基于MODIS数据的中国三种主要土地类型变化的空间特征分析

人类活动使得土地利用和植被覆盖发生了巨大变化,直接影响着全球气候。本研究通过从2000—2013年对中国三种主要土地利用类型的NDVI变化特征进行了分析,结果表明:(1)14年来,中国三种主要土地利用类型NDVI平均值均有增强的趋势。(2)三种主要土地利用类型中除耕地中的水田,林地中的有林地和草地中的高覆盖草地增长速率不显著外,其他土地类型增长速率均显著。(3)三种土地利用类型均以改善面积大于退化面积,耕地中改善面积占总耕地的64.21%,退化的区域占18.50%;林地改善的区域占总林地的54.21%,退化的区域占20.13%;草地改善的区域占55.53%,退化的区域占18.23%。三种土地类型均有所改善且改善明显的区域主要集中在甘肃以南,陕西以北和东北部分地区。     

基于MODIS NDVI、SPOT NDVI数据的GIMMS NDVI性能评价

以MODIS NDVI和SPOT NDVI数据为基准对2000—2015年重叠时段的GIMMS NDVI数据进行评价.在全国尺度以及水田、旱地、林地、草地4种土地类型上对比分析3种数据的数值差异、动态一致性、变化趋势差异和两两间相关性.结果表明: GIMMS NDVI在数值上整体高于MODIS NDVI和SPOT NDVI,3种数据在反映植被月动态方面能力相当;研究期内3种NDVI数据在全国大部分区域均呈增加趋势,GIMMS的增加幅度最小,且在我国西北、东北、中南、青藏高原及云贵高原的部分地区与另两套数据差异较大,表明在研究该区域时应对GIMMS NDVI数据的使用有所保留;各数据间两两相关性较强,在全国尺度上MODIS NDVI与SPOT NDVI的相关性更好,旱地GIMMS NDVI与MODIS NDVI的相关性更好,水田、林地、草地MODIS NDVI与SPOT NDVI的相关性更好.     

基于MODIS的中国陆地植被生长及其与气候的关系

基于MODIS2000~2005(缺2004年)5a每8d的GPP资料,分析了中国陆地植被生长特征,讨论了我国气候因子(温度、降水以及辐射)对同期植被生长的影响。研究结果显示,中国陆地植被的年均GPP分布范围在0~3252.6gC.m-.2a-1之间,5a平均值为491.1gC.m-.2a-1;年均GPP最大的地方主要分布于云南南部、海南、台湾以及东南沿海部分地区,最小值主要出现在青藏高原、新疆以及内蒙古西部等高寒、干旱地区。温度是影响同期我国陆地植被生长的主要因子,其次为降水,辐射对我国陆地植被的影响比较小,主要影响区域在华南地区。陆地植被GPP与温度和降水的相关系数在我国表现为自北向南逐渐减小的分布特征,与对应气候因子的分布呈反向关系;而GPP与云量的相关系数则自北向南逐渐增大。     

Terrestrial growth in China and its relationship with climate based on the MODIS data

The characteristics of terrestrial growth in China and its relationship with various climatic factors (e.g. temperature, precipitation and radiation) were investigated by using the data collected with the Moderate Resolution Imaging Spectroradiometer (MODIS). These data were collected once every 8 days during 2000–2003 and then again in 2005. The average annual gross primary production (GPP) in China during this period ranged from 0 to 3252.6 gC·m^?2·a^?1 with an average value of 491.1 gC·m^?2·a^?1. The maximum GPP values were observed over the regions of Yunnan, Hainan and Taiwan, and the southeast coastal areas, while the minimum values were observed in the cold and arid regions of the Tibetan Plateau, Xinjiang and Inner Mongolia. Correlation analysis showed that temperature was the primary factor influencing this terrestrial growth, while precipitation played a secondary role. However, only the terrestrial growth that occurred in southern China was affected by radiation. The correlation coefficients of GPP with temperature and precipitation decreased from northern to southern China and were negatively correlated with the distribution of the associated climatic factors within China. Furthermore, the correlation coefficient of GPP with cloud contents was observed to increase from northern to southern China.     

