Mapping forest leaf area index using reflectance and textural information derived from WorldView-2 imagery in a mixed natural forest area in Florida,US

The leaf area index (LAI) of plant canopies is an important structural parameter that controls energy, water, and gas exchanges of plant ecosystems. Remote sensing techniques may offer an alternative for measuring and mapping forest LAI at a landscape scale. Given the characteristics of high spatial/spectral resolution of the WorldView-2 (WV2) sensor, it is of significance that the textural information extracted from WV2 multispectral (MS) bands will be first time used in estimating and mapping forest LAI. In this study, LAI mapping accuracies would be compared from (a) spatial resolutions between 2-m WV2 MS data and 30-m Landsat TM imagery, (b) the nature of variables between spectrum-based features and texture-based features, and (c) sensors between TM and WV2. Therefore spectral/textural features (SFs) were first selected and tested; then a canonical correlation analysis was performed with different data sets of SFs and LAI measurement; and finally linear regression models were used to predict and map forest LAI with canonical variables calculated from image data. The experimental results demonstrate that for estimating and mapping forest LAI, (i) using high resolution data (WV2) is better than using relatively low resolution data (TM); (ii) extracted from the same WV2 data, texture-based features have higher capability than that of spectrum-based features; (iii) a combination of spectrum-based features with texture-based features could lead to even higher accuracy of mapping forest LAI than their either one separately; and (iv) WV2 sensor outperforms TM sensor significantly. However, we need to address the possible overfitting phenomenon that might be brought in by using more input variables to develop models. In addition, the experimental results also indicate that the red-edge band in WV2 was the worst on estimating LAI among WV2 MS bands and the WV2 MS bands in the visible range had a much higher correlation with ground measured LAI than that red-edge and NIR bands did.     

基于Ｌｏｔｋａ Ｖｏｌｔｅｒｒａ方程的基因调控网络的稳定性分析

在2007年7—8月棉花生长旺季,将冠层按高度分多层,通过简单的试验方法确定了棉冠内叶片丛聚指数（clumping index,Ω）,以此区分计算出田间各层逐时阳叶（受光叶）和阴叶（被遮荫叶）叶面积指数的动态值。在8月23日用LI-6400R便携式光合测量系统分多层分别测定阴、阳叶单张叶片净光合作用的日变化,结合阴、阳叶面积权重,探讨利用Ω区分阴阳叶之后对整个冠层日总光合作用的影响。试验结果表明：（1）花铃期棉花冠层内Ω约为0.68;（2）利用Ω计算得到8月23日冠层日间（09：00—18：00）总净光合作用日平均值大约为20.3μmol·m-2·s-1,其中阳叶贡献约占总量的72%,阴叶约占总量的28%;（3）上层叶片贡献约占总量的75%,中层叶片约占总量的22%,下层叶片约占总量的3%。     

Thermal Anomalies and Earthquakes： Evidence from Wenchuan, China

Earthquake prediction is a difficult problem in Earth sciences.Unsuccessful predictions one after another urged people to explore more synthetic and comprehensive methods for earthquake prediction.The Lithosphere-Atmosphere-Ionosphere(LAI)coupling theory pays great attention to the processes taking place within the near ground layer of atmosphere.It has achieved great results recently,and can enlighten us about the nature of an earthquake's precursor.Based on the NCEP reanalysis dataset,this paper attempts to track the anomalies of the surface's upward long wave radiation flux(ULWRF),the temperature at the depth of 10cm～20cm below ground surface layer(BGL)and the air temperature at 2 meters above ground surface(AIR)around the time of the strong Wenchuan earthquake.Thermal anomalies were observed before and after May 12,2008,the time of the Wenchuan earthquake.Perhaps the thermal anomaly that occurred prior to the earthquake can be taken as indicators of the earthquake,but in view of the complexity of the earthquake phenomena,using thermal anomaly as a precursor should be done with caution.     

影响植被内部辐射状况的冠层结构特征研究

植被冠层结构特征是影响植被内部辐射状况的重要因子之一,对于植被群体的光合特性来说,冠层结构特性影响了光合有效辐射的截获、吸收和透射。本文着重分析了冠层结构的数量特征（如叶面积指数）和冠层几何结构特征,综合考虑叶倾角、叶方位角和Ｇ函数等群体几何特征,以便直接用于遥感光合植被生物量机理估测模型的建立。     

面向LAI 反演的参数化SAILH 模型

建立了一种基于植被冠层辐射传输模型SAILH 的参数化模型。该模型首先对SAILH 模型中用到的9 个 中间变量的计算过程进行简化, 然后用一个明确的表达式计算光照冠层的单次散射贡献。分别用模拟数据和2008 年黑河地区星-机-地同步实验中获取的地面测量数据对该参数化模型的反演精度和效率进行了评价。评价结果表明 该参数化模型能在保证反演精度的基础上极大的提高反演效率; 利用模拟数据进行的模型稳定性评价表明, 参数 化模型的稳定性优于SAILH 模型。     

两种叶面积指数动态模拟方法的对比研究

为了获得宁夏灌区春小麦叶面积指数( Leaf Area Index,LAI)动态模拟的最佳方法,根据宁夏灌区典型农业试验观测站春小麦LAI的大田观测数据,分别运用农业气象学和遥感反演等方法模拟春小麦LAI的动态变化,并对两种方法的模拟精度进行综合对比分析.结果表明,运用分段函数(三叶至抽穗期运用遥感反演法,抽穗至乳熟期...     

