Abstract：
The Moderate Resolution Imaging Spectroradiometer (MODIS) of the National Aeronautics and Space Administration (NASA) offers numerous land products of the Earth\'s datasets. On the other hand, researchers find it difficult to retrieve this data for specific places. The methods for extracting and analyzing land surface temperature (LST), land use and land cover (LULC), and elevation are presented in this study. The R commands provided make the time-consuming process of extracting data for specific places much more accessible. As a result, a statistical study of LST over Bali is shown as an example. Over the 15 regions of Bali, a quadratic polynomial identified five possible warming patterns, while a logistic regression model assessed the probability of warming. The findings suggest that 25.2% of Bali has warmed during the last two decades, with temperatures being highest in urban and built-up areas and deciduous forests and inversely associated with elevation. Global warming has sparked a lot of academic interest and has become a serious climate problem. The techniques proposed in this work simplify the extraction of LST, LULC, and elevation data from MODIS satellites. These approaches can also be used on other datasets with identical topologies, such as the normalized difference vegetation index (NDVI), aerosol optical depth (AOD), and night light data.
摘要：
美国国家航空航天局（NASA）的中分辨率成像光谱仪（MODIS）提供了大量地球数据集的陆地产品。另一方面,研究人员发现很难在特定地点检索这些数据。地表温度（LST）的提取和分析方法，土地利用和土地覆盖（LULC），和高程在这项研究中提出。所提供的R命令使提取特定位置的数据的耗时过程更易于访问。因此,以巴厘岛LST的统计研究为例。在巴厘岛的15个地区，二次多项式确定了五种可能的变暖模式，而逻辑回归模型评估了变暖的可能性。调查结果表明，在过去的二十年中，巴厘岛有25.2％的人口变暖，城市和建成区以及落叶林的温度最高，与海拔成反比。全球变暖引发了许多学术兴趣，并已成为一个严重的气候问题。这项工作中提出的技术简化了LST的提取，LULC,和来自MODIS卫星的高程数据。这些方法也可以用于具有相同拓扑的其他数据集，如归一化植被指数(NDVI)，气溶胶光学深度（AOD），和夜光数据。
