Digital enhancement as an aid to detecting patterns of vegetation stress using medium-scale aerial photography

The application of image processing algorithms, originally developed for satellite image analysis, has been shown to improve pattern recognition of environmental change and vegetation stress with medium-scale aerial photography. Image enhancement helps to identify subtle features and spatial patterns embedded in a digitized air photo transparency that might otherwise escape visual identification. Our procedure combines visual interpretation with computer-aided image enhancement, including Normalized Difference Vegetation Index (NDVI) and supervised and unsupervised classification. The motiviation for the application of these techniques came from the need to provide a multi-season record of environmental changes in the immediate vicinity of power generation facilities. The procedure involves simple, on-call, acquisition of colour infrared and colour aerial photography that can be electronically enhanced and evaluated, resulting in accurate, timely, and cost-efficient information on vegetation changes related to land management, weather, diseases, insects, or other environmental stressors.     

无人机载荷航拍控制系统设计

针对无人机(UAV)遥感航拍过程中相机载荷参数自动化控制与飞行航迹实时跟踪的问题,提出一种能自动完成相机载荷控制与航拍控制的设计方案.首先,系统根据实验要求实时获取所在地理位置信息及环境预判信息,再根据相机控制参数表进行参数编码;然后,通过通信口发送自定义协议指令集给硬件控制电路,完成相机载荷参数设置并进行拍摄,同时航迹规划软件实时记录飞行轨迹地理坐标信息.系统设计使硬件控制平台和软件数据处理相结合,实现软硬协同控制.经无人机飞行验证,与单一参数航拍控制模式相比,该系统能根据不同的拍摄环境和拍摄场景进行相机参数的自动化控制与飞行轨迹实施跟踪.     

Vegetated coastal dunes: growth detection from aerial infrared photography

Aerial infrared photography is used to detect topographic changes in vegetation-induced sand dunes of the North Carolina Outer Banks. High infrared reflectance produced by the mutual interdependence of pioneer dune vegetation and wind-blown sand accumulation makes possible the prediction of dune growth and deflation patterns in vegetated coastal dune systems.     

航拍磁带图像读取系统的研究与实现

航拍磁带图像读取系统主要用于读取记录了飞机上雷达所拍摄图像的磁带,通过计算机软硬件的结合,实现了记录在磁带上的数据的快速、准确读取以及相应的图像处理功能.该系统采用了最新的工控机配置,和工作站独立开来工作,极大地提高了磁带的读取速度.新的软件提供了更加人性化的界面,操作简洁方便,无需输入任何命令,只需用鼠标进行简单的点击就可完成所有的操作.     

On group assessment of utility and worth attributes using interpretive structural modeling

This paper develops a special purpose interpretive structural modeling methodology to determine single sink digraph tree structures for attribute assessment. Rather than force group response into a single sink structure the procedure allows a group to adapt a set of initially defined set of attribute elements to one for which a single sink structure is acceptable to the group. The single sink digraph structure is a vitally important one for decision and policy analysis as well as project selection and other areas. The results in this paper appear to be more efficient in utilization of group effort in determination of a structure for these important problems as contrasted with previous efforts using a general form of interpretive structural modeling.     

Mapping land cover from detailed aerial photography data using textural and neural network analysis

Automated mapping of land cover using black and white aerial photographs, as an alternative method to traditional photo‐interpretation, requires using methods other than spectral analysis classification. To this end, textural measurements have been shown to be useful indicators of land cover. In this work, a neural network model is proposed and tested to map historical land use/land cover (LUC) from very detailed panchromatic aerial photographs (5 m resolution) using textural measurements. The method is used to identify different land use and management types (e.g. traditional versus mechanized vineyard systems). These have been tested with known ground reference data. The results show the potential of the methodology to obtain automatic, historic, and very detailed cartography information from a complex landscape such as the mountainous and Mediterranean region to which it is applied here, and the advantages that this method has over traditional methods.     

Mapping the concentration and dispersion of dye from a long sea outfall using digitized aerial photography

Many long sea outfalls discharge sewage effluent into the sea surrounding the United Kingdom. To monitor the dispersion and dilution performance of existing or planned outfalls, tracers can be released into the sewage and the resultant plume tracked by boat. In recent years aerial photography has proved to be a useful adjunct to boat surveys as it provides a synoptic view of a plume at one instant, which is something that a boat survey is unable to do as a result of tides, winds and currents.

