Predicting gross primary production from the enhanced vegetation index and photosynthetically active radiation: Evaluation and calibration

The approach of using primarily satellite observations to estimate ecosystem gross primary production (GPP) without resorting to interpolation of many surface observations has recently shown promising results. Previous work has shown that the remote sensing based greenness and radiation (GR) model can give accurate GPP estimates in crops. However, the feasibility of its application and the model calibration to other ecosystems remain unknown. With the enhanced vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) images and the surface based estimates of photosynthetically active radiation (PAR), we provide an analysis of the GR model for estimating monthly GPP using flux measurements at fifteen sites, representing a wide range of ecosystems with various canopy structures and climate characteristics. Results demonstrate that the GR model can provide better estimates of GPP than that of the temperature and greenness (TG) model for the overall data classified as non-forest (NF), deciduous forest (DF) and evergreen forest (EF) sites. Calibration of the GR model is also conducted and has shown reasonable results for all sites with a root mean square error of 47.18 g C/m²/month. Different coefficients acquired for the three plant functional types indicate that there are shifts of importance among various factors that determine the monthly vegetation GPP. The analysis firstly shows the potential use of the GR model in estimating GPP across biomes while it also points to the needs of further considerations in future operational applications.     

Modeling and analysis of effects of precipitation and vegetation coverage on runoff and sediment yield in Jinsha River Basin

This paper focuses on the effects of precipitation and vegetation coverage on runoff and sediment yield in the Jinsha River Basin. Results of regression analysis were taken as input variables to investigate the applicability of the adaptive network-based fuzzy inference system (ANFIS) to simulating annual runoff and sediment yield. Correlation analysis indicates that runoff and sediment yield are positively correlated with the precipitation indices, while negatively correlated with the vegetation indices. Furthermore, the results of stepwise regression show that annual precipitation is the most important factor influencing the variation of runoff, followed by forest coverage, and their contributions to the variation of runoff are 69.8% and 17.3%, respectively. For sediment yield, rainfall erosivity is the most important factor, followed by forest coverage, and their contributions to the variation of sediment yield are 49.3% and 24.2%, respectively. The ANFIS model is of high precision in runoff forecasting, with a relative error of less than 5%, but of poor precision in sediment yield forecasting, indicating that precipitation and vegetation coverage can explain only part of the variation of sediment yield, and that other impact factors, such as human activities, should be sufficiently considered as well.     

POTENTIAL FOR VEGETATION‐BASED RIVER MANAGEMENT IN DRYLAND,SALINE CATCHMENTS

The approaches used to manage rivers have been developed and adapted to many different problems and settings. Because of their relatively low cost, vegetation‐based approaches implemented at the reach, landholder and catchment scales have become the foundation for river management in most landscapes. In many dryland agricultural catchments, secondary (anthropogenic) salinity caused by clearing native vegetation has resulted in rising saline groundwater, streamflow salinity values that exceed seawater and severe the degradation of riparian vegetation communities. The potential effectiveness of vegetation‐based strategies in these landscapes remains largely unknown, yet these strategies are still widely pursued. This study initially investigated the patterns of vegetation recovery and recolonization following a large flood in a saline river that disturbed the system. A conceptual model was developed to describe spatial patterns of where different vegetation types had regrown and recovered in relation to controls exerted by streamflow salinity, surface texture characteristics, topography and reach morphology. Using this model, vegetation‐based river management options for different reaches were developed, and their potential effectiveness in stabilizing reaches was investigated using a 1‐D hydraulic modelling approach. This study finds that in a dryland catchment with high stream salinity (20 000–93 000 mg L^?1), there is still a strong potential for successful vegetation‐based management, but only in selected reaches. Results showed that changes in stream power and channel velocity were not associated with the areas of most severe vegetation degradation. Rather, there is a complex interplay between channel morphology, channel slope and places of potential vegetation growth within a reach. This paper outlines an approach to evaluate the potential success of vegetation‐based river management in saline landscapes. It identifies the need to prioritize investment based on the following: an understanding of factors controlling revegetation potential, the likely impact of revegetation in mitigating adverse channel changes and the proximity of reaches to high‐value infrastructure and biodiversity assets. Copyright © 2011 John Wiley & Sons, Ltd.     

