实景三维在土壤普查表层样点校核中的应用

针对传统的土壤表层样点校核方式耗时费力且质量不佳的问题，该文提出了基于实景三维实现土壤表层样点快速校核的方法。在实景三维中，采用缓冲区分析、叠置分析、网络分析等空间分析技术，实现了青岛市即墨区土壤表层样点的高效校核。研究结果表明：实景三维能够较好地解决传统校核方式中现场踏勘局限性多、资料利用不足、环境变量把控不强、校核成本高等弊端，并且当表层样点数量越多，地形地貌越复杂时，优势越明显。该研究模式为第三次全国土壤普查提供了在实景三维中运用空间分析技术实现表层样点校核的借鉴，适宜在全国范围内推广。     

针对地质灾害隐患点的无人机航摄像控点布点方案

以陕西省某地质灾害隐患点1∶2000航飞生产任务为背景，本文结合垂直起降式无人机航摄技术特点和地质灾害隐患点区域实际情况，通过详细对比几种无人机航摄像控点布控方案的优劣，研究无人机像控点布设方案对空三加密精度的影响，总结了适用于不同地质灾害隐患点的像控点布设方案。通过本文研究，为今后制定地质灾害隐患点的无人机航摄像控点布设方案提供了参考依据。     

基于困难地区的无人机影像像控点布设研究

近几年来,GPS/INS组合的导航系统——POS系统已逐步成熟,并应用于无人机飞控系统,虽然POS精度不是很高,但是其实现了影像外方位元素的直接获取,并且摆脱了传统摄影测量对大量地面控制点的严重依赖,方便了影像像控点的布设。同时,为了使成果DOM精度达到项目要求,少量控制点的布设仍不可避免,为此,如何合理选取困难地区像控点布设方案成为工程项目中急需解决的问题。为了获取针对困难地区的像控点合理布设方案,本文基于甘肃陇南地区土地确权项目,通过对测区无人机影像采用不同的像控点布设方案进行空三平差处理,分析正射影像图的平面精度情况来选取适合当地的布设方案。实验结果表明,在满足生产精度的前提下,适当放宽国家规范的像控点布设要求的同时,给出困难地形的像控点布设方案,能极大提高像控点测量野外作业效率,并且可以在其他测区推广使用。     

旋翼无人机外业像控点布设方案研究

为了解决提高旋翼无人机外业影像控制点测量质量的问题,本文深入研究了基于旋翼无人机低空多视角航空摄影的像控点布设方案.通过大量实验数据和不同像控点布设方案比对,研究确定高质量的布设原则,结果表明:测区四周均匀布设控制点有利于保证区域内部的精度.一般情况下,单点布设的精度不如点组布设精度高,而且点组布设可以提高平面高程的精度.     

建筑点群在城市3维形态量化中的应用

利用将建筑实体进行高度抽象，提出了建筑点群，以GIS的空间分析理论为依据，通过实体高度、起伏度、空间聚集度三个指标对城市的3维形态进行量化与分析。选取南京市主城区为实验样区，提取该区域的建筑点群，用三个指标对实验样区内3维形态的空间分布格局和时间发展特点进行定量分析与描述。实验结果证明，这三个指标从不同角度分析了建筑实体在区域内的组合方式，能够在一定程度上反映城市3维形态的基本特征，有助于对城市空间分布格局及城市历史演变过程的研究。     

从GIS数据库中挖掘空间离群点的一种高效算法

根据GIS的空间特性，借鉴已有的定义和概念，定义了空间离群点是和在其非空间属性邻域内其他空间对象在空间位置上差异十分显著的空间对象，并设计了SOD算法。实验结果验证了SOD算法的有效性和优越性，给出了从GIS数据库中挖掘空间离群点的一般步骤。     

