利用虚拟农业的虚拟现实研究

虚拟农业是农业科学和虚拟现实技术相结合的产物,它将彻底开辟农业研究方法的新途径,是一个新的研究方向.虽然其过程相当复杂,但是它将改变传统的科研、规划、教学方式,并且带来巨大的经济效益,其发展前景十分可观.本文通过对虚拟现实技术的分析,给出了基于虚拟现实技术的虚拟农业的基本概念和一般结构,深入探讨了虚拟现实与虚拟农业的联系和区别,并对虚拟农业的应用进行展望.     

Estimating woody browse abundance from aerial imagery

In the deciduous forests of the eastern US, timber harvest programmes are often designed to increase the availability of woody browse for terrestrial wildlife. However, assessing the efficacy of timber harvest at increasingly available browse has traditionally required labour‐intensive field‐based measurements of woody plant growth and abundance. The objective of this study was to use readily available digital aerial imagery to estimate the amount of woody browse in regenerating clearcuts in central West Virginia. Aerial imagery from the National Agriculture Imagery Program and woody browse data collected from 11 regenerating clearcuts in the summer of 2007 were used in this analysis. Red, green and blue visible bands, as well as a simple texture metric, were used to create a multiple linear regression model to predict the amount of woody browse. The final model exhibited large correlation (R ² = 0.94) and was statistically significant (F = 22.48, p = 0.0009), indicating that simple measures of image digital numbers and texture have potential utility in assisting forest and wildlife managers to assess habitat quality in forest regeneration areas.     

Assessment of forest damage caused by an ice storm using multi-temporal remote-sensing images: a case study from Guangdong Province

In early 2008, forest ecosystems in southern China suffered damage due to a severe ice storm disaster. The area and degree of forest damage caused by the ice storm was assessed using Satellite Pour l’Observation de la Terre (SPOT)-Vegetation images for Guangdong Province acquired between 1999 and 2008. By using the maximum value composition method and image thresholding techniques, the forest vegetation loss, expressed as the change in net primary productivity (NPP) and two indicators (I₁, I₂), was estimated. The damage threshold was determined by comparing the standard deviation of pixels of the undamaged areas in 2008 and other years without any disaster, which was 10%. The area of damaged forest vegetation was 47,670 km², with the northern Guangdong Province most seriously affected. The total loss of NPP for forest vegetation was 50,578,055 t (DW) year^?1, with 52 counties (43.7%) suffering forest vegetation damage. Evergreen coniferous forest was most widely affected, but evergreen broad-leaved forest was the most severely damaged vegetation type. Terrain topography influenced the damage to forest vegetation, which was found to increase with increasing elevation and slope gradient. The range and degree of damaged forest determined by remote-sensing data is consistent with the extent of the ice storm, indicating that this study provides a new approach for rapid assessment of forest disasters at a regional scale.     

Modelling the ancient maize agriculture potential of landforms in Tikal National Park,Guatemala

The ancient polity of Tikal has been extensively studied by archaeologists and soil scientists, but more information is needed to determine the specific subsistence and ancient farming techniques that sustained its inhabitants for more than eight centuries. Recent settlement, soil resource, and vegetation surveys were completed during a re-evaluation of the earthworks of Tikal. The objective of this research was to combine non-parametric multiplicative regression, stable carbon isotopes, soil properties, and remote-sensing data for cost-effective, predictive modelling of ancient maize (Zea mays L.) agricultural areas. The study area is positioned within a 300 km² region surrounding the Tikal site centre (17° 13′ 19.0″ N, 89° 27′ 25.2″ W). In the study area, ancient maize agriculture was determined using carbon (C) isotopic signatures of C₄ vegetation that were incorporated into the soil humin fraction. Probability models predicting C isotopic enrichment were used to outline areas of potential long-term maize agriculture. A binomial model predicted areas mainly along the bajo margins, indicating that these areas may have been used for sustained ancient maize agriculture. Upland areas with shallow Rendolls soil were found to lack strong C₄ isotopic signatures. They showed a long-term C₃ vegetation signature that could have supported native forest, silvicultural activities, or C₃ cropping practices (i.e. forest gardens). The mosaic of C₃ and C₄ signatures within the study site soils suggests that the Tikal area supported a variety of food production systems.     

