基于Hyperion的锡林郭勒草原光合植被、非光合植被覆盖度估算

掌握草原生态系统光合植被覆盖度(fPV)与非光合植被覆盖度(fNPV)时空动态对了解干旱半干旱草原生态系统特征(覆盖状况、火灾负载、载畜量、干扰及恢复等)及进行科学、有效地草地资源管理具有重要的意义。选取锡林郭勒典型草原为试验区,以Hypeiron高光谱数据为数据源,利用NDVI-CAI三元线性混合模型对试验区fPV和fNPV的时空动态分布进行了估算,并对不同端元选择方法(最小包含端元特征法、纯净象元指数法和实测法)对估算结果的影响进行了比较分析。研究结果表明,NDVI-CAI三元线性混合模型是同时估测锡林郭勒草原fPV和fNPV的有效方法,且估算的fPV和fNPV的季节变化与牧草的物候发育特征相吻合。不同端元选择方法对估算精度具有一定的影响,其中基于最小包含端元特征法提取端元进行估算的精度最高,fPV估算的均方根误差RMSE=4.57,估算精度EA=91.2%;fNPV估算的RMSE=5.90,EA=67.91%(样本数N=52)。     

内蒙古不同类型草原光合植被覆盖度对降水变化的响应

植被是影响土壤侵蚀过程的重要因素。论文基于MODIS遥感数据和同期降水数据,用相关和回归分析方法从不同时间尺度揭示了内蒙古草甸草原、典型草原和荒漠草原2002—2016年光合植被覆盖度(Fractional Photosynthetic Vegetation,f_(PV))的变化规律及其对降水变化的响应。结果表明:(1)2002—2016年间多年平均f_(PV)草甸草原为46.5%,典型草原和荒漠草原分别为36.3%和22.4%;草甸草原f_(PV)随时间变化呈不显著增长趋势(线性变化斜率为0.29%/a),典型草原和荒漠草原f_(PV)呈不显著下降趋势(线性变化斜率分别为-0.04%/a和-0.21%/a);相应时期年降水量随时间变化都呈现不显著波动上升趋势。(2)内蒙古草原的月植被覆盖度对月降水量存在明显的1—2个月滞后效应和显著的累积效应,且表现出草原类型越干旱,滞后效应越明显的特征;相比草甸草原和典型草原,荒漠草原植被对降水量变化更加敏感。(3)内蒙古3类草原年平均植被覆盖度对降水量的响应,均表现出年、季、月尺度上分别受当年降水量、生长季降水量以及6、7、8月份降水量的显著影响的特征;3类草原年植被覆盖度与生长季降水线性拟合结果都较好,内蒙古3种草原类型的年植被覆盖度与降水量具有的强相关性,可为区域土壤侵蚀动态评价提供科学依据。     

不同生活型植物非光合部分反射光谱和盖度的关系

非光合植被(Non-photosynthetic Vegetation, NPV)既是陆地生态系统重要组成部分,也是全球C、N平衡分析中关键节点,其盖度是判断我国北方沙尘源区风沙活动强弱的重要指征。基于ASD光谱仪(Analytical Spectral Devices)所测地面高光谱数据对鄂尔多斯沙地草场不同生活型植物(草本、半灌木和灌木)NPV光谱特征进行了分析,构建了干枯燃料指数(Dead Fuel Index, DFI)、纤维素吸收指数(Cellulose Absorption Index, CAI)和NPV盖度(f_NPV)应用模型,并使用MCD43A4数据在不同草原区进行了验证。结果表明:(1)草本、半灌木、灌木和总体混合NPV光谱反射率具有相似变化趋势,但反射值存在显著差异。(2)DFI和CAI、CAI和f_NPV、DFI和f_NPV均呈显著正相关关系(P<0.001),DFI可以代替CAI进行f_NPV的估算。(3)不同草原区f_NPV存在异质性,草甸草原、典型草原...     

