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基于东亚飞蝗生育周期的遥感蝗灾监测新模式 总被引：6，自引：1，他引：6
当前 ,国际遥感蝗灾监测的技术路线一般是爆发蝗灾后受损面积、程度的监测与评价 ,研究灾害的有效预警与预测方法 ,对防灾减灾更具有现实意义。通过连续 2 0 0 1、2 0 0 2年连续实地对渤海湾夏蝗孵化期、生长期和成虫期等 7个阶段的野外观测 ,对蝗虫生境物理和生物依赖条件样方统计、光谱测试和遥感机理实验 ,提出了“飞蝗生育周期遥感三段监测”的论点 ,根据这个论点将遥感监测设计为 3个阶段 :(1 )孵化期水热条件遥感反演 ;(2 )生长期食量猛增遥感监测芦苇叶面积指数和植被盖度变化 ;(3)成虫期寻找新食源对芦苇盖度 (温度 )和地表水条件 ,进而对聚集条件和迁移方向的分析指导灭蝗。有效发挥了遥感连续动态观测的技术特点 ,为建立环渤海湾东亚飞蝗遥感监测体系提供了基本技术路线 ,介绍的思路与方法也可以对森林病虫害等大规模突发病虫灾害起到借鉴作用 相似文献
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以长时间序列的SPOT-Vegetation遥感数据为基础,利用Theil-Sen斜率估计与Mann-Kendall趋势检验相结合的方法分析了中亚地区1999-2012年间的土地退化强度和趋势;并结合高程数据,分析人类活动对土地退化的影响。结果表明：土地退化强烈地区主要位于环卡拉库姆沙漠、克孜勒库姆沙漠边缘的绿洲经济带和哈萨克斯坦西部盐碱地带。环卡拉库姆沙漠、克孜勒库姆沙漠边缘的绿洲经济带地区近年来着重发展经济,对自然植被破坏加剧,对生态系统造成了一定的负面影响;哈萨克斯坦西部盐碱地地区,由于盐碱化程度不断加重导致土地退化更加强烈。中亚地区在沿里海、各湖周边、各沙漠边缘以及山区雪线下的地区土地退化状况有明显改善,表明海湖地区围湖造田兴起,农业生产活动强度显著增加,同时沙漠周边各项环境治理工程和防风固沙工程得到有效实施,也起到一定作用。气候环境的变化使高海拔区域冰雪融化,原先不适合植被生长的苔原地区逐渐有林木和灌木生长,这与前人研究的全球变暖,中亚气候逐渐转向暖湿,植被“北侵”的认识相吻合。各沙漠内部土地改善趋势显著但强度非常小,这可能是由于这些区域的气候特征逐渐转向暖湿,从而造成沙漠植被的植物生理过程发生了微弱变化;然而沙漠植被并不能为人们所利用,其繁茂程度对促进区域经济发展意义不大。所以总体来看,中亚地区人类的生存环境可能在恶化。 相似文献
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针对以往植被地上生物量(以下简称“生物量”)多尺度估算方法在数据收集、尺度转化、结果呈现等方面的局限,该文提出了面向植被均质单元的生物量多尺度估算方法：(1)定义了具有实际景观意义的植被均质单元,作为植被生物量估算的基本单元;(2)基于多源数据提取直接反映和间接影响植被生物量的多源因子,利用多尺度分割技术构建多尺度下的植被均质单元;(3)通过随机森林回归模型实现植被生物量多尺度估算。结果表明,该方法可避免多尺度下的数据获取,仅基于一套数据实现了研究区植被生物量多尺度估算,产生了较好的建模和估算精度。该方法不仅可量化生物量大小,还可描绘生物量均质区域,具有尺度变换便捷、灵活等优势。 相似文献
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针对目前复杂植被山区滑坡蠕变监测受植被覆盖影响较大、不同植被覆盖度下滑坡蠕变关系研究缺乏等问题,该文联合Sentinel-1和ALOS PALSAR-2数据集,分别利用SBAS-InSAR和D-InSAR两轨差分技术,获取研究区2019年7月—2020年8月的雷达视线向形变时间序列,分析了复杂植被山区滑坡蠕变与植被覆盖度的内在关系。结果表明：(1)不同植被覆盖度等级对平寨水库库岸山区滑坡蠕变的影响具有显著差异,在低、中高和高植被覆盖度等级时诱发坡体沉降,在中植被覆盖度等级时抑制滑坡蠕变;(2)平寨水库库岸山区的滑坡蠕变体主要集中在库区NW-SE方向,分布与三岔河流域的流向相近;(3)联合多源数据对复杂植被山区滑坡蠕变进行组合探测能够有效克服时间、空间去相干影响,使滑坡蠕变体监测结果更为可靠。研究结果揭示了滑坡蠕变与植被覆盖的内在联系,可以为区域尺度防灾减灾事业提供科学支持。 相似文献
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基于GIMMS AVHRR NDVI数据的中国寒旱区植被动态及其与气候因子的关系 总被引：21，自引：0，他引：21
本文基于遥感和地理信息系统技术,用气象数据对中国的寒旱区作了初步的定义.利用GIMMS AVHRR NDVI (Normalized Difference Vegetation Index)数据对中国寒旱区植被覆盖的情况进行了动态监测.采用最大化合成植被指数SINDVI,一元线性回归趋势分析和偏差分析得出寒旱区植被变化特征,并且结合各个气象台站的年平均气温和年总降水数据采用相关分析方法,分析植被动态对气候对气候变化的响应.得出结论:东北的长白山、大小兴安岭、山西的太行山、新疆的准格尔盆地和阿尔泰山的部分地区植被呈现明显退化趋势;而天山、喜马拉雅山、祁连山、阴山、蒙古高原、东北平原及大巴山的高山区,植被呈现改善趋势.中国寒旱区大部分区域植被变化与降水和温度均呈现正相关关系. 相似文献
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基于MODIS-NDVI数据分析澜沧江流域生长季植被NDVI时空特征和变化趋势,结合地形数据、气象站点数据和植被类型数据,利用趋势分析和相关性分析法研究植被NDVI变化对气候因子的响应。结果表明:1)2000-2017年澜沧江流域生长季植被NDVI均值为0.592,整体呈现出由西北向东南波动增加趋势,增长速率为0.09%/10年;2) 2000-2017年澜沧江流域气温呈上升趋势,降水呈下降趋势,植被NDVII总体与平均气温的相关性高于累积降水量;3)澜沧江流域生长季植被NDVI驱动因子分析表明,气候驱动中以气温降水联合驱动为主,流域植被NDVI变化整体为非气候驱动。 相似文献
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不同分辨率影像反演植被覆盖度的参数确定与尺度效应分析 总被引：3，自引：0，他引：3
选择新疆古尔通班古特沙漠南缘的石河子地区作为研究区,针对统计回归模型需要大量实测数据,而像元二分模型(dimidiate pixel model,DPM)参数难以确定的缺点,提出了利用统计回归的结果反推像元二分模型参数来建立研究区遥感反演植被覆盖度的方法。运用该方法研究了利用TM和MODIS遥感影像数据分别反演植被覆盖度的参数化方案;同时,还研究了采用不同遥感数据源和不同反演模型时研究区植被覆盖度信息提取中存在的尺度效应。 相似文献
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近15年中国西南地区植被覆盖度动态变化 总被引：1，自引：0，他引：1
《国土资源遥感》2017,(3)