Terrestrial growth in China and its relationship with climate based on the MODIS data

The characteristics of terrestrial growth in China and its relationship with various climatic factors (e.g. temperature, precipitation and radiation) were investigated by using the data collected with the Moderate Resolution Imaging Spectroradiometer (MODIS). These data were collected once every 8 days during 2000–2003 and then again in 2005. The average annual gross primary production (GPP) in China during this period ranged from 0 to 3252.6 gC·m^?2·a^?1 with an average value of 491.1 gC·m^?2·a^?1. The maximum GPP values were observed over the regions of Yunnan, Hainan and Taiwan, and the southeast coastal areas, while the minimum values were observed in the cold and arid regions of the Tibetan Plateau, Xinjiang and Inner Mongolia. Correlation analysis showed that temperature was the primary factor influencing this terrestrial growth, while precipitation played a secondary role. However, only the terrestrial growth that occurred in southern China was affected by radiation. The correlation coefficients of GPP with temperature and precipitation decreased from northern to southern China and were negatively correlated with the distribution of the associated climatic factors within China. Furthermore, the correlation coefficient of GPP with cloud contents was observed to increase from northern to southern China.     

基于MODIS的中国草地NPP综合估算模型

草地生态系统是陆地生态系统分布最广的生态系统类型之一,其碳储量的估算在全球变化中的作用越来越受到重视。为了快速、便捷地实现中国草地净初级生产力(NPP)的估算,在获取野外调查资料与同期遥感影像数据的基础上,利用归一化植被指数(NDVI)以及气候数据,构建了草地NPP综合估算模型。模型包括叶面积指数(LAI)和光合累积量(PA)两个子模型,其中LAI子模型利用了遥感数据NDVI,PA子模型利用了温度、降水和辐射等气候数据。通过建模以外独立的实测数据的验证,模拟值与实测值之间有很好的相关性,R2为0.8519,相关性达到极显著水平。RMSE和RRMSE均较小,表明模型的模拟结果比较可靠。同时模拟值与实测值之间的平均相对误差仅为1.97%,模拟结果的准确度较高,因此利用上述模型估算中国草地NPP是可行的。以上结果为中国草地NPP估算提供了新的方法。     

基于MODIS数据的三北防护林工程区植被覆盖度提取与分析

以像元二分模型为基础,构建了基于归一化植被指数(NDVI)的植被覆盖度定量估算模型,并利用MODIS-NDVI时间序列数据,估算了三北防护林工程区2001年8月和2007年8月的植被覆盖度,分析了三北防护林工程区植被覆盖度的时空变化特征.结果表明:2001-2007年三北防护林工程区植被覆盖度变化较为明显,平均覆盖度增加了2.07%,其中吉林、山西、陕西和宁夏四省变化幅度最为显著,增加幅度分别达到27.37%、14.12%、9.29%和9.22%.研究区植被覆盖度增加的主要自然原因是降雨量的增加,主要人为原因是人们环境意识的提高以及国家实施的封山育林、退耕还林还草等一系列生态保护政策,特别是三北防护林体系建设工程.     

基于MODIS/NDVI时间序列的森林灾害快速评估方法——以贵州省为例

以2005—2008年中分辨率成像光谱仪(MODIS)的归一化植被指数(NDVI)数据集为主要数据源构建研究区时间序列,结合统计学分析方法设计一套快速有效的森林灾害评估体系,用以探测森林资源损失的空间分布范围与灾害等级,并利用森林资源雪凝灾害损失的实际调查数据对评估结果进行一致性检验。结果表明:通过计算2005—2007年研究区所有森林像元的平均值R珔2005-2007和平均绝对偏差δall,确定森林灾害阈值DT为0.048;利用该阈值,获取2008年受灾较重的森林空间分布,主要密集分布在贵州省东南部和东北部,包括了黔南自治州、黔东南自治州和铜仁市等地区;受灾森林像元数占总森林像元数的28.6%,高于凝冻灾害森林资源损失实际调查结果(17.7%);在县域尺度上,根据MODIS/NDVI关键期影像获取的森林资源损失区域和灾害等级,确定德江、沿河和都匀等11个重度受灾县(市、区)和湄潭、榕江和桐梓等10个中度受灾县(市、区),与小班调查结果具有较高的一致性,其Kappa系数为0.86。方法为大区域尺度的森林灾害快速评估提供了一种新思路。     

基于MODIS黄河三角洲湿地NPP与NDVI相关性的时空变化特征

应用EOS/MODIS卫星遥感资料,分析2001-2006年黄河三角洲地区植被净初级生产NPP及NDVI时空变化特征,在到海岸线不同距离的区域内,讨论了年植被净初级生产力( aNPP)与年均归一化植被指数(ANDVI)的相关性,并建立一元回归分析模型.可以看出,黄河三角洲湿地生态系统分布自海向陆具有明显的空间异质性,滩涂湿地分布于沿海地区,生产力高,该地区aNPP值高且与ANDVI呈显著正相关;其他区域由于是盐碱荒地或农业生态系统,因土壤盐分含量高而系统生产力低,或农耕地受人类干扰严重,一年总的生产力下降,而导致这些区域ANDVI与aNPP呈负相关.利用NDVI进行黄河三角洲生产力监测的可行区域,在距离海岸线小于6_km的范围内,所研究的6a回归模型均通过α=0.01的显著水平的F检验,模型的R2值为0.86-0.97.同时在生产力无法估测的区域,可以使用NDVI有效管理黄河三角洲生态系统,提高其生产力水平.     