黄土高原典型干旱区退耕还林后植被覆盖变化研究

以MODIS NDVI 为数据源, 选择退耕还林意义最为典型的甘肃省会宁地区为示范区, 应用像元二分模型计算该地区2000-2010 年11 a 的植被覆盖度, 分析了退耕还林后该地区植被覆盖度动态变化特征及趋势。结果表明: 从实施退耕还林还草政策以来, 会宁县植被覆盖度虽然年际间有较大波动, 但总体上呈微弱的增加趋势, 并以低植被覆盖度类型和中低植被覆盖度类型为主, 11 a 监测期植被覆盖度增加的面积达到70.60%, 且植被覆盖度主要向10%-45%范围内转化。空间上植被覆盖度差异较大, 南部高、中部和北部显著偏低。人类活动与气候变化是影响植被覆盖度变化的主要因素。     

乌梁素海湿地芦苇最大羧化速率的高光谱遥感

湿地植被生产力和固碳潜力的研究是全球碳循环和全球变化的热点研究问题。湿地植被的光合能力能够指示其生长的健康状态。最大羧化速率是重要的植被光合参数之一,对精确模拟湿地植被光合作用和气体交换模型中的固碳过程具有重要的作用。以内蒙古乌梁素海湖泊湿地为研究区,进行了芦苇叶片光合参数和光谱的测量。芦苇叶片最大羧化速率(V_(cmax))数值是基于Farquhar光合作用模型,从光合测量获取的A-C_i曲线计算并校正到25℃得到的。分别基于bootstrap PLSR模型、单波段和高光谱植被指数(包括简单比值指数SR和归一化差值指数ND),构建湿地芦苇叶片最大羧化速率(V_(cmax))估算模型。基于高光谱遥感图像HJ-1A HSI,采用ND高光谱指数中具有较高V_(cmax)估算精度的入选波段702和756 nm,获取研究区湿地芦苇最大羧化速率空间分布图。研究结果表明,湿地植被光谱特征和高光谱植被指数,可用于估算湿地芦苇V_(cmax),其中最高精度产生于基于bootstrap PLSR模型的建模方法(R~2=0.87,RMSECV=3.90,RPD=2.72),ND高光谱指数的V_(cmax)估算精度高于SR高光谱指数的估算精度;从获取的V_(cmax)空间分布图上提取估算值,其与测量值对比,存在较好的相关性(R~2=0.80,RMSE=4.74)。     

黄土高原近10年植被覆盖的动态变化及驱动力

基于Timesat的非对称高斯函数(AG)拟合法重建MODIS-NDVI数据,利用像元二分模型估算了黄土高原近10年的植被覆盖度(VC),并分析了年植被覆盖度的变化趋势和其与降水温度的相关性。研究结果表明:黄土高原植被覆盖度总体上呈现东南高西北低、由东南向西北递减的特征。其中森林生态系统平均覆盖度最高,灌木、草地生态系统次之,荒漠生态系统最低,空间差异明显。2010年森林生态系统植被覆盖度达到81.6%,主要包括太行山、吕梁山和秦岭地区。暖温带森林区植被组成以落叶阔叶林为主,覆盖度常年较高,为80%以上。西北部温带草原区,植被覆盖度达到38.8%。温带草地主要依水分梯度,由东南到西北分布有以旱生性多年生草本植物为主的典型草原,植被覆盖度呈现相应的递减趋势。黄土高原总面积78.6%的地区年植被覆盖度呈增加趋势;而占总面积19.4%的地区年植被覆盖度呈下降趋势。在空间分布上,植被覆盖度显著增加的区域主要分布在榆林至延安周边地区和秦岭一带;植被覆盖度显著减少区域沿兰州至银川呈条带状分布。     

