色开放空间的分布,分析萨马林达城市绿色开放空间的特征,分析区域温度与萨马林达城市绿色开放空间分布的关系。为了实现这一目标,本研究使用了Landsat 8、Sentinel 2图像的解译分析和回归分析形式的统计分析。在哨兵图像分析中,获得的数据是温度的分布和绿色开放空间的分布。其中最低温度为29.8oC,最高温度为38.8oC,得到绿色开放空间的分布。人工神经网络分析结果表明,绿色开放空间分布数据有4类,即聚类、散类、均匀和非绿色开放空间。在两次分析得到数据后,利用SPSS编程进行定量分析,得到Y变量与X变量之间的关系。在本分析中,计算出的F值为1.930,显著性水平为0.009,回归模型可以用来预测该数据中的自变量。RTH与温度有显著的密切关系。研究区绿色开放空间与区域温度分布有显著的关系。此外,研究结果还表明,绿色开放空间的比例、绿色开放空间的分布与密集植被的比例呈反比关系,即绿色开放空间增加则温度降低,反之亦然。
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POLA DISTRIBUSI RUANG TERBUKA HIJAU TERHADAP TEMPERATUR WILAYAH KOTA SAMARINDA
The physical development of the city of Samarinda that is not in harmony between the existence of Built Space and the distribution of Green Open Space has an impact on changes in the urban microclimate. These changes occur in microclimate elements such as temperature, humidity, intensity of sunlight and wind. If the microclimate element changes, it is feared that a change will occur in a direction that is not in accordance with the comfort of the human body condition. Then it becomes a question in this study, namely how is the relationship between regional temperature and the distribution of green open space in Samarinda City. The targets carried out to achieve the research objectives are to analyze the temperature distribution of the Samarinda City area, analyze the distribution of Samarinda City Green open space, analyze the characteristics of Samarinda City Green open space, and analyze the relationship between regional temperature and the distribution of Samarinda City Green open space. To answer this goal, this research uses interpretation analysis of Landsat 8, Sentinel 2 imagery and statistical analysis in the form of regression analysis. In the sentinel image analysis, the data obtained are the distribution of temperature and the distribution of green open space. Where the minimum temperature is 29.8oC, maximum temperature is 38.8oC, and the distribution of green open space is obtained. The results of the ANN analysis show that there are 4 categories of green open space distribution data, namely clustered, spread out, uniform, and non-green open space. After the data obtained from the two analyzes, a quantitative analysis was carried out using SPSS programming to obtain the relationship between the Y variable and the X variable. In this analysis, the calculated F value was 1.930 with a significance level of 0.009 where the regression model can be used to predict the independent variables in this data. RTH with temperature showed a significant closeness. In the research area, it is stated that green open space has a significant relationship to the regional temperature distribution. In addition, the research findings also show that the ratio of green open space, the distribution of green open space, and the percentage of dense vegetation have an inverse relationship, which means that if green open space increases then the temperature decreases and vice versa.
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