Performance evaluation of underwater platforms in the context of space exploration

Robotic platforms are essential for future human planetary and lunar exploration as they can operate in more extreme environments with a greater endurance than human explorers. In this era of space exploration, a terrestrial analog that can be used for development of the coordination between manned and robotic vehicles will optimize the scientific return of future missions while concurrently minimizing the downtime of both human explorers and robotic platforms. This work presents the use of underwater exploratory robots - autonomous underwater vehicles (AUV), remotely operated vehicles (ROV), and manned submersibles - as analogues for mixed human-robot exploration of space. Subaqueous settings present diverse challenges for navigation, operation and recovery that require the development of an exploration model of a similar complexity as required for space exploration. To capitalize on the strengths of both robotic and human explorers this work presents lessons learnt with respect to the fields of human-robotic interface (HRI) and operator training. These are then used in the development of mission evaluation tools: (1) a task efficiency index (TEI), (2) performance metrics, and (3) exploration metrics. Although these independent evaluations were useful for specific missions, further refinement will be required to fully evaluate the strengths and capabilities of multiple platforms in a human-robotic exploration campaign in order to take advantage of unforeseen science opportunities in remote settings.     

ROV based underwater blurred image restoration

1　Introduction　TheROV (RemoteOperatedVehicle)isakindofsystemthatcanbeusedforunderwatermeasurementanddetection (Caimi,1996 ;KevernandLeGall,1991) .Inthispaper ,theirradianceofthelightre flectedbythetargetthroughwaterbodiesindifferentconditionsissimulatedbyacomputer .Underdiffer entwaterconditions,therelationbetweentheirradi anceandthedistanceispresented .Thenthemaxi mumdetectiondistanceofthedetectorcanbeob tained .WealsorestoretheunderwaterblurryimagesusingtheWienerfilterbasedonthesimula…     

K-T变换的林学意义及其在森林蓄积量估算中的应用

本文讨论了K-T变换在林学方面的意义,它可以用于森林信息分析。就K-T的特征空间而言,其林学意义是很明确的,森林具有较高的绿度、湿度和较低的亮度,它们在光谱空间具有相对稳定的位置,利用这一特殊性质,即可用反射光谱描述森林的林学意义及其环境特征。 本文还用K-T变换特性构造了浙江省临安县森林蓄积量的遥感估算模型,它在结构上考虑了林学和环境特征,从而使模型具有一定的物理含义。模型经试验,其结果较为理想,对主要立地类型、其平均森林蓄积量估算精度达到90％左右,可以用于我国南方山区。     

全球植被叶面积指数对温度和降水的响应研究

利用一套新的遥感信息反演的叶面积指数(LAI)数据和生物气候数据,建立了全球尺度的LAI与降水及温度的总体相关和距平相关,用以揭示全球尺度的植被季节和年际的变化对气候变化的响应特征.结果发现,全球尺度植被与气候因子的季节和年际变化随不同的生态系统差异明显.植被LAI与温度的总体正相关的最大值出现在北半球的中高纬度地区;LAI与降水的总体正相关高值(＞0.8)出现在亚洲东部、北美洲北部腹地和热带非洲北部的Sahel地区;最大的LAI与温度的正距平相关(0.4-0.6)出现在东南亚南部、非洲Sahel地区的南部和巴西东部等热带地区;而从LAI与降水的距平相关来看,最明显的特征是出现在西伯利亚、亚洲北部和北美西北部的强的负距平相关.本文进一步阐明了出现相关特征差异的陆-气过程物理机制.     