基于无人机和决策树算法的榆树疏林草原植被类型划分和覆盖度生长季动态估计

植被覆盖度是评估生态环境质量与植被生长的重要指标,也是全球众多陆面过程模型和生态系统模型中表达植被动态的重要参数。卫星遥感和地面测量是估算植被覆盖度的常见方法。然而,如何精确估计榆树疏林草原上木本、草本不同类型植被的覆盖度仍然具有挑战性。无人机飞行系统有效的补充了区域尺度低空间分辨率的卫星遥感影像与样地尺度实地调查之间的缺口,为精确的监测、评估疏林草原的植被动态提供了新途径。利用无人机监测平台和决策树算法构建了一套快速、准确、自动获取景观尺度植被类型和估算植被覆盖度的自动化工具,以浑善达克沙地榆树疏林草原为对象,应用无人机监测平台对榆树疏林草原长期定位监测大样地2017年生长季植被状况进行7次监测。结果表明:1)无人机植被监测平台数据飞行高度100 m,获取的样地数字正射影像空间分辨率为2.67 cm/像元,远高于高分卫星影像,利用决策树算法基于数字正射影像可以实现自动划分榆树疏林草原木本和草本植被类型和估算植被覆盖度; 2)生长季内榆树疏林草原木本植被覆盖度为(19±2)%,草本植被覆盖度为(50±8)%,植被总覆盖度为(69±9)%,相对于木本植被,草本植被生长季内盖度变幅较大; 3)在整个生长季中,木本植被和草本植被对植被总覆盖度的平均贡献率分别为27%和73%,草本植被对植被总盖度的贡献远大于木本植被,榆树疏林草原植被的盖度主要受草本植被的影响。本研究证明无人机监测平台是一种高效、准确的植被监测工具,结合机器学习算法,实现了景观尺度植被类型的自动划分和不同类型植被覆盖度快速获取;在浑善达克沙地榆树疏林草原地区首次获取了木本植被和草本植被覆盖度的生长季动态。该平台未来可应用于各种类型生态系统植被类型划分、监测和评估。     

连江流域植被的空间分布特征

利用1973、1988和2006年3期遥感数据,以归一化植被指数像元二分法为植被覆盖度估算模型计算连江流域不同时期的植被覆盖度,然后运用DEM地形高程数据及回归分析法和相关分析法,分析海拔高度、坡向、坡度与植被覆盖度的关系.结果表明:(1)高程200～1600 m、坡向90°～160°和坡度10°～30°范围内,因人类活动干扰较少和温度、水分等条件较好,植被覆盖度高、质量较好.(2)植被覆盖度的空间分布特征主要受高程影响,其次为坡向,与坡度的相关性较小.(3)近33年连江流域植被覆盖度以剧烈增加区和稳定区为主,多分布于林场、自然保护区和人造林区等植被生境优越点.     

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.     

基于修正的亚像元模型的植被覆盖度估算

植被覆盖度是陆地生态过程模型、气象和气候模型的一项重要参数.通过消除植被类型分类精度以及遥感影像噪声带来的误差,结合实际测量值确定了归一化植被指数(NDVI)的最大值和最小值,修正了亚像元模型,并通过计算北京市植被覆盖度对模型进行了验证. 结果表明: 修正后模型的模拟值与实测值非常接近,尤其是对植被类型一致但密度有不同变化的草本植被, 但对乔木植被覆盖度的估算误差相对较大,这可能与遥感影像分辨率、植被破碎度及采用的混合像元模型有关.     

Measuring and modelling the radiation balance of a heterogeneous shrubland

The accurate quantification of the energy available for sensible and latent heat transfer from plant canopies is essential for the prediction of impacts of climate on vegetation water use and growth. Unlike agricultural fields and extensive forests of more humid zones, vegetation growing in semi‐arid climates is usually sparse creating a heterogeneous surface of shrubs, annuals and bare soil. Under these conditions many of the assumptions of the basic equations used in microclimatology, which assume a uniform vegetated surface, may be violated. It is proposed here that heterogeneous canopies may require a formulation of their energy balance that includes a measure of the canopy complexity in order to both interpret field measurements and be used in predictive models. This paper explores the need for a more complex formulation of the vegetation energy balance through a series of experiments on a sparse clumped shrubland of Retama sphaerocarpa in the Tabernas Desert, Almería, south‐east Spain. These experiments investigated the importance of the radiative properties of each surface on energy balance of soil, annuals and shrubs individually, and the surface as a whole. The study evaluated the use of the fractional vegetative cover (f) and the radiative characteristics of each surface (reflection coefficients and emissivities) for calculating net radiation partitioning between shrubs and bare soil. Results indicated that partitioning of net radiation between components could be accurately calculated from values of fractional vegetative cover, reflection coefficients and emissivities for both bare soil and plant surfaces. A sensitivity analysis showed the importance of specific radiation properties of each surface. Measurements of horizontal long‐wave fluxes between components showed that the location of a plant with respect to other plants made little difference to its long‐wave energy balance. The results also emphasized the importance of soil water content on the energy balance, through its influence on albedo and soil heat storage. This was particularly true when measurements of soil heat flux were used to measure the available energy for soil under shrubs and bare soil because of strong hysteresis cycles. These cycles were larger in the bare soil than in the substrate under shrubs.     