基于三维激光扫描的植被覆盖边坡监测

针对植被覆盖边坡难以获取高精度地面点云数据,导致精确监测边坡地表变形较为困难的问题,本文提出了一种利用布设在边坡体上的传感器获取表面点云数据以提取边坡变形的方法。布设在边坡上的GNSS天线整流罩外形是半径逐渐变化的球形设备,利用点云切片拟合出圆心坐标和半径,通过拟合残差和验后中误差评估点云精度,实现质量控制。通过两期半径的对比,实现同名点匹配,根据两期圆心坐标达到点式监测的目的;根据边坡上的台阶及雨量计的外围设备实现面式监测。实测数据表明,三维激光扫描与GNSS的监测结果一致,可以提取毫米级别的变形。     

一种结合已有DOM和DEM的高精度自动刺像控点方法

针对基础地理数据更新需求，为了免去外业布设控制点，减少内业刺点工作量，提高控制点精度、密度，提出了一种基于已有DOM和DEM数据，利用IPS软件和辅助软件，实现高精度自动刺像控点的方法。将已有DOM根据具体匹配需求裁切，裁切后的DOM和像片同时加载到IPS中进行同名像点匹配，根据DOM的地理参考、匹配点像平面坐标、TFW头文件及DEM共同解算出匹配点的物方坐标。通过平差探测和目视检查剔除错误点，改变匹配点属性为控制点，即完成了控制点刺入工作。之后可在IPS中继续完成空三处理、地理信息产品制作等，也可导出、转换为其他软件的文件格式，供后续处理使用。     

三维激光扫描在建设工程竣工规划核实中的应用研究

本文介绍了建设工程竣工规划核实的主要方式,阐述了测量在竣工规划核实中的重要性,及目前核实方式中存在的问题.然后,针对三维激光扫描的技术原理,分析了三维激光扫描技术在竣工规划核实中应用的可行性,并通过对控制点布设、点云配准、建筑物特征点提取等技术方法的研究,实现了三维激光扫描在竣工规划核实中的应用,具有一定理论意义和实用价值.     

像控点布设对无人机小范围非规则区域实景建模精度的影响

像控点布设方式和数量对实景建模精度有重要影响.本文选取阜阳市临泉县某0.25 km^2非规则区域为实验区,另选两个非规则型的验证区(0.27 km^2和0.28 km^2),按边缘布设、边缘加少量中心布设、中心布设三种不同的像控点布设方式进行实景模型构建,对比分析像控点数量和布设位置对模型精度的影响特征.结果表明:1)当像控点连线围成的凸多边形包含整个非规则测区时,才能有效保证构建的模型精度.2)在1∶500比例尺测图精度的要求下,边缘布设五个像控点为最佳点位布设方式,满足高效率、高精度、低成本的建模要求.3)在像控点布设位置理想的情况下,增加布设数量并不能显著提升实景模型精度,像控点应按需布设.     

Comparison of sampling methods for inventorying the stand volume using satellite remote sensing

Remote sensing is being increasingly used for forest resource inventory as it saves time and the cost. Aerial photographs and satellite images have been effectively utilized for forest inventory all over the world. This study highlights the application of IRS LISS-III imagery for inventorying the stand volume in Lachchhiwala Forest Range of Siwaliks. The satellite image was visually interpreted for forest type and density stratification. Both random as well as stratified random sampling techniques were used to see their impact on the volume estimates. Field sampling was done in the plots of 0.1 ha size. The total growing stock in all types of forests in the study area was estimated to be 1.87 mill.m³, of which Sal Forest accounted for 1.32 mill.m³, Sal Mixed Forest for 0.09 mill.m³, Mixed Sal Forest for 0.08 mill.m³, Miscellaneous Forest for 0.06 mill.m³ and Forest Plantations for 0.02 mill.m³. The results were compared with an independent field-based inventory carried out by forest department. The two sampling methods were compared by ratioing of the mean of variance (gain in precision) and it was found that the timber volume estimates using stratified random sampling technique were 15 per cent more accurate than simple random sampling. The satellite image-based inventory using stratified random sampling was found to have about 90 per cent correspondence with the inventory done by the Forest Department.     