Linking archival and remotely sensed data for long-term environmental monitoring

The broad objective of this paper is to illustrate how archival, historical and remotely sensed data can be used to complement each other for long-term environmental monitoring. One of the major constraints confronting scientific investigation in the area of long-term environmental monitoring is lack of data at the required temporal and spatial scales. While remotely sensed data have provided dependable change detection databases since 1972, long-term changes such as those associated with typical climate scenarios often require longer time series data. The lack of data in readily accessible and usable formats for periods predating commercial satellite products has for a long time restricted the scope of environmental studies to temporally brief, synoptic overviews covering short time scales, thereby compromising our understanding of complex environmental processes. One way to improve this understanding is by cross-linking different forms of data at different temporal scales. However, most remote sensing based change research has tended to marginalize the utility of archival and historical sources in environmental monitoring. While the accuracy of data from non-instrumental records is often source-specific and varies from place to place, carefully conducted searches can yield useful information that can be effectively used to extend the temporal coverage of projects dependant on time series data. This paper is based on an ongoing project on environmental monitoring in the world's largest Ramsar site, the Okavango Delta, located on the northeastern fringes of Southern Africa's Kalahari–Namib desert in northern Botswana. With a database covering over 150 years between 1849 and 2001, the primary objectives of this paper are to: (1) outline how modern remotely sensed data (i.e., CORONA and Landsat) can be complemented by historical in situ observations (i.e., travellers’ records and archival maps) to extend temporal coverage into the historical past, (2) illustrate that different forms of declassified Cold War intelligence data (i.e., CORONA) can be constructively exploited to further scientific understanding and (3) provide a conceptual framework for collating and disseminating data at regional and international levels through electronic media.     

自治水下机器人在深海采矿系统湖试中的应用

以大洋采矿前期的湖试为例,介绍了AUV在矿产资源调查和深海采矿中的应用。在深海采矿系统作业前期,利用AUV调查湖底的地形地貌、结核的分布与覆盖率,确定集矿机作业地点的大地坐标。在深海采矿系统作业后期,利用AUV调查集矿机在湖底的行走轨迹和压陷深度,估算回采率。     

遥感影像理解智能化系统与模型集成方法

智能化遥感影像分析理解是当前遥感地学分析中的研究热点。本文通过分析当前智能化方法在应用中存在的两个主要问题,指出了智能化遥感影像分析向基于多特征单元为分析对象转变的必要性以及如何在分析过程中更好的融合知识。在此基础上,介绍了多特征单元遥感影像分析和基于神经网络的知识处理的基本思想。并对如何建立基于知识智能计算的多特征单元遥感影像分析理解方法体系进行了探讨,给出了概念框架图。     

GPS星历对LEO星载GPS精密定轨精度的影响

目前,越来越多的低轨卫星上都搭载了用于精密定轨的星载GPs接收机,星载GPS已成为低轨卫星精密定轨的主要手段之一.星载GPS精密定轨精度依赖于GPS星历及钟差精度.基于SHORDE-Ⅲ非差动力学定轨功能,以2005年8月1日至8月7日一周的GRACE卫星实测数据为例,采用事后精密轨道(igs)、快速轨道(igr)和超快速轨道(igu)三种GPS星历在同等条件下定轨,估计GPS星历精度对低轨卫星定轨精度的影响,实际计算结果表明igs和igr两类GPS星历定轨精度相当,约为9.5 cm,igu星历定轨精度略低于igs和igr星历,约为10.5cm:高频GPS卫星钟差数据对定轨精度会产生1-6cm影响.     

水环境COD遥感识别模式及其应用

利用2006年4月6-7日在甘肃省庆阳市境内环江、柔远河和马莲河实测的水体波谱数据,以及化学需氧量COD测定数据,采用Fisher判别分析方法,建立了基于地面实测光谱数据并适用于本研究区域的水环境COD遥感识别模式;将该模式应用于2005年10月16日和2006年4月10日过境的两景Landsat/TM图像;根据遥感模式反演结果图,对该区域水环境COD的时空变化进行了分析。水环境COD污染遥感模式的建立可为从遥感影像上快速、大面积获取COD信息提供了一种技术手段。     

基于遥感技术的土地利用与土地覆盖的分类方法

分类方法在土地利用和土地覆盖变化研究中占据重要的地位。土地利用与覆盖分类首先涉及图像的处理以及分类系统的建立。目前机助分类技术主要着眼于统计模式识别和基于知识的分类决策。最终的精度评价可以进一步完善分类决策。