Influence of Aerospace Imagery Spatial Resolution on Mapping Results of Tundra Vegetation

IF 0.6 4区物理与天体物理 Q4 ASTRONOMY & ASTROPHYSICS Cosmic Research Pub Date : 2024-02-27 DOI:10.1134/s0010952523700557

V. V. Elsakov

{"title":"Influence of Aerospace Imagery Spatial Resolution on Mapping Results of Tundra Vegetation","authors":"V. V. Elsakov","doi":"10.1134/s0010952523700557","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Abstract</h3><p>Multiscale thematic maps of vegetation cover of the eastern Bolshezemelskaya tundra model area have been analyzed in this work. The primary mapping data has been obtained by processing satellite (<i>Quickbird</i> (Qb), <i>Landsat</i> TM5 (L5)) and aerial (DJI Phantom 2 (unmanned aerial vehicle (UAV)) images. Same imaging dates, survey conditions, and the spectral channel ranges of satellite radiometers have determined the identity of the vegetation cover characteristics on the satellite images. Homogeneous areas have been used for spectral signatures calculation of classes (Qb and L5 classifications) and have been obtained based on UAV imagery. A comparison of aerial and satellite images of the model area have showed that the bulk of the Qb image contained mixed pixels with a composition of the dominant class below 50%. Only 14.6% of the pixels had a share of the dominant class exceeding 80%. The majority (53.8%) of such homogeneous image elements included water surface classes (39.2%) and willow (24.6%). The number of homogeneous pixels of L5 (composition of more than 50% of the surface belongs to the same Qb class) did not exceed 14.1%. The spectral brightness coefficients for homogeneous pixels had high convergence between Qb and L5. Mixed pixels have been able to form spectral signatures with new values and sometimes with classes often missing inside. Overlapping the land cover and water surface class spectral features in mixed pixels formed spectra of eroded peatlands and bare soil. With reduction of resolution, an increase in the presence of an exposed peat class was noted (1.6- to 2.2-fold for transition UAV to Qb and 3.1- to 4.4-fold for Qb to L5, with the highest result being detected during UAV-L5 transition (6.9-fold)). Methods of spectral selection of etalon classes affected the convergence of classification results of spatially different images as well. A weak degree of conjunction was observed between UAV and Qb (30.3% (total) and 20.7% (κ)) and Qb and L5 classifications (44.5 and 30.3%, respectively). This index was negligible for UAV and L5 vegetation maps (28.5 and 15.5%). The main factors influencing the level of convergence and the ratio of class areas on different-scale images were the radiometric features of the class etalons and the spatial homogeneity of the mapped landscapes.</p>","PeriodicalId":56319,"journal":{"name":"Cosmic Research","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cosmic Research","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1134/s0010952523700557","RegionNum":4,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}

引用次数: 0

Abstract

Multiscale thematic maps of vegetation cover of the eastern Bolshezemelskaya tundra model area have been analyzed in this work. The primary mapping data has been obtained by processing satellite (Quickbird (Qb), Landsat TM5 (L5)) and aerial (DJI Phantom 2 (unmanned aerial vehicle (UAV)) images. Same imaging dates, survey conditions, and the spectral channel ranges of satellite radiometers have determined the identity of the vegetation cover characteristics on the satellite images. Homogeneous areas have been used for spectral signatures calculation of classes (Qb and L5 classifications) and have been obtained based on UAV imagery. A comparison of aerial and satellite images of the model area have showed that the bulk of the Qb image contained mixed pixels with a composition of the dominant class below 50%. Only 14.6% of the pixels had a share of the dominant class exceeding 80%. The majority (53.8%) of such homogeneous image elements included water surface classes (39.2%) and willow (24.6%). The number of homogeneous pixels of L5 (composition of more than 50% of the surface belongs to the same Qb class) did not exceed 14.1%. The spectral brightness coefficients for homogeneous pixels had high convergence between Qb and L5. Mixed pixels have been able to form spectral signatures with new values and sometimes with classes often missing inside. Overlapping the land cover and water surface class spectral features in mixed pixels formed spectra of eroded peatlands and bare soil. With reduction of resolution, an increase in the presence of an exposed peat class was noted (1.6- to 2.2-fold for transition UAV to Qb and 3.1- to 4.4-fold for Qb to L5, with the highest result being detected during UAV-L5 transition (6.9-fold)). Methods of spectral selection of etalon classes affected the convergence of classification results of spatially different images as well. A weak degree of conjunction was observed between UAV and Qb (30.3% (total) and 20.7% (κ)) and Qb and L5 classifications (44.5 and 30.3%, respectively). This index was negligible for UAV and L5 vegetation maps (28.5 and 15.5%). The main factors influencing the level of convergence and the ratio of class areas on different-scale images were the radiometric features of the class etalons and the spatial homogeneity of the mapped landscapes.

Abstract Image

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

航空航天成像空间分辨率对苔原植被绘图结果的影响

摘要本研究分析了博尔舍泽梅尔斯卡亚苔原模型区东部植被覆盖的多尺度专题地图。主要绘图数据是通过处理卫星图像（Quickbird (Qb)、Landsat TM5 (L5)）和航空图像（DJI Phantom 2（无人机））获得的。相同的成像日期、勘测条件和卫星辐射计的光谱通道范围决定了卫星图像上的植被覆盖特征。同质区域被用于计算等级的光谱特征（Qb 和 L5 分类），这些特征是根据无人机图像获得的。对模型区域的航空和卫星图像进行比较后发现，大部分 Qb 图像包含混合像素，主要类别的组成低于 50%。只有 14.6% 的像素的优势类比例超过 80%。大部分（53.8%）同质图像元素包括水面类（39.2%）和柳树类（24.6%）。L5 级同质像素（超过 50%的表面组成属于同一 Qb 级）的数量不超过 14.1%。同质像素的光谱亮度系数在 Qb 和 L5 之间高度趋同。混合像素能够形成具有新值的光谱特征，有时其内部往往缺少类别。在混合像素中重叠的土地覆被和水面类别光谱特征形成了侵蚀泥炭地和裸露土壤的光谱。随着分辨率的降低，裸露泥炭类的出现也有所增加（从 UAV 到 Qb 的过渡为 1.6-2.2 倍，从 Qb 到 L5 的过渡为 3.1-4.4 倍，UAV-L5 过渡期间检测到的结果最高（6.9 倍））。等离子体类别的光谱选择方法也影响了空间不同图像分类结果的趋同性。在 UAV 和 Qb（30.3%（总）和 20.7%（κ））以及 Qb 和 L5 分类（分别为 44.5% 和 30.3%）之间观察到微弱的会合度。这一指数在 UAV 和 L5 植被图中可忽略不计（28.5% 和 15.5%）。影响不同比例尺图像上等级面积的趋同程度和比例的主要因素是等级等值线的辐射特征和测绘景观的空间均匀性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Cosmic Research 地学天文-工程：宇航

CiteScore

1.10

自引率

33.30%

发文量

审稿时长

6-12 weeks

期刊介绍： Cosmic Research publishes scientific papers covering all subjects of space science and technology, including the following: ballistics, flight dynamics of the Earth’s artificial satellites and automatic interplanetary stations; problems of transatmospheric descent; design and structure of spacecraft and scientific research instrumentation; life support systems and radiation safety of manned spacecrafts; exploration of the Earth from Space; exploration of near space; exploration of the Sun, planets, secondary planets, and interplanetary medium; exploration of stars, nebulae, interstellar medium, galaxies, and quasars from spacecraft; and various astrophysical problems related to space exploration. A chronicle of scientific events and other notices concerning the main topics of the journal are also presented.