天津盘山风景名胜区植被覆盖状况

以天津国家级盘山风景名胜区为研究区,利用2004-2007年覆盖天津国家级盘山风景区的中巴资源卫星数据,用主成分变换方法,对原始CCD影像进行提取,与归一化植被指数(NDVI)相结合,进行土地利用/土地覆盖(LULC)的提取。通过研究发现,2007年6月项目区植被面积为85 km2,9月为97 km2,与2004、2005年同期植被面积相比均有较大变化。     

1982—2006年中国半干旱、干旱区气候与植被覆盖的时空变化

利用1982-2006年英国CRU(Climatic Research Unit)全球气温降水数据和NOAA/NASA归一化植被指数(theNormalized Difference Vegetation Index,NDVI)数据,分析了中国内陆半干旱和干旱区的气候、植被覆盖的时空变化。结果表明,虽然中国内陆半干旱和干旱区的部分区域降水减少,但整体上向暖湿化发展。在暖湿化背景下,中国内陆半干旱和干旱区的植被总体以改善为主(>1%.(10a)-1),特别是新疆西北部和青海东南部;但局部有微弱的减少趋势[(0~-1)%.(10a)-1],如新疆南部和东部、甘肃西北部。最后,以乌鲁木齐为例,分析发现气温增加导致植被生长季延长和降水的增加,使得过去25年乌鲁木齐的植被覆盖有明显的改善。     

1982—2006年京津冀地区植被时空变化及其与降水和地面气温的联系

利用NOAA/AVHRR归一化植被指数（Normalized difference vegetation index,NDVI）,分析过去25年（1982—2006年）京津冀地区生长季（4—10月）植被覆盖时空变化、趋势及其与降水和地面气温的联系。经验正交函数展开（EOF）、奇异值分解（SVD）及相关分析,结果表明：过去25年京津冀地区植被总体呈增加趋势,其中,河北中部地区增长速率超过3%/10 a。植被覆盖年际变化与气温变化呈正相关,但与降水变化的正相关更加显著。1989年和1999—2002年的干旱导致当年NDVI显著减少,而1990、1998年和2003—2005年降水增加使得研究区NDVI明显增加。     

气候因子与植被的时滞相关分析——以广西为例

广西地区地下河发育,地表水缺乏,生态系统脆弱、抗干扰能力低,灾害频繁,森林生态系统严重退化,石漠化程度加剧,属于生态脆弱区域,而植被变化是生态系统对气候变化响应的指示器,其变化研究对该地区生态环境建设具有重要意义。文章基于1999--2010年气温与降水数据和GIMMS．NDVI（GlaobalInventoryModellingandMappingMtudies-NormalDifferenceVegetionIndex）数据集,研究近12年来广西地区植被覆盖时空特征。通过时滞相关分析法,分析研究区不同植被类型受气温和降水的影响,即植被NDVI对气温和降水的响应程度。结果表明,（1）植被NDVI与温度的时滞相关程度强于降水,而响应时间刚好相反,植被NDVI对降水的响应比对温度的响应程度要快。（2）植被NDvI与降水的时滞相关规律呈桂南较弱—桂中较强—桂北较弱,但响应时间刚好相反,即桂南较快一桂中较慢—桂北较快。（3）植被NDvI与温度的时滞相关性变化规律呈由南向北递减,响应时间由南向北变快。（4）植被NDVI与气候因子时滞相关越强,响应的时间就越迟缓,反之越快。（5）不同的植被类型对水热条件响应程度不同,与水热条件时滞相关越强的植被则滞后时间相对越久。     

Some approaches to the construction of a sustainable development index for the Philippines

Principal Component Analysis (PCA) is a convenient tool used in aggregating the indicators of sustainable development and providing indices where different weights are assigned to the various indicators. There are, however, problems in interpreting of indices, especially if time series data are used. This study explores the feasibility of applying recent developments in PCA of time series using Philippine data. We present the comparative advantages of SPCA (Sparse Principal Component Analysis) relative to averaging of an adequacy/inadequacy index and PCA in index construction from various indicators of sustainable development in the Philippines in terms of usefulness and validity of indices being developed. SPCA can attain sparse and non-overlapping loadings without losing a large amount of explained variance compared to PCA. Because of the non-overlapping contribution of variables in SPCA components, indices can have clear and mutually exclusive meanings, facilitating interpretation. Even with a more complicated algorithm, reduced dimensions and simpler interpretation of indices justify the advantages of SPCA over PCA in index construction. The indices are interpreted in terms of the milestone of sustainability in the Philippines. The resulting indices provide an adequate summary of the sustainable indicators and evidence of the importance of leadership and political will in sustainable development.     