网络虚拟存储技术的研究

虚拟存储不关心资源具体存储在哪个实体上,只负责数据的读写操作,使其存储的管理更加集中化。通过对网络虚拟存储技术中常用的协议进行分析的基础上,设计了网络虚拟存储系统。     

Geo-referencing forest field plots by co-registration of terrestrial and airborne laser scanning data

Remote sensing plays an important role within the field of forest inventory. Airborne laser scanning (ALS) has become an effective tool for acquiring forest inventory data. In most ALS-based forest inventories, accurately positioned field plots are used in the process of relating ALS data to field-observed biophysical properties. The geo-referencing of these field plots is typically carried out by means of differential global navigation satellite systems (dGNSS), and often relies on logging times of 15–20 min to ensure adequate accuracy under different forest conditions. Terrestrial laser scanning (TLS) has been proposed as a possible tool for collection of field data in forest inventories and can facilitate rapid acquisition of these data. In the present study, a novel method for co-registration of TLS and ALS data by posterior analysis of remote-sensing data – rather than using dGNSS – was proposed and then tested on 71 plots in a boreal forest. The method relies on an initial position obtained with a recreational-grade GPS receiver, in addition to analysis of the ALS and TLS data. First, individual tree positions were derived from the remote-sensing data. A search algorithm was then used to find the best match for the TLS-derived trees among the ALS-derived trees within a search area, defined relative to the initial position. The accuracy of co-registration was assessed by comparison with an accurately measured reference position. With a search radius of 25 m and using low-density ALS data (0.7 points m^?2), 82% and 51% of the TLS scans were co-registered with positional errors within 1 m and 0.5 m, respectively. By using ALS data of medium density (7.5 points m^?2), 87% and 78% of the scans were co-registered with errors within 1 m and 0.5 m of the reference position, respectively. These results are promising and the method can facilitate rapid acquisition and geo-referencing of field data. Robust methods to identify and handle erroneous matches are, however, required before it is suitable for operational use.     

Linear Spectral Mixing Model for estimating optically active components in estuarine waters of Patos Lagoon,Brazil

Understanding about type and concentration of components in large continental waterbodies is of great value to environmental studies. The synoptic view of multispectral remote-sensing images has the potential to systematically estimate important parameters like suspended solids (SS) and chlorophyll (Chl). However, measures derived directly from radiometric image data usually retrieve inaccurate estimations, preventing discrimination of the spectra and amount of specific components. This work proposes the application of Linear Spectral Mixing Model to estimate concentrations of SS and Chl in the Patos Lagoon estuary, Brazil, through Landsat-8 Operational Land Imager sensor data. The linear mixing model was applied to produce fraction images of SS, sandy bottom, and dissolved organic matter. Simple and multiple linear regressions were performed in order to produce empirical models confronting parameters measured in situ with traditional radiometric data from spectral bands and with the resulting fraction images. The proposed empirical models estimates reached concentration of SS (coefficient of determination, R² = 0.84) and Chl (R² = 0.77) in comparison to the data collected in situ. These results showed great potential for using Spectral Mixing Models to indirectly estimate water components by remote-sensing data.     

A multi-sensor approach for improving biodiversity estimation in the Hyrcanian mountain forest,Iran

ABSTRACT

Modelling tree biodiversity in mountainous forests using remote-sensing data is challenging because forest composition and structure change along elevation. Topographic variations also affect vegetation’s spectral and backscattering behaviour. We demonstrate the potential of multi-source integration to tackle this challenge in a mountainous part of the Hyrcanian forest in Iran. This forest is a remnant of a deciduous broadleaved forest with heterogeneous structure affected by natural and anthropogenic factors. The multi-source approach (i.e. Landsat Enhanced Thematic Mapper Plus (ETM +), Advanced Land Observing Satellite/ Phased Array type L-band Synthetic Aperture Radar (ALOS/PALSAR), and topographic variables) allows us to propose a biodiversity estimation model using partial least square regression (PLSR) calibrated and validated with limited field data. The effective number of species was calculated based on field measurements of the biodiversity in the study area. In order to model species diversity in more homogeneous extrinsic environmental conditions, we divided data into two groups with relatively uniform slope values. In each slope group, we modelled the correlation between observed biodiversity and satellite-derived data. For that, we followed three scenarios: (A) multispectral Landsat ETM + alone, (B) ALOS/PALSAR alone, and (C) inclusion of both sensors. In each scenario, elevation and slope data were also considered as predictors. We observed that in all scenarios, coefficient of determination (R²) in gentler slopes was higher than that in areas with steeper slopes (average difference in R²: ?R² = 0.21). The highest correlation was achieved by inclusion of synthetic aperture radar (SAR) and ETM + (R² = 0.87). The results clearly confirm that the multi-source remote-sensing approach can provide a practical estimate of biodiversity across the Hyrcanian forest and potentially in other deciduous broadleaved forests in complex terrain.     