叶面积指数遥感尺度效应与尺度纠正

由于地表空间异质性的普遍存在,遥感反演模型的非线性必然会导致不同分辨率观测的遥感结果不一致,从而产生遥感产品尺度效应。本文研究了遥感产品尺度效应概念、模拟方法和定量计算模型,并利用锡林浩特草原研究区的实测数据,对尺度效应模型和方法进行了定量计算与验证分析。首先,基于不同升尺度方法与多尺度遥感成像机理之间的机理联系,通过“先反演再平均”与“先平均再反演”之间的差异,可计算“高”分辨率与“低”分辨率之间的遥感产品尺度差异。其次,分别以红光、近红外两波段反射率和归一化植被指数(NDVI)为自变量,对叶面积指数(LAI)非线性遥感模型进行泰勒展开,研究了模型非线性、遥感数据空间异质性对LAI遥感产品尺度差异的影响,发现高阶项可忽略,利用二阶导数项和遥感数据方差项可定量计算遥感产品尺度差异,经过二阶导数项纠正后的尺度差异相对偏差从5.6%分别降低到0.78%和1.45%。最后,分析了LAI遥感产品尺度效应的特征规律,得出以下结论:随着植被覆盖的增大,同等遥感空间异质性的LAI遥感产品尺度差异越大,且红光波段比近红外波段的尺度差异敏感性高近2个数量级;对于绝大部分陆地植被区域,存在“低分辨率低估”尺度效应,且遥感产品尺度差异的主导要素为LAI模型非线性,NDVI变量自身非线性对尺度效应贡献占23.5%;对于湿地类植被与水体混合情形,NDVI变量非线性的贡献为主导贡献,出现“低分辨率高估”尺度效应,必须利用红光、近红外两波段的二阶导数项非线性尺度差异,才能解释这一类型的LAI遥感产品尺度效应。本文建立了具有一定普适意义的遥感产品尺度效应定量模拟与尺度纠正方法,对推动定量遥感的尺度问题研究有一定参考价值。     

Simulated watershed responses to land cover changes using the Regional Hydro‐Ecological Simulation System

In this work, we used the Regional Hydro‐Ecological Simulation System (RHESSys) model to examine runoff sensitivity to land cover changes in a mountain environment. Two independent experiments were evaluated where we conducted simulations with multiple vegetation cover changes that include conversion to grass, no vegetation cover and deciduous/coniferous cover scenarios. The model experiments were performed at two hillslopes within the Weber River near Oakley, Utah watershed (USGS gauge # 10128500). Daily precipitation, air temperature and wind speed data as well as spatial data that include a digital elevation model with 30 m grid resolution, soil texture map and vegetation and land use maps were processed to drive RHESSys simulations. Observed runoff data at the watershed outlet were used for calibration and verification. Our runoff sensitivity results suggest that during winter, reduced leaf area index (LAI) decreases canopy interception resulting in increased snow accumulations and hence snow available for runoff during the early spring melt season. Increased LAI during the spring melt season tends to delay the snow melting process. This delay in snow melting process is due to reduced radiation beneath high LAI surfaces relative to low LAI surfaces. The model results suggest that annual runoff yield after removing deciduous vegetation is on average about 7% higher than with deciduous vegetation cover, while annual runoff yield after removing coniferous vegetation is on average as about 2% higher than that produced with coniferous vegetation cover. These simulations thus help quantify the sensitivity of water yield to vegetation change. Copyright © 2013 John Wiley & Sons, Ltd.     

基于TM数据的植被覆盖度反演

本文首先对TM影像进行了几何纠正、辐射校正、大气校正;然后根据混合像元的结构特征,利用TM数据从植被指数(NDVI)中采用“等密度模型”和“非密度模型”提取了宜昌南部地区的植被覆盖度。在用“非密度模型”反演植被覆盖度的过程中,叶面积指数(LAI)是一个必要的参数,本文提出了一种改进的借助可见光波段和近红外波段反射值来提取叶面积指数(LAI)的方法。通过和MODIS数据反演结果比较表明:“非密度模型”的估算精度要高于“等密度模型”;利用“等密度模型”和“非密度模型”反演植被覆盖度是可行。     

Interdependent Dynamics of LAI-ET across Roofing Landscapes: the Mongolian and Tibetan Plateaus

The Mongolian and Tibetan Plateaus have experienced warming higher than the global average in recent decades, resulting in many significant changes to ecosystem structures and functions. Among items that show change are the leaf area index (LAI) and evapotranspiration (ET), both of which play a fundamental role in shaping many causes and consequences of land surface processes and climate. This study examines the spatiotemporal changes of the LAI and ET and their relationships on these two roofing landscapes. Based on the MODIS products from 2000 through 2014, we found that there existed a general positive relationship between LAI and ET on the Mongolia Plateau (MP), while synergy did not exist on the Tibetan Plateau (TP). Overall, 49.38% (50.62%) of land areas on the TP experienced significant increases (decreases) in LAI, while on the MP the percentages of increase and decrease were 94.92% (5.09%). For ET, the increased land area was 21.70% (124100 km²) on the TP and 88.01% (341600 km²) on the MP. More importantly, the relationships varied substantially across space and over time, with mismatches found in some parts of the landscapes. Additional observational investigations and/or experimental research are needed to explore the relationships, including the influences of vegetation characteristics and disturbances.