基于宽波段遥感光谱混合分解的干旱区土地退化监测评价理论和技术方法探讨

土地退化遥感监测可以服务于政策制定、修复优化、效果评价以及安全预警,亟需建立和完善土地退化理论知识和遥感方法技术体系相结合的框架体系。在借鉴国内外干旱区土地退化(荒漠化)相关理论的基础上,以生态系统服务为连接,以植被-生境互动为核心,构建了生物-物理-社会经济系统耦合的干旱区土地退化监测理论框架。其次,围绕提出的理论框架,基于光谱混合分解端元空间的一致性、稳定性、包容性优势,以宽波段遥感为例建立干旱区遥感监测评价技术方法体系,主要包括当地环境知识挖掘、旱地生态系统景观要素提取、地表(生物物理)参数遥感反演与定标、旱地生态系统结构分析与制图、旱地生态系统功能量化与评价和旱地生态系统与社会经济综合模型七个部分。所建立的理论框架和技术体系可以为干旱区不同区域和尺度间土地退化遥感监测评价和对比分析提供参考。     

土地整理遥感监测系统设计与实现

随着遥感技术的发展,高分辨率遥感已广泛应用于土地利用调查及其变化监测,监测土地整理项目的实施状况和对土地整理项目进行评价已经成为可能。本文基于此目的,建设了土地整理遥感监测系统,文中对系统进行了架构设计和系统功能设计。系统总体架构自底向上由设备层、数据层、支撑层、业务层和用户层构成,并建有统一的标准体系与作业规范的信息化制度。并将系统划分成六个功能模块,包括项目管理模块、数据库管理模块、信息提取模块、项目监测模块、土地整理评价模块、帮助模块。系统采用C/S架构,服务器/客户端双端数据管理模式,利用Titan Image 7.0二次开发平台,使用Visual C++.NET平台搭建了系统主体框架,并把开发的土地整理遥感监测业务模块集成到平台之下实现了整个土地整理遥感监测系统。     

区域生态环境空间信息服务系统的设计与实现

针对传统生态环境监测方法难以满足宏观区域生态环境变化监测需要的问题。基于空间信息服务理念,面向区域生态环境监测与评价的具体需求,应用遥感反演和GIS空间分析技术,在Microsoft.NET平台上,利用ArcEngine中间件实现了遥感影像数据和矢量数据的浏览、空间分析、专题图制作以及海量空间数据组织和管理功能;利用IDL(Interactive Data Language)开发的遥感反演模块,实现了生态环境关键参数的遥感提取,构建了面向区域生态环境监测与评价需求的运行系统。系统实现了海量空间数据的存储和管理,比较方便和准确地通过遥感手段反演关键生态环境参数,并根据需要生成相应的生态环境监测空间信息产品,从而为区域内生态环境保护和监测提供了技术支撑。     

若尔盖高原区域碳收支参量多尺度遥感综合观测试验:科学目标与试验设计

介绍了若尔盖高原区域碳收支参量多尺度遥感综合观测试验的研究背景、科学目标、关键问题、观测方案、观测系统设置和后续观测计划.总体目标是,开展若尔盖高原区域湿地-草地生态系统碳收支参量多尺度遥感与地面同步观测试验,为人为干扰条件下湿地-草地生态系统碳收支变化过程研究积累基础数据;发展能够融合多源、多尺度遥感观测的碳收支相关参量反演模型,为实现卫星遥感对区域尺度碳收支研究提供方法和范例;建立区域尺度上的多尺度观测体系,通过多源遥感技术与生态过程模型的耦合,降低碳收支遥感监测及模拟的不确定性,更加综合地理解湿地-草地生态系统不同时空尺度上的碳收支过程;增强遥感技术在湿地生态研究的应用性,并最终为区域湿地保护提供重要依据.试验以人为干扰剧烈的若尔盖高原湿地-草地区域为试验区,以碳循环过程的关键参量为主要观测对象,利用卫星遥感、航空遥感、地基遥感、通量观测、生态观测等相关设备,开展航空、卫星和地面配合的大型综合观测试验,精细化观测若尔盖高原沼泽化草甸、湿草甸、草甸、草原等不同覆被类型的碳收支过程的各个分量.讨论了碳收支参量的多尺度观测与时空尺度扩展问题,展望了同步综合观测试验在陆地生态系统碳循环研究的应用前景.     

