环境卫星CCD与Landsat TM影像质量及生态监测应用比对研究——以青海湖区域为例

针对环境卫星 CCD 影像,结合影像质量评价、专题制图、土地利用/覆被解译以及常用植被指数构建,以青海湖区域为例,与Landsat TM影像进行比对研究。结果表明,在与TM影像质量评价参数比较中,TM影像较优,而环境卫星影像具有很大的改善空间;在对地物判译中,环境卫星影像色彩稍暗淡,但对大多数地物解译判读的边界更清晰;环境卫星覆盖度大,区域制图的优势非常明显;生态监测定量遥感常用的植被指数比较中两种数据大致相同。     

遥感技术在察布查尔县土壤侵蚀调查中的应用

依据陆地卫星TM遥感影像资料,在ERDAS软件下,通过室内判读与野外调查相结合的方法,解译出土地利用类型图、植被覆盖度图、坡度图。在建立知识库的基础上,利用土壤侵蚀专家分类系统,快速获得察布查尔县土壤侵蚀分类分级状况,为今后该区域的水土保持工作提供参考和依据。     

乌鲁木齐市土地利用景观格局变化研究

运用GIS、RS技术及景观生态学理论和方法,基于乌鲁木齐市2006年和2010年遥感影像解译数据,对乌鲁木齐市5年间土地利用景观格局变化特征进行分析,分别从斑块类型和景观水平2个方面对研究区土地利用景观类型进行动态分析。揭示其变化原因和内在规律,为研究区生态治理提供数据支撑,对景观的规划与管理、资源的有效利用和生物多样性保护具有重要意义。     

基于IDL Export Bridge技术的湖泊水环境遥感监测系统设计

通过使用IDL连接桥(IDL Export Bridges)技术,构建可调用IDL运行库的COM封装对象;并结合.NET在开发Windows桌面应用程序方面的优点,设计开发能够满足业务化需求的湖泊水环境遥感自动化监测系统.该系统可对多种遥感影像进行预处理,并针对不同湖泊区域进行水质参数反演,最终完成制图输出和报告文档.     

新疆伊犁州2000～2005年生态环境质量变化评价与分析

利用Landsat-5 TM遥感影像解译的土地利用数据分析了新疆伊犁州(州直辖)2000～2005年的土地利用变化,同时根据<生态环境状况评价技术规范>(试行)(HJ/T192-2006),对该区域生态环境质量状况进行综合评价,对生态环境指标变化情况进行对比分析.结果表明,2000～2005年伊犁州的生态环境质量均为一般,生态环境质量指数(E1)减少0.71.主要原因为草地面积明显减少,耕地面积明显增加.     

新疆环境监测中心站积极开展生态环境遥感监测工作

新疆独特的地理环境造就了区域典型的大陆性干旱气候 ,加之人类不合理的开发 ,使新疆生态环境极其脆弱。为了及时准确地掌握和了解新疆宏观生态环境的现状 ,自治区环境监测中心站积极开展生态环境遥感监测工作。监测技术人员在获取全区气象卫星 NOAA— 12五个波段影像数据的基础上 ,利用遥感软件完成了全区和有关地、州、市土地荒漠现状程度 (五个级别 )的评价和制图工作 ,并针对荒漠化程度的差异 ,提出了生态环境保护的措施和建议 ,为全区生态环境的动态监测和管理提供了依据。通过此次监测 ,不仅提高了全区生态环境遥感监测的水平 ,也为…     

基于RS-GIS伊犁河谷土地利用-土地覆盖变化研究

解译2000和2005年伊犁河谷的Landsat TM遥感影像,分析和探讨土地利用-土地覆盖现状和动态变化及其特征.结果表明,伊犁河谷土地利用总体程度低,土地利用过程还处于发展阶段,土地利用-土地覆盖面积变化显著,由此引起的生态环境问题也日益明显.     

