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基于哨兵2号多光谱遥感数据的草原植被盖度反演--以内蒙古自治区为例
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作者 田海静 王林 +2 位作者 韩立亮 范云豹 杨吉林 《林业资源管理》 北大核心 2022年第4期134-140,共7页
建立高精度草原植被盖度遥感估算模型对定量评估草原资源质量和支撑草原精细化管理至关重要。研究利用内蒙古自治区草原样地调查数据,基于哨兵2号多光谱遥感数据进行了草原植被盖度分类遥感建模及反演。研究表明:1)23种植被指数与实测... 建立高精度草原植被盖度遥感估算模型对定量评估草原资源质量和支撑草原精细化管理至关重要。研究利用内蒙古自治区草原样地调查数据,基于哨兵2号多光谱遥感数据进行了草原植被盖度分类遥感建模及反演。研究表明:1)23种植被指数与实测植被盖度均呈现显著相关性(P<0.001),其中相关性最强的为NDVI,相关系数为0.834;2)正弦函数在高值部分(植被盖度>75%)的低估现象更明显,而线性函数在低值部分(植被盖度<25%)的高估现象更明显,通过采用两种函数对植被盖度进行分段模拟,结果较好;3)按照草地类分为6组分别进行植被盖度建模后,内蒙古自治区1 894个符合质量要求的样地模拟植被盖度与实测植被盖度的相关系数R^(2)=0.722,显著性水平P<0.01,RMSE=12%;4)内蒙古自治区不同草地类植被盖度从高到低分别为山地草甸78.91%,温性草甸草原73.7%,低地草甸53.89%,温性草原52.57%,温性荒漠草原32.76%,温性草原化荒漠25.52%,温性荒漠19.29%。 展开更多
关键词 草原植被盖度 分类建模 遥感反演 哨兵2号 内蒙古自治区
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辽宁省草原植被生长状况简析——以2023年为例
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作者 姜祛寒 《农业与技术》 2024年第20期57-60,共4页
受2023年辽宁省主要草原区降水量较上年偏少影响,全省草原植被长势差于上年同期,返青期、盛期、枯黄期较上年推迟。草原植被平均高度、产草量较上年有所下降。2023年全省草原综合植被盖度值为67.35%,草原生态水平为良,保持基本稳定趋势。
关键词 草原植被长势 草原综合植被 草原生态水平
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甘肃省不同生态功能区草地资源综合评分及其原因分析
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作者 尚艺婕 王新源 程小云 《草学》 2024年第4期66-71,77,共7页
根据甘肃省自然气候的地域分异性规律,将全省草原划分为甘南高寒草原生态功能区,祁连山-阿尔金山山地草甸、草原生态功能区,河西走廊荒漠草原生态功能区,黄土高原干旱草原生态功能区,陇南山地草丛草原生态功能区5个草原生态功能区。从... 根据甘肃省自然气候的地域分异性规律,将全省草原划分为甘南高寒草原生态功能区,祁连山-阿尔金山山地草甸、草原生态功能区,河西走廊荒漠草原生态功能区,黄土高原干旱草原生态功能区,陇南山地草丛草原生态功能区5个草原生态功能区。从甘肃省林草资源现状数据库中,提取草地图斑和相关属性因子,形成草原专题数据库。分别计算全省5个草原生态功能区的草原综合植被盖度、单位面积牧草产量、可食牧草占比、草原载畜能力4个指标。结果表明,通过加入权重系数计算求得全省草原不同生态功能区草地资源综合分析评价得分,并对计算结果采取百分制赋分,得分最高的陇南山地草丛草原生态功能区赋值100分,则甘南高寒草原生态功能区百分制得分为94.11分,黄土高原干旱草原生态功能区百分制得分为50.41分,河西走廊荒漠草原生态功能区百分制得分为26.07分,祁连山-阿尔金山山地草甸、草原生态功能区百分制得分为18.36分。 展开更多
关键词 甘肃省 生态功能区 草地资源 草原综合植被
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Detecting Vegetation Fractional Coverage of Typical Steppe in Northern China Based on Multi-scale Remotely Sensed Data 被引量:15
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作者 李晓兵 陈云浩 +1 位作者 史培军 陈晋 《Acta Botanica Sinica》 CSCD 2003年第10期1146-1156,共11页
One of the study objectives of global change is land use/cover change (LUCC) by using multiscale remotely sensed data on global and regional scale. In this paper, field sample, digital camera, Landsat-ETM+ (ETM+, Enha... One of the study objectives of global change is land use/cover change (LUCC) by using multiscale remotely sensed data on global and regional scale. In this paper, field sample, digital camera, Landsat-ETM+ (ETM+, Enhanced Thematic Mapper) image and the National Oceanic and Atmospheric Administration/the advanced very high resolution radiometer (NOAA/AVHRR) image were integrated to detect, simulate and analyze the vegetation fractional coverage of typical steppe in northern China. The results show: (1) Vegetation fractional coverage measured by digital camera is more precise than results measured by other methods. It can be used to validate other measuring results. (2) Vegetation fractional coverage measured by 1 m 2 field sample change fluctuantly for different observers and for different sample areas. In this experiment, the coverage is generally high compared with the result measured by digital camera, and the average absolute error is 9.92%, but two groups measure results, correlation coefficient r(2) = 0.89. (3) Three kinds of methods using remotely sensed data were adopted to simulate the vegetation fractional coverage. Average absolute errors of the vegetation fractional coverage, measured by ETM+ and NOAA, are respectively 7.03% and 7.83% compared with the result measured by digital camera. When NOAA pixel was decomposed by ETM+ pixels after geometrical registry, the average absolute errors measured by this method is 5.68% compared with the digital camera result. Correction coefficients of three results with digital camera result r(2) are respectively 0.78, 0.61 and 0.76. (4) The result of statistic model established by NOAA-NDVI (NDVI, Normalized Difference Vegetation Index) and the vegetation fractional coverage measured by digital camera show lower precision (r(2) = 0.65) than the result of statistic model established by ETM+-NDVI and digital camera coverage then converted to NOAA image (r(2) = 0.80). Pixel decomposability method improves the precision of measuring the vegetation fractional coverage on a large scale. This is a significant practice on scaling by using remotely sensed data. Integrated application of multi-scale remotely sensed data in earth observation will be an important approach to promoting measuring precision of ecological parameters. 展开更多
关键词 multi-scale remote sensing typical steppe vegetation fractional coverage
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