Coupling spectral unmixing and multiseasonal remote sensing for temperate dryland land-use/land-cover mapping in Minqin County,China

Temperate dryland ecosystems in China are undergoing accelerated changes due to natural and anthropogenic disturbances. Using the Minqin oasis as a case study area, this article examined linear spectral mixture analysis (LSMA) with the fixed four-image endmember (EM) model comprising sand, green vegetation, saline land, and dark materials (i.e. the degraded symptoms/EMs) for temperate dryland land-use and land-cover mapping. Dryland covers defined by landscape seasonality of the four EMs at the subpixel level are more easily interpreted to achieve acceptable accuracy, and allow better understanding of the processes of land degradation, such as two distinct salt/water movements were found in the study area. The Minqin oasis faces a significant challenge that requires a long-term monitoring system to understand the relationship between land-use decisions and ecological consequences. The approach developed with the mutiseasonal LSMA, representing dryland land-cover seasonality with the common surface degradation types (i.e. the four EMs) in a tree-structure framework, promises a robust and operative tool for land degradation assessment and monitoring and would be applied in a more different dryland environment in the future.     

土壤侵蚀调查中的遥感应用综述

土壤侵蚀引起土壤肥力下降、土地退化及荒漠化和生态环境恶化等一系列区域性和世界性的重大环境问题。中国是土壤侵蚀最严重的国家之一。遥感是进行环境和灾害动态监测的有效技术手段。自从20世纪70年代以来．人们就开始应用遥感技术进行土壤侵蚀的调查。对遥感技术在土壤侵蚀调查中的应用方法进行概括和汇总，分别是影像判读法、指数提取法、图像分类法、光谱分解和正射影像DEM提法等方法，分析不同方法之间的优缺点以及它们各自的适用范围，并结合当前研究的热点问题，指出未来研究的重点及趋势。     

基于3S技术的荒漠化监测技术系统研究

武威市地处典型温带荒漠气候区,绿洲边缘地带的土地沙化、河流下游土地盐渍化和中低山草场的植被退化是荒漠化的主要表现形式。武威市荒漠化监测技术系统的构建,应以“3S”技术的综合与集成应用为主要技术手段,构建以矢量数据为主要数据结构形式的荒漠化空间数据管理系统,用于满足中大尺度荒漠化动态监测的需要为原则。该技术系统可分为数据的获取和输入、遥感影像处理和分类成图、空间数据管理以及监测结果输出等4个子系统。研究提出了荒漠化监测技术系统建立中适合当地荒漠化特点的荒漠化潜在发生范围确定、荒漠化土地类型划分体系、遥感影像荒漠化信息提取、基于DEM的坡耕地荒漠化评价等关键技术的解决方法。     

CropStraw Fire Remote Sensing Monitoring and Its Algorithm Implementation

in order to obtain the information and achieve the effective control of crop straw fire spatial distribution in Central China Region.The MODIS L1B remote sensing datasets during 2014 for the main data source in this article,and combined with land use data,the farmland of Central China Region was taken as study region.Based on the enhanced contextual fire remote sensing detection algorithm,and make full use of the theoretical knowledge of quantitative remote sensing and Geospatial Data Abstraction Library (GDAL)and other technical means,to achieve the crop straw fire recognition in Central China Region.Using Ministry of Environmental Protection of the People’s Republic of China release the daily newspaper of crop straw fire in China and the standard fire products (MYD14)of MODIS for the comparative analysis of the quantitative and spatial.The results indicate that the algorithmof this paper can achieve crop straw fire remote sensing monitoring of this study region effectively,and the parameters can be adjusted in real time based on the characteristic of the study region,and improve the automation and working efficiency of crop straw fire monitoring.     

沙漠化遥感动态监测的方法与实践

土地沙漠化是我国北方地区一个严重的环境经济问题,进行遥感动态监测是了解其发展过程、状态和趋势的有效方法。本项研究在确定了沙漠化土地遥感判别指征体系和监测技术路线的基础上,提出遥感动态监测的方法,并以毛乌素沙 地为例,利用不同时期的TM遥感资料对土地沙漠化进行了动态监测。结果表明,该方法能够揭示出研究区内沙漠化土地时空分布及其变化规律,为防治沙漠化提供科学的依据。     

Progress of Chinese Coastal Wetland based on Remote Sensing

Coastal wetlands as a unique ecosystems with high productivity and abundant biology diversity,has many important resource values,ecological values,economic values and scientific research values.Due to the multi\|temporal,multi\|platform,macroscopic,objective,informative,real\|time,highly effective,comparable and so on,so the remote sensing technology has been gradually approved and widely promoted in coastal wetland research in the past three decades.Current status of coastal wetland research based on remote sensing technique in China was systematically discussed from multiple aspects,including remote sensing data sources,theories and methods,and the application of remote sensing technology to Chinese coastal wetland is reviewed from the aspects of coastal wetland resource investigation and management,landscape pattern and dynamic change,ecological environment monitoring,ecosystem quality and service evaluation.This paper also points out some shortcomings existed in Chinese coastal wetland research by remote sensing technology include the spatial and temporal distributions of the study area is uneven and dominated by small and medium scale,lack of interdisciplinary comprehensive research,focus on theoretical research and ignore application intelligent application of remote sensing technology,information sharing ability is poor,the improve of interpretation accuracy is difficulties.Related research prospects should be to carry out such as monitoring and mapping on all scale,strengthen the multidisciplinary collaboration,strengthen the comprehensive and comparative study,establish a unified classification system of coastal wetland based on remote sensing and the national coastal wetland information system,emphasis on the development of new remote sensing technology and fusion of multi\|source data,emphasis on the use of new methods and new models.     

Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects

Remote sensing provides a broad view of landscapes and can be consistent through time, making it an important tool for monitoring and managing protected areas. An impediment to broader use of remote sensing science for monitoring has been the need for resource managers to understand the specialized capabilities of an ever-expanding array of image sources and analysis techniques. Here, we provide guidelines that will enable land managers to more effectively collaborate with remote sensing scientists to develop and apply remote sensing science to achieve monitoring objectives. We first describe fundamental characteristics of remotely sensed data and change detection analysis that affect the types and range of phenomena that can be tracked. Using that background, we describe four general steps in natural resource remote sensing projects: image and reference data acquisition, pre-processing, analysis, and evaluation. We emphasize the practical considerations that arise in each of these steps. We articulate a four-phase process that guides natural resource and remote sensing specialists through a collaborative process to articulate goals, evaluate data and options for image processing, refine or eliminate unrealistic paths, and assess the cost and utility of different options.     

Remote sensing of soil salinity: potentials and constraints

Soil salinity caused by natural or human-induced processes is a major environmental hazard. The global extent of primary salt-affected soils is about 955 M ha, while secondary salinization affects some 77 M ha, with 58% of these in irrigated areas. Nearly 20% of all irrigated land is salt-affected, and this proportion tends to increase in spite of considerable efforts dedicated to land reclamation. This requires careful monitoring of the soil salinity status and variation to curb degradation trends, and secure sustainable land use and management. Multitemporal optical and microwave remote sensing can significantly contribute to detecting temporal changes of salt-related surface features. Airborne geophysics and ground-based electromagnetic induction meters, combined with ground data, have shown potential for mapping depth of salinity occurrence. This paper reviews various sensors (e.g. aerial photographs, satellite- and airborne multispectral sensors, microwave sensors, video imagery, airborne geophysics, hyperspectral sensors, and electromagnetic induction meters) and approaches used for remote identification and mapping of salt-affected areas. Constraints on the use of remote sensing data for mapping salt-affected areas are shown related to the spectral behaviour of salt types, spatial distribution of salts on the terrain surface, temporal changes on salinity, interference of vegetation, and spectral confusions with other terrain surfaces.As raw remote sensing data need substantial transformation for proper feature recognition and mapping, techniques such as spectral unmixing, maximum likelihood classification, fuzzy classification, band ratioing, principal components analysis, and correlation equations are discussed. Lastly, the paper presents modelling of temporal and spatial changes of salinity using combined approaches that incorporate different data fusion and data integration techniques.     

基于深度学习的遥感影像目标检测系统设计

遥感影像目标检测虽然是一种极为有效的地表变化监测手段,但极易受到自然环境复杂性的影响,从而造成遥感影像中存在混合的杂质像素,导致目标检测准确性较差;为解决此问题,设计基于深度学习的遥感影像目标检测系统;建立深度学习框架,分层次连接遥感影像输入模块、图像帧预处理模块与目标检测算法模块,再借助影像目标输出结构单元,对已获得的遥感影像像素数据进行整合,实现系统硬件设计;在此基础上,提取遥感影像的多特征条件,完善现有的目标检测系统设计方案;通过分割多级目标节点的方式,得到遥感影像特征的小波分解结果,利用计算求得的边缘纹理系数,实现融合深度学习理论的遥感影像目标变化能力检测;实验结果表明,所设计遥感影像目标检测系统的有效像素的占比量较大,杂质像素节点的占比量较小,且二者之间的对比情况极为明显,能够有效剔除杂质像素量,更能适应复杂多变的自然环境,获得更为准确的地表变化监测结果.     

基于特征空间的黄河三角洲垦利县土壤盐分遥感提取

土壤盐渍化是实现土地资源可持续利用所面临的重要挑战,在我国滨海的黄河三角洲区域遥感定量反演适宜方法可为区域盐渍化监测与防治提供技术方法参考。研究以Landsat 8 OLI数据和野外实测数据为基础,提取关键地表特征参量,定量化探讨土壤盐分与地表生物物理参数之间的规律及关系,建立黄河三角洲土壤盐分最优反演模型。结果表明:Albedo-MSAVI、SI-Albedo、SI-NDVI反演精度分别为83.4%、88.8%和80.6%。分析认为SI-Albedo模型最适用于滨海地区盐渍化程度反演,对滨海地区土壤盐分的预测能力较强;Albedo-MSAVI、SI-NDVI模型对内陆干旱、半干旱地区的盐渍化信息提取具有一定的参考意义。基于精度最高的SI-Albedo所反演的结果来看,垦利县盐渍化程度自东向西总体呈高低高走向,与该区域盐分积聚的成因机理相符。     