锡林浩特市露采煤炭区土地利用的扰动分析

利用锡林浩特市周边3个时期(2005,2009和2015年)的Landsat系列遥感影像,采用监督分类及人机交互解译的方法,将研究区土地利用类型分为露天采场、剥离区、排土场、矿山工业场地、农用地、城市建设用地和草地7类,对土地利用和土地覆被变化(Land-Use and Land-Cover Change,LUCC)进行分析。结果表明,草原区露天煤矿开发对草原生态系统扰动剧烈,采矿作业区(露天采场、剥离区、排土场、矿山工业场地)的面积及占比呈上升趋势,草地的面积及占比不断减少;土地利用变化转移矩阵表明,采矿扰动因素中,排土场对LUCC影响较大,对排土场进行有效复垦,可减缓生态环境破坏速度,对保护脆弱的草原生态系统具有重要意义;提出草原露采煤炭区LUCC的遥感监测可以准确反映矿区土地利用变化的动态过程和发展趋势,为矿区生态重建提供科学支持。     

兴化市生态环境遥感动态监测与分析

基于遥感(RS)和地理信息系统(GIS)技术,对兴化市的生态环境状况作分析。以2005年和2012年的影像图为数据源,经过图像预处理,通过解译与分类,得到该市2个时期土地利用状况的变化情况。在此基础上,对2个时期的土地利用类型作对比,结果表明,耕地面积减少明显,城镇、农村居民点和其他建设用地面积增加突出。分别计算2个时期的生物丰度指数和植被覆盖指数,并分析了影响生态环境的主要因素。     

高分辨率遥感影像在土壤环境质量监测点位布设中的应用

在土壤环境质量监测点位布设工作中,利用高分辨率遥感影像等数据和资料,可以增强点位布设结果的规范性和合理性。基于环境保护部和中国环境监测总站下发的土壤环境质量监测点位布设技术方案,分别介绍了基础点位、风险点位和背景点位的总体布设方式和布设要求,以及高分辨率遥感影像在各类点位理论布设中的具体应用方法。     

Desert disturbance assessments of regional oil exploitation by Aster and ETM+ images in Taklimakan Desert China

To feed its rapidly growing energy demand, oil exploitation in China has never been more intensive. The most obvious characteristics of oil exploitation are progressive and regional, which can be monitored by remote sensing, such as land use and cover change, either perpetual or temporary, during oil field development such as construction of oil well, roads, transportation systems and other facilities. In this paper, the oil field located on the north edge of Taklimakan Desert, in the Tarim River watershed in northwest of China. The disturbance effects of regional oil exploitation were the main content of regional environmental managements and monitoring. Based on Enhanced Thematic Mapper Plus (ETM+) and Aster images, analyzed regional land use and landscape change from 2001 to 2003. By the comparison, it can be concluded that the ecological quality was deteriorating in these 3 years. The woodland was degrading to grass and dessert. The area of woodland dropped from 9.06 km(2) in 2001 to 3.24 km(2) in 2003 with a 64.23% decrease. At the same time, the area of shrubbery lessened 18.23%. On the other hand, the whole area of dessert and Saline soils inflated from 15.08 km(2) in 2001 to 25.36 km(2) in 2003. The patch number of bare land did climb dramatically, but single patch area increased. The research demonstrated that dessert and Saline soils patches were activated by the human behavior and climate change. The information from the ETM+ and Aster images was proved be an effective and efficient way to be applied in regional environmental managements.     

基于Landsat ETM+等影像的无锡市十年陆地生态环境遥感评价

遥感和GIS技术的发展为研究区域生态环境变化提供了有效手段，以无锡市2004-2013年的ETM＋等遥感影像和GDEM高程数据为数据源，运用遥感和GIS方法提取生态因子信息并进行陆地生态状况遥感评价。结果表明，无锡市近十年陆地生态环境整体趋好。     