基于FDE-IRF的室内指纹定位方法

针对传统指纹库存在建立工作量大以及随机森林匹配误差大等问题,提出了一种基于指纹库自动扩充的改进随机森林指纹定位方法(FDE-IRF)以提升指纹库构建的效率和指纹匹配的精度. 该方法对传统全采样构建指纹库方法和随机森林回归定位方法进行改进,稀疏采样多时间段的指纹数据和Kriging插值方法组合补全未采样指纹点,提升建库效率,得到强代表性的指纹库. 同时,利用决策树加权策略改进传统随机森林平均投票的方式,根据袋外数据评估决策树的预测误差,分配相应的权重,提高该算法的回归准确率. 实验结果表明:该方法的平均定位误差为1.26 m,其误差值比同类方法至少降低14.3%,验证了算法的准确性和有效性.      

Influences of fragmentation on plant diversity: An observation in eastern Himalayan tropical forest

Tropical forest fragmentation has been a major concern towards biodiversity conservation. Indices to determine the community structure and their relationship with forest fragmentation have been a matter of investigation. Here, I investigated the plant diversity across a fragmentation gradient in a typical human-influenced forested landscape in eastern Himalaya. The stratification for guiding field sampling was done using satellite remote sensing derived forest type map at 1:50,000 scale. The results of 49 sample plots (nested quadrant of 20×20 m size) following stratified random sampling method were analysed. It was observed that high fragmented forests have fewer plant species, reduced anthropogenic use evidence and newer community types than medium and low fragment forests. In general, species diversity and species dominance were observed to be inversely proportional and directly proportional to forest fragmentation. Basal area followed a decreasing trend along fragmentation gradient. These results revealed that higher level of fragmentation permits low diversity in the eastern Himalayan tropical forests.     

Modeling the Potential Distribution of Pine Forests Susceptible to Sirex Noctilio Infestations in Mpumalanga,South Africa

Reducing the impact of the siricid wasp, Sirex noctilio is crucial for the future productivity and sustainability of commercial pine resources in South Africa. In this study we present a machine learning model that serves as a spatial guide and allows forest managers to focus their existing detection and monitoring efforts on key areas and proactively adopt the most appropriate course of intervention. We implemented the random forest model within a spatial framework to determine which pine forests in Mpumalanga are highly susceptible to S. noctilio infestations. Results indicate that a majority (63%) of pine forest plantations located in Mpumalanga have a high susceptibility (>70%) to S. noctilio infestation. A KHAT value of 0.84 and F measures above 0.87 indicate that the random forest model is a robust classifier that produces accurate results. Additionally, the use of the backward variable selection method enabled us to simplify the random forest modeling process and identify the minimum number of explanatory variables that offer the best discriminatory power and help in the empirical interpretation of the final random forest model. Overall, the results show that pine forests that experience stress caused by evapotranspiration and evaporation followed by rainfalls, especially during the summer months are more susceptible to S. noctilio infestations.     

Growing stock estimation through stratified sampling on satellite remote sensing data

Aerial photographs are being extensively used for forest surveys i.e. forest cover type mapping, assessment of growing stock, estimation of area, vegetation studies, etc. Satellite remote sensing technology offers new possibilities and scope for achieving some of the above applications with higher accuracy and reliability. The assessment of growing stock through subjective stratification has also become possible with increase in spatial and spectral resolution. In the present study, the LANDSAT TM FCC (1966) has been visually interpreted on the basis of tonal characteristics. Stratified random sampling method has then used for determination of number of sample units for collection of ground Inventory data. Using regression equations, the volume per hectare of individual forest cover types were calculated. Satellite remote sensing data has been used for initial stratification, distribution of sample plots and calculation of area under various forest cover types. Estimate has been made for available commecial and non-commercial growing stocks in the study area.     

