基于NDVI的中国天然森林植被净第一性生产力模型

根据叶面积指数、归一化植被指数 (N DVI)建立了中国森林植被净第一性生产力 (N PP)模型 :N PP=- 0 .6 394- 6 7.0 6 4ln(1- N DVI)经我国 13组森林植被生产力数据的验证表明 ,该模型的预测结果与实测值相符较好。通过与 Chikugo模型和综合模型 (周广胜等 ,1996 )预测结果的比较 ,该模型在总体上优于 Chikugo模型和综合模型。表明基于 N DVI的净第一性生产力模型对我国森林植被有良好的适应性 。

Examining Forest Net Primary Productivity Dynamics and Driving Forces in Northeastern China During 1982–2010

Forest net primary productivity （NPP） is a key parameter for forest monitoring and management. In this study, monthly and annual forest NPP in the northeastern China from 1982 to 2010 were simulated by using Carnegie-Ames-Stanford Approach （CASA） model with normalized difference vegetation index （NDVI） sequences derived from Advanced Very High Resolution Radiometer （AVHRR） Global Invento y Modeling and Mapping Studies （GIMMS） and Terra Moderate Resolution Imaging Spectroradiometer （MODIS） products. To address the problem of data inconsistency between AVHRR and MODIS data, a per-pixel unary linear regres- sion model based on least ~;quares method was developed to derive the monthly NDVI sequences. Results suggest that estimated forest NPP has mean relative error of 18.97% compared to observed NPP from forest inventory. Forest NPP in the northeastern China in- creased significantly during the twenty-nine years. The results of seasonal dynamic show that more clear increasing trend of forest NPP occurred in spring and awmnn. This study also examined the relationship between forest NPP and its driving forces including the climatic and anthropogenic factors. In spring and winter, temperature played the most pivotal role in forest NPR In autumn, precipitation acted as the most importanl factor affecting forest NPP, while solar radiation played the most important role in the summer. Evaportran- spiration had a close correlation with NPP for coniferous forest, mixed coniferous broadleaved forest, and broadleaved deciduous forest. Spatially, forest NPP in the Da Hinggan Mountains was more sensitive to climatic changes than in the other ecological functional re- gions. In addition to climalie change, the degradation and improvement of forests had important effects on forest NPP. Results in this study are helpful for understanding the regional carbon sequestration and can enrich the cases for the monitoring of vegetation during long time series.

Seasonal Dynamics of Terrestrial Net Primary Production in Response to Climate Changes in China

Study on seasonal responses of terrestrial net primary production (NPP) to climate changes is to help understand feedback between climate systems and terrestrial ecosystems and mechanisms of increased NPP in the northern middle and high latitudes. In this study, time series dataset of normalized difference vegetation index (NDVI) and corresponding ground-based information on vegetation, climate, soil, and solar radiation, together with an ecological process model, were used to explore the seasonal trends of terrestrial NPP and their geographical differences in China from 1982 to 1999. As the results,. seasonal total NPP in China showed a significant increase for all four seasons (spring, summer, autumn and winter) during the past 18 years. The spring NPP indicated the largest increase rate, while the summer NPP was with the largest increase in magnitude. The response of NPP to climate changes varied with different vegetation types. The increased NPP was primarily led by an advanced growing season for broadleaf evergreen forest, needle-leaf evergreen forest, and needle-leaf deciduous forest, whilst that was mainly due to enhanced vegetation activity (amplitude of growth cycle) during growing season for broadleaf deciduous forest, broadleaf and needle-leaf mixed forest, broadleaf trees with groundcover, perennial grasslands, broadleaf shrubs with grasslands, tundra, desert, and cultivation. The regions with the largest increase in spring NPP appeared mainly in eastern China, while the areas with the largest increase in summer NPP occurred in most parts of Northwestern China, Qinghai-Xizang Plateau, Mts. Xiaoxinganling-Changbaishan, Sanjiang Plain, Songliao Plain, Sichuan Basin, Leizhou Peninsula, part of the middle and lower Yangtze River, and southeastern mountainous areas of China. In autumn, the largest NPP increase appeared in Yunnan Plateau-Eastern Xizang and the areas around Hulun Lake. Such different ways of the NPP responses depended on regional climate attributes and their changes.

基于CASA模型的皖江城市带植被净初级生产力时空变化特征研究

运用GIS和RS技术,利用植被、气候和辐射等地面空间数据,基于CASA模型估算2001-2010年之间皖江城市带植被净初级生产力(NPP),并分析其时空变化特征.结果表明:10年之间皖江城市带植被净初级生产力呈减少趋势,其中NPPMAX年均减少速度5.3gC/m2·a,NPPMEAN年均减少率0.513%;10年NPPMAX均值为805.09gC/m2·a,NPPMEAN均值为463.26gC/m2·a;净初级生产力年累计量变化幅度较大,约在30.052-43.483TgC/a之间;年际变化十分明显,最大值出现在2008年,为43.483TgC,最小值在2006年,为30.052TgC,年均减少率0.51%.植被净初级生产力空间格局表现出较大的不均匀性,整体分布状况是以长江为界,长江以南植被净初级生产力较大,但有逐渐变小趋势;长江以北植被净初级生产力较小,却表现出逐渐增加的趋势.

