Near real-time high-resolution airborne camera,AEROCam, for precision agriculture

Precision agriculture often relies on high-resolution imagery to delineate the variability within a field. Airborne Environmental Research Observational Camera (AEROCam) was designed to meet the needs of agriculture producers, ranchers, and researchers, who require high-resolution imagery in a near real-time environment for rapid decision support. AEROCam was developed and operated through a unique collaboration between several departments at the University of North Dakota, including the Upper Midwest Aerospace Consortium (UMAC), the School of Engineering and Mines, and flight operations at the John D. Odegard School of Aerospace Sciences. AEROCam consists of a Redlake MS4100 area-scan multi-spectral digital camera that features a 1920 × 1080 CCD array (7.4-μm detector) with 8-bit quantization. When operated at ～2 km above ground level, multispectral images with four bands in the visible and near infrared have a ground sample distance of 1 m with a horizontal extent of just over 1.6 km. Depending on the applications, flying at different altitudes can adjust the spatial resolution from 0.25 to 2 m. Rigorous spectral and radiometric calibrations allow AEROCam to be used in a variety of applications, qualitative and quantitative. Equipped with an inertial measurement unit (IMU) system, the images acquired can be geo-referenced automatically and delivered to end users near real time through our Digital Northern Great Plains system (DNGP). The images are also available to zone mapping application for precision farming (ZoneMAP), an online decision support tool for creating management zones from remote sensing imagery and data from other sources. Operational since 2004, AEROCam has flown over 250 sorties and delivered over 150,000 images to the users in the Northern Great Plains region, resulting in numerous applications in precision agriculture and resource management.     

Visualizing aerial wildlife movements: Internet sources of Doppler radar for the classroom

Doppler radar imagery is a useful classroom tool for studying the movement and spatio-temporal distribution of animals. In this paper we present a basic introduction to Doppler radar and the base products used to garner biological and geographical data. We draw upon imagery depicting bat and avian movements to illustrate how radar imagery may be beneficially used in the classroom to examine habitat use and species distribution at the landscape scale. Additionally we provide references for data acquisition and real-time animated imagery available on the Internet. We hope the information and imagery provided here will help instructors enrich the classroom experience for their students, while at the same time demonstrating real-world applications for the use of radar imagery in biogeographic studies.     

Evaluation of diverse classification approaches for land use/cover mapping in a Mediterranean region utilizing Hyperion data

Information on Earth's land surface cover is commonly obtained through digital image analysis of data acquired from remote sensing sensors. In this study, we evaluated the use of diverse classification techniques in discriminating land use/cover types in a typical Mediterranean setting using Hyperion imagery. For this purpose, the spectral angle mapper (SAM), the object-based and the non-linear spectral unmixing based on artificial neural networks (ANNs) techniques were applied. A further objective had been to investigate the effect of two approaches for training sites selection in the SAM classification, namely of the pixel purity index (PPI) and of the direct selection of training points from the Hyperion imagery assisted by a QuickBird imagery and field-based training sites. Object-based classification outperformed the other techniques with an overall accuracy of 83%. Sub-pixel classification based on the ANN showed an overall accuracy of 52%, very close to that of SAM (48%). SAM applied using the training sites selected directly from the Hyperion imagery supported by the QuickBird image and the field visits returned an increase accuracy by 16%. Yet, all techniques appeared to suffer from the relatively low spatial resolution of the Hyperion imagery, which affected the spectral separation among the land use/cover classes.     

基于GIS和RS的矿区土地利用变化分析

以1997年的TM和2007年的ASTER遥感影像数据的为主要数据源,利用遥感和地理信息系统技术,对影像进行监督分类获得土地利用变化的数据,并计算出研究区的土地利用类型的动态转移矩阵、LUCC幅度、动态度和状态指数等指数模型,定量分析研究区的土地利用变化情况。结果表明：1997-2007年间,耕地和草地大量减少,其他土...     