太行山南麓山区不同植被恢复类型土壤理化和细根结构特征

在干旱半干旱地区,由于水分匮乏、土壤贫瘠等因素,将形成一定的裸地斑块,而这些斑块极易造成水土流失、滑坡等灾害,而具有不同植被覆盖的林地则能有效的保持水土。为完善干旱半干旱地区不同植被恢复类型下土壤理化和细根特征,选择太行山南麓山区具有代表性的裸露地、草地、荆条地、侧柏地、栓皮地和刺槐地等植被恢复类型,比较了各植被恢复类型下的土壤养分、粒径及细根状况等差异。研究表明:1)相对于裸露地,有植被覆盖的植被恢复类型拥有良好的土壤及细根状况。2)在不同植被类型中,刺槐林的有效氮转化速率较高;侧柏林有较高的细根参数;草地能够提高土壤中可吸收的磷组分。3)林地类型和土层均对土壤中含水率、黏粒、细根生物量和比根长产生极显著影响(P0.001)。4)各植被类型的对于土壤斑块的利用能力不同;不同植被类型中土壤及细根状况变化量具有一定的相似性,研究为生态恢复中植被类型的合理布局提供了新思路。     

Desertification alters regional ecosystem–climate interactions

We studied the spatial patterns and temporal dynamics of vegetation structural responses to precipitation variation in grassland, transitional, and desertified‐shrubland ecosystems in an 800 km² region of Northern Chihuahua, USA. Airborne high‐fidelity imaging spectroscopy data collected from 1997 to 2001 provided spatially detailed measurements of photosynthetic and senescent canopy cover and bare soil extent. The observations were made following wintertime and summer monsoonal rains, which varied in magnitude by >300% over the study period, allowing an assessment of ecosystem responses to climate variation in the context of desertification. Desertification caused a persistent increase in both photosynthetic vegetation (PV) and bare soil cover, and a lasting decrease in nonphotosynthetic vegetation (NPV). We did not observe a change in the spatial variability of PV cover, but its temporal variation decreased substantially. In contrast, desertification caused the spatial variability of NPV to increase markedly, while its temporal variation did not change. Both the spatial and temporal variation of exposed bare surfaces decreased with desertification. Desertification appeared to be linked to a shift in seasonal precipitation use by vegetation from mainly summer to winter inputs, resulting in an apparent decoupling of vegetation responses to inter‐annual monsoonal variation. Higher winter rainfall led to decreased springtime spatial variability in the PV cover of desertified areas. Higher summer rainfall resulted in decreased PV cover variation in grassland, transition and desertified‐shrubland regions. The effects of desertification on NPV dynamics were more than three times greater than on PV or bare soil dynamics. Using remotely sensed PV and NPV as proxies for net primary production (NPP) and litter dynamics, respectively, we estimated that desertification decreases the temporal variability of NPP and increases spatial variation of litter production and loss. Quantitative studies of surface biological materials and ecosystem processes can now be measured with high ‘structural’ detail using imaging spectroscopy and shortwave‐infrared spectral mixture analysis.     

