利用 Sentinel-2 A 卫星图像生成的不同植被指数检测 Pinus brutia Ten.利用哨兵-2 A 卫星图像生成的不同植被指数

IF 2.2 4区 地球科学 Q3 ENVIRONMENTAL SCIENCES
Tunahan Çınar, R. Ceyda Beram, Abdurrahim Aydın, Sultan Akyol, Nurzhan Tashigul, H. Tuğba Lehtijärvi, Steve Woodward
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引用次数: 0

摘要

Heterobasidion 属包括一些对北半球针叶树最具破坏性的病原体。Heterobasidion 根腐病会导致大多数松属植物(包括土耳其红松)的根部功能丧失,树冠出现明显症状。受感染的松树最终会死亡。被风吹倒的树木根部腐烂或树丛中有空隙,通常表明存在异尖孢菌根腐病。最近,人们经常利用卫星图像来检测受损区域,以便对森林中的害虫或疾病实施早期管理程序,减少受影响区域内和其他地方的蔓延。在本文所述的工作中,使用不同的植被指数对哨兵-2 A 卫星图像进行了测试,以检测土尔其西南部一个地区 P. brutia 再生中的异型巴西杉根腐病。在谷歌地球引擎(GEE)平台上,通过哨兵-2 A 卫星图像计算归一化红边差异指数(NDRE)、归一化植被差异指数(NDVI)和植物衰老反射率指数(PSRI),以检测病害。计算出的指数作为合成波段被添加到 GEE 平台上的哨兵-2 A 卫星图像中。使用随机森林(RF)对添加了合成波段的图像进行分类,然后使用卡帕系数(Kappa Coefficient)和总体准确度(Overall Accuracy)进行评估。根据统计分析,NDRE 是检测疾病最有用的指数,总体准确率为 89%,Kappa 系数为 0.84,其次分别是 NDVI 和 PSRI。在对总体准确度和 Kappa 系数进行评估后,根据这些指数确定了该地区的发病率(发病公顷数)。在总计 67.8 公顷的土地上,NDRE 发现了 7.21 公顷受影响的土地,NDVI 发现了 7.9 公顷,PSRI 发现了 6.49 公顷。哨兵-2 A 波段可测量各种土地和植被健康参数,根据所用指数确定波段对射频分类的影响。对 NDRE 和 NDVI 分类最重要的波段是哨兵-2 A 的 B2(蓝色)波段,对 PSRI 最重要的波段是 B5(红色边缘)波段。根据这些波段,在 Sentinel-2 A 中,492.4-740.5 nm 波段是检测环斑红杉病害区域的最佳波段。该系统能够检测树冠退化的差异,以及根部腐烂的风倒树或林间空隙。这项研究首次表明,Sentinel-2 A 卫星图像可成功用于检测野百合根腐病。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Detection of Heterobasidion Root Rot on Pinus brutia Ten. Using Different Vegetation Indices Generated from Sentinel-2 A Satellite Imagery

Detection of Heterobasidion Root Rot on Pinus brutia Ten. Using Different Vegetation Indices Generated from Sentinel-2 A Satellite Imagery

The genus Heterobasidion includes some of the most destructive pathogens of conifers in the Northern hemisphere. Heterobasidion root rot leads to loss of root function and visible symptoms in the crowns of most Pinus spp., including Turkish red pine (P. brutia). Infected pines will eventually die. Wind-thrown trees with decayed roots or open gaps in the stand often indicate the presence of Heterobasidion root rot. Satellite imagery has recently been utilized regularly to detect damaged areas in order to apply early management procedures to pests or diseases in forests, reducing spread within an affected site and to other places. In the work described here, Sentinel-2 A satellite imagery was tested for detecting Heterobasidion root rot in P. brutia regeneration in an area in south-western Turkiye, using different vegetation indices. Normalized Difference Red Edge Index (NDRE), Normalized Difference Vegetation Index (NDVI), and Plant Senescence Reflectance Index (PSRI) indices were calculated from Sentinel-2 A satellite images in the Google Earth Engine (GEE) platform to detect disease. Calculated indices as synthetic band were added to the Sentinel-2 A satellite image on the GEE platform. Images with the added bands were classified using Random Forest (RF) before evaluation using the Kappa Coefficient and Overall Accuracy. Based on a statistical analysis, NDRE was the most useful index for detecting the disease with an overall accuracy of 89% and a Kappa Coefficient of 0.84, followed by NDVI and PSRI, respectively. After evaluation of General Accuracy and Kappa Coefficient, disease incidence in the area was determined (affected hectares), based on the indices. NDRE detected 7.21 affected hectares, NDVI 7.9 hectares and PSRI 6.49 hectares in a total of 67.8 hectares. Sentinel-2 A bands, which allow the measurement of various land and vegetation health parameters, the effect of bands on RF classification was determined according to the indices used. The most important band for classification of NDRE and NDVI was the B2 (BLUE) band of Sentinel-2 A, and the most important band with PSRI was the B5 (RED EDGE) band. Based on these bands, the best wavelengths for detecting H. annosum diseased areas were in the range 492.4–740.5 nm in Sentinel-2 A. The system enabled the detection of differences in crown deterioration and also wind-thrown trees with decayed roots or open gaps in the stand. This study is the first to show that Sentinel-2 A satellite imagery can be applied successfully for the detection of Heterobasidion root rot on P. brutia.

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来源期刊
Journal of the Indian Society of Remote Sensing
Journal of the Indian Society of Remote Sensing ENVIRONMENTAL SCIENCES-REMOTE SENSING
CiteScore
4.80
自引率
8.00%
发文量
163
审稿时长
7 months
期刊介绍: The aims and scope of the Journal of the Indian Society of Remote Sensing are to help towards advancement, dissemination and application of the knowledge of Remote Sensing technology, which is deemed to include photo interpretation, photogrammetry, aerial photography, image processing, and other related technologies in the field of survey, planning and management of natural resources and other areas of application where the technology is considered to be appropriate, to promote interaction among all persons, bodies, institutions (private and/or state-owned) and industries interested in achieving advancement, dissemination and application of the technology, to encourage and undertake research in remote sensing and related technologies and to undertake and execute all acts which shall promote all or any of the aims and objectives of the Indian Society of Remote Sensing.
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