基于MODIS-NDVI数据,利用像元二分模型估算获得中国西南地区2000—2014年间的250 m分辨率月度植被覆盖度(fractional vegetation cover,FVC),结合气象数据,采用趋势分析、相关分析和残差分析方法,对西南地区近15 a间FVC时空变化及与气候、人类活动的关系进行了综合分析。结果表明:(1)2000—2014年间西南地区森林生态系统的年最大FVC显著增加,增加速率为0.096 2 a~(-1)(p0.05),农田年最大FVC增幅最小(0.031 1 a~(-1),p=0.582);(2)FVC变化存在明显的空间差异,滇北、黔渝地区的森林和灌丛、三江源地区的草地以及广西南部的农田FVC显著增加,但汶川、横断山、川西北等地FVC显著下降;(3)西南地区年最大FVC与秋季降水和夏季均温的相关性最好,相关系数分别为0.320和0.281;(4)2000—2014年间西南地区FVC残差的增加速率为0.023 2 a~(-1),说明人类活动对西南地区植被生长整体上起促进作用。 相似文献
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Climate change scenarios predict that Central Asia may experience an increase in the frequency and magnitude of temperature and precipitation extremes by the end of the 21st century, but the response regularity of different types of vegetation to climate extremes is uncertain. Based on remote-sensed vegetation index and in-situ meteorological data for the period of 2000–2012, we examined the diverse responses of vegetation to climate mean/extremes and differentiated climatic and anthropogenic influence on the vegetation in Central Asia. Our results showed that extensive vegetation degradation was related to summer water deficit as a result of the combined effect of decreased precipitation and increased potential evapotranspiration. Water was a primary climatic driver for vegetation changes regionally, and human-induced changes in vegetation confined mainly to local areas. Responses of vegetation to water stress varied in different vegetation types. Grasslands were most responsive to water deficit followed by forests and desert vegetation. Climate extremes caused significant vegetation changes, and different vegetation types had diverse responses to climate extremes. Grasslands represented a symmetric response to wet and dry periods. Desert vegetation was more responsive during wet years than in dry years. Forests responded more strongly to dry than to wet years due to a severe drought occurred in 2008. This study has important implications for predicting how vegetation ecosystems in drylands respond to climate mean/extremes under future scenarios of climate change. 相似文献
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MODIS NDVI和AVHRR NDVI 对草原植被变化监测差异 总被引：5，自引：0，他引：5
以草地作为研究载体,对比分析草原植被AVHRR NDVI和MODIS NDVI两种NDVI序列的年内、年际变化特征,讨论两种NDVI序列对降水量、平均气温和水汽压3种气候因子的响应差异,为合理选择NDVI序列对植被进行监测研究提供参考。结果表明：(1)两种NDVI序列所反映的草原植被年内变化趋势相似,但MODIS NDVI对各类草原的区分度优于AVHRR NDVI;(2)两种NDVI序列所反映的2000年—2003年草原植被年际变化差异明显。较之于MODIS NDVI,AVHRR NDVI变化趋势分类图表现出更强的植被改善趋势,植被改善面积在AVHRR NDVI变化趋势分类图中占94.25%,在MODIS NDVI中为83.33%;两种NDVI变化趋势分类图反映的植被变化趋势吻合度为52.88%。(3)两种NDVI序列与水汽压、降水量相关性差异显著。MODIS NDVI与各站点平均气温的相关系数均大于GIMMS NDVI;而MODIS NDVI与水汽压的相关系数83%(10个站点)小于GIMMS NDVI,与降水量的相关系数67%(8个站点)小于GIMMS NDVI。 相似文献
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《地理信息系统科学与遥感》2013,50(3):371-393
