School of Information, Computer and Communication Technology, Sirindhorn International Institute of Technology, Thammasat University, Khlong Nueng, Thailand.
School of Knowledge Science, Japan Advanced Institute of Science and Technology, Nomi, Japan.
Environ Monit Assess. 2022 Jul 6;194(8):566. doi: 10.1007/s10661-022-10252-z.
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.
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，研究人员发现很难为特定地点检索这些数据。本研究提出了提取和分析地表温度（LST）、土地利用和土地覆盖（LULC）以及海拔的方法。提供的 R 命令使提取特定地点数据的耗时过程变得更加容易。因此，以巴厘岛的 LST 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概率。研究结果表明，在过去的二十年中，巴厘岛有 25.2%的地区变暖，城市和建成区以及落叶林的温度最高，与海拔呈反比。全球变暖引发了很多学术兴趣，已成为一个严重的气候问题。本工作中提出的技术简化了从 MODIS 卫星提取 LST、LULC 和海拔数据的过程。这些方法也可以用于其他具有相同拓扑结构的数据集，如归一化差异植被指数（NDVI）、气溶胶光学深度（AOD）和夜光数据。
