无人机与Sentinel-2 NDVI和GNDVI在坦桑尼亚Burunge野生动物管理区生境条件初步诊断中的比较评估

IF 1.6 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY
Lazaro J. Mangewa, P. Ndakidemi, R. D. Alward, Hamza K. Kija, J. Bukombe, Emmanuel Nasolwa, L. Munishi
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引用次数: 13

摘要

生境条件是保护区野生动物保护与管理的重要生态属性,包括坦桑尼亚布伦格野生动物管理区。传统技术,包括用于评估生境条件的卫星遥感和地基技术,在成本和卫星平台的低分辨率方面存在局限性。归一化植被指数(NDVI)和绿色植被指数(GNDVI)具有评估生境条件的潜力,如饲料数量和质量、植被覆盖和退化、土壤侵蚀和盐渍化、火灾和植被覆盖污染。因此,我们研究了最近出现的无人机(UAV)平台与传统的Sentinel-2在使用NDVI和GNDVI指示栖息地条件方面的差异。我们在主要土地覆盖类型中随机设置了13个调查样地:草地、灌丛和林地3个调查样地,河流和马赛克覆盖2个调查样地。我们使用了安装在无人机上的多光谱传感器,并在2020年2月至3月期间获得了哨兵2号的图像。我们将NDVI和GNDVI值分为栖息地状况等级(非常好、良好、差和非常差)。我们使用R-software中的描述性统计和线性回归模型对数据进行分析。结果表明,无人机具有较高的灵敏度和提供必要的生境条件初步诊断指示的能力。基于无人机的NDVI和GNDVI地图比Sentinel-2地图显示了所有类型栖息地条件的更多细节。线性回归结果显示两个平台之间呈正相关(p < 0.001)。差异主要归因于空间分辨率和轻微的大气影响。我们建议进一步研究其他植被指数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparative Assessment of UAV and Sentinel-2 NDVI and GNDVI for Preliminary Diagnosis of Habitat Conditions in Burunge Wildlife Management Area, Tanzania
Habitat condition is a vital ecological attribute in wildlife conservation and management in protected areas, including the Burunge wildlife management areas in Tanzania. Traditional techniques, including satellite remote sensing and ground-based techniques used to assess habitat condition, have limitations in terms of costs and low resolution of satellite platforms. The Normalized Difference Vegetation Index (NDVI) and Green NDVI (GNDVI) have potential for assessing habitat condition, e.g., forage quantity and quality, vegetation cover and degradation, soil erosion and salinization, fire, and pollution of vegetation cover. We, therefore, examined how the recently emerged Unmanned Aerial Vehicle (UAV) platform and the traditional Sentinel-2 differs in indications of habitat condition using NDVI and GNDVI. We assigned 13 survey plots to random locations in the major land cover types: three survey plots in grasslands, shrublands, and woodlands, and two in riverine and mosaics cover types. We used a UAV-mounted, multi-spectral sensor and obtained Sentinel-2 imagery between February and March 2020. We categorized NDVI and GNDVI values into habitat condition classes (very good, good, poor, and very poor). We analyzed data using descriptive statistics and linear regression model in R-software. The results revealed higher sensitivity and ability of UAV to provide the necessary preliminary diagnostic indications of habitat condition. The UAV-based NDVI and GNDVI maps showed more details of all classes of habitat conditions than the Sentinel-2 maps. The linear regressions results showed strong positive correlations between the two platforms (p < 0.001). The differences were attributed primarily to spatial resolution and minor atmospheric effects. We recommend further studies to test other vegetation indices.
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来源期刊
Earth Interactions
Earth Interactions 地学-地球科学综合
CiteScore
2.70
自引率
5.00%
发文量
16
审稿时长
>12 weeks
期刊介绍: Publishes research on the interactions among the atmosphere, hydrosphere, biosphere, cryosphere, and lithosphere, including, but not limited to, research on human impacts, such as land cover change, irrigation, dams/reservoirs, urbanization, pollution, and landslides. Earth Interactions is a joint publication of the American Meteorological Society, American Geophysical Union, and American Association of Geographers.
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