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基于HJ-1A高光谱的黄河口碱蓬和柽柳盖度反演模型研究 总被引：3，自引：2，他引：1
碱蓬和柽柳是黄河口湿地典型的盐生植物类型,是多种保护珍禽的主要栖息地,具有景观尺度较小、分布广且多混生的特点。应用覆盖黄河口北部潮滩的HJ-1A高光谱遥感影像,基于现场测量的端元光谱和从遥感影像中使用顺序最大角凸锥法(SAMCC)自动提取的端元光谱,应用线性光谱分解法(LSU)、正交子空间投影法(OSP)、匹配滤波法(MF)、最小能量约束法(CEM)和自适应一致估计法(ACE)5种不同光谱解混方法进行混合像元光谱解混,对比两种方法得到的端元光谱分别对碱蓬和柽柳盖度的反演能力,并给出相应的反演模型。结果显示:(1)现场测量端元光谱取得了较好的碱蓬和柽柳盖度反演结果,其中应用LSU方法的光谱解混结果与现场测量盖度的决定系数对于碱蓬和柽柳分别达到了0.88和0.95;(2)两种端元获取方式的光谱解混结果中,LSU和OSP方法均获得了较高的相关性,ACE解混方法的相关性都最低;(3)SAMCC方法提取端元光谱对柽柳的分解结果与现场测量盖度的相关性远高于碱蓬。 相似文献
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《International Journal of Digital Earth》2013,6(3):217-228
Chinese tamarisk (saltcedar) is a deciduous shrub that occurs widely across the Yellow River Delta in China. The spatial structure of Chinese tamarisk is believed to have an influence on the landscape and habitats of rare birds. In this study, first, Chinese tamarisk is detected using Canny edge detector and mathematical morphological operators based on SPOT 5 fusion-ready imagery. Then the numbers, areas, locations, and patch spacing of Chinese tamarisk patches are calculated. The experiments show that the detection accuracy of Chinese tamarisk patches is about 93.4% after the disconnection of connected patches. The distribution orientation of about 70% of the patches is approximately south–north. About 91% of the minimum distances among the patches are between 12.5 and 57.5 m. The rose graph indicates that the main azimuth between patches is north–northwest, and the second is northeast and southeast. The present study indicates that the integrating Canny edge detector with the algorithms for extracting circular and elliptical objects based on mathematical morphology is simple and effective for detecting Chinese tamarisk patches and is easy to identify the spatial structure of Chinese tamarisk patches, which reduces the time and labor for the visual interpretation of Chinese tamarisk patches. 相似文献
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Christopher J. Jarchow William J. Waugh Kamel Didan Armando Barreto-Muñoz Stefanie Herrmann Pamela L. Nagler 《水文研究》2020,34(12):2739-2749
Because groundwater recharge in dry regions is generally low, arid and semiarid environments have been considered well-suited for long-term isolation of hazardous materials (e.g., radioactive waste). In these dry regions, water lost (transpired) by plants and evaporated from the soil surface, collectively termed evapotranspiration (ET), is usually the primary discharge component in the water balance. Therefore, vegetation can potentially affect groundwater flow and contaminant transport at waste disposal sites. We studied vegetation health and ET dynamics at a Uranium Mill Tailings Radiation Control Act (UMTRCA) disposal site in Shiprock, New Mexico, where a floodplain alluvial aquifer was contaminated by mill effluent. Vegetation on the floodplain was predominantly deep-rooted, non-native tamarisk shrubs (Tamarix sp.). After the introduction of the tamarisk beetle (Diorhabda sp.) as a biocontrol agent, the health of the invasive tamarisk on the Shiprock floodplain declined. We used Landsat normalized difference vegetation index (NDVI) data to measure greenness and a remote sensing algorithm to estimate landscape-scale ET along the floodplain of the UMTRCA site in Shiprock prior to (2000–2009) and after (2010–2018) beetle establishment. Using groundwater level data collected from 2011 to 2014, we also assessed the role of ET in explaining seasonal variations in depth to water of the floodplain. Growing season scaled NDVI decreased 30% (p < .001), while ET decreased 26% from the pre- to post-beetle period and seasonal ET estimates were significantly correlated with groundwater levels from 2011 to 2014 (r2 = .71; p = .009). Tamarisk greenness (a proxy for health) was significantly affected by Diorhabda but has partially recovered since 2012. Despite this, increased ET demand in the summer/fall period might reduce contaminant transport to the San Juan River during this period. 相似文献
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