Preparation of volume table of SAL (Shorea robusta) - an approach using satellite data

Sal (Shorea robusta) is an important forest tree species in north and north-eastern India. Large-scale plantations of this species have been raised there under taungya and coppice system of management. The conventional volume table prepared for high sal forest is referred to infer the volume of production of this species. Earlier workers have used aerial remote sensing data to develop volume tables of this species. In the present study a volume table for sal is developed based on remotely sensed satellite data using a regression technique. A two-step method was developed to estimate mean tree volume from satellite data. In step 1, mean crown diameter — an intermediate variable - was estimated from satellite data. In step 2, the estimated mean crown diameter was used to estimate the mean tree volume. Addition of age of the crop as an independent variable improved the predictive ability of the regression equation.     

Habitat analysis for sambar in corbett national park using remote sensing and gis

Habitat analysis for sambar in terms of food, cover, water, space and extent of edge in Corbett National Park using remote sensing and GIS has been attempted. Other physical parameters include climate, topography, fire history, disturbance regimes, weeds etc. IRS-IB LISS II data (FCC, hardcopy) on 1:50.000 scale was interpreted to generate vegetation cover and density map. Other maps showing drainage, water bodies, roads, human habitations and contours were prepared using Survey of India topographical maps. During evaluation of sambar habitat information regarding habitat parameters and their tolerance was collected from existing literature as well as during field observations. Twenty-two transects of one km. length were laid down in all the strata randomly to collect information regarding the structure and composition of the forest and also habitat use (direct and indirect evidences) by sambar. This was then integrated using condition-based equations in the GIS domain to generate suitability maps. Actual sightings on the ground to a large extent supported the results.     

Cotton yield prediction through spectral parameters

To predict the crop yield from spectral parameters, a field experiment was conducted on cotton crop during 1997-98 Kharif season on a sandy loam soil at the Punjab Agricultural Unjversity, Ludhiana. India. Spectral reflectance and agronomic measurements were made for cotton species (American and Desi cotton), sown on two dates (May 1 and May 29) under five nitrogen levels (0, 40, 80, 120 and 160 kg/ha). Regression analysis showed that growth variables had poor correlation with seed cotton yield for all three models, however, yield attributes were significantly and highly correlated for second degree model with seed cotton yield. The integrated Radiance Ratio (RR) and Normalized Difference Vegetation Index (NDVI) measured over time were significantly correlated quadratically with seed cotton yield on three time segment periods viz., 81–110, 111–140 and 141–200 DAS, but highest correlation values were obtained during 81–110 DAS, In American cotton, the highest correlation coefficient for RR and NDVI were 0.91 and 0.81, respectively; whereas for Desi cotton these values were 0.88 and 0.84, respectively.     

机车车辆滚动振动试验台的精密测量

本文针对国家重点牵引力动力实验室的机车车辆整车滚动振动试验台的特点，探讨了一套适合试验台安装和养护的精密测量方法，实践证明，这套方法能满足试验台安装所需的精度要求。     

The generalized Mollweide projection of the biaxial ellipsoid

Summary The standard Mollweide projection of the sphere S _R ² which is of type pseudocylindrical — equiareal is generalized to the biaxial ellipsoid E _A,B ² .Within the class of pseudocylindrical mapping equations (1.8) of E _A,B ² (semimajor axis A, semiminor axis B) it is shown by solving the general eigenvalue problem (Tissot analysis) that only equiareal mappings, no conformal mappings exist. The mapping equations (2.1) which generalize those from S _R ² to E _A,B ² lead under the equiareal postulate to a generalized Kepler equation (2.21) which is solved by Newton iteration, for instance (Table 1). Two variants of the ellipsoidal Mollweide projection in particular (2.16), (2.17) versus (2.19), (2.20) are presented which guarantee that parallel circles (coordinate lines of constant ellipsoidal latitude) are mapped onto straight lines in the plane while meridians (coordinate lines of constant ellipsoidal longitude) are mapped onto ellipses of variable axes. The theorem collects the basic results. Six computer graphical examples illustrate the first pseudocylindrical map projection of E _A,B ² of generalized Mollweide type.     