The aim of the survey reported here was to use aerial photography not just to provide a synoptic view for a boat survey but to produce maps of dye tracer plumes, to known levels of accuracy. Calibrated black-and-white aerial photographs were digitized and then manipulated on a digital image processor to enable the correlation of dye concentration in the sea with reflectance (r = 0.93, significant at the 99 per cent confidence level). This correlation was then used as the basis for predictive mapping of dye concentration on other digitized and calibrated black-and-white aerial photographs. As a result, detailed isopleth plots of dye concentration were prepared. The accuracy of these plots, which was determined by reference to boat-survey data, was 77-82 per cent at the 95 per cent confidence level for a seven-class classification increasing to 78-87 per cent at the 95 per cent confidence level for a four-class classification.     

基于改进SSD的航拍城市道路车辆检测方法

为提升无人机(UAV)航拍视角下城市道路车辆检测性能,基于SSD深度学习网络框架,改进并搭建了一种航拍城市道路车辆检测网络.一方面充分挖掘无人机航拍视角下车辆多为小目标的先验知识,利用K-means++聚类算法获取适应航拍车辆目标的默认候选框参数信息;另一方面,为保证小尺度目标特征的有效传递和准确提取,对基准SSD网络...     

Estimating pre-harvest production of maize in Kenya using large-scale aerial photography and radiometry

Pre-harvest production of maize in Kenya was estimated using radiometry and aerial photography. Twenty-five strata covering 61 000?km² contained 900 000 ha of maize. The ratio of near-infrared (NIR) to red reflected from maize fields was measured with airborne radiometers over 100 fields. The actual yields were measured immediately prior to harvesting. A regression (R² = 0·77) predicting yield from NIR/red was obtained. A systematic radiometric survey was conducted and the regression was used to estimate the pre-harvest yield in all maize growing strata. The average nation-wide yield was 372?t/km², giving a total production of 3360 kt.     

Classification of Australian forest communities using aerial photography, CASI and HyMap data

Within Australia, the discrimination and mapping of forest communities has traditionally been undertaken at the stand scale using stereo aerial photography. Focusing on mixed species forests in central south-east Queensland, this paper outlines an approach for the generation of tree species maps at the tree crown/cluster level using 1 m spatial resolution Compact Airborne Spectrographic Imager (CASI; 445.8 nm–837.7 nm wavelength) and the use of these to generate stand-level assessments of community composition. Following automated delineation of tree crowns/crown clusters, spectral reflectance from pixels representing maxima or mean-lit averages of channel reflectance or band ratios were extracted for a range of species including Acacia, Angophora, Callitris and Eucalyptus. Based on stepwise discriminant analysis, classification accuracies of dominant species were greatest (87% and 76% for training and testing datasets; n = 398) when the mean-lit spectra associated with a ratio of the reflectance (ρ) at 742 nm (ρ₇₄₂) and 714 nm (ρ₇₁₄) were used. The integration of 2.6 m HyMap (446.1 nm–2477.8 nm) spectra increased the accuracy of classification for some species, largely because of the inclusion of shortwave infrared wavebands. Similar increases in accuracy were achieved when classifications of field spectra resampled to CASI and HyMap wavebands were compared. The discriminant functions were applied subsequently to classify crowns within each image and produce maps of tree species distributions which were equivalent or better than those generated through aerial photograph interpretation. The research provides a new approach to tree species mapping, although some a priori knowledge of the occurrence of broad species groups is required. The tree maps have application to biodiversity assessment in Australian forests.     

The estimation of the surface moisture of a vegetated soil using aerial infrared photography

The bidirectional reflectance of near infrared wavelengths of electromagnetic radiation from a vegetation canopy is primarily determined by the relative area and reflectance of the canopy and canopy dependent components: leaves, non-green vegetation, soil and shadow. It has been shown that when the percentage cover of leaves and non-green vegetation are both known and constant and the effect of shadow is minimal, then the near infrared bidirectional reflectance from the-canopy is negatively related to surface soil moisture.

This study was based on the above observation to estimate surface soil moisture of a vegetated soil from remotely sensed measurements of near infrared bidirectional reflectance.

The near infrared bidirectional reflectance, surface soil moisture and vegetation cover were measured at 10 heathland sites on 18 dates. The surface soil moisture was significantly related (at better than the 1 per cent level) to the Y axis intercept, when near infrared bidirectional reflectance (Y) was regressed against the percentage cover of green vegetation (X). This relationship between soil moisture and canopy reflectance was then used to enable the surface soil moisture of vegetated heathland soil to be estimated by means of five flights of black and white infrared aerial photography. It proved possible to estimate the surface soil moisture of the vegetated soil with an accuracy of ±18·4 percent at the 95 percent confidence limits. Possible improvements to the technique are discussed.     