This study uses a multiple linear regression method to composite standard Normalized Difference Vegetation Index (NDVI) time series (1982-2009) consisting of three kinds of satellite NDVI data (AVHRR, SPOT, and MODIS). This dataset was combined with climate data and land cover maps to analyze growing season (June to September) NDVI trends in northeast Asia. In combination with climate zones, NDVI changes that are influenced by climate factors and land cover changes were also evaluated. This study revealed that the vegetation cover in the arid, western regions of northeast Asia is strongly influenced by precipitation, and with increasing precipitation, NDVI values become less influenced by precipitation. Spatial changes in the NDVI as influenced by temperature in this region are less obvious. Land cover dynamics also influence NDVI changes in different climate zones, especially for bare ground, cropland, and grassland. Future research should also incorporate higher-spatial-resolution data as well as other data types (such as greenhouse gas data) to further evaluate the mechanisms through which these factors interact. 相似文献
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In this paper, we apply lagged correlation analysis to study the effects of vegetation cover on the summer climate in different zones of China, using NOAA/AVHRR normalized difference vegetation index (NDVI) data during the time period from 1982 to 2001 and climate data of 365 meteorological stations across China (precipitation from 1982 to 2001 and temperature from 1982 to 1998). The results show that there are positive correlations between spring NDVI and summer climate (temperature and precipitation) in most zones of China; these suggest that, when the vegetation cover increases, the summer precipitation will increase, and the lagged correlations show a significant difference between zones. The stronger correlations between NDVI in previous season and summer climate occur in three zones (Mid-temperate zone, Warm-temperate zone and Plateau climate zone), and this implies that vegetation changes have more sensitive feedback effects on climate in the three zones in China. 相似文献
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The authors derived the normalized difference vegetation index (NDVI) from the NOAA/AVHRR Land dataset, at a spatial resolution of 8km and 15-day intervals, to investigate the vegetation variations in China during the period from 1982 to 2001. Then, GIS is used to examine the relationship between precipitation and the Normalized Difference Vegetation Index (NDVI) in China, and the value of NDVI is taken as a tool for drought monitoring. The results showed that in the study period, China’s vegetation cover had tended to increase, compared to the early 1980s; mean annual NDVI increased 3.8%. The agricultural regions (Henan, Hebei, Anhui and Shandong) and the west of China are marked by an increase, while the eastern coastal regions are marked by a decrease. The correlation between monthly NDVI and monthly precipitation/temperature in the period 1982 to 2001 is significantly positive (R2=0.80, R2=0.84); indicating the close coupling between climate conditions (precipitation and temperature) and land surface response patterns over China. Examination of NDVI time series reveals two periods: (1) 1982–1989, marked by low values below average NDVI and persistence of drought with a signature large-scale drought during the 1982 and 1989; and (2) 1990–2001, marked by a wetter trend with region-wide high values above average NDVI and a maximum level occurring in 1994 and 1998. 相似文献
