基于经验法则的水稻细菌性条斑病气候年型分析

利用广东省化州市1989-2016年晚稻细菌性条斑病资料和同期气象资料,采用合成分析和秩相关分析,筛选出影响细菌性条斑病发生的关键气象因子;基于经验法则,利用水稻细菌性条斑病发生阶段的温度、降水距平,判别细菌性条斑病发病程度,并确定了细菌性条斑病发生流行的气候年型与预测指标。经历史回代,判别细菌性条斑病发病程度符合率为82.1%,并进行了2017-2019年的外延指标判别,符合率达100%,综合判别符合率在83%以上。     

A semi‐theoretical model of canopy rainfall interception for a broad‐leaved tree

Through a series of simulation experiments in the laboratory on the broad‐leaved tree Acer mono Maxim, we obtain interception datasets of individual events under different rainfall intensities and leaf area indexes (LAIs). Based on the data, the relationship between rainfall intensity and maximum interception of per unit LAI is quantified. The variation of interception with canopy wetness index is also identified. Hence, an interception model, in which interception is calculated using rainfall intensity and LAI, is constructed with consideration of canopy wetness. Finally, according to the validation experiments, it is concluded that the precision of the model is 92·7%. Copyright © 2007 John Wiley & Sons, Ltd.     

春秋季节侧柏-山毛桃群落演替初期的小气候特征

开展森林小气候研究,对于协调生物与环境的关系、保护生物多样性以及实现森林的可持续高效管理,都是十分重要的。选择5月和10月典型的晴朗无风天气条件,以侧柏纯林为对照,研究了郁闭度为0.25、0.54和0.87的侧柏-山毛桃群落演替初期小气候特征。结果表明,侧柏-山毛桃混交林对春季和秋季林内空气温度的早间增温效应和午间降温效应,随着郁闭度增加而增大。春季的高温峰值出现在15时,晚于秋季的高温峰值13时。春季和秋季林内10 cm处地温日间呈持续增加趋势,春季以郁闭度为0.25的B点为最高,秋季侧柏纯林在12时前为最低,14时后为最高。春季林内空气相对湿度从07时到11时呈快速降低的趋势,然后逐渐缓慢回升;而秋季林内的相对湿度,随着郁闭度的增加而增大,但日间变化幅度比较小。无论春季还是秋季,侧柏和山毛桃的叶片温度日间变化均呈先升高后缓慢降低的趋势。春季郁闭度对侧柏和山毛桃的叶片温度影响不显著,但秋季11-15时,随着郁闭度的增加,叶片温度有降低的趋势。在太行山区,以山毛桃为保护树种,快速提高侧柏-山毛桃混交林的郁闭度,对有效地改善林内小气候,促进森林更新和管理都是十分重要的。     

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。     

Deriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis

Leaf mass per area (LMA), the ratio of leaf dry mass to leaf area, is a trait of central importance to the understanding of plant light capture and carbon gain. It can be estimated from leaf reflectance spectroscopy in the infrared region, by making use of information about the absorption features of dry matter. This study reports on the application of continuous wavelet analysis (CWA) to the estimation of LMA across a wide range of plant species. We compiled a large database of leaf reflectance spectra acquired within the framework of three independent measurement campaigns (ANGERS, LOPEX and PANAMA) and generated a simulated database using the PROSPECT leaf optical properties model. CWA was applied to the measured and simulated databases to extract wavelet features that correlate with LMA. These features were assessed in terms of predictive capability and robustness while transferring predictive models from the simulated database to the measured database. The assessment was also conducted with two existing spectral indices, namely the Normalized Dry Matter Index (NDMI) and the Normalized Difference index for LMA (ND_LMA).Five common wavelet features were determined from the two databases, which showed significant correlations with LMA (R²: 0.51–0.82, p < 0.0001). The best robustness (R² = 0.74, RMSE = 18.97 g/m² and Bias = 0.12 g/m²) was obtained using a combination of two low-scale features (1639 nm, scale 4) and (2133 nm, scale 5), the first being predominantly important. The transferability of the wavelet-based predictive model to the whole measured database was either better than or comparable to those based on spectral indices. Additionally, only the wavelet-based model showed consistent predictive capabilities among the three measured data sets. In comparison, the models based on spectral indices were sensitive to site-specific data sets. Integrating the ND_LMA spectral index and the two robust wavelet features improved the LMA prediction. One of the bands used by this spectral index, 1368 nm, was located in a strong atmospheric water absorption region and replacing it with the next available band (1340 nm) led to lower predictive accuracies. However, the two wavelet features were not affected by data quality in the atmospheric absorption regions and therefore showed potential for canopy-level investigations. The wavelet approach provides a different perspective into spectral responses to LMA variation than the traditional spectral indices and holds greater promise for implementation with airborne or spaceborne imaging spectroscopy data for mapping canopy foliar dry biomass.     

Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations

Assessment of the susceptibility of forests to mountain pine beetle (Dendroctonus ponderosae Hopkins) infestation is based upon an understanding of the characteristics that predispose the stands to attack. These assessments are typically derived from conventional forest inventory data; however, this information often represents only managed forest areas. It does not cover areas such as forest parks or conservation regions and is often not regularly updated resulting in an inability to assess forest susceptibility. To address these shortcomings, we demonstrate how a geometric optical model (GOM) can be applied to Landsat-5 Thematic Mapper (TM) imagery (30 m spatial resolution) to estimate stand-level susceptibility to mountain pine beetle attack. Spectral mixture analysis was used to determine the proportion of sunlit canopy and background, and shadow of each Landsat pixel enabling per pixel estimates of attributes required for model inversion. Stand structural attributes were then derived from inversion of the geometric optical model and used as basis for susceptibility mapping. Mean stand density estimated by the geometric optical model was 2753 (standard deviation ± 308) stems per hectare and mean horizontal crown radius was 2.09 (standard deviation ± 0.11) metres. When compared to equivalent forest inventory attributes, model predictions of stems per hectare and crown radius were shown to be reasonably estimated using a Kruskal–Wallis ANOVA (p < 0.001). These predictions were then used to create a large area map that provided an assessment of the forest area susceptible to mountain pine beetle damage.     

基于被动微波遥感技术的玉米冠层叶面积指数反演

基于玉米冠层结构参数实测数据和Matrix-Doubling(MD)模型构建了玉米出苗期至抽穗期的冠层多波段、双极化微波辐射特性模拟数据库;通过对模拟数据的回归分析得到了玉米冠层在各波段的微波发射率及其与透过率之间的经验关系,并将经验关系应用于0阶微波辐射传输模型;结合土壤发射率模型构建了玉米冠层覆盖地表的微波辐射亮温参数化计算模型,并基于该参数化模型、利用玉米样地微波亮温观测试验数据,采用迭代方法进行了玉米叶面积指数(LAI)的反演.研究表明,LAI反演值与实测值的相关系数r＞0.9,说明多波段被动微波遥感数据在植被冠层LAI反演方面具有较大的应用潜力.     

光学与微波植被指数协同反演农作物叶面积指数的可行性分析

光学遥感是目前反演植被叶面积指数LAI（Leaf Area Index）的主要手段,但是当叶面积指数较大时存在光学遥感信息饱和、反演精度显著降低的问题。叶面积指数和平均叶倾角对光学、微波波段范围内反射和散射特性都有重要影响,主要表现在植被结构参数的变化可以引起冠层孔隙率和消光截面大小的改变。本文以典型农作物玉米为例,通过构建统一的PROSAIL和MIMICS模型输入参数,生成一套玉米全生长期光学二向反射率和全极化微波后向散射系数模拟库和冠层参数库。通过对模拟数据与LAI敏感性和相关性分析得出：（1）光学植被指数MNDVI_{(800 nm,2000 nm)},在LAI为0—3时敏感,基于MNDVI与LAI的回归模型可以估算LAI变化 0.4的情况,RMSE是0.33,R²是0.958。（2）微波植被指数SAR_{SRVI(1.4 GHz HH,9.6 GHz HV)},在LAI为3—6时敏感,基于SAR_SRVI与LAI的回归模型可以估算LAI变化1的情况,RMSE为0.22,R²是0.9839。研究表明,采用分段敏感的植被指数,协同光学和微波遥感反演玉米全生长期叶面积指数是可行的。     

Employing spatial information technologies to monitor biological control of saltcedar in West Texas

The saltcedar leaf beetle (Diorhadha spp.) has shown promise as a biocontrol agent for saltcedar (Tamarix spp.) invasions in the USA. In Texas, natural resource managers need assistance in monitoring biological control of invasive saltcedars. This study describes application of a medium-format, digital camera acquiring natural colour imagery and global positioning system (GPS) and geographic information system (GIS) technologies to check biological control of saltcedar in west Texas. On 8 July and 8 September 2011, natural colour airborne digital imagery was collected along a 155.8?km transect covering portions of Presidio and Brewster counties of Texas. The camera was tethered to a GPS receiver that geotagged each image and saved the coordinates to a key-hole marked up language file that was viewable on Google Earth. Saltcedar trees exhibiting severe feeding damage and those that were totally defoliated were easily identified in the imagery. The former appeared in orange to brown colour tones; the latter exhibited grey colour tones. Point distribution maps showing locations of saltcedar trees exhibiting feeding damage were developed from GPS information in the GIS. Coordinate points on the map were linked to the corresponding image, permitting the user to have quick access to view imagery. The results of this study show a practical method for monitoring biological control of saltcedar.     

Applying broadband spectra to assess biological control of saltcedar in west Texas

Broadband field spectra were assessed to discriminate invasive saltcedar (Tamarix spp.) trees exhibiting feeding damage caused by the saltcedar leaf beetle (Diorhadba spp.) from other land cover types. Data were collected at two study sites near Presidio, Texas in 2010 and 2011. Spectral bands evaluated were coastal blue (400–450?nm), blue (450–510?nm), green (510–580?nm), yellow (585–625?nm), red (630–690?nm), red-edge (705–745?nm), and near-infrared (770–895, 860–1040?nm). Data were evaluated with analysis of variance and Scheffe’s multiple comparison test (α?=?0.05). The red band generally separated severely damaged saltcedar trees from other land cover features. Near-infrared bands separated defoliated saltcedar trees. Broadband spectra has potential for distinguishing saltcedar trees exhibiting feeding damage caused by the saltcedar leaf beetle from other associated features, thus supporting future explorations of airborne and satellite-borne multispectral systems to monitor biological control of saltcedar within complex landscapes.