Advances in active fire detection using a multi-temporal method for next-generation geostationary satellite data

ABSTRACT

A vital component of fire detection from remote sensors is the accurate estimation of the background temperature of an area in fire's absence, assisting in identification and attribution of fire activity. New geostationary sensors increase the data available to describe background temperature in the temporal domain. Broad area methods to extract the expected diurnal cycle of a pixel using this temporally rich data have shown potential for use in fire detection. This paper describes an application of a method for priming diurnal temperature fitting of imagery from the Advanced Himawari Imager. The BAT method is used to provide training data for temperature fitting of target pixels, to which thresholds are applied to detect thermal anomalies in 4?μm imagery over part of Australia. Results show the method detects positive thermal anomalies with respect to the diurnal model in up to 99% of cases where fires are also detected by Low Earth Orbiting (LEO) satellite active fire products. In absence of LEO active fire detection, but where a burned area product recorded fire-induced change, this method also detected anomalous activity in up to 75% of cases. Potential improvements in detection time of up to 6?h over LEO products are also demonstrated.     

Remote sensing for geology,geomorphology and lineament study of Vindhyan basin,north of Shivpuri,Madhya Pradesh

The study area comprises Bundelkhand Granite of Archaean age in the east, unconformably overlain by Upper Vindhyan sequence, ranging from Upper Kaimur Sandstone to Lower Bhander Sandstone Groups, in the west. Geomorphologically, the area has been divided into three geomorphic provinces viz. (1) Bundelkhand inselberg — pediplain, (2) Vindhyan structural plateau, consisting of two major sub-levels of Upper and Lower Bhander Sandstone Groups and two minor sub-levels of Upper and Lower Rewa Sandstone Groups, separated by escarpment and/or valleys, and (3) Chambal alluvial plain. Photo-interpretation and field studies indicate that there are three sets of lineament trends in the area out of which the NNW-SSE trend comes out very strongly on imagery and is correlatable with basement fracture trend of Bundelkhand massif. The synoptic view through imagery also gives the impression that the course of Chambal river towards north and west is controlled by a major lineament, possibly a regional fault trending NE-SW. The NNW-SSE lineament trend mentioned above then probably reflects tension release aspect of the faulting. The field check has brought out some very broad, gentle warps also with NNE-SSW trend in the area. The paper presents the salient observations on geological, structural and geomorphological studies for Shivpuri area based on remote-sensing techniques and their utility for such regional investigations.     

An Agricultural Monitoring System Based on the Use of Remotely Sensed Imagery and Field Server Web Camera Data

In this study, the authors develop an integrated agricultural monitoring system based on the use of high-spatial-resolution remote sensing imagery and Field Server data for a cabbage field in Tsumagoi, Gunma Prefecture, Japan. The use of the integrated system made it possible to verify the accuracy of cabbage coverage estimated from high-spatial-resolution QuickBird imagery using an unmixing method, because the authors were able to remotely examine cabbages growing in real-time using a Field Server web camera linked to their laboratory via the Internet. Using the developed integrated system, they produced a cabbage coverage map that provided information on cabbage growth that could be used for agricultural land management, particularly with regard to the application of fertilizer and forecasting crop production. The results support the validity of using remote sensing technology in conjunction with a Field Server to manage agricultural crop land.     

Direct georeferencing of oblique and vertical imagery in different coordinate systems

Reconstruction of 3D models through integrating vertical and oblique imagery has been studied extensively. For a 3D reconstruction, object point cloud coordinates could be calculated using direct georeferencing (DG) obtained from the direct orientation data of a GPS/INS system. This paper implemented DG approaches for vertical and oblique imagery in the earth centered earth fixed frame (e-frame), local tangent frame (l-frame), and map projection frame (p-frame), respectively. In the p-frame, the earth curvature correction formulas were derived through naturalizing oblique imagery to vertical imagery to achieve a high positioning precision. Five basic stereo-pair models for vertical and oblique imagery were simulated to verify the positioning accuracy of different frames. Simulation experiments showed that DG in the e-frame and l-frame of these five scenarios were rigorous, and no systematic errors were imported by the DG model as these frames are Cartesian. DG in the p-frame has obvious systematic errors which are aroused by the earth curvature and projection deformation unconformity in the vertical and horizontal directions. These errors, however, can be compensated effectively through correcting image coordinates of the oblique imagery by extending the standard image coordinate correction approach and the exterior orientation (EO) height term. After the correction, the absolute positioning error is lower than 1/20 GSD for simulation test-1. In the p-frame, the process is straightforward, and it is convenient for producing maps. For high accuracy DG, though, it is recommended to adopt e-frame or l-frame options.     