植被恢复对黄土区煤矿排土场土壤团聚体特征的影响

目前关于植被恢复对排土场土壤团聚性的影响还不清楚,以植被恢复下黄土区露天煤矿排土场为研究对象,采用湿筛法测定了排土场土壤水稳性团聚体组成,研究了植被恢复类型(草地、灌木)和排土场地形(平台、边坡)对土壤团聚体特征的影响。结果表明:植被恢复促进了排土场水稳性团聚体的形成,平台0—20 cm土层水稳性大团聚体数量(R_(0.25))、平均重量直径(MWD)和几何平均直径(GMD)分别达到31.1%,0.70 mm和0.26 mm,边坡分别达到13.3%,0.37 mm和0.17 mm,均显著高于裸地,分形维数(D)在平台和边坡分别为2.91和2.96,均显著低于裸地;平台土壤团聚性要好于边坡,草地对于平台土壤团聚结构改良效果较好,而灌木对于边坡改良效果较好;排土场土壤有机碳和粘粒含量均与土壤团聚体指标有显著相关性。植被恢复提高了排土场土壤团聚性,植被恢复类型和地形对排土场土壤团聚体特征有显著影响。     

滩涂湿地入侵种互花米草植被覆盖度的高空间分辨率遥感估算

互花米草是沿海滩涂生态系统的重要入侵物种,其分布状况和覆盖度是湿地生态研究的重要参数和基础。以宁德三沙湾(三都澳)滩涂湿地为研究区,以SPOT6 6 m空间分辨率卫星影像为数据源,对互花米草分布和植被覆盖度进行研究,并与同期10 cm空间分辨率无人机影像进行比较验证。结果表明,影像覆盖区域内互花米草总面积为20.19 km~2,其中蕉城区互花米草分布较广,面积为9.63 km~2,占研究区互花米草总面积的47.70%。互花米草植被覆盖度整体上以40%-60%和60%-80%的中、高覆盖度分布为主,其分布面积分别为5.44 km~2和4.95 km~2,占互花米草总分布面积的26.92%和24.52%,而40%以下的低覆盖度和80%以上较高覆盖度分布相对较少。SPOT6遥感影像估算得到的互花米草植被覆盖度具有较好的精度,与无人机影像值之间的均方根误差RMSE为0.117,线性回归决定系数R~2为0.918,可用于滩涂湿地植被覆盖度分析。     

Satellite-based Studies on Large-Scale Vegetation Changes in China

Remotely-sensed vegetation indices, which indicate the density and photosynthetic capacity of vegetation, have been widely used to monitor vegetation dynamics over broad areas. In this paper, we reviewed satellite-based studies on vegetation cover changes, biomass and productivity variations, phenological dynamics, desertification, and grassland degradation in China that occurred over the past 2–3 decades. Our review shows that the satellite-derived index (Normalized Difference Vegetation Index, NDVI) during growing season and the vegetation net primary productivity in major terrestrial ecosystems (for example forests, grasslands, shrubs, and croplands) have significantly increased, while the number of fresh lakes and vegetation coverage in urban regions have experienced a substantial decline. The start of the growing season continually advanced in China's temperate regions until the 1990s, with a large spatial heterogeneity. We also found that the coverage of sparsely-vegetated areas declined, and the NDVI per unit in vegetated areas increased in arid and semi-arid regions because of increased vegetation activity in grassland and oasis areas. However, these results depend strongly not only on the periods chosen for investigation, but also on factors such as data sources, changes in detection methods, and geospatial heterogeneity. Therefore, we should be cautious when applying remote sensing techniques to monitor vegetation structures, functions, and changes.     

Seasonally different response of photosynthetic activity to daytime and night‐time warming in the Northern Hemisphere

Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night‐time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in the response of NDVI to changes in day‐ vs. night‐time temperatures. For instance, while higher daytime temperature (T_max) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between T_max and NDVI is much larger in spring (41% of area in boreal zone – total area 12.6 × 10⁶ km²) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in T_max, increases in T_max tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night‐time temperature (T_min) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day‐ and night‐time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Understanding the seasonally different responses of vegetation photosynthetic activity to diurnal temperature changes, which have not been captured by current land surface models, is important for improving the performance of next generation regional and global coupled vegetation‐climate models.