森林资源监测中GF-2卫星影像波段配准误差分析

通过对GF-2卫星影像正射校正及波段模拟配准误差试验,分析GF-2卫星正射校正方法的选择以及不同配准误差下对GF-2卫星影像自动分类结果的影响;最后介绍GF-2遥感影像在森林资源监测应用中的初步测试。研究结果表明:正射校正时,当校正精度要求控制在RMS2时,控制点数量选择范围在85~95间较为合理,且控制点数在90个时,RMS值最小;经有理函数模型与卫片模型比较后,卫片模型校正精度较高;以目视判读为主时,实践中建议使用三次卷积重采样法输出结果最好;波段模拟配准误差试验中,配准误差与各地类面积变化间存在显著的线性关系;对于森林面积监测时,配准误差应小于0.3个像元。此研究可为新型国产卫星数据在森林资源监测中的应用提供参考。     

结合随机森林面向对象的森林资源分类

针对森林资源分类研究较少且缺少相对简单有效的方法的情况,提出一种结合面向对象和随机森林的森林资源分类方法。面向对象分割技术可减少“椒盐效应”,随机森林分类算法具有高准确度、抗噪声能力强、性能稳定等优势。鉴于此,通过调整面向对象的分割参数,构造最优特征空间及估算随机森林中决策树的数量等,构建了最优的面向对象随机森林分类模型。另外,选择了SVM算法作对比试验。试验结果显示,本文分类算法的总体精度达到83.34%,Kappa系数为0.7892,明显高于SVM,能够有效提高森林资源分类的精度。     

Predictive Analysis for Vegetation Biomass Assessment in Western Ghat Region (WG) Using Geospatial Techniques

Forests play a critical role in ecological functioning, global warming and climate change through its unique potential to capture and hold carbon (C). Biomass is one of the indicator of the status of forests hence accurate assessment and biomass mapping is important for sustainable forest management. The objectives of this study is to estimate above ground biomass (AGB) from field inventory data and to map AGB combining field inventory data, remote sensing and geo-statistical model. In the present study stratified random sampling were used for estimation of biomass in which 59 plots were laid down in different homogenous strata depending on the NDVI values for the region of Maharashtra Western Ghats. The above ground biomass from field ranged from 0.05 to 271 t-dry wt ha^?1 in which trees added maximum towards total biomass followed by shrubs and herbs. This paper evaluates the best vegetation indices to estimate biomass. This study was carried out by using Landsat TM satellite data and field inventory data in the Ratnagiri district of Maharashtra, India. A significant correlation was observed between biomass and vegetation indices. The best fit regression equation developed from field above ground biomass and NDVI with R² value of 0.61 was used for spectral modeling to estimate the geospatial distribution of AGB in the entire region. The results of spatial predictions Geostatistical technique and remotely sensed data as auxiliary variables were compared using statistical error methods. This study employed Mean error, Root-Mean-Square error, Average Standard error and Root-Mean Square Standardized error. The ME, RMSE, Average Standard error and Root-Mean Square Standardized error was 0.078, 8.032, 7.982 and 0.967 respectively. The results showed that cokriging technique is one of the geostatistical method for spatial predictions of biomass in the studied region. The present study revealed that remote sensing technique combined with field sampling provides quick and reliable estimates of above ground biomass and carbon pool and can be used as baseline information for further temporal studies of biomass status of the region and in planning of forest and natural resources management.     

基于GIS的森林资源变化研究

以黑龙江省汤旺河林业局部分区域森林资源为研究对象,以1968年和2004年森林分布图、小班数据库和其他数据资料为基础,以地理信息系统为技术支持,分析林地资源的数量、种类、空间分布及其森林资源的结构变化,在此基础上,调整恢复合理的森林结构,实现森林资源的永续利用。研究结果表明:有林地和非林地面积增加;针叶林所占比例减少,阔叶林增加;森林资源的结构不太合理,中龄林和近熟林面积占据较大比例。     

基于随机森林的遥感影像变化检测

随机森林是一种新兴的、高度灵活的机器学习算法，在预测和分类方面有着良好的稳定性，且算法性能要优于许多单预测器。鉴于此，本文提出了随机森林的遥感影像变化检测算法，利用熵率法对遥感影像进行超像素分割，获取最优分割结果；构建了基于随机森林的遥感影像变化检测模型，以所提取的Gabor特征和光谱特征作为模型输入进行训练和预测，并将有决策树的投票作为最终的变化检测结果。试验结果表明，本文所构建的随机森林变化检测模型在漏检率和虚检率上明显低于其他算法，且总体正确率高，在算法时间上也明显优于其他算法。