Use of a ground‐based scanning lidar for estimation of biophysical properties of western larch (Larix occidentalis)

Ground‐based laser scanners represent a relatively new technology that promises to enhance the ability to remotely sense biophysical properties of vegetation. In this study, we utilized a commercially available discrete‐return ground‐based laser scanning system to sample properties of western larch (Larix occidentalis) in a northern Idaho forest. Three young trees <5 m in height were scanned before and after leaf abscission in the autumn of 2004. Leaf areas represented by the number of laser returns were estimated by subtracting leaf‐off laser returns from leaf‐on returns. Leaf areas represented by number of laser returns were significantly correlated with manual‐based estimates of leaf area (r ² = 0.822). Ratios of woody‐to‐total tree area were estimated based on number of laser returns from woody material. Ratios of woody‐to‐total area ranged from 0.24 to 0.58 for nine one‐metre sections of tree for which estimates were made. Ratios of woody‐to‐total area were also estimated using intensity of laser returns and fell near the range of estimates made using the number of laser returns. Improved estimation of leaf area, woody‐to‐total area ratios, and other biophysical parameters using ground‐based laser scanning technology may be possible with a careful consideration of instrument specifications and sampling design.     

Assessment of tsunami and anthropogenic impacts on the forest of the North Andaman Islands,India

Forests are being depleted drastically at higher rates to cater to the needs of growing population. In this context, an attempt was made to identify the drivers of forest changes on the vegetation of the North Andaman islands by broadly categorising the changes as anthropogenic and natural disturbances (tsunami) using satellite images of 1976, 1999 and 2005. The images were classified using visual interpretation technique to generate land cover maps of the area under study. A detailed change analysis of the 1976, 1999 and 2005 images showed that a high proportion of the natural vegetation has been converted into agriculture, settlement, sand and water. The overall forest change from 1976 to 2005 is 11,670 ha with a deforestation rate of 389 ha yr^?1. The tsunami of 26 December, 2004 was found to be a major cause of deforestation of coastal forests in the North Andaman Islands, deforesting an area of 3292.5 ha. Simulation of forest cover in the next 25 and 50 years predicted a deforestation of 13,100 and 22,700 ha with a corresponding increase in non‐forest land cover to 19,600 and 29,600 ha respectively. It is predicted that after 50 years the forest area of 131,200 ha, estimated from the 1999 satellite data, may reduce to 108,500 ha, if proper conservation measures are not taken.     

基于Unity3D的地铁三维虚拟漫游设计

随着虚拟现实技术的飞速发展,如何利用计算机展示现实场景的三维漫游效果,已成为当下研究的热点.以Unity3D为平台,利用3DMax软件进行场景建模,结合Unity3D自身强大的界面交互技术,完成整个南昌地铁一号线虚拟漫游系统的开发.最后通过地面站点全景的外链衔接,实现了地铁站内三维模型场景与地铁站外全景的一体化漫游功能.实践研究结果表明,整个虚拟漫游系统能够给用户带来直观的地铁漫游体验.     

