Influence of vegetation index to the rainfall intensity in Pasuruan Area, East Java Province, Indonesia

Q4 Immunology and Microbiology
Agus Suharyanto, Alwafi Pujiraharjo, M. T. Iqbal, Article Info
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Abstract

An increase in population increases the rate of urbanization. This results in changes in land cover from vegetation to artificial material. As a result, much of the land surface reflects the sun's energy. Consequently, this increases the surface temperature of the land. An increase in land surface temperature (LST) will increase the intensity of rainfall. Therefore, the present study aimed to investigate the relationship between the increase in LST and rainfall intensity. Changes in land cover can be detected by normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI) parameters. Landsat satellite imagery was used to detect NDVI, NDBI, and LST. Image processing was done for imageries scanned in 1995, 2015, 2017, and 2021. Two areas in the East Java Province of Indonesia, namely Malang City and Pasuruan Area, were selected. The daily rainfall intensity data were collected from related rainfall stations in the same year. The Mononobe method was applied to analyze hourly and minute rainfall intensity. IDF curves were drawn from the analyzed results. The relationship between both parameters was analyzed by comparing the LST and hourly rainfall intensity from the IDF curve. The studied results showed that the maximum temperature increase from 1995 to 2021 for the Malang City and Pasuruan Area was 2.60 C and 7.60 C, respectively. For rain, the maximum rainfall intensity increased by 58 mm for Malang City and 18 mm for the Pasuruan Area. LST and rainfall intensity change trends of the two areas had a positive coefficient of regression. The findings can be used to predict the rainfall intensity and floods based on the LST data.  
印度尼西亚东爪哇省 Pasuruan 地区植被指数对降雨强度的影响
人口的增加提高了城市化的速度。这导致土地覆盖物从植被变为人工材料。因此,大部分地表会反射太阳能量。因此,这增加了陆地的表面温度。地表温度的升高会增加降雨强度。因此,本研究旨在调查地表温度上升与降雨强度之间的关系。土地覆被的变化可通过归一化差异植被指数(NDVI)和归一化差异堆积指数(NDBI)参数来检测。陆地卫星图像用于检测归一化差异植被指数、归一化差异建成指数和 LST。对 1995 年、2015 年、2017 年和 2021 年扫描的图像进行了处理。研究选取了印度尼西亚东爪哇省的两个地区,即玛琅市和帕苏鲁安地区。当年的日降雨强度数据来自相关雨量站。采用 Mononobe 方法分析每小时和每分钟的降雨强度。根据分析结果绘制 IDF 曲线。通过比较 LST 和 IDF 曲线得出的每小时降雨强度,分析了这两个参数之间的关系。研究结果表明,从 1995 年到 2021 年,马朗城和 Pasuruan 地区的最高气温分别上升了 2.60 摄氏度和 7.60 摄氏度。在降雨方面,马朗市的最大降雨强度增加了 58 毫米,而 Pasuruan 地区的最大降雨强度增加了 18 毫米。两个地区的 LST 和降雨强度变化趋势的回归系数为正。研究结果可用于根据 LST 数据预测降雨强度和洪水。
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来源期刊
Journal of Applied and Natural Science
Journal of Applied and Natural Science Immunology and Microbiology-Immunology and Microbiology (all)
CiteScore
0.80
自引率
0.00%
发文量
168
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