TM/ETM+影像大气校正产品质量评价方法研究

对TM/ETM+的大气校正产品质量进行评价是改进影像质量的必要手段。提出采用已有高质量TM/ETM+表面反射率产品作为参考影像评价TM/ETM+的大气校正产品质量的方法。该方法设计了面向产品质量评价的影像光谱采样方案和多时相遥感影像PIFs(pseudo invariant features,PIFs)样本自动识别方法,能对多时相/季相TM/ETM+大气校正产品质量进行评价。试验表明该方法能准确识别PIFs地物,评价结果真实反映了遥感影像大气校正结果准确度。方法具有快速和低成本等特点,能开展规模化应用。     

浅谈农村集体土地所有权确权登记发证地理信息工程

农村集体土地确权登记发证工作涉及广大农民切身利益,对农村经济社会发展影响巨大而深远。运用现代测绘地理信息技术,通过外业调查和内业处理,利用第二次土地调查成果,形成从土地数据的获取、处理、存储、汇总分析到信息服务全过程的地籍管理信息系统。农村集体土地确权登记发证工作必须严把质量关,建立质量保证体系;对工程质量进行全面检查,保证各项成果准确无误。     

Downscaling in remote sensing

Downscaling has an important role to play in remote sensing. It allows prediction at a finer spatial resolution than that of the input imagery, based on either (i) assumptions or prior knowledge about the character of the target spatial variation coupled with spatial optimisation, (ii) spatial prediction through interpolation or (iii) direct information on the relation between spatial resolutions in the form of a regression model. Two classes of goal can be distinguished based on whether continua are predicted (through downscaling or area-to-point prediction) or categories are predicted (super-resolution mapping), in both cases from continuous input data. This paper reviews a range of techniques for both goals, focusing on area-to-point kriging and downscaling cokriging in the former case and spatial optimisation techniques and multiple point geostatistics in the latter case. Several issues are discussed including the information content of training data, including training images, the need for model-based uncertainty information to accompany downscaling predictions, and the fundamental limits on the representativeness of downscaling predictions. The paper ends with a look towards the grand challenge of downscaling in the context of time-series image stacks. The challenge here is to use all the available information to produce a downscaled series of images that is coherent between images and, thus, which helps to distinguish real changes (signal) from noise.     

GIS专业云计算人才培养模式探索

云计算技术的出现对传统GIS行业带来了巨大的影响以及良好的发展前景,结合云计算技术发展GIS系统及服务已成为GIS行业的发展趋势。因此,云计算技术的培养在GIS专业人才培养中十分重要,然而目前GIS专业的传统课程却没有涉及云计算技术方面,学生无法掌握目前行业所需要的云计算相关知识及技能。为解决这一问题,本文根据云计算技术在GIS中的知识模块,分析了通过竞赛提高学生云计算能力的方式,探索了"以赛促学"的培养模式,为培养高素质GIS专业云计算人才培养提供了新的方法。     

济南市土地利用变化监测分析

济南作为山东省省会城市,在城市发展与土地利用变化方面应做到合理监测。本文以山东省济南市为研究对象,对济南市的土地遥感影像图进行分类。利用2005年和2016年济南市区Landsat遥感影像为基础数据,结合济南市矢量边界文件,对济南市的遥感影像图进行处理,通过目视解译,建立合理的训练样本,再结合野外调查的结果,制作济南市的土地利用分类图,根据分类结果对济南市土地利用变化进行分析与评价,为今后的济南市土地利用提供科学的依据和合理的建议[1]。     

Remote perceiving: A step toward a unified science of remote sensing

In a previous article (Hoffman & Conway, 1989), we reviewed some of the available psychological research that pertains to remote sensing. We focused on two major problem areas: Research on the knowledge of expert interpreters of remotely‐sensed imagery, and research on the use of color in graphic displays. Here, we pursue one of the broad implications of the research ‐ that the field of remote sensing can benefit by incorporating research methods and ideas from experimental psychology. From the experimental psychology viewpoint, “remote sensing”; is actually a misnomer when used to denote a field or area of scientific inquiry. Remote perceiving, as a total process, depends not only on the technology of remote sensing, but also depends critically on the ability of humans to interpret remote sensing displays. This perspective is contrasted with traditional approaches to remote sensing. The discussion involves some ideas about the theoretical and methodological foundations of remote sensing as a unified science.     