Remotely sensing the ecological influences of ditches in Zoige Peatland,eastern Tibetan Plateau

Zoige Peatland in the eastern Tibetan Plateau, the largest alpine peatland in China, was widely ditched in 1970s for pasture expansion. The ditching is believed to have caused peatland degradation, but there is still no widespread agreement on this due to the absence of essential regional and temporal information about ditch drainage. Therefore, this study used both remote-sensing observations and field surveys to examine the ecological influences of ditching for this alpine peatland. In the study, ditch distribution was interpreted with remote-sensing imagery and the ecological responses were investigated with temporal observation by Moderate Resolution Imaging Spectroradiometer (MODIS) and field surveys. The results showed that there were ~1200 km ditches interpreted, mainly in three spatial patterns depending on hydro-geomorphologies. The MODIS enhanced vegetation index (EVI) was more sensitive to peatland surface water depth (R² = 0.678, P < 0.001) than the normalized difference water index (NDWI) (R² = 0.583, P < 0.001), because the latter would become saturated at a certain surface water depth (~50 cm in Zoige). The temporal MODIS imagery reflected the ecological responses of ditched peatland to drainage in terms of vegetation density and water conditions. This study indicated that ditching depressed the surface water depth of the Zoige Peatland in summer, but not to the extent of completely transforming peatland into steppe due to the recharging of local beneficial hydro-geomorphologies. The MODIS indices investigated in the study could be used to monitor the annual regional status of vegetation cover and surface water for Zoige peatland.     

基于VRML的在线虚拟现实场景设计与实现

介绍了构建在线虚拟现实场景的关键技术,提出基于VRML技术的虚拟现实场景构成和应用,利用VRML技术设计了在线虚拟现实的场景环境原型,通过结合VR技术和ASP技术实现了一个在Internet上表现的、能和用户交互的、可由用户设计的、可扩展的平台,让用户能够按照自己的意愿设置的虚拟现实场景应用系统.     

The application of a binary division procedure to the classification of forest subcategories using MODIS time-series data during 2000–2010 in China

Forests account for more than 23% of China’s total area. As the most important terrestrial ecosystem, forests have tremendous ecological value. However, it remains difficult to classify forest subcategories at the national scale. In this study, a newly developed binary division procedure was used to categorize forest areas, including their spatiotemporal dynamics, during the period 2000–2010. Time-series images acquired using the Moderate Resolution Imaging Spectroradiometer (MODIS), together with auxiliary data on land use, climate zoning, and topography, were utilized. Hierarchical classification and zoning were combined with remote-sensing auto-classification. Based on the forest extent mask, the state-level forest system was divided into four classes and 18 subcategories. The method achieved an acceptable overall accuracy of 73.1%, based on a comparison to the sample points of China’s fourth forest general survey data set. In 2010, the total forest area was 1.755 × 10⁶ km², and the total area of and shrubs was 4.885 × 10⁵ km². The total area of woodland increased by 2536.25 km² during the decade 2000–2010. The shrub subcategories exhibited almost no change during this time period; however, significant changes in forest area occurred in the mountainous region of Northeast China as well as in the hilly regions of Southern China. The main transformations took place in cold-temperate and temperate mountainous deciduous coniferous forest, subtropical deciduous coniferous forest, subtropical evergreen coniferous forest, and temperate and subtropical deciduous broadleaved mixed forests. The binary division procedure proposed herein can be used not only to rapidly classify more forest subcategories and monitor their dynamic changes, but also to improve the classification accuracy compared with global and national land-cover maps.     

VRML生成网络虚拟环境技术研究

虚拟现实建模语言（VRML）是虚拟现实技术与网络技术的融合，它已成为Internet三维虚拟世界的主要开发工具。文中深入分析了VRML创建网络虚拟环境的基本方法，并针对常规方法存在的不足，提出了改进意见。     

基于虚拟现实的三维城市漫游关键技术分析与实践

“虚拟城市”、“三维城市漫游”等技术引人城市规划、设计领域中,已经成为一个有效的辅助手段.结合虚拟现实的概念和Web3D虚拟现实技术的特点,探讨了三维城市漫游的特征及关键技术,包括三维模型的建立、相关软件技术运用、数据的获取及三维城市漫游的实践应用.     

