Determination of self-foresting areas by remote sensing data

• Дата: 2024
• Автори: Horelyk, Stanislav, Sych, Roman, Saul-Hoze, Denys
• Формат: Стаття
• Мова: Ukrainian
• Опубліковано: Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine, Kyiv, Ukraine 2024
• Теми: remote sensing; GIS; self-foresting; NDVI; ArcGIS; mapping model
• Онлайн доступ: https://ujrs.org.ua/ujrs/article/view/273
• Назва журналу: Ukrainian Journal of Remote Sensing of the Earth

The military aggression of the Russian Federation causes enormous damage to the ecosystems of Ukraine, destroying natural resources and biodiversity. In particular, as of January 2024, the loss of the forest fund is estimated at $4.5 billion. During the hostilities, not only inventoried forest areas are destroyed, but also self-forested areas that are not taken into account in the damage assessment. Thus, an urgent task is to identify self-forested areas with the definition of their geometric characteristics and calculation of the probable number of trees. The study area was selected as the Donetsk and Luhansk regions controlled by Ukraine as of 22.02.2024. The task was realized through the use of contact and remote methods. The study used the following data obtained by contact methods: a vector layer of forest plots registered with the State Agency of Forest Resources, the Public Cadastral Map of Ukraine, and the open register of logging tickets. This data allows us to immediately identify inventoried forest resources. Remote sensing data, namely multi-temporal satellite images in the visible range of high and ultra-high spatial resolution, and a synthesized map of NDVI indices, allow us to quickly identify areas of forest cover. The integrated use of contact and remote data makes it possible to identify areas of self-foresting with minimal time and material costs. The boundaries of these areas with the calculation of their area and number of trees were determined using licensed geographic information system (GIS) software ArcGIS. The use of GIS technologies made it possible to simultaneously process geodata obtained by contact and remote survey methods and to analyze forest plots to identify unaccounted for resources. Thanks to the developed methodology for determining self-forested areas using remote sensing data, more than 10 thousand plots with a total area of 505.37 km2 were identified. The estimated number of trees in these areas is 3287.2 thousand. The data obtained can be used in the future to more accurately calculate the damage from military aggression. Funding: This research received no external funding. Data Availability Statement: Not applicable. Acknowledgments: The authors would like to express their sincere gratitude to the Earth Observing System Data Analytics company (eosda.com) for support. We are also grateful to reviewers and editors for their valuable comments, recommendations, and attention to the work.