CBERS-2B数据提取平原区细小地物系数的方法探讨

利用Landsat TM等中等分辨率影像对区域生态环境进行监测与评价时,由于影像分辨率的局限性,仍有许多地物无法解译出来,如农田中的道路、水渠等,文章主要研究了利用图像融合增强和人机交互式解译等技术方法,对CBERS-2B的CCD影像和HR影像进行处理,提取平原区农田中道路面积比系数,从而将农田中未解译的地物扣除。结果表明,CCD影像与HR影像经过融合增强处理后,可以进行平原地区村级及以上道路的提取。     

Landsat5 TM遥感影像上太湖蓝藻水华反射光谱特征研究

利用ENVI遥感软件的FLAASH工具对2005年10月17日大规模蓝藻水华暴发的太湖Landsat5 TM影像进行大气校正处理,反演获得蓝藻水华和其他地物类型的遥感反射率图像,提取了不同集聚程度蓝藻水华的可见波段至近红外波段反射率数据,并与陆生植被、无蓝藻水面等地物的光谱反射率进行了比较。研究表明,与陆生植被、无蓝藻水面相比,蓝藻水华在TM2波段和TM4波段具有更高的反射率,在可见光波段整体反射率略高于陆生植被,在TM5、TM7波段则受水的影响反射率很低。从蓝藻水华、陆生植被的细胞生理结构、生长环境、复杂的遥感反射、散射及透射模型方面初步讨论了光谱差异的原因。     

利用GE Plus快速解译土地利用类型和辅助制图

GE Plus超强版比GE普通版具有更强的空间编辑功能。本文介绍了一种利用GE Plus超强版软件,无需使用ArcGIS等专用地理信息软件和无需购买高分辨率遥感影像实现区域土地利用类型快速解译和辅助制图的方法。该方法主要使用GE中工具菜单、添加菜单和标尺工具栏完成区域土地利用类型快速解译和辅助制图。本文以乌鲁木齐市某社区为例,成功完成了案例区基于高分辨率遥感影像的土地利用类型信息提取和快速制图,并附经纬度和比例尺,可为开展建设项目工业场地类环境影响评价和建设项目竣工环保验收监测(调查)工作提供基础数据和背景资料。     

基于欧洲航天局“哨兵-2A”卫星的太湖蓝藻遥感监测

欧洲航天局(ESA)2015年6月23日成功发射"哨兵-2A"卫星,该卫星搭载的多光谱成像仪(MSI)在可见光(VIS)至短波红外(SWIR)波长区间配置了多种光谱波段/地面分辨率组合,可以获取大范围、较短重访周期、较高空间分辨率(10 m)的遥感影像。以太湖2016年6月13日MSI数据为例,在完成大气校正的基础上,分析了太湖典型地物类型光谱特征,采用归一化植被指数(NDVI)结合叶绿素反射峰强度(ρchl)构建的综合阈值法对贡湖湾的蓝藻水华信息进行了提取实验。结果表明:"哨兵-2A"卫星MSI影像质量清晰,可精细地反映植被、蓝藻、水体等典型地物类型的光谱特征;ρchl指数对中-高蓝藻聚集区与水生植被、轻度蓝藻聚集区与混合水体具有较好的分离能力;利用综合阈值法提取贡湖湾中-高蓝藻聚集区面积为60.37 km2,主要分布在贡湖北部沿岸、湖心和南部沿岸。"藻-水"混悬体面积为79.49 km2,贡湖湾东部蓝藻水华相对较轻。     

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.     

基于TM影像的桂林市植被覆盖时空动态监测与分析

以西部地区中等规模城市——桂林市为例,利用1991、2006年两期TM卫星影像数据,在对原始数据预处理的基础上,提取归一化植被指数(NDVI)。依据混合像元二分模型,生成桂林市所辖5城区的两期植被覆盖度监测分类图像,对区域植被覆盖状况进行时空动态变化分析。结果表明,1991年~2006年间,城市植被覆盖区面积总体呈现下降趋势;在划分的3类植被覆盖类型中,低植被覆盖区面积减少幅度最为明显,中、高植被覆盖区面积有不同程度增长;低植被覆盖区主要分布在城市建成区与一些村镇外围区域,中、高植被覆盖区集中分布在城市远郊地带。此外,随着城市化的迅速发展,城乡各类建设用地面积不断增加,城市边缘地带的绿色植被正逐步被人工景观所取代。     

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。     

塔里木河干流区域土地利用遥感动态监测

介绍了TM数据在土地利用动态监测中的应用方法，通过不同时期(2000年和2002年)的TM卫星影像，单独分类结果的对比，得出塔里木河干流区域土地利用动态变化信息。     

环境与灾害监测预报小卫星数据应用评价

以环境与灾害监测预报小卫星(HJ-1A/B)和TM的CCD数据,从波段配准、空间分辨力、非监督分类、数理统计分析和地统计分析等方面与TM数据比对,对HJ-1A/B星数据质量进行评价。结果认为,HJ-1A/B CCD数据整体数据质量较好,在今后的宏观区域环境监测、灾害监测预报中将会发挥重要作用。     