Remote sensing estimates of boreal and temperate forest woody biomass: carbon pools, sources, and sinks

The relation between satellite measurements of the normalized difference vegetation index (NDVI), cumulated over the growing season, and inventory estimates of forest woody biomass carbon is estimated statistically with data from 167 provinces and states in six countries (Canada, Finland, Norway, Russia and the USA for a single time period and Sweden for two periods). Statistical tests indicate that the regression model can be used to represent the relation between forest biomass and NDVI across spatial, temporal and ecological scales for relatively long time scales. For the 1.42 billion ha of boreal and temperate forests in the Northern Hemisphere, the woody biomass carbon pools and sinks are estimated at a relatively high spatial resolution (8×8 km). We estimate the carbon pool to be 61±20 gigatons (10⁹) carbon (Gt C) during the late 1990s and the biomass sink to be 0.68±0.34 Gt C/year between the 1982 and 1999. The geographic detail of carbon sinks provided here can contribute to a potential monitoring program for greenhouse gas emission reduction commitments under the Kyoto Protocol.     

基于灾害仿真的虚拟应急演练系统

基于虚拟现实技术的虚拟应急演练有着广泛的应用,但现有演练系统往往缺少对灾害场景的有效仿真,以及预案支撑下的完整系统框架.针对上述问题,该文首先提出了一种面向应急演练的仿真系统VEDSimu,解决了实体间消息高效传输、大规模仿真模型计算问题;并基于VEDSimu开发预案脚本系统、预案推理机、考核评价以及虚拟现实客户端等其他模块,构建虚拟应急演练系统VEDSys.最后,结合VEDSys在实际企业虚拟消防演练中的应用,验证了系统的可行性、高效性与可扩展性.     

Estimating montane forest above-ground biomass in the upper reaches of the Heihe River Basin using Landsat-TM data

In this work, the results of above-ground biomass (AGB) estimates from Landsat Thematic Mapper 5 (TM) images and field data from the fragmented landscape of the upper reaches of the Heihe River Basin (HRB), located in the Qilian Mountains of Gansu province in northwest China, are presented. Estimates of AGB are relevant for sustainable forest management, monitoring global change, and carbon accounting. This is particularly true for the Qilian Mountains, which are a water resource protection zone. We combined forest inventory data from 133 plots with TM images and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) global digital elevation model (GDEM) V2 products (GDEM) in order to analyse the influence of the sun-canopy-sensor plus C (SCS+C) topographic correction on estimations of forest AGB using the stepwise multiple linear regression (SMLR) and k-nearest neighbour (k-NN) methods. For both methods, our results indicated that the SCS+C correction was necessary for getting more reliable forest AGB estimates within this complex terrain. Remotely sensed AGB estimates were validated against forest inventory data using the leave-one-out (LOO) method. An optimized k-NN method was designed by varying both mathematical formulation of the algorithm and remote-sensing data input, which resulted in 3000 different model configurations. Following topographic correction, performance of the optimized k-NN method was compared to that of the regression method. The optimized k-NN method (R² = 0.59, root mean square error (RMSE) = 24.92 tonnes ha^–1) was found to perform much better than the regression method (R² = 0.42, RMSE = 29.74 tonnes ha^–1) for forest AGB retrieval over this montane area. Our results indicated that the optimized k-NN method is capable of operational application to forest AGB estimates in regions where few inventory data are available.     

Remote-sensing assessment of forest damage by Typhoon Saomai and its related factors at landscape scale

The remote-sensing technique is a cost-effective tool for monitoring large-scale forest damage sustained by typhoon events. Taking Cangnan County as the study area, this study aimed to extract the spatial pattern of damaged forest and determine the influencing factors of Typhoon Saomai in 2006, using Landsat Enhanced Thematic Mapper Plus (ETM+) data before and after the typhoon event. The results showed that 183 km² of forest land were damaged by Typhoon Saomai. There was no obvious diverse influence on forest damage within 25 km of Saomai’s path, after that the area of damaged forest decreased rapidly. For the land uses of construction, crop, and grass, decrease in normalized difference vegetation index was considerable under 100 m elevation and the number of damaged forest pixels showed positive correlation with vegetation aggregation, because trees standing in isolation, alongside roads, or in small groupings were easily damaged. For forest land, the number of damaged forest pixels decreased with higher elevation and relative aspect; when the relative aspect was in the range 0–40°, the number of damaged forest pixels was highest. Considering the interactive effects of these factors on forest damage caused by the typhoon, vegetation aggregation had the strongest influence followed by elevation, land use, relative aspect, and distance from the typhoon’s path.