沙尘暴EOS/MODIS监测指数模型

利用EOS/MODIS数据,采用最佳波段组合指数法和方差-协方差矩阵特征值法,从36个MODIS波段中筛选出用于沙尘暴图像最佳彩色合成增强的最佳组合波段。在敏感性差异分析的基础上应用波段数学组合的方法建立了沙尘暴判识的条件:构建了提取沙尘暴区域范围和强度等级信息的沙尘暴卫星遥感监测指数SVI(Sand storm value index),利用指数SVI值的大小对沙尘暴进行了等级的定级和分类。     

Glacier mapping based on Chinese high-resolution remote sensing GF-1 satellite and topographic data

The precise glacier boundary is a fundamental requirement for glacier inventory,the assessment of climate change and water management in remote mountain areas.However,some glaciers in mountain areas are covered by debris.The high spatial resolution images bring opportunities in mapping debris-covered glaciers.To discuss the capability of Chinese GaoFen-1 satellite lacking the short wave infrared band and thermal infrared band in mapping glaciers,this study distinguished supraglacial terrain from surrounding debris by combining GaoFen-1(GF-1)wide-field-view(WFV)images,the ratio of the thermal infrared imagery and morphometric parameters(DEM and slope)with 30 m resolution.The overall accuracy of 90.94%indicated that this method was effective for mapping supraglacial terrain in mountain areas.Comparing this result with the combination of GF-1 WFV and low-resolution morphometric parameters shows that a high-quality DEM and the thermal infrared band enhanced the accuracy of glacier mapping especially debris-covered ice in steep terrain.The user's and producer's accuracies of glacier area were also improved from 89.67%and 85.95%to 92.83%and 90.34%,respectively.GF data is recommended for mapping heavily debris-covered glaciers and will be combined with SAR data for future studies.     

Mapping abandoned agricultural land in Kyzyl-Orda,Kazakhstan using satellite remote sensing

In many regions worldwide, cropland abandonment is growing, which has strong and known environmental and socio-economic consequences. Yet, spatially explicit information on the spatial pattern of abandonment is sparse, particularly in post-Soviet countries of Central Asia. When thriving reaching for key Millennium Development Goals such as food security and poverty reduction, the issue of cropland abandonment is critical and therefore must be monitored and limited, or land use transformed into an alternative one. Central Asia experienced large changes of its agricultural system after the collapse of the Soviet Union in 1991. Land degradation, which started already before independence, and cropland abandonment is growing in extent, but their spatial pattern remains ill-understood. The objective of this study was to map and analyse agricultural land use in the irrigated areas of Kyzyl-Orda, southern Kazakhstan, Central Asia. For mapping land use and identifying abandoned agricultural land, an object-based classification approach was applied. Random forest (RF) and support vector machines (SVM) algorithms permitted classifying Landsat and RapidEye data from 2009 to 2014. Overlaying these maps with information about irrigated land parcels, installed during the Soviet period, allowed indicating abandoned fields. Fusing the results of the two approaches, RF and SVM, resulted in classification accuracies of up to 97%. This was statistically significantly higher than with RF or SVM alone. Through the analysis of the land use trajectories, abandoned agricultural fields and a clear indication of abandoned land were identified on almost 50% of all fields in Kyzyl-Orda with an accuracy of approximately 80%. The outputs of this study may provide valuable information for planners, policy- and decision-makers to support better-informed decision-making like reducing possible environmental impacts of land abandonment, or identifying areas for sustainable intensification or re-cultivation.     

Classification of snow cover days in western China and comparison with satellite remote sensing data

The daily snow cover data from 232 meteorological stations to the west of 105°E in China for the period 1951–2004 were used to classify the snow cover and analyze decadal variations of snow cover types in western China, and comparison was made between the observational data and those retrieved from passive microwave remote sensing data (SMMR and SSM/I) in 1980–2004. The results show that stable snow-covered areas included northern Xinjiang, the Tianshan Mountains, and the eastern Tibetan Plateau with more than 60 snow cover days; no snow cover was found in the center of the southern Xinjiang Basin, the Sichuan Basin, and southern Yunnan. In addition to the above-mentioned, there were unstable snow-covered areas in western China. Furthermore, the snow cover types in northern Xinjiang, the Tianshan Mountains, the Hexi Corridor, and the vast areas from Chengdu to Kunming were unchanged. In the 1980s, the south-north dividing line between the major snow-covered area and snow-free area advanced to its most southern position. The snow cover days calculated from satellite remote sensing were generally longer than those from observational data in western China, mainly in the higher-altitude mountains, the Hexi Corridor, and the western Sