2011年至2022年间巴西火灾点的贝叶斯空间时空建模
Jonatha Sousa Pimentel1, Rodrigo S Bulhões2,3, Paulo Canas Rodrigues4,5
1Department of Statistics, Federal University of Pernambuco, Recife, Pernambuco, Brazil.
Scientific reports
|September 16, 2024
概括
由于气候变化和人类活动,野火的频率正在增加. 这项研究发现,湿度和空气温度显著影响巴西各地的野火事件,突出了关键的环境驱动因素.
科学领域:
- 环境科学 环境科学
- 气候科学 气候科学
- 遥感 遥感 遥感 遥感
背景情况:
- 野火是一个日益严重的全球性问题,由气候变化,当地政策和人类行为加剧.
- 识别野火起源对于理解和减轻它们对生活质量的影响至关重要.
- 火点是卫星探测到的温度升高的区域,是森林火灾监测的关键指标.
研究的目的:
- 分析2011-2022年巴西历史火点数据.
- 用气象和土地利用变量建模火点的时空分布.
- 为了确定影响巴西生物群中野火发生的主要驱动因素.
主要方法:
- 使用时空通用线性混合模型用于面积单位数据.
- 采用贝叶斯推理框架进行参数估计.
- 纳入气象数据 (降雨量,空气温度,湿度,风速) 和土地利用数据作为共变量.
主要成果:
- 在巴西领土上分析了超过220万个火灾点.
- 湿度和空气温度被确定为影响火点数量的最重要的气象变量.
- 该模型提供了关于巴西野火的空间和时间动态的见解.
结论:
- 气象因素,特别是湿度和空气温度,在巴西野火发生方面发挥着关键作用.
- 了解这些驱动因素对于制定有效的野火管理和预防策略至关重要.
- 该研究强调了将卫星探测到的火点数据与生态研究的环境变量整合起来的重要性.
相关概念视频
Time-Series Graph
4.3K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.3K
Flame Photometry: Overview
506
Flame photometry, also known as flame emission spectrometry, is a technique used for the qualitative and quantitative analysis of elements present in a sample using a flame as the source of excitation energy. The concept of flame photometry was realized in the early 1860s by Kirchhoff and Bunsen, who discovered that specific elements emit characteristic radiation when excited in flames. The first instrument developed for this purpose was used to measure sodium (Na) in plant ash using a Bunsen...
506
Design Example: Analyzing Capacity Contours for Flood Risk Assessment
41
Flood risk assessment involves careful planning and analysis to ensure the safety of communities near water retention structures. Capacity contours are a vital tool in this process, as they illustrate the potential spread of water at specific levels in a given area. In the context of building a bund across a small valley, these contours play a critical role in evaluating the safety of nearby residential areas.In this example, the bund is intended to store stormwater in the valley. The engineers...
41
Precipitation Processes
434
The experimental conditions in a gravimetric analysis should be optimized to maximize the particle size and purity of the obtained precipitate. Ideally, the concentration of the precipitating reagent should be low with effective stirring to maintain low relative supersaturation for the growth of large crystals. In homogeneous precipitation, the precipitant is slowly generated by a chemical reaction in the solution to avoid local reagent excesses. For example, urea decomposes gradually to...
434
Prediction Intervals
2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.2K
Probability Histograms
11.1K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
11.1K