Critical assessment of vegetation indices from AVHRR in a semi-arid environment

The most frequently used vegetation index (VI), the Normalized Difference Vegetation Index (NDVI) and its variants introduced recently to correct for atmospheric and soil optical response such as Global Environment Monitoring Index (GEMI) and Modified Soil-Adjusted Vegetation Index (MSAVI) are evaluated over a Sahelian region. The usefulness and limitations of the various vegetation indices are discussed, with special attention to cloud contamination and green vegetation detection from space. The HAPEX Sahel database is used as a test case to compare these indices in arid and semi-arid environments. Selected sites are characterized by sparse vegetation cover and day-to-day variability in atmospheric composition. Simulated indices values behaviour at the surface level shows that these VIs were all sensitive to the presence of green vegetation but were affected differently by changes in soil colour and brightness. We showed that GEMI is less sensitive to atmospheric variations than both NDVI and MSAVI since it exhibits a high atmospheric transmissivity over its entire range for various atmospheric aerosol loadings and water vapour contents. These results were first tested on a vegetation gradient, and secondly evaluated on a transect which encompasses various soils formations. On the vegetation gradient, it was found that GEMI computed from measurements at the top of the atmosphere is invariable from one day to the next. On the bare soils transect, MSAVI calculated at the surface level, has shown a great insensitivity to soil optical responses modifications, while GEMI exhibits from space noticeable variability in this bright soil context. Finally, it was illustrated that GEMI exhibits interesting properties for cloud detection because of the strong decrease of its value on cloudy pixels.     

Comparison of hyperspectral imagery with aerial photography and multispectral imagery for mapping broom snakeweed

Broom snakeweed (Gutierrezia sarothrae (Pursh) Britt. & Rusby) is one of the most widespread and abundant rangeland weeds in western North America. The objectives of this study were to evaluate airborne hyperspectral imagery and compare it with aerial colour-infrared (CIR) photography and multispectral digital imagery for mapping broom snakeweed infestations. Airborne hyperspectral imagery along with aerial CIR photographs and digital CIR images was acquired from a rangeland area in south Texas. The hyperspectral imagery was transformed using minimum noise fraction (MNF) and then classified using minimum distance, Mahalanobis distance, maximum likelihood, and spectral angle mapper (SAM) classifiers. The digitized aerial photographs and the digital images were respectively mosaicked as one photographic image and one digital image; these were then classified using the same classifiers. Accuracy assessment showed that the maximum likelihood classifier performed the best for the three types of images. The best overall accuracies for three-class classification maps (snakeweed, mixed woody and mixed herbaceous) were 91.0%, 92.5%, and 95.0%, respectively, for the CIR photographic image, the digital CIR image and the MNF-transformed hyperspectral image. Kappa analysis showed that there were no significant differences in maximum likelihood-based classifications among the three types of images. These results indicate that airborne hyperspectral imagery along with aerial photography and multispectral imagery can be used for monitoring and mapping broom snakeweed infestations on rangelands.     

Using aerial imagery and digital photography to monitor growth and yield in winter wheat

Monitoring wheat (Triticum aestivum L.) performance throughout the growing season provides information on productivity and yield potential. Remote sensing tools have provided easy and quick measurements without destructive sampling. The objective of this study was to evaluate genetic variability in growth and performance of 20 wheat genotypes under two water regimes (rainfed and irrigated), using spectral vegetation indices (SVI) estimated from aerial imagery and percentage ground cover (%GC) estimated from digital photos. Field experiments were conducted at Bushland, Texas in two growing seasons (2014–2015 and 2015–2016). Digital photographs were taken using a digital camera in each plot, while a manned aircraft collected images of the entire field using a 12-band multiple camera array Tetracam system at three growth stages (tillering, jointing and heading). Results showed that a significant variation exists in SVI, %GC, aboveground biomass and yield among the wheat genotypes mostly at tillering and jointing. Significant relationships for %GC from digital photo at jointing was recorded with Normalized Difference Vegetation Index (NDVI) at tillering (coefficient of determination, R² = 0.84, p< 0.0001) and with %GC estimated from Perpendicular Vegetation Index (PVI) at tillering (R² = 0.83, p< 0.0001). Among the indices, Ratio Vegetation Index (RVI), Green-Red VI, Green Leaf Index (GLI), Generalized DVI (squared), DVI, Enhanced VI, Enhanced NDVI, and NDVI explained 37–99% of the variability in aboveground biomass and yield. Results indicate that these indices could be used as an indirect selection tool for screening a large number of early-generation and advanced wheat lines.     