基于深度学习的高分辨率卫星遥感影像围填海检测识别

基于高分辨率卫星遥感影像自动、准确提取围填海土地利用现状,是实现围填海集约使用的重要技术手段。针对高分辨率卫星遥感影像地物特征复杂,依赖人工提取特征的传统方法较难满足业务部门实际需求的问题,提出了基于深度学习的围填海检测识别技术框架,该框架使用UNet网络的多约束变体结构,并针对高分辨率遥感影像地物特征复杂导致地物分类不一致的问题,引入全连接条件随机场和图像腐蚀运算对分割结果进行后处理。以天津市滨海新区2016年和2020年高分辨卫星遥感影像为数据源进行了验证,实验表明围填海地物分割整体准确率、F1-score、Kappa系数以及mIoU分别达到96.73%、92.87%、90.28%、86.82%。在此基础上,分析提取了该围填海区域土地利用动态变化特征,为围填海集约使用管理提供了有效技术支撑。     

Remote Sensing Extraction of Soil Salinity in Yellow River Delta Kenli County based on Feature Space

Soil salinization is an important challenge to achieve sustainable use of land resources. The appropriate method for remote sensing quantitative inversion in the coastal Yellow River Delta region of China can provide technical reference for regional salinization monitoring and prevention. Utilizing Landsat 8 OLI image and field measured data, we extracted key surface characteristic parameters, quantitatively discussed the law and relationship between soil salinity and surface biophysical parameters and established a soil salinity inversion model. The results show that the inversion precisions of Albedo-MSAVI, SI-Albedo and SI-NDVI feature space are 83.4%, 88.8% and 80.6% respectively. The analysis shows the SI-Albedo model is suitable for the inversion of salinization level in Binhai areas. For Albedo-MSAVI and SI-NDVI models, they have certain reference significance for salinization information extraction in inland arid and semi-arid areas. Based on the inversion of the SI-Albedo feature space with the highest accuracy, the level of salinization in Kenli County is generally high-low-high trends from the east to the west, which is consistent with the formation mechanism of salt accumulation in this area.     

COSMO雷达数据在多云多雾地区土地变化监测研究

近年来新型成像雷达遥感(极化、干涉)及数据处理技术的发展,SAR遥感影像上获得的地表信息越来越多,如何利用雷达信息探测土地变化成为研究的新课题。但是雷达影像不同于光学影像,目前雷达数据解译仍存在着一些困难。本文主要针对多云多雾地区雷达数据土地变化监测,以四川成都地区COSMO数据为例,利用雷达相干影像,后向散射强度,强度比值影像,提出一种新的雷达处理手段,减少了雷达数据土地变化监测的工作量,提高工作效率。     

区域土壤盐渍化遥感监测研究综述

对国内外遥感监测土壤盐渍化发展情况作了介绍,对土壤盐渍化及其动态变化遥感监测方法进行了总结,数字图像处理将成为区域土壤盐渍化遥感监测研究的主要手段,土壤盐渍化是一个世界性的问题,应将遥感琢遥感图像处理的最新成果充分运用到盐渍土监测研究中,为盐渍土治理与农业可持续发展提供信息保障。     

基于“3S”技术的县级土地资源动态监测技术系统

土地资源日新月异的变化使得传统的土地资源管理手段无法满足土地资源信息及时更新的要求。探讨了利用遥感、地理信息系统和全球定位系统为代表的“3S”技术进行县级土地资源动态监测和更新的原理和方法。遥感是进行土地利用变化动态监测,发现土地利用变化区域的主要手段。全球定位系统接收仪用于对变化区域进行现场精确定位和实测。实测的变更数据可用于对原有的地理信息系统本底数据库进行修改,从而完成对土地资源的动态监测和数据库的及时更新。福清市土地资源动态监测技术系统就是利用“3S”技术建立起来的业务运行系统。系统所具备的功能可以满足县级土地资源的动态监测和及时更新。     

遥感卫星灾害应急监测效能评估指标体系构建

遥感卫星广泛应用于包括防灾减灾在内的多个领域,发挥了巨大的社会效益。自然灾害应急对卫星监测的需求具有针对多时空要素的动态高效多源多维的特点,而卫星的全球化可重访、无国界观测能力与灾害的监测需求高度契合。在研究分析遥感卫星在灾害应急任务中的能力需求和应用模式的基础上,从单项性能、能力指标和应用效能三个层次展开分析,构建遥感卫星灾害应急监测效能评估指标体系,给出主要指标的评估方法,为我国卫星有效用于国内外重大灾害应急监测服务提供有效的评估手段和技术支撑。