三维激光扫描技术在数字矿山领域的应用

随着数字矿山概念的提出,矿山管理对空间三维信息的需求也显得更加迫切,三维可视化的管理模式已经成为数字矿山的主要内容之一,而目前常规的测量方式所获取的数据很难满足三维数字矿山的需要。三维激光扫描技术具有高分辨率、高采样率以及非接触式测量优势,非常适用于获取矿山的复杂表面和高危区域的空间三维信息。本文结合三维激光扫描的技术优势探讨该技术在数字矿山中的应用和方法,总结了三维激光扫描技术在数字矿山领域的应用方向。     

Monitoring disasters with a constellation of satellites – type examples from the International Charter ‘Space and Major Disasters’

In the case of a major disaster, information derived from satellite observation is not only highly useful, it may at times be indispensable because of the damage caused by the disaster to ground infrastructure. The International Charter ‘Space and Major Disasters’ (‘the Charter’) has been one of the primary sources of satellite data for the past 11 years to cover events like floods, fires, tsunamis, ocean storms, earthquakes, volcanic eruptions and oil spills. With the growing membership of the Charter, an increasingly large number of sensors are now available, which can be planned with the required temporal frequency and spectral range to cover a disaster event. Some of the type Charter activation cases are reported in this article to demonstrate the innovative use of multi-satellite imagery for disaster response.     

Characterizing wetland dynamics: a post-classification change detection analysis of the East Kolkata Wetlands using open source satellite data

The East Kolkata Wetlands is a unique resource recovery system. The Ramsar Convention recognized it as a ‘Wetland of International Importance’ in August 2002. However, the long-term resource exploitation and land use changes in the dynamic ecosystem have resulted in non-linear environmental responses. This is an attempt using open source remote sensing datasets to capture the spatio-temporal transformation of the wetland resulting from various anthropogenic activities. Landsat MSS and TM imageries of 1973, 1980, 1989, 2001 and 2010 were classified using Maximum Likelihood Classifier to monitor the wetland change; however, to study wetland dynamics, the post-classification wetland change detection maps have been generated for two temporal phases, i.e. 1973–1989 and 1989–2010. This study finds that the area under wetlands has reduced comprehensively in the past 40 years due to the conversion of wetlands into various other uses such as urban expansion of the Kolkata metropolitan city.     

Change detection of surface mining activity and reclamation based on a machine learning approach of multi-temporal Landsat TM imagery

Being able to quantify land cover changes due to mining and reclamation at a watershed scale is of critical importance in managing and assessing their potential impacts to the Earth system. In this study, a remote sensing-based methodology is proposed for quantifying the impact of surface mining activity and reclamation from a watershed to local scale. The method is based on a Support Vector Machines (SVMs) classifier combined with multi-temporal change detection of Landsat TM imagery. The performance of the technique was evaluated at selected open mining sites located in the island of Milos in Greece. Assessment of the mining impact in the studied areas was based on the confusion matrix statistics, supported by co-orbital QuickBird-2 very high spatial resolution imagery. Overall classification accuracy of the thematic land cover maps produced was reported over 90%. Our analysis showed expansion of mining activity throughout the whole 23-year study period, while the transition of mining areas to soil and vegetation was evident in varying rates. Our results evidenced the ability of the method under investigation in deriving highly and accurate land cover change maps, able to identify the mining areas as well as those in which excavation was replaced by natural vegetation. All in all, the proposed technique showed considerable promise towards the support of a sustainable environmental development and prudent resource management.     

Use of multitemporal remote sensing data for mapping the Alfios River network changes from 1977 to 2000

Alfios is the biggest river of the Peloponnese and the ninth longest river in Greece. It drains an area of almost 2575 km² in Western Peloponnese and discharges at Kiparissiakos Gulf. Due to its extent, the Alfios basin presents complex physiography and geomorphology.