Photo-realistic visualization of seismic dynamic responses of urban building clusters based on oblique aerial photography

Highly realistic visualizations of seismic dynamic responses of building clusters are critical for earthquake safety education. To this end, a photo-realistic visualization method of the seismic dynamic responses of urban building clusters is proposed based on oblique aerial photography. Specifically, a sparsification algorithm of aerial photograph footprints and the model optimization solutions are designed to reduce the size of a city model reconstructed by oblique aerial photography. A building segmentation algorithm based on Boolean operations and building footprints is designed to separate buildings from a reconstructed three-dimensional city model. A visualization algorithm for the seismic dynamic responses of building clusters is designed based on the Callback mechanism, by which the shaking process of building clusters can be realistically displayed according to the results of a city-scale nonlinear time-history analysis. New Beichuan City in China is adopted as a case study to visualize seismic dynamic response. The visualization produced by the proposed method is more realistic than that of the finite element method and can support decision making on earthquake safety actions. The outcome of this study provides well-founded and photo-realistic scenes of the seismic dynamic response of building clusters and has promising application prospects for earthquake safety education.     

Aerial photography for biomass assessment in the intertidal zone

Abstract

A method for quantitative biomass assessment of macrophytes growing at intertidal mudflats was recently developed using aerial false-colour photography. A verification of the method has been carried out and subsequently the method has been applied over a vast area (400 km²). The method developed is based on a direct relationship between colour densities and field biomass at a number of sample plots. This relationship includes the necessary radiometric corrections. It appeared that the bidirectional reflectance properties of the macrophytes play a minor role, probably because of the flat character of theintertidal area and the small thicknessof the macrophyte layer. It is concluded that the method is highly reliableand very well applicable over extended areas.     

Multi-scale linkages between topographic attributes and vegetation indices in a mountainous landscape

This paper addresses a few issues that are fundamental for the understanding of vegetation-topography relations: scale dependency, seasonal variability, and importance of observing individual properties. Particularly, it uses two statistical tools - Pearson's r and Moran's I - to define relationships of several topographic attributes with the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Infrared Index (NDII), and their seasonal changes (from May to July and then September) in the Mediterranean-type landscape of the Santa Monica Mountains, California. The analyses are conducted at both the original data resolution and 20 aggregated resolutions, covering a total range of 30 m to 1500 m, so that topography-vegetation relationships can be compared at different scales. Large sample sizes have supported the significance of the following main findings for this landscape. First, elevation, slope, and southness are the most relevant primary topographic attributes among the tested attributes and their importance changes across seasons. Second, NDVI, NDII, and their seasonal variations have notably different relationships (including no relationship) with topography. Third, the observed topography-vegetation correlations (r) tend to change - typically increase - with the coarsening of spatial scale. Lastly, the spatial autocorrelation of vegetation variables and topographic attributes are often comparable, and the comparability is more apparent when topography-vegetation correlations are stronger. In all, the topography-NDVI/NDII relations defined in this paper may improve the understanding of the multi-scale and property-specific role that mountain topography plays in the formation and seasonal change of vegetation patterns.     

基于无人机航拍技术的地面施工设备质量远程控制系统设计

传统控制系统在控制地面施工设备质量时,很容易受到外界因素影响,出现误差。为了解决这一问题,基于无人机航拍技术设计了一种新的地面施工设备质量远程控制系统,系统硬件结构分为接入层、管理层和应用层,控制主机选用HT500主机,选用的传感器为光纤传感器,以DSP信号处理器处理信息。软件共分为地面施工设备信息采集、地面施工设备信息处理、远程控制工作实现和控制结果显示四步。为验证系统效果,与传统系统进行对比,结果表明,设计的控制系统在控制过程中产生的误差很小,具备很强的控制能力,值得推广使用。     

Imparting desired attributes in structural design by means of multi-objective optimization

Commonly available optimization methods typically produce a single optimal design as a constrained minimum of a particular objective function. However, in engineering design practice it is quite often important to explore as much of the design space as possible, with respect to many attributes, to discover what behaviors are possible and not possible within the initially adopted design concept. This paper shows that the very simple method of the sum of weighted objectives is useful for such exploration. By geometrical argument it is demonstrated that if every weighting coefficient is allowed to change its magnitude and its sign then the method returns a set of designs that are all feasible, diverse in their attributes, and include the Pareto and non-Pareto solutions, at least for convex cases. Numerical examples in the paper include the case of an aircraft wing structural box with thousands of degrees of freedom and constraints, and over 100 design variables, whose attributes are structural mass, volume, displacement, and frequency. The weighted coefficients method is inherently suitable for parallel, coarse-grained implementation that enables exploration of the design space in the elapsed time of a single structural optimization.