基于像元二分模型的森林郁闭度估测方法

以遥感影像与森林资源一类调查数据为基础,基于归一化植被指数(NDVI)的像元二分模型对密云县森林郁闭度进行遥感估测,模型的纯像元植被指数通过样地数据来确定。经验证,模型估测值与实测值相关系数为0.73,相对误差为14.40%。结果说明,采用像元二分模型与森林资源一类调查数据结合进行森林郁闭度估测,技术路线简单可靠,精度可满足要求,同时能弥补TM影像分辨率的不足,具有一定的推广价值。

多源遥感影像林火信息检测和植被恢复动态监测

以Landsat 5 TM和GF–1 WFV影像为主要数据源,利用归一化植被指数和像元二分模型,结合0.2 m分辨率的航空CCD数据和全球30 m精细地表覆盖产品,建立植被覆盖度的估算模型,利用火烧前后NDVI差值提取了2001—2020年间大兴安岭地区的火灾信息;通过FVC定量分析了林区整体覆盖度变化和影响因素,并利用热点区域植被覆盖度变化对不同林火后植被恢复力进行了分析和研究。结果表明:以NDVI值为参数,运用基于像元二分模型的植被覆盖度遥感估算方法技术路线简单、可操作性强,适用于不同分辨率的遥感数据;dNDVI可以对过火区信息进行有效分离;研究区整体FVC较高,但频发的火灾是影响研究区FVC分布状况及其动态变化的主要因素;不同程度过火区的FVC恢复效果不同,小范围过火区的FVC可以恢复到原始状态,中等范围过火区的FVC经过长时间的自然恢复与原始FVC仍有一定差距,而对于大范围,尤其是特大范围的过火区经过长时间恢复虽然FVC会增加,但和原始FVC相比相差甚远。因此,火灾干扰对森林生态系统破坏性较强,受火灾干扰后森林恢复时间较长且其林分组成与物种难以恢复至原型。

基于遥感的四面山林区植被覆盖度动态监测

为了解重庆市四面山林区植被覆盖度的变化情况,先利用卫星遥感分析计算归一化植被指数(NDVI),再运用混合像元分解模型对1995,2001年及2007年三景Landsat 5 TM影像进行处理。最后应用ENVI软件对三景影像像元进行统计分析,得出了3个时期林区植被覆盖变化情况及相应动态变化驱动因子。结果表明,自四面山林区成为国家AAAA级风景区以来,植被覆盖度先呈增加趋势,然后稳定在一个相对较高水平,植被覆盖度变化主要与林区的森林保护、旅游开发及水利工程建设等因素有关。

中国植被活动变化的主导因素

利用GIMMS-NDVI3g、MOD13A2、气温、降水、辐射和DMSP夜间灯光数据集分析1992—2020年中国归一化植被指数(NDVI)时空变化特征,并借助随机森林算法模型在栅格尺度上确定其变化主导因素.结果显示:1992—2020年,中国NDVI均值范围为0~0.90,华北平原、长江中下游平原、东北平原、四川盆地、东南丘陵和云贵高原地区为高值区,均值约为0.60,西北和青藏高原地区较低,约为0.18;中国NDVI总体呈上升的趋势,黄土高原地区和南方地区增长趋势较为明显,而新疆西北部、青藏高原东南部、横断山脉地区以及中国东部的黑龙江、吉林、辽宁、江苏、广东、台湾地区和海南等一些城市化进程较快的地区则呈现出明显的下降趋势.气温和降水是影响中国NDVI变化的主导因素.气温影响的面积约为中国总面积的35.2%,主要分布在青藏和云贵高原地区,西藏和云南部分地区气温与NDVI呈显著的负相关;降水仅次于气温,所占面积约为34.3%,主要分布在西北、东北及华南等地区,其中西北地区NDVI与降水呈显著的正相关,东北和华南地区则表现出显著的负相关;辐射主导区所占面积约为27.1%,主要分布在黄淮海平原、长江中下游平原以及四川盆地,与NDVI呈显著的正相关;人类活动主导的区域所占面积约为2.7%,主要集中分布在黄土高原和东部经济较为发达的地区,黄土高原地区与NDVI呈显著正相关,而山东、河北和东北一带则表现出显著负相关性.考虑人类活动(农业、城市化和生态修复等)影响的植被活动分析可为未来生态碳精准管理提供科学支持.

中国潜在植被NPP的空间分布模拟

在对1980年以来气候要素进行空间化的基础上,利用分类回归树模型CART计算中国的潜在归一化植被指数(NDVI),采用改进的光能利用率模型(CASA)和潜在NDVI数据对中国的潜在植被净初级生产力(NPP)进行模拟。结果表明:中国潜在NDVI和潜在NPP均呈现出南高北低、东高西低的格局,低值多分布在沙漠、戈壁等干旱地带,高值多出现在低、中山平原区;400 mm等降水量线是潜在NDVI和潜在NPP高值与低值的分界线;全国潜在NDVI和潜在NPP的平均值分别为0.396和319.31 g C·m-2;夏季潜在NPP的平均值最大,其次是春季,冬季最小;依据潜在NPP与2015年现实NPP的差异,可将中国植被恢复区划分为西部高潜力区、北部低潜力区和南部非潜力区3部分;潜在NDVI和潜在NPP的空间模拟可以将人类活动对自然生态系统的直接影响与气候变化的影响分离,量化了外界压力下真实的生态状况和潜在生态状况的差异,为制定差别化的生态恢复对策提供了科学依据。