During the last 50 years, major direct human activities have had an important impact on the river network shape and on the valley floor morphology. The most important human activities were the channel straightening caused by meander cut-offs in 1950, the construction of two dams: the Ladonas dam in 1955 and the Flokas dam in 1968 and the illegal in-stream gravel extraction that started in the 1960s and continues until today. As a result, the Alfios riverbed has presented very rapid vertical and horizontal (lateral) erosion and significant changes to its network shape. The drainage network follows a straighter course, the number of meanders has been reduced and the seventh order branch is deeply incised. Besides the morphological impacts to the river network shape there are also serious economic damages caused by human activity. During the winter of 1999, the Flokas dam bridge was closed for a long period due to damages at its foundation caused by the heavy rain and illegal gravel extraction. Transportation between the villages in the area became extremely difficult and time consuming and the cost of the repairs was estimated at 500 000 euros. In this study, there is an effort to map the network shape transformation for the period 1977–2000 using multitemporal and multisensor satellite images. One Landsat MSS image, three Landsat TM images, two Landsat ETM images, and one Terra ASTER image have been orthorectified and processed in order to cover the specific period. Principal Component Analysis (PCA) method and Geographical Information System (GIS) techniques have been applied to map the changes in the Alfios River channel. The drainage network straightening and the cut-off of five big meanders were detected and mapped. These changes occurred between 1986 and 2000.     

基于旋翼无人机的大气边界层环境气象垂直观测及订正方法的研究

基于旋翼无人机开展大气边界层观测可为气象要素和大气污染物垂直结构的研究提供具有高时空解析能力的新方法,有助于深入理解低层大气物理化学变化机制。本文详述了旋翼无人机在开展大气边界层环境气象垂直观测实验的应用及优势。基于自主研发的旋翼无人机环境气象观测平台,通过开展传感器在无人机上不同的搭载位置,以及旋翼无人机与探空气球、高塔的对比观测实验,明确了旋翼无人机对气象环境观测的影响及合理的搭载方式。研究进一步在湖北重污染天气条件下开展了0—1000 m的大气边界层垂直观测,并研发了基于旋翼无人机姿态数据的大气边界层气象要素及污染物垂直观测的订正方法。结果表明:实验获取了2—10 m垂直分辨率的高质量大气廓线数据,可精细捕捉大气边界层及其逆温层高度和污染物浓度等要素的垂直变化特征。本文旨在为无人机观测的科研应用提供一种技术可行且数据可靠的观测手段。     

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image

Cloud Masking is one of the most essential products for satellite remote sensing and downstream applications. This study develops machine learning-based (ML-based) cloud detection algorithms using spectral observations for the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to provide reference labels for model development and validation. We introduce both daytime and nighttime algorithms that differ according to whether solar band observations are included, and the artificial neural network (ANN) and random forest (RF) techniques are adopted for comparison. To eliminate the influences of surface conditions on cloud detection, we introduce three models with different treatments of the surface. Instead of developing independent ML-based algorithms, we add surface variables in a binary way that enhances the ML-based algorithm accuracy by ~5%. Validated against CALIOP observations, we find that our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection by ~5%, while at the same time, reducing misjudgment by ~3%. The nighttime model with only infrared observations is also slightly better than the AHI operational product but may tend to overestimate cloudy pixels. Overall, our ML-based algorithms can serve as a reliable method to provide cloud mask results for both daytime and nighttime AHI observations. We furthermore suggest treating the surface with a set of independent variables for future ML-based algorithm development.     

三维激光扫描技术在矿山采空区测绘中的应用

三维激光扫描技术可以实现三维场景复制,而能在较短的时间内高速、精确地记录建筑物（或景象）的三维空间位置。以马坑铁矿三维激光扫描工程项目为实例,详述三维激光扫描技术在矿山地下采空区测量中的应用优势。     

电法在秦岭钼多金属矿区找盲应用

本文以电法在秦岭某钼多金属矿区寻找深部盲矿的应用为例,介绍了电法勘查方法应用效果,说明物探资料在地球物理前提条件具备时,可以为矿区设计和开发生产过程提供重要的信息和依据,在相似地区深部找矿和寻找盲矿体具有一定借鉴意义。     

福建宁化下伊锡矿地质特征及成因探讨

宁化下伊锡矿产于晚白垩世花岗斑岩内外接触带附近,受北东向、北北东向断裂控制。目前已发现锡矿体6个,各矿体呈脉状、长透镜状产出,锡石贮存于硅化、黄铁矿化、云英岩化蚀变岩中,属中-高温热液脉状型矿床。