A remote sensing-based primary production model for grassland biomes

That data from polar orbiting satellites have detected a widespread increase in photosynthetic activity over the last 20 years in the grasslands of the Sahel is justifies investigating its role in the tropical carbon cycle. But this task is undermined because ground data that are generally used to support the use of primary production models elsewhere are lacking. In this paper, we profile a Light Use Efficiency (LUE) model of primary production parameterised with satellite information, and test it for the West African Sahel; solar radiation is absorbed by plants to provide energy for photosynthesis, while moisture shortfalls control the efficiency of light usage. In particular, we show how an economical use of existing, yet meagre data sets can be used to circumvent nominal, yet untenable approaches for achieving this for the region. Specifically, we use a cloudiness layer provided with the NOAA/NASA 8 km Pathfinder Land data archive (PAL) data set to derive solar radiation (and other energy balance terms) required to implement the model (monthly time-step). Of particular note, we index growth efficiency via transpiration by subsuming rangeland-yield formulations into our model. This is important for partially vegetated landscapes where the fate of rainfall is controlled by relative vegetation cover. We accomplish this by using PAL-derived Normalised Difference Vegetation Index (NDVI) to partition the landscape into fractional vegetation cover. A bare soil evaporation model that feeds into bucket model is then applied, thereafter deriving actual transpiration (quasi-daily time-step). We forgo a formal validation of the model due to problems of spatial scale and data limitations. Instead, we generate maps showing model robustness via Monte Carlo simulation. The precision of our Gross Primary Production (GPP) estimates is acceptable, but falls off rapidly for the northern fringes of the Sahel. We also map the locations where errors in the driving variables are mostly responsible for the bulk of uncertainty in predicted GPP, in this case the water stress factor and the NDVI. Comparisons with an independent model of primary production, CENTURY, are relatively poor, yet favourable comparisons are made with previous primary production estimates found for the region in the literature. A spatially exhaustive evaluation of our GPP map is carried out by regressing randomly sampled observations against integrated NDVI, a method traditionally used to quantify absolute amounts of primary production. Our model can be used to quantify stocks and flows of carbon in grasslands over the recent historical period.     

榆林地区植被时空分异特征及其影响因素研究

植被作为反映陆地生态系统和气候的重要指标,对研究全球或区域生态环境变化具有重要作用.以地处黄土高原生态脆弱区的榆林市为研究区,基于地理探测器模型,选取坡向、坡度、气温、降水和土壤类型5类自然因子,土地利用类型、人口密度和GDP 3类人文因子,分析榆林地区植被空间分异特征及其驱动力,并揭示了促进植被生长影响因子的最适宜特...     

基于SPOT—VGT的黄河流域植被覆盖时空演变

植被是土地覆盖中的最主要部分,是连接土壤、大气和生物等要素的自然“纽带”。植被覆盖动态变化对全球能量循环和物质循环具有重要影响,是全球变化研究的重要内容之一。黄河流域作为我国重要的粮食生产基地,其环境变化直接影响到流域经济的可持续发展。为了快速准确地提取地表植被状况,了解黄河流域生态环境,利用1998—2011年的SPOT-VGT遥感数据,结合地理信息技术,采用均值法和趋势分析法对黄河流域植被NDVI时空分布特征和变化趋势进行了动态监测。结果表明,（1）黄河流域14年NDVI均值的空间分布整体特征是东南部平原、盆地和西部山地植被状况要好于北部地区。其次,黄河流域属于干旱半干旱地区,植被发育主要依赖于水文条件,所以沿黄河干流和支流区域也具有较高的植被NDVI值。（2）黄河流域植被NDVl年均值近14年间整体呈缓慢增长趋势,1998--2000年呈现急剧减少态势,2001--2003年出现了较为快速的增长,2004--2011年又出现了较长时间的连续增长过程。（3）黄河流域植被NDVI基本不变的区域约占研究区总面积的71．13％;植被NDVI轻微改善的区域约占流域总面积的27．30％,且主要分布于流域东南部的盆地、平原和西部的山地、丘陵地区,植被NDVI退化的区域面积约占流域总面积的0．98％。黄河流域自1998年以来,植被NDVI整体在不断提高,生态环境在不断改善。     

A review of prehistoric and early historic mainland salt marsh vegetation in the northern-Netherlands based on the analysis of plant macrofossils

The article presents an overview of archaeobotanical research on artificial dwelling mounds, so-called ‘terps’, in the northern-Netherlands. A total of 40 studies carried out over the past 40 years is evaluated. The vegetation diversity in the area as well as the differences with the present marsh are studied. Seriation, Principal Component Analysis and Sørensen similarity indices are used to assess the diversity of both individual samples and sites. For comparison with the present marshes, an index based on the TMAP vegetation typology was defined. Based on these methods, a selection of the individual samples was analyzed phytosociologically. It is found that all samples represent a mixture of vegetation types, but that the salt marsh species are a constant factor. The variation in the sample composition is not related to their dating, except for some of the latest samples that reflect the earliest endikements. Great similarity to the present marshes is found, but the analysis also testifies of a landscape profoundly disturbed by human activities throughout history.     