深度学习在裸地扬尘源监测中的应用研究

裸地是扬尘的重要来源，施工建设过程中形成的裸地极易在大风天气作用下造成扬尘污染。因此，快速、有效地定位裸地位置，并确认其管控措施落实情况，对于开展裸地扬尘源监管具有重要意义。基于高分辨率遥感监测数据，结合人工解译裸地扬尘源数据集，以北京市大兴区为例，利用深度学习方法对裸地和防尘网覆盖裸地进行分类识别。同时，利用颜色匹配法对大兴区防尘网覆盖裸地进行识别，横向评估深度学习方法的识别精度。结果显示：深度学习方法对防尘网覆盖裸地的识别精度达97%,对裸地的识别精度达61%;颜色匹配法对防尘网覆盖裸地的识别精度达85%。防尘网覆盖裸地的颜色特征鲜明，深度学习方法和颜色匹配法对防尘网覆盖裸地的识别精度都在85%以上。深度学习方法对于面积大于2 000 m²的图斑有着较好的识别精度。深度学习方法可以提高裸地遥感解译的效率，实现规范化图像识别，可以作为人工判读的辅助手段。在实际应用中，可通过进一步积累样本来增强模型性能。深度学习方法适用于裸地扬尘源线索快速发现、工地防尘网措施落实情况快速检测等场景。     

On the intensity and type transition of land use at the basin scale using RS/GIS: a case study of the Hanjiang River Basin

The purpose of this study is to investigate the land use intensity and land use change type at the basin scale in the middle and lower reaches of the Hanjiang River Basin (in Hubei Province, China) by combining the Landsat TM images in 1995 and 2000 with the land use database (in scale 1:10,000) and relative data. In this study, the basic data is acquired from the interpretation of remote sensing (RS) images. The intensity of land use and the rate of change in double-directions of land use dynamics are calculated with the support of software ARC/INFO. The intensity of land use is indicated by the intensity coefficient of land use, and the transition of land use types is quantified as the rate of change in double-direction of land use types and also expressed as the transition matrix of land use types. The results are expressed in space by Geographic Information System (GIS) software. Results of this study show that (1) the intensity of land use is high in the study region, the intensity coefficients of land use in 1995 and 2000 are 260.025 and 290.526, respectively, and the intensity of development and utilization of land is trend to increscent; and (2) the rate of land use change in double directions in the whole study region is 0.52 with great spatial variation and the differentiation of land use types. In the differentiation of land use types, the unutilized land (with the rate to 4.391) is developed fast, the grassland (with 2.836) and water area (with 1.664) are disturbed severely, and these changes will influence the eco-environment in the Hanjiang River Basin and all the Yangtze Basin. The rates of the farmland and the woodland are 0.424 and 0.344, respectively, meaning that the fundamentals of regional human-environmental system are relative stable. With this study, we can conclude that (1) the patterns of land use are increasingly changing in the study region, the environmental impacts are escalated on this stage, and the further outcomes are destined to change the stability of the regional human–environmental system; and (2) the most useful method to study the present land use and its change is through the use of the RS/GIS with the land use database (in scale 1:10,000).     

基于高分辨率影像的固体废物自动识别技术

随着经济快速发展,工业固废、非正规垃圾、未覆盖建筑渣土等固体废物急剧增加,对区域生态环境造成极大威胁。固废堆场具有面积小、分布散等特点,目前国内仍缺少针对各类固废堆场的遥感自动识别研究。为此,基于国产高分辨率卫星遥感数据,根据野外实地光谱采集结果,分别开展了未覆盖建筑渣土、工业固废及非正规垃圾的自动识别方法研究,提取研究区各类固废堆场。结果表明:未覆盖建筑渣土在蓝波段与绿波段分别存在"吸收谷"与"反射峰",基于该特征构建的比值指数模型,结合直方图双峰法阈值分割可以有效提取未覆盖建筑渣土区域;工业固废、非正规垃圾2种固废类型多样,光谱反射率没有明显规律,结合其纹理、色调等特征,采用面向对象多尺度分割、支持向量机监督分类方法能够较好地识别2种类型固废;基于自动化提取技术并结合人机交互判读方法,提取的研究区未覆盖建筑渣土、工业固废及非正规垃圾等3种固废堆场的精度分别达到96.83%、88.26%、85.71%,各类固体废物遥感识别精度较高,极大提高了固废监测效率。     