影响岩质路堑边坡表层土稳定性因素的敏感度分析

针对渝怀铁路鱼嘴车站岩质路堑植被边坡,采用直剪切试验获得边坡表层绿色防护层的物理力学参数。在此基础上,选取5个影响边坡表层土稳定性的因素(坡度、土层厚度、重度、粘聚力、内摩擦角),采用数学及数理统计的方法进行敏感度分析,得出各影响因素的敏感度顺序为内摩擦角>坡度>重度>土层厚度>粘聚力,分析表明绿色防护层的内摩擦角是控制其稳定性的主控因素。     

基于温度植被干旱指数的黄河源区土壤表层含水量反演

为了对黄河源区的土壤表层含水量进行反演与时空分析,利用黄河源区2006年第65—321天MODIS温度和植被指数产品数据,计算了温度植被干旱指数(TVDI),构建了不同像元尺度窗口的LST/NDVI斜率与实测表层土壤相对含水量之间的线性关系,比较了不同尺度像元窗口的拟合效果。分析结果表明:9×9像元窗口的拟合效果(回归系数R2为0.65)优于其他像元窗口尺度;季节尺度的拟合精度(回归系数R2为0.76)优于长时间序列的拟合精度;夏季模拟值与实测值的均方根误差为0.09,模拟精度满足实验要求,可用于黄河源区短时间序列的土壤表层含水量反演。     

漓江流域沿岸风光带植被覆盖度的遥感动态监测与估算

以1990、2008年TM影像和2001年ETM＋影像为数据源,研究漓江精华段沿岸风光带植被覆盖度的动态变化规律,采用归一化植被指数（NDVI）像元二分模型,半定量估算了研究区的植被覆盖度,生成了不同时相的植被覆盖度等级图及面积转移矩阵,并结合植被覆盖度的监测结果对研究区植被覆盖度的变化趋势进行建模分析.结果表明,研究区1990、2001和2008年均以高植被覆盖度等级为主,估算的面积分别为207.058、216.538和232.795 km2.1990-2008年间,研究区内植被覆盖度稳定不变的区域占总面积的44.887％,减少和增加的区域分别占总面积的22.077％和33.036％,说明植被覆盖度总体上呈现增加的趋势;结合1990-2001年和2001-2008年的变化分析结果,植被覆盖度变化趋势是先略微增加,后显著增加,与植被覆盖度均值走势一致,从定量遥感的角度证明了漓江精华段沿岸风光带的绿色生态环境得到了快速的改善.     

An experimental study of the incipient bed shear stress partition in mobile bed channels filled with emergent rigid vegetation

This paper investigates the bed shear stress based on the condition of the incipient motion of sediment in a uniform-flow flume covered with emergent rigid vegetation,which is represented by arrays of circular cylinders arranged in a regular pattern.A total of 148 tests are performed to observe the influence of the vegetation density,bed slope,flow depth and sediment size on the bed shear stress.The tests reveal that when the sediment is in incipient motion,the resistances acting on the flow passing the rigid vegetation contain the vegetation resistance and the bed shear stress.This shear stress could be divided into two parts:the grain shear stress and the shear stress caused by sand dunes,which are the deformed bedform with the sediment incipient motion.An empirical relationship between the shear stress of the sand dune and vegetation density,the Froude number,the apparent vegetation layer velocity is developed.     

北京市土地利用变化对地表温度的影响分析

运用遥感(RS)和地理信息系统(GIS)技术,对北京1995年至2005年的土地利用时空变化特征进行了分析,并分析了土地利用变化对区域内地表温度的影响。北京在1995年至2000年的土地利用变化较小,随后五年城镇面积大量扩张,占用了大量的耕地和林地。北京地表温度等级较高的区域在数量上呈逐年增加的趋势,同时在空间分布上呈现从分散向城市中心集中的趋势。构建了TVX空间研究土地利用变化对地表温度的影响,计算了不同土地利用类型转变为建设用地的变化向量长度,并选取未变化的土地利用类型的平均温度作为控制点,消除不确定性因素,分析得出变化向量的幅度依次是:有林地>水域>其他林地>灌木林地>草地>耕地,由此可以看出,林地和水域对缓解地表热环境作用较强,在城市规划中,要尽量保护林地和水域。     

科尔沁沙地土壤酶活性与植被的关系

为揭示科尔沁沙地植被的生长情况，从实验地取样。测定科尔沁沙地不同地貌及典型植被近根际的土壤酶活性，主要包括磷酸酶、脲酶、蛋白酶等．结果表明：固定沙丘的土壤酶活性最高。而流动沙丘的酶活性最低；羊草、大油芒、断肠草等多年生草本植被的近根际土壤酶活性普遍高于小叶锦鸡儿、差巴嘎蒿、山竹子等灌木植被；而小叶锦鸡儿的近根际土壤酶活性在灌木植被中为最高，说明小叶锦鸡儿为一种较好的固沙植被.     

森林叶面积指数遥感反演与空间尺度转换研究

以贵州省黎平县为研究区,着重研究森林叶面积指数(LAI)的ETM遥感信息反演和向1km空间尺度转换算法.通过LAI-2000的针叶林和阔叶林等植被类型的LAI实地观测,建立实测LAI与ETM影像归一化植被指数(NDVI)的相关关系并进行LAI遥感制图,并在陆地覆盖类型遥感分类信息提取的基础上,发展了针叶林、混交林和空旷地三种地表类型LAI的向上空间尺度转换算法,以对粗分辨MODIS遥感数据的LAI产品实现LAI算法的转换与校正,并通过示例应用显示了本研究空间尺度转换算法的有效性.