植被覆盖度与沙尘暴形成条件分析

以归一化差值植被指数（Normalized Difference Vegetation Index,NDVI）为指标分析了我国1981年到1998年期间植被覆盖变化情况,给出了植被急剧减少产生新沙源的实例。通过对1998年4月强沙尘暴的分析,指出影响沙尘暴产生和运移的因素除了地形、风速、风向、大气稳定度外,当地植被覆盖和土壤因素也是关键因素之一。并通过对植被覆盖度（NDVI）与浮尘指数（Aerosol Index）进行定量分析,发现二者之间存在明显的负相关关系,表明植被的存在可以从一定程度上抑制浮尘现象的产生。因此,在沙尘运移路径上,采取封山封荒,植树种草,增加植被覆盖度以固结当地土壤和泥沙的措施,可以在一定程度上抑制沙尘暴灾害的发生。     

Satellite detection of bird communities in tropical countryside.

The future of biodiversity hinges partly on realizing the potentially high conservation value of human-dominated countryside. The characteristics of the countryside that promote biodiversity preservation remain poorly understood, however, particularly at the fine scales at which individual farmers tend to make land use decisions. To address this problem, we explored the use of a rapid remote sensing method for estimating bird community composition in tropical countryside, using a two-step process. First, we asked how fine-grained variation in land cover affected community composition. Second, we determined whether the observed changes in community composition correlated with three easily accessible remote sensing metrics (wetness, greenness, and brightness), derived from performing a tasseled-cap transformation on a Landsat Enhanced Thematic Mapper Plus image. As a comparison, we also examined whether the most commonly used remote sensing indicator in ecology, the Normalized Difference Vegetation Index (NDVI), correlated with community composition. We worked within an agricultural landscape in southern Costa Rica, where the land comprised a complex and highly heterogeneous mosaic of remnant native vegetation, pasture, coffee cultivation, and other crops. In this region, we selected 12 study sites (each < 60 ha) that encompassed the range of available land cover possibilities in the countryside. Within each site, we surveyed bird communities within all major land cover types, and we conducted detailed field mapping of land cover. We found that the number of forest-affiliated species increased with forest cover and decreased with residential area across sites. Conversely, the number of agriculture-affiliated species using forest increased with land area devoted to agricultural and residential uses. Interestingly, we found that the wetness and brightness metrics predicted the number of forest- and agriculture-affiliated species within a site as well as did detailed field-generated maps of land cover. In contrast, NDVI and the closely correlated greenness metric did not correlate with land cover or with bird communities. Our study shows the strong potential of the tasseled-cap transformation as a tool for assessing the conservation value of countryside for biodiversity.     

Knowing fire incidence through fuel phenology: A remotely sensed approach

Fire is a basic ecological factor that contributes to determine vegetation diversity and dynamics in time and space. Fuel characteristics play an essential role in fire ignition and propagation; at the landscape scale fuel availability and flammability are closely related to the vegetation phenology that directly affects wildfire pattern in time and space. In this view, the annual normalized difference vegetation index (NDVI) profiles derived from high temporal resolution satellites, like SPOT Vegetation, represent an effective tool for monitoring the coarse-scale vegetation seasonal timing. The objective of this study thus consists in quantifying the explanatory power of multitemporal NDVI profiles on the fire regime characteristics of the potential natural vegetation (PNV) types of Sardinia (Italy) over a 5-year period (2000-2004). The results obtained show a good association between the NDVI temporal dynamics of the PNV of Sardinia and the corresponding fire regime characteristics, emphasizing the role of the bioclimatic timing of the vegetation in controlling the coarse-scale wildfire spatio-temporal distribution of Sardinia. By providing a sound phytogeographical framework for describing different wildfire regimes, PNV maps can thus be considered helpful cartographic documents for fire management strategies at the landscape scale.     