Environmental controls of NDVI dynamics in Patagonia based on NOAA-AVHRR satellite data

Abstract. Variation in vegetation in extra-Andean Patagonia (Argentina) was analyzed using spectral data derived from AVHRR/NOAA satellite. The study of seasonal dynamics of the Normalized Difference Vegetation Index (NDVI, i.e. a combined index of the reflection in the red and infrared bands) highlighted similarities in functional aspects between regional vegetation units which are dissimilar in a geographical, physiognomical and/or floristical way, and also suggested that gross primary production is correlated with mean annual rainfall. The first axis in a Principal Component Analysis of NDVI data was correlated (r² = 0.90) with NDVI as integrated for the study period. The second axis was correlated (r² = 0.50) with the differences in NDVI during the growing season, reflecting seasonality. Mean annual rainfall accounted for 60% of integrated NDVI variability among vegetation units. Much of the residual variance (62%) was accounted for by the inverse of the distance to the Atlantic Ocean, which is interpreted as an ocean effect on vegetation functioning in the extra-Andean Patagonia.     

MODIS NDVI饱和性对高寒草甸草地生物量遥感估测的影响——以青藏高原东缘为例

自20世纪70年代开始,归一化植被指数(NDVI)在天然草地地上生物量估测研究中得到了广泛应用。然而,NDVI对高密度植被生物量遥感估测存在饱和现象,使草地生物量遥感估测有较大的不确定性。以青藏高原东缘高寒草甸为例,基于比值植被指数(RVI)探讨了NDVI的饱和性,并评估了NDVI饱和性对高寒草甸地上生物量时空动态变化分析的影响。结果表明:(1)虽然基于中分辨率成像光谱仪(MODIS) NDVI构建的草地地上生物量估测模型精度较基于RVI构建的估测模型高,但模型对高寒草地地上生物量(生物量大于2314.627 kg/hm²)灵敏度较RVI估测模型低,即NDVI阈值大于0.73时,估测模型呈现饱和现象(低估了草地地上生物量);(２)结合RVI 和 NDVI 的相关关系,对饱和部分NDVI 遥感植被指数进行校正,校正后最优地上生物量遥感估测模型为线性模型(y=5908.5x-2198.9,R=0.6190,RMSE=902.41 kg/hm²),较调整前RMSE降低了11.72 kg/hm²;(3)就NDVI饱和性空间分布而言,从全年6月-9月初(全年第161-257天)饱和性呈现先自东南向西北延伸,后自西北向东南消退的变化趋势,平均低估值介于158.45-293.92 kg/hm²之间,最大低估值出现在8月初(全年第225天),超过600 kg/hm²;(4)此外,NDVI饱和性对草地地上生物量年际动态变化趋势分析具有较大的影响,去除饱和性影响后草地地上生物量基本不变的区域减小了21.44%,而年际变化小于-10 kg/hm²和大于30 kg/hm²的区域分别增加了8.48%和16.19%。研究探讨了NDVI饱和性对草地地上生物量遥感估测的影响,以期为精确评估高寒草地地上生物量提供理论依据,同时也为高寒草地资源可持续发展提供科学依据。     

基于时序植被指数的华北地区作物物候期/种植制度的时空格局特征

随着气候变化对农业系统的影响不断加剧,为保障粮食安全,须掌握变化中的自然与人文因素,而农业生态系统中变化最为明显直观的是农作物物候特征,如何提取大区域尺度上农作物物候期以及种植制度的时空格局特征,是评价区域粮食安全的重要因素.基于多时相遥感信息可以有效反映年内/年际农作物物候特征变化的原理,首先利用近10a来的SPOT/VGT-NDVI时间序列数据,在进行数据序列平滑重构处理基础上,提取了华北地区农作物典型物候期的数量分布与空间格局特征;然后,基于上述物候期的分异特性建立了一年一熟和一年二熟等种植制度类型的遥感识别标志;最后,重点分析了上述种植制度的空间格局及其时间波动特征,并利用农业统计资料对提取结果进行了简单验证.分析结果表明,作物物候期特征的数量分布和空间分布在不同生长季均具有显著差异,直接体现了与外界环境条件(诸如区域温度、降水和光照等)的匹配程度以及作物类型自身的生长特征;从主要种植制度空间分布来看,华北地区南部地区农作物类型以夏收作物和二熟秋收作物为主,与之对应的农田种植制度以一年两熟为主;华北地区北部主要为一熟制区域,作物类型以一年一熟秋收作物为主,作物种植制度空间分布随着纬度递减呈现出简单到复杂的总体趋势;从近10a的种植情况来看,一年一熟作物种植面积最大,年际变化幅度亦较大,一年二熟的夏收作物种植比例次之,而年际变幅最小,二熟秋收作物比例最低,其年际变幅居中.研究中亦提出,在进一步加强多时相遥感技术监测大区域农业生态系统动态变化的同时,亦需深入探讨作物物候特征及种植制度变化的驱动因素及其对国家粮食安全的影响.     