综合多特征的Landsat 8时序遥感图像棉花分类方法

传统的多时相遥感图像分类大多拘泥于单一特征,本文基于多时相的Landsat 8遥感数据,开展了综合多特征的特征提取与特征选择方法研究。综合了NDVI时间序列、最佳时相反射率光谱特征以及纹理特征作为初始分类特征,并采用基于属性重要度的粗糙集特征选择算法对其进行特征约简。分类结果表明:(1)利用初始分类特征,分类的总体精度达到92.81%,棉花提取精度达87.4%,与仅利用NDVI时间序列相比,精度分别提高5.53%和5.05%;(2)利用粗糙集选择后的特征分类,分类总体精度可达93.66%,棉花分类精度达92.73%,与初始分类特征提取结果相比,棉花分类精度提高5.33%。基于属性重要度的粗糙集特征选择不仅提高了分类精度,同时有效降低了分类器的计算复杂度。     

3维块匹配小波变换的极化SAR非局部均值滤波

极化合成孔径雷达(SAR)图像受相干斑噪声的影响,难以很好地保持结构特性,针对这个问题提出了一种采用3维块匹配小波变换的非局部均值滤波算法NL-3DWT(Nonlocal Filter based on 3-D Patch Matching Wavelet Transform)。该算法使用块匹配的3维非抽样小波变换对极化总功率图进行预滤波,在此基础上使用边界对齐窗提取结构相似像素,同时使用Sigma范围选择极化SAR数据的散射相似像素,共同构成相似像素集合;构建结构保持权重函数增大图像结构信息在块相似性度量时的权重,最终实现极化SAR图像结构保持的相干斑抑制。该算法增强了图像结构特征的表达,提高了结构相似像素选择的准确性,机载极化SAR数据实验结果表明,NL-3DWT算法能够在抑制相干斑噪声的同时,更有效地保持极化SAR图像的结构特性和极化散射特性。     

Sentinel-2数据的冬小麦地上干生物量估算及评价

作物生物量快速精确的监测对于农业资源的合理利用与农田的精准管理具有重要意义。近年来,遥感技术因其独特的优势已被广泛用于作物生物量的估算中。本文主要针对不同宽波段植被指数在冬小麦生物量(文中的生物量均是指地上干生物量)估算方面的表现进行探索。首先利用欧洲空间局最新的Sentinel-2A卫星数据提取出17种常见的植被指数,之后分别构建其与相应时期内采集的冬小麦地上生物量间的最优估算模型,通过分析两者间的相关性与敏感性,获取适宜进行生物量估算的指数。最后,绘制了研究区的生物量空间分布图。结果表明,所选的植被指数均与生物量显著相关。其中,红边叶绿素指数(CI_(re))与生物量的估算精度最高(决定性系数R~2为0.83;均方根误差RMSE为180.29 g·m~(–2))。虽然相关性较高,但部分指数,如归一化差值植被指数(NDVI)等在生物量较高时会出现饱和现象,从而导致生物量的低估。而加入红边波段的指数不仅能够延缓指数的饱和趋势,而且能够提高反演精度。此外,通过敏感性分析发现,归一化差值指数和比值指数分别在作物生长的早期和中后期对生物量的变化保持较高的敏感性。由于红边比值指数(SR_(re))和MERIS叶绿素敏感指数(MTCI)在冬小麦全生长季内一直对生物量的变化保持高灵敏性,二者是生物量估算中最为稳定的指数。     

黑土区田块尺度遥感精准管理分区

基于格网采样与空间插值的精准管理分区方法精度高,但时效性差、成本高。本文以东北农垦地区红星农场农田为研究对象,提出一种基于遥感影像的精准管理分区方法:以裸土高空间分辨率遥感影像作为数据源,结合田间格网采样数据,基于裸土反射光谱特征与黑土主要理化性质的显著相关关系,运用面向对象分割、空间统计分析方法,对典型黑土区田块进行精准管理分区研究,并利用土壤理化性质和农作物生理参数,对分区结果进行评价。得出如下结论:(1)典型黑土区田块内部土壤养分含量空间变异显著;(2)基于裸土影像与面向对象的精准管理分区方法精度高,增强了分区之间的土壤养分与归一化植被指数(NDVI)差异性、分区内部各属性的一致性;(3)基于2015年4月1日和2015年5月20日单期影像分区和两期影像波段叠加(Layer stacking)分区,区间变异系数与区内变异系数之比分别为1.42、1.39和7.63,基于两期影像综合信息的分区结果显著优于基于单期影像分区;(4)基于裸土影像面向对象分割的精准管理分区方法时效性强、成本低、精度高。研究成果为田间变量施肥、发展精准农业、实现农业可持续发展提供依据。