试论地理国情监测专业的人才培养和学科体系

地理国情监测是我国提出的一项国家战略,已经成为我国测绘地理信息事业今后20年发展的重要内容,是测绘地理信息部门未来的重要职责。人才是地理国情监测的第一资源,培养地理国情监测的优秀人才是地理国情监测的基础性工作。本文在对地理国情监测的基础理论和支撑技术进行分析的基础上,从地理国情监测工作的需求出发,立足于科学发展和学科前沿,对地理国情监测的学科体系和人才培养进行了分析和探讨。     

遥感科学与技术专业建设中的几个关键问题

根据遥感专业发展特点及学生具体情况,在分析遥感科学与技术专业现状的基础上,从师资队伍建设和方向凝练、课程体系建设以及人才培养模式3个方面探讨了遥感科学与技术专业的建设情况,并结合南京信息工程大学的具体情况进行了总结与探讨,使该专业能够适应我国遥感科学技术的发展和人才培养的需要。     

结合空间分析的面向对象无人机影像土地利用分类

利用高分辨遥感影像进行土地利用分类,为农村土地利用动态监测及土地综合整治快速地提供基础地理空间数据。以高分辨无人机影像为数据源,研究利用面向对象多尺度分割技术结合GIS空间分析对影像进行土地利用分类。根据对象内同质性高、对象间异质性高的准则,引入加权局部方差与空间自相关指数构建全局最优分割非监督评价指数,然后利用最邻近分类器对影像进行分类。实验结果表明,该方法减少人工目视确定最优分割尺度的主观性,能够避免某些地物不能被有效归类的现象,在单一尺度下获得较高的分类精度。     

利用雷达干涉数据进行城市不透水层百分比估算

人工不透水层是城市地区的重要特征.作为城市生态环境的关键指数,不透水层百分比(Impervious Surfaces Percentage, ISP)常用于城市水文过程模拟、水质面源污染及城市专题制图等研究中.本文利用ERS-1/2 重复轨道雷达干涉数据,采用分类与回归树(CART)算法探究了雷达遥感在城市ISP估算中的可行性和潜力,并与SPOT5 HRG光学遥感图像的估算结果进行了分析比较.香港九龙港岛实验区的初步研究结果表明,雷达干涉数据在城市不透水层研究中具有一定的应用潜力,特别是裸土和稀疏植被的ISP估算结果要好于光学遥感,这主要得益于雷达干涉数据(特别是长时间相干图像)在人工建筑物和裸土或稀疏植被之间具有很强的区分能力,另外,雷达干涉数据和光学遥感数据间的融合能够提高ISP估算精度.     

基于空间共现核的遥感影像分类

采用了基于模糊关系的图像空间共现核来进行高分辨率遥感影像的分类。首先分析了遥感影像的特点,指出其不存在绝对的参考帧。针对该特点,采用了具有较好方向不变性的描述子MROGH（multi-support region order-based gradient histogram）来进行遥感影像底层特征的描述;随后针对图像编码时的软编码情形采用了基于模糊关系的图像空间共现核来构建遥感影像的全局特征汇聚。在公用基准数据集上进行的遥感影像分类实验表明,采用本文方法得到的分类正确率显著优于传统的方式。此外,针对遥感影像分类时采用的不同分类框架进行了评估。     

基于CNN海上钻井平台检测模型的构建及训练算法分析

卷积神经网络(CNN)是深度学习(DL)中最具代表性的一种网络结构。合成孔径雷达(SAR)图像具有位置结构关系,CNN模型可以利用图像的位置结构关系,能够更好地提取图像特征,因此更适合采用CNN模型检测海洋目标。本文首先基于CNN框架构建了海上钻井平台检测的DL模型Ocean TDAx,并对模型进行训练和测试。试验结果表明,Ocean TDA9模型精度最高。然后针对Ocean TDA9模型,采用Adam、RMSprop、Stochastic gradient descent (SGD)、Adagrad、Momentum等7种模型训练算法进行试验,比较不同算法的训练损失和精度与训练批次的相关性。最后基于渤海海域的极化SAR数据,对提出的Ocean TDA9模型、已有的CNN模型及VGG模型进行海上钻井平台检测对比。结果表明,构建的Ocean TDA9模型在钻井平台检测中整体性能优良。