Regional landscape-ecological planning and desertification control in arid regions of the Commonwealth of Independent States

Scale-dependent present-day landscape mapping and assessment were used to study the relationship among physical environment, land use, and degree of landscape modification in the Aral Sea region and the Karakum Desert, areas prone to desertification in the Commonwealth of Independent States (CIS). Applying geographic information system (GIS) techniques at global (1:15,000,000), regional (1:1,000,000), and local (1:300,000) scales, researchers found that large-scale landscape assessment and mapping allow them to recognize landscape changes under desertification processes and assess the type and intensity of these processes. Remote sensing has been widely used to evaluate data reliability, to fill information gaps, and to reveal the dynamics of land use types resulting from landscape changes.     

An object-based image analysis approach for aquaculture ponds precise mapping and monitoring: a case study of Tam Giang-Cau Hai Lagoon, Vietnam

Monitoring and mapping shrimp farms, including their impact on land cover and land use, is critical to the sustainable management and planning of coastal zones. In this work, a methodology was proposed to set up a cost-effective and reproducible procedure that made use of satellite remote sensing, object-based classification approach, and open-source software for mapping aquaculture areas with high planimetric and thematic accuracy between 2005 and 2008. The analysis focused on two characteristic areas of interest of the Tam Giang-Cau Hai Lagoon (in central Vietnam), which have similar farming systems to other coastal aquaculture worldwide: the first was primarily characterised by locally referred “low tide” shrimp ponds, which are partially submerged areas; the second by earthed shrimp ponds, locally referred to as “high tide” ponds, which are non-submerged areas on the lagoon coast. The approach was based on the region-growing segmentation of high- and very high-resolution panchromatic images, SPOT5 and Worldview-1, and the unsupervised clustering classifier ISOSEG embedded on SPRING non-commercial software. The results, the accuracy of which was tested with a field-based aquaculture inventory, showed that in favourable situations (high tide shrimp ponds), the classification results provided high rates of accuracy (>95 %) through a fully automatic object-based classification. In unfavourable situations (low tide shrimp ponds), the performance degraded due to the low contrast between the water and the pond embankments. In these situations, the automatic results were improved by manual delineation of the embankments. Worldview-1 necessarily showed better thematic accuracy, and precise maps have been realised at a scale of up to 1:2,000. However, SPOT5 provided comparable results in terms of number of correctly classified ponds, but less accurate results in terms of the precision of mapped features. The procedure also demonstrated high degrees of reproducibility because it was applied to images with different spatial resolutions in an area that, during the investigated period, did not experience significant land cover changes.     

Environmental change monitoring in the arid and semi-arid regions: a case study Al-Basrah Province, Iraq

In recent years, land use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. This research utilizes the integrated remote sensing and geographic information systems (GIS) in the southern part of Iraq (Basrah Province was taken as a case) to monitor, map, and quantify the environmental change using a 1:250,000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation land, sand land, urban area, unused land, and water bodies. Supervised classification and normalized difference buildup index, normalized difference vegetation index, normalized difference bare land index, the normalized differential water index, crust index (CI) algorithms, and change detection techniques were adopted in this research and used, respectively, to retrieve its class boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. The results showed that the urban area, sand lands, and bare lands had increased by the rate of 1.2%, 0.8%, and 0.4% per year, with area expansion from 3,299.1, 4,119.1 km², and 3,201.9 km² in 1990 to 3,794.9, 4,557.7, and 3,351.7 km² in 2003, respectively. While the vegetation cover and water body classes were about 43.5% in 1990, the percentage decreased to about 39.6% in 2003. This study demonstrates the effectiveness of the remote sensing and GIS technologies in detecting, assessing, mapping, and monitoring the environmental changes.