基于LSMM和改进的FCM提取城市植被覆盖度——以北京市海淀区为例

植被是城市生态系统的重要组成部分,及时获取植被覆盖信息对城市生态环境监测具有重要意义。利用中分辨率Landsat TM遥感数据,采用线性光谱分解模型(LSMM)开展城市植被覆盖度提取;同时,通过改进训练样本选择方式,在最小噪声变换(MNF)、像元纯净指数分析(PPI)、N维可视化分析基础上得到端元样本,再运用模糊C-均值(FCM)获取植被覆盖度;最后以高分辨率SPOT5遥感数据对两种方式的提取结果进行精度检验。结果显示,基于LSMM和改进的FCM提取的城市植被覆盖度与检验数据相关系数分别为0.8252和0.9381,后者可以较好地处理其他要素的非线性影响,因而具有较高精度。     

Assessing the recent grassland greening trend in a long-term context based on tree-ring analysis: A case study in North China

Records of the Normalized Difference Vegetation Index (NDVI) and of the productivity of grassland are not long enough to reliably capture natural variation of the grassland dynamics. Herein, we compared a 20-year long growing-season NDVI time series of a typical steppe in North China, and the first principal component (PC1) of four tree-ring width chronologies (based on 69 trees from 3 Pinus tabulaeformis sites and 1 Picea meyeri site) with climate data. Both variables are significantly correlated to each other and to April–July rainfall as well as relative air humidity. This is why PC1 was taken as an indicator of greenness of vegetation in a typical steppe since 1850. The recent greening trend may have happened several times in the past as part of the moisture-driven natural variability. Periods of low growing-season NDVI values derived from tree rings were validated by historical documents. In spite of the ecological complexity, tree-ring analysis provides a simple and efficient method to mirror the key characteristics of the underlying ecological process that was primarily controlled by moisture availability. Thus, tree-ring width time series, clearly documenting the signals of environmental influences, conveys invaluable information about the steppe greenness dynamics and enables us to put the recent greening trend in a long-term context.     

Global pattern of NPP to GPP ratio derived from MODIS data: effects of ecosystem type, geographical location and climate

Aim To examine the global pattern of the net primary production (NPP)/gross primary production (GPP) ratio of the Earth's land area along geographical and climatic gradients. Location The global planetary ecosystem. Methods The 4‐year average annual NPP/GPP ratio of the Earth's land area was calculated using 2000–03 Moderate Resolution Imaging Spectroradiometer (MODIS) data. The global pattern of the NPP/GPP ratio was investigated by comparing it among each typical terrestrial ecosystem and plotting it along a geographical and climatic gradient, including latitude, altitude, temperature and precipitation. Results The global terrestrial ecosystem had an average NPP/GPP ratio value of 0.52 with minor variation from 2000 to 2003. However, the NPP/GPP ratio showed considerable spatial variation associated with ecosystem type, geographical location and climate. Densely vegetated ecosystems had a lower NPP/GPP ratio than sparsely vegetated ecosystems. Forest ecosystems had a lower NPP/GPP ratio than shrub and herbaceous ecosystems. Geographically, the NPP/GPP ratio increased with altitude. In the Southern Hemisphere, the NPP/GPP ratio decreased along latitude from 30° to 10° and it exhibited high fluctuation in the Northern Hemisphere. Climatically, the NPP/GPP ratio exhibited a decreasing trend along enhanced precipitation when it was less than 2300 mm year^?1 and a static trend when the annual precipitation was over 2300 mm. The NPP/GPP ratio showed a decreasing trend along temperature when it was between –20 °C and 10 °C, and showed an increasing trend along rising temperature when it was between –10 °C and 20 °C. Within each ecosystem, the NPP/GPP ratio revealed a similar trend to the global trend along temperature and precipitation. Conclusions The NPP/GPP ratio exhibited a pattern depending on the main climatic characteristics such as temperature and precipitation and geographical factors such as latitude and altitude. The findings of this research challenge the widely held assumption that the NPP/GPP ratio is consistent regardless of ecosystem type.     