Variation in vegetation cover and livestock mobility needs in Sahelian West Africa

A new approach was developed to evaluate the implications of the spatiotemporal variability of green vegetation for the dispersion of livestock that is required to access quality forage in semi-arid Africa. Maximum NDVI (Normalized Difference Vegetation Index) at 1 km² resolution was determined for concentric rings (0–31 km radii) around 227 individual sample locations within the study area for 14 dates (between 1 April to 1 November) annually over the 2000–2010 period. A sigmoidal curve was fitted to points within the maximum NDVI × distance radii space to determine the asymptote distance (AD) – the radius at which further dispersion from the sample location does not lead to significant gains in access to green forage. AD was found to: increase with latitude (or increasing aridity); decline as the rainy season proceeds; and show no trend over the 2000–2010 period. These results introduce much-needed empirical data to current debates surrounding the scales of governance to support livestock mobility.     

基于SPOT5影像多辐射校正水平的植被绿量遥感估算

选用南京市SPOT5图像的灰度值(DN)、星上辐射率(SR)、表观反射率(TOA)和地物反射率(PAC)数据,提取了两种植被指数(VI),即归一化植被指数(NDVI)和比值植被指数(RVI),并与地面实测的绿量(LVV)进行相关分析,建立了165个关系模型.结果表明,LVV与VI呈极显著的相关关系,其相关系数多以相对均质植被高于植被总体,基于灰度值高于常用的地物反射率为主.LVV-VI关系模型的R~2均值以多元线性回归模型最高(0.821),指数模型最低(0.536),而1～3次多项式模型均接近0.7.每种植被样方优选出一个模型,即阔叶林LVV-7.802 RVI_(PAC)-2.455(R~2=0.827,RMSE=0.498);针阔叶混交林LVV=-15.421 RVI_(TOA)+26.971 RVI_(DN)-8.261(R~2=0.918,RMSE=0.356);灌木LVV=-342.591 NDVI_(DN)~3-20.553 NDVI_(DN)~2+14.013 NDVI_(DN)+1.509(R~2=0.764,RMSE=0.689);草地LVV=2.934 RVI_(PAC)+2.147 RVI_(TOA)-3.193(R2=0.903,RMSE=0.464);总体植被LVV=1.789RVI_(PAC)-6.814NDVIs+4.258NDVI_(PAC)+12.854 NDVI_(DN)-0.342(R~2=0.810,RMSE=0.638).这些优选模犁的自变量包括了4种辐射校正水平下提取的两种植被指数,显示基于不同辐射校正水平的植被指数在植被LVV遥感反演中具有一定的应用潜力.     

盐池柳杨堡人工封育区植被特征研究

封育措施是一种主要的草场恢复和重建的措施。在宁夏自治区盐池县人工封育区采用样方调查法对不同封育年限和不同封育措施下封育区植被的群落结构和生物量进行调查分析。结果表明：封育可以提高生物多样性,使群落的组成趋于稳定。但是长期封育并不利于植被恢复,边缘区和外围区分别在封育后的第五年和第四年生物多样性指数达到最大,边缘区的丰富度指数（R1）和综合多样性指数D、H分别为22、2.26、6.18,外围区的分别达到13、1.67、3.24,然后逐年减小。在不同封育措施下,生物多样性指数核心区最大,说明封育是有效的植被恢复措施。植被盖度和生物量都是外围区最大,说明对草场进行适当的利用是有利于植被恢复的。带状翻耕对植被的恢复作用并不明显,建议进行适当的放牧或刈割。     

Temporal-spatial dynamics of vegetation variation on non-point source nutrient pollution

The temporal-spatial interaction of land cover and non-point source (NPS) nutrient pollution were analyzed with the Soil and Water Assessment Tool (SWAT) to simulate the temporal-spatial features of NPS nutrient loading in the upper stream of the Yellow River catchment. The corresponding land cover data variance was expressed by the normalized difference vegetation index (NDVI) that was calculated from MODIS images. It was noted that the temporal variation of land cover NDVI was significantly correlated with NPS nutrient loading. The regression analysis indicated that vegetation not only detained NPS nutrient pollution transportation, but also contributed to sustainable loading. The temporal analysis also confirmed that regional NDVI was an effective index for monthly assessment of NPS nitrogen and phosphorus loading. The spatial variations of NPS nutrient loading can be classified with land cover status. The high loadings of NPS nitrogen in high NDVI subbasins indicated that forestry and farmland are the main critical loss areas. Farmland contributed sustainable soluble N, but the loading of soluble and organic N from grassland subbasins was much lower. Most P loading came from the areas covered with dense grassland and forestry, which cannot directly discharge to local water bodies. However, some NPS phosphorus from suburban farmland can directly discharge into adjacent water bodies. The interactions among nutrient loading, NDVI, and slope were also analyzed. This study confirmed that the integration of NPS modeling, geographic information systems, and remote sensing is needed to understand the interactive dynamics of NPS nutrient loading. Understanding the temporal-spatial variation of NPS nutrients and their correlations with land cover will help NPS pollution prevention and water quality management efforts. Therefore, the proposed method for evaluating NPS nutrient loading by land cover NDVI can be an effective tool for pollution evaluation and watersheds planning.     

