School of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD 4000, Australia.
Sensors (Basel). 2019 Jan 17;19(2):361. doi: 10.3390/s19020361.
This paper presents a method for employing satellite data to evaluate spatial and temporal patterns in environmental indices of interest. In the first step, linear regression coefficients are extracted for each area in the image. These coefficients are then employed as a response variable in a boosted regression tree with geographic coordinates as explanatory variables. Here, a two-step approach is described in the context of a substantive case study comprising 30 years of satellite derived fractional green vegetation cover for a large region in Queensland, Australia. In addition to analysis of the entire image and timeframe, separate analyses are undertaken over decades and over sub-regions of the study region. The results demonstrate both the utility of the approach and insights into spatio-temporal trends in green vegetation for this site. These findings support the feasibility of using the proposed two-step approach and geographic coordinates in the analysis of satellite derived indices over space and time.
本文提出了一种利用卫星数据评估环境指数空间和时间模式的方法。在第一步中,从图像中的每个区域提取线性回归系数。然后,这些系数被用作增强回归树的响应变量,地理坐标作为解释变量。在一个实质性的案例研究中,描述了一种两步法,该案例研究包括 30 年来澳大利亚昆士兰州一个大区域的卫星衍生的分数绿色植被覆盖。除了对整个图像和时间框架进行分析外,还分别对几十年和研究区域的子区域进行了分析。结果表明了该方法的实用性,并深入了解了该地点绿色植被的时空趋势。这些发现支持了在空间和时间上使用提议的两步法和地理坐标分析卫星衍生指数的可行性。