内蒙古大青山国家级自然保护区植被归一化指数时空变化及其与环境因子的关系

选取2000—2020年MODIS影像的归一化指数(NDVI)数据及同期的气象数据,采用趋势分析、变异系数、相关分析等方法,从海拔、坡度和坡向的角度分析了内蒙古大青山国家级自然保护区生长季NDVI的时空变化特征,并进一步探讨了NDVI时空变化与气候因子的相关性。结果表明：(1)2000—2020年,内蒙古大青山国家级自然保护区植被总体覆盖状况良好且呈增长趋势,增长速率为0.058/10a;(2)保护区NDVI空间分布呈现出西部低、东部高的从西到东逐渐增加的特征。保护区生长季NDVI均值随着海拔的升高而明显增加,随着坡度的增加呈缓慢增加趋势,在不同坡向上,生长季NDVI均值大小依次为阴坡>半阴坡>半阳坡>阳坡;(3)从NDVI变化趋势分析来看,2000—2020年大青山自然保护区植被覆盖改善的面积占总面积的61.75%,其中,显著改善、极显著改善面积分别占总面积的41.13%、20.62%,基本保持不变的面积占总面积的38.17%,退化面积占总面积的0.07%。在空间分布上,NDVI显著、极显著增加的区域主要分布在保护区西部和东部,中部以变化不显著为主。保护区各功能区N...     

汶川地震区灾后植被恢复时空过程及特征——以都江堰龙溪河流域为例

定量评估地震区灾后植被恢复,对于灾区生态系统恢复重建及区域社会经济可持续发展规划具有重要科学意义.以都江堰龙溪河流域为案例区,采用MODIS-NDVI的时间序列数据,确定植被恢复评估的Landsat影像时间,并以Landsat影像定量揭示龙溪河流域植被在“5.12”汶川地震前后的动态变化;进而根据区域水系和地形因子,定量解析并揭示植被覆盖度受损恢复率的时空变化特征.结果表明:研究区植被覆盖受损恢复情况整体较好,但植被覆盖度对地震损害的响应存在滞后现象;受损植被恢复率与河流水系距离、海拔、坡度和坡向存在显著的相关性.本研究结果可为地震灾后植被恢复的决策干预提供技术支撑.     

用MODIS遥感数据监测东亚飞蝗灾害——以河北省南大港为例

东亚飞蝗自20世纪80年代以来在我国再度猖獗危害。本文选择国家一类蝗区河北省南大港农场水库为实验区,以2002年东亚飞蝗（夏蝗）大发生为背景,测定了不同受害程度芦苇的光谱曲线,并用MODIS遥感数据分析蝗灾危害范围和程度。结果表明,健康芦苇（未受害）呈现出典型植被光谱的“峰和谷”特征;而受害芦苇,其红光区处反射率增加,且受害程度越重,增加愈显著,近红外区的反射率则显著降低,且受害程度越重,反射率愈低。比较多时相归一化植被指数（NDVI）受灾前后的变化,NDVI值增加表明未受蝗虫危害,而其下降则表明是受灾区域,结合地面数据,找出了不同危害程度的NDVI临界值;其次根据像元累计法,确定了不同受灾程度的面积。结果显示,NDVI小于0.2156和0.2389分别为严重受灾区和中等受灾区,其发生面积依次为168.74 hm²和337.48 hm²,判对率分别为72.97%和68.35%。MODIS遥感监测蝗灾发生面积（中等受灾及严重受灾）占实际发生面积的82.76%。研究结果为实时、快速、大面积监测蝗虫种群动态奠定了基础,并为合理 、经济地防治蝗灾提供了科学依据。     

基于大气辐射校正的广州市植被覆盖度遥感估算

植被覆盖度是描述生态系统的基本参数,也是进行生态系统健康与安全评价的重要生态参数.基于1990、1995、2000和2005年4个时相的TM遥感数据源,以广州市为研究区域,运用减少大气辐射影响的植被指数计算模型,通过非监督分类及图像空间模型运算,修正了大气辐射校正参数,建立了植被覆盖度与校正植被指数的模型,估算了不同时期内广州市的植被覆盖度.结果显示,广州市植被覆盖度在1990—2000年的10年内持续下降,从2000年开始呈上升趋势,符合广州市的经济发展与环境建设实际.所建立的模型适合于区域植被覆盖度动态变化研究,且在植被覆盖度的动态变化特征研究方面有较大优势,其结果适于进行城市生态环境质量与动态评价.