Classification of Pest Damaged Trees with Multi-Temporal Sentinel-2 Data

Authors

DOI:

https://doi.org/10.5564/pib.v38i1.2540

Keywords:

Random Forest, remote sensing, forest pest insects, forest research

Abstract

The Forest covers 8 percent of the land in Mongolia. In the last 20 years, 1.2 million ha area has been lost due to forest fires, pests damages, and illegal cutting. There are many ways to determine the state of forests in Mongolia, but there is an urgent need to introduce new technical and technological achievements that have appeared in recent years.
This study focuses on assessing the potential of Sentinel-2 satellite images and the Random Forest (RF) classifier for mapping forest cover in part of the Bayan Davaа forest in Mongolia.

Хөнөөлт шавжийн нөлөөнд өртсөн ойн талбайг сансрын “Сентинел-2” хиймэл дагуулын өгөгдөлөөс илрүүлэх боломж

Монгол орны нийт нутаг дэвсгэрийн найм орчим хувийг ой бүхий талбай эзлэх бөгөөд сүүлийн 20 гаруй жилийн
хугацаанд 1.2 сая га талбай нь ойн түймэр, хортон шавжийн нөлөө болон хууль бусаар мод бэлтгэх үйл ажиллагааны
уршигаар хорогдсон. Монгол орны ойн төлөв байдлыг тодорхойлох олон арга байх боловч сүүлийн жилүүдэд гарч
буй шинэ техник технологийн ололт амжилтыг нэвтрүүлэх зайлшгүй шаардлага тулгарсаар байна. Энэхүү судалгааны
хүрээнд Төв аймгийн Эрдэнэ сумын нутаг дэвсгэрт орших Баян давааны арын баруун хойд налууд орших ойн төлөв
байдлыг үнэлэхдээ Сентинел-2 (Sentinel-2) хиймэл дагуулаас илгээгдсэн зураглалд боловсруулалт хийж “бүлэглэн
ялгах” (Random Forest) арга зүйг туршив.

Түлхүүр үгс: Random Forest, зайнаас тандан судлах, хөнөөлт шавж, ойн судалгаа

Abstract
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Published

2022-12-25

How to Cite

[1]
D. Bayarmaa, G. Gantulga, C. Gantigmaa, and D. Ganbat, “Classification of Pest Damaged Trees with Multi-Temporal Sentinel-2 Data”, Proc. Inst. Biol., vol. 38, no. 1, pp. 113–125, Dec. 2022.

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