Thirty years of vegetation change in the coastal Santa Cruz Mountains of Northern California detected using landsat satellite image analysis

The Santa Cruz Mountains is a coastal landscape with a history of extensive forest logging, and a future with projected climate warming that may alter vegetation cover and surface water runoff in new ways. Results from Landsat satellite image time-series analysis since 1983 of this study area showed gradual, statistically significant increases in the normalized difference vegetation index (NDVI) in more than 90 % of the (predominantly second-growth) evergreen forest locations sampled. The cumulative distribution of NDVI values in 2013 was significantly different and higher overall from the cumulative distribution of NDVI values in 1983. The extreme drought year of 2013 (and other previous years of low precipitation) did not affect average NDVI growth rates in most drainage basins of the study area, with the exception of four relatively small basins that had less than 30 % forested land cover. Notably different patterns of NDVI change were detected in areas burned by wildfires in recent years. Within the perimeters of the 2008 Summit Fire and the 2009 Lockheed Fire, NDVI showed notable declines from pre-fire levels to those calculated in 2013 Landsat imagery. In contrast to these recent fires, the burned area from the 1985 Lexington Fire showed the highest rate of NDVI increase (over 27 years of regrowth) of any relatively large contiguous area within the Santa Cruz Mountains.     

南疆西部不同植被类型NDVI对风沙灾害的响应

不同植被类型对风沙灾害的响应研究有助于风沙灾害的遥感监测评估和防灾减灾工作。采用传统统计学和空间自相关方法,利用MODIS的每日反射率和土地类型产品,分析了风沙灾害后南疆西部不同植被类型NDVI的变化规律及其空间分布特征。结果表明：风沙灾害后,研究区不同植被类型NDVI的差异在增大,NDVI变化值在一0．3865~0．4148之间,NDVI减小的面积占整个研究区面积的54．98％,变异系数增大值在2．44％～36．75％之间;受到风沙灾害的影响,研究区植被NDVI全局Moran’SI系数从0．7982减小到0．6786,但在空间上仍存在显著的正相关性,具有显著的空间集聚特征;由NDVI差值的局部空间自相关指标集聚图以及不同植被类型NDVI差值的空间关联区域面积百分比,可以发现落叶针叶林和裸地或低植被覆盖地受风沙灾害的影响较小,郁闭灌丛和作物受风沙灾害的影响较大。上述关于风沙灾害后南疆西部不同植被类型的变化及其空间格局的研究结果,不仅证明了防护林的风沙阻挡作用,也可以为风沙灾害的防治工作提供参考依据。     

Assessing the effectiveness of specially protected areas for conservation of Antarctica's botanical diversity

Vegetation is sparsely distributed over Antarctica's ice‐free ground, and distinct plant communities are present in each of the continent's 15 recently identified Antarctic Conservation Biogeographic Regions (ACBRs). With rapidly increasing human activity in Antarctica, terrestrial plant communities are at risk of damage or destruction by trampling, overland transport, and infrastructure construction and from the impacts of anthropogenically introduced species, as well as uncontrollable pressures such as fur seal (Arctocephalus gazella) activity and climate change. Under the Protocol on Environmental Protection to the Antarctic Treaty, the conservation of plant communities can be enacted and facilitated through the designation of Antarctic Specially Protected Areas (ASPAs). We examined the distribution within the 15 ACBRs of the 33 ASPAs whose explicit purpose includes protecting macroscopic terrestrial flora. We completed the first survey using normalized difference vegetation index (NDVI) satellite remote sensing to provide baseline data on the extent of vegetation cover in all ASPAs designated for plant protection in Antarctica. Large omissions in the protection of Antarctic botanical diversity were found. There was no protection of plant communities in 6 ACBRs, and in another 6, <0.4% of the ACBR area was included in an ASPA that protected vegetation. Protected vegetation cover within the 33 ASPAs totaled 16.1 km² for the entire Antarctic continent; over half was within a single protected area. Over 96% of the protected vegetation was contained in 2 ACBRs, which together contributed only 7.8% of the continent's ice‐free ground. We conclude that Antarctic botanical diversity is clearly inadequately protected and call for systematic designation of ASPAs protecting plant communities by the Antarctic Treaty Consultative Parties, the members of the governing body of the continent.