基于遥感技术的生态保护红线区域监测与评价

从生态保护红线区域监管需求出发,利用遥感技术建立生态保护红线区域监测方法,并采用生态保护红线区域自然生态系统构成及变化、生态景观平均斑块面积变化和NDVI植被指数变化3个评价指标,对江苏省盐城沿海地区2012-2013年各类型生态保护红线区域生态环境变化进行了评价.结果表明,水源水质保护和生物多样性保护红线区域生态环境质量综合指数相对较高;桑蚕品种多样性保护红线区域自然生态系统类型占比较低,生态景观较为破碎,生态环境质量综合指数相对较低;大部分生态红线区域生态环境质量保持稳定.     

丹江湿地国家级自然保护区及其内外区域2000—2015年土地覆被变化分析

为研究2000—2015年丹江湿地国家级自然保护区及其内外生态状况变化和保护成效,基于高分1号数据生产的2m高分辨率遥感影像数据对丹江湿地国家级自然保护区2015年人类活动状况进行分析,基于30 m分辨率的4期TM遥感影像生产的土地覆被数据和基于Modis遥感影像生产的植被覆盖度数据,对淅川县、丹江湿地国家级自然保护区及其核心区的土地覆被状况、土地覆被转类指数及其土地覆被转类途径的主导程度和3个相关区域范围内的生态系统质量以及不同区域土地覆被变化的主要变化原因进行分析。结果表明,保护区核心区的格局和质量在该区域处于最优,且土地覆被变化状况也以核心区转类指数最高;丹江湿地国家级自然保护区内的主要人类活动影响为耕地,其次包括居民点、采石场、养殖场; 15年间,保护区内外土地覆被均呈现转好趋势,但是保护区内变化优于保护区外,保护区核心区优于整个保护区,且转好的主导因素均是耕地变为湿地; 15年间植被覆盖度变化较小。     

Assessment of some remote sensing techniques used to detect land use/land cover changes in South-East Transilvania,Romania

This paper assesses the image differencing technique for the Normalized Difference Vegetation Index (NDVI), the second principal component (PC2), and the TM 4 band (TM 4), as well as the post-classification comparison (PCC) in order to analyze the land use/land cover changes in the South-East Transilvania, Romania. The analysis was performed using two frames from Landsat 5 TM satellite images acquired on August 5, 1993 and July 24, 2009. After applying the NDVI, PC2, and TM 4 image differencing techniques, the images obtained were transformed into change/no change maps. The thresholds identified to highlight the changes were set at 0.6 s for NDVI and 0.7 s for PC2 and TM 4. Before applying the PCC technique, the satellite images were classified through the supervised classification method. The overall accuracy obtained was 85.91 % and the kappa statistics 0.8249 for 1993, 88.18 % and 0.8497 for 2009, respectively. The assessment of the changes detection methods in the studied area shows that the first place is occupied by NDVI image differencing with an overall accuracy of 83.80 %, followed by PCC method with 83.20 %, PC2 difference with an overall accuracy of 81.60 %, and TM 4 difference with an overall accuracy of 79.40 %.     

Analysis of the changes of vegetation coverage of western Beijing mountainous areas using remote sensing and GIS

Mentougou District acts as a crucial component in the ecological buffer in western Beijing mountainous areas, Beijing, China. Using two Landsat MSS/TM images acquired on July 14, 1979 and July 23, 2005, the vegetation coverage of Mentougou District was calculated based on normalized difference vegetation index and spectral mixture analysis (NDVI-SMA) model. Its temporal and spatial changes were analyzed according to digital elevation model (DEM) image, social and economic data. The results showed that the vegetation coverage decreased from 76.4% in 1979 to 72.7% in 2005. Vegetation degradation was probably the result of human disturbance, such as outspreading of resident areas, and coal and stone mining activities, while vegetation restoration might be contributed by the combined effects of both natural processes and ecological construction effort. Vegetation changes were closely related to topographical characteristics. Plants at high altitude were more stable and less degraded than the plants at low altitude, while the plants on steep slope or northwest aspect were more vulnerable to degradation. During the period of 26 years, landscape appeared to become more fragmental, and ecological quality of the land seemed deteriorated sharply in that highly-covered vegetation area has been decreased by 24%.     

Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area

Istanbul is the most populated city of Turkey with a population of around 10.58 M (2000) living on around 5,750 km². In 1980, the population was only 4.7 M and then it has been more than doubled in only two decades. The population has been increasing as a result of mass immigration. An urbanization process continues and it causes serious increases in urban areas while decreasing the amount of green areas. This rapid, uncontrolled, and illegal urbanization accompanied by insufficient infrastructure has caused degradation of forest and barren lands in the metropolitan area, especially through the last two decades. The watershed basins inside the metropolitan area and the transportation network have accelerated the land-cover changes, which have negative impacts on water quality of the basins. Monitoring urban growth and land cover change will enable better management of this complex urban area by the Greater Istanbul Metropolitan Municipality (GIMM). A temporal assessment of land-cover changes of Istanbul has been documented in this study. The study mainly focuses on the acquisition and analysis of Landsat TM and Landsat GeoCover LC satellite images reflecting the significant land-cover changes between the years of 1990 and 2005. Raster data were converted to vector data and used in Geographic Information Systems (GIS). A database was created for Istanbul metropolitan area to plan, manage, and utilize statistical attribute data covering population, water, forest, industry, and topographic position. Consequently an overlay analysis was carried out and land use/cover changes through years have been detected for the case study area. The capability of Landsat images in determining the alterations in the macro form of the city are also discussed.     

基于Landsat TM/ETM+/OLI遥感大数据分析南京市1984—2015年大气能见度变化趋势

对南京市1984—2015年Landsat 4／5／7／8卫星TM／ETM＋／OLI传感器获取的遥感数据，利用ENVI遥感软件的FLAASH大气校正模块，进行了区域大气能见度（ VIS）遥感反演。结果表明，时间跨度达30余年的Landsat卫星遥感数据影像序列反演的VIS呈明显的下降趋势，20世纪80年代数值较高，“差”能见度（＜10 km）的观测率不到6％，21世纪以来VIS下降明显，“差”能见度的观测率为20％～25％。与2010—2015年南京市PM10、PM2．5监测数据进行了对比，在城市空气清洁及污染较轻时，星地监测结果有较好的一致性，但中到重污染天气时FLAASH算法反演VIS偏高，侧重于代表离主城区距离远的偏远乡野山林地区的能见度状况。     

Mapping chlorophyll-a through in-situ measurements and Terra ASTER satellite data

This paper presents an application of water quality mapping through real-time satellite and ground data. The Lake Beysehir which is the largest freshwater lake and drinking water reservoir in Turkey was selected as the study area. Terra ASTER satellite image is used as remote sensing data source for water quality mapping in addition to simultaneously performed in-situ measurements. Ground data is collected simultaneously with the ASTER overpass on June 09, 2005 over the Lake Beysehir. The spatial distribution map is developed by using multiple regression (MR) technique for water quality parameter, which is chlorophyll-a (chl-a). The results indicate that simultaneous ground and satellite remote sensing data are highly correlated (R (2) > 0.86). In the image processing step, geometric correction, image filtering and development of water quality map procedures are performed with the ERDAS Imagine and ArcGIS 9.0 software. The trophic status of Lake Beysehir is considered to be oligotrophic with an average 1.55 microg/l chl-a concentration.     

遥感技术在湖泊叶绿素ａ 监测中的应用研究———以太湖为例

水质遥感技术在湖泊水质监测领域内的应用具有十分积极的意义。在总结现有水质遥感反演方法的基础上，选取了遥感指数法和神经网络法两种理论完全不同的反演方法，构建太湖叶绿素a与MODIS影像波段间的函数关系，并从反演能力和反演精度两个角度对上述方法进行了比较研究。结果表明，神经网络模型的非线性特征能够敏感地把握住叶绿素a浓度变化在反射波谱信息上的微小响应，较为成功地反演出叶绿素a与反射光谱信息间的非线性关系。神经网络模型的反演能力和反演精度均优于遥感指数方法，具有较好的应用前景。     

Land cover change of watersheds in Southern Guam from 1973 to 2001

Land cover change can be caused by human-induced activities and natural forces. Land cover change in watershed level has been a main concern for a long time in the world since watersheds play an important role in our life and environment. This paper is focused on how to apply Landsat Multi-Spectral Scanner (MSS) satellite image of 1973 and Landsat Thematic Mapper (TM) satellite image of 2001 to determine the land cover changes of coastal watersheds from 1973 to 2001. GIS and remote sensing are integrated to derive land cover information from Landsat satellite images of 1973 and 2001. The land cover classification is based on supervised classification method in remote sensing software ERDAS IMAGINE. Historical GIS data is used to replace the areas covered by clouds or shadows in the image of 1973 to improve classification accuracy. Then, temporal land cover is utilized to determine land cover change of coastal watersheds in southern Guam. The overall classification accuracies for Landsat MSS image of 1973 and Landsat TM image of 2001 are 82.74% and 90.42%, respectively. The overall classification of Landsat MSS image is particularly satisfactory considering its coarse spatial resolution and relatively bad data quality because of lots of clouds and shadows in the image. Watershed land cover change in southern Guam is affected greatly by anthropogenic activities. However, natural forces also affect land cover in space and time. Land cover information and change in watersheds can be applied for watershed management and planning, and environmental modeling and assessment. Based on spatio-temporal land cover information, the interaction behavior between human and environment may be evaluated. The findings in this research will be useful to similar research in other tropical islands.