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研究采矿扰动区内植被变化规律,能够为矿区生态修复提供理论依据。本文以山西省西山煤田为研究区,通过设立对比试验区,利用MODIS/NDVI（2001-2019年）结合同期的气温、降水气候因子,分别从植被指数的时空变化及与气象因子之间的关系等方面展开对比,用于探究采矿扰动区内植被变化情况。研究结果表明：①19年来西山煤田与间接影响区及校验区的植被均呈增加趋势,但西山煤田相比于校验区NDVI均值低11.42%。②西山煤田相较于自然生态条件下植被增长率为-5.53%。③西山煤田与校验区的NDVI值均受到气温、降水两种气象因子的影响,但是与降水的相关性更高,即受降水影响更大。 相似文献
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Moderate Resolution Imaging Spectroradiometer (MODIS) 16-day 1-km vegetation index products, daily temperature, photosynthetically active radiation (PAR), and precipitation from 2001 to 2004 were utilized to analyze the temporal variations of the MODIS normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), as well as their correlations with climate over the evergreen forested sites in Zhejiang-a humid subtropical region in the southeast of China. The results showed that both NDVI and EVI could discern the seasonal variation of the evergreen forests. Attributed to the sufficient precipitation in the study area, the growth of vegetation is mainly controlled by energy; as a result, NDVI, and especially EVI, is more correlated with temperature and PAR than precipitation. Compared with NDVI, EVI is more sensitive to climate condition and is a better indicator to study vegetation variations in the study region 相似文献
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In this paper, we apply lagged correlation analysis to study the effects of vegetation cover on the summer climate in different zones of China, using NOAA/AVHRR normalized difference vegetation index (NDVI) data during the time period from 1982 to 2001 and climate data of 365 meteorological stations across China (precipitation from 1982 to 2001 and temperature from 1982 to 1998). The results show that there are positive correlations between spring NDVI and summer climate (temperature and precipitation) in m... 相似文献
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In this paper, we apply lagged correlation analysis to study the effects of vegetation cover on the summer climate in different
zones of China, using NOAA/AVHRR normalized difference vegetation index (NDVI) data during the time period from 1982 to 2001
and climate data of 365 meteorological stations across China (precipitation from 1982 to 2001 and temperature from 1982 to
1998). The results show that there are positive correlations between spring NDVI and summer climate (temperature and precipitation)
in most zones of China; these suggest that, when the vegetation cover increases, the summer precipitation will increase, and
the lagged correlations show a significant difference between zones. The stronger correlations between NDVI in previous season
and summer climate occur in three zones (Mid-temperate zone, Warm-temperate zone and Plateau climate zone), and this implies
that vegetation changes have more sensitive feedback effects on climate in the three zones in China.
Supported by the National 973 Program of China (No.2006CB701300), the National Natural Science Foundation of China (No.40721001),
the Sino-Germany Joint Project (No. 2006DFB91920), the Open Fund of Shanghai Leading Academic Discipline Project (T0102) and
the Open Fund of LIESMARS, Wuhan University. 相似文献