Research of the state of forests in the precarpathian region by satellite images using the method of supervised classification

YU. Petryk, Kh. Burshtynska, B. Polishchuk
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Abstract

The purpose of the research is to monitor the forest objects of the Rava-Ruska forestry and determine changes in their areas from 2002 to 2022. The methodology of monitoring the state of the forests of the Rava-Ruska forestry is based on the using of multi-temporal medium-resolution satellite images with their subsequent processing using geographic information systems. For processing, we use images from Landsat 7 (July 2002) and Sentinel-2 (August 2022). We use csupervised classification using the maximum likelihood method. To post-process the classification results, we use Majority Filter. Based on the results, we calculate the area of classes for the relevant years. We perform a comparative analysis of these areas to determine changes in forest objects. Results. The research was conducted on a part of the territory of the Rava-Ruska forestry. Training samples were created for the following objects: deciduous and coniferous forest, fresh deforestation and overgrown deforedtation, open ground and roads, water and agricultural land. Histograms and scatter plots are used to evaluate the training samples. The suoervised classification was carried out using the maximum likelihood method on a part of the forestry territory with further post-processing. As a result of using GIS tools, a comparison of forest changes over two decades was made. The monitoring of the forests of the Rava-Ruska forestry allowed us to identify changes in forest objects, in particular deforestation, which in 2022 amounted to 679.2 hectares. Scientific novelty and practical significance. A methodology for monitoring forests using remote sensing materials has been developed. The possibilities of detecting changes in forest objects using the method of supervised classification are investigated.
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使用监督分类法通过卫星图像研究前喀尔巴阡地区的森林状况
研究的目的是监测 Rava-Ruska 林场的森林对象,并确定其面积在 2002 年至 2022 年期间的变化情况。监测 Rava-Ruska 林场森林状况的方法是使用多时中分辨率卫星图像,然后利用地理信息系统对其进行处理。在处理过程中,我们使用了 Landsat 7(2002 年 7 月)和 Sentinel-2(2022 年 8 月)的图像。我们使用最大似然法进行监督分类。为了对分类结果进行后处理,我们使用了多数过滤器。根据分类结果,我们计算出相关年份的等级面积。我们对这些面积进行比较分析,以确定森林对象的变化。研究结果研究是在拉瓦-鲁斯卡(Rava-Ruska)林场的部分领土上进行的。为以下对象创建了训练样本:落叶林和针叶林、新砍伐森林和过度砍伐森林、空地和道路、水域和农田。使用直方图和散点图对训练样本进行评估。使用最大似然法对部分林业区域进行了监督分类,并进行了进一步的后处理。通过使用地理信息系统工具,对二十年来的森林变化进行了比较。通过对拉瓦-鲁斯卡(Rava-Ruska)林场森林的监测,我们发现了森林对象的变化,特别是毁林情况,2022 年毁林面积达 679.2 公顷。科学新颖性和实用意义。利用遥感材料监测森林的方法已经开发出来。研究了利用监督分类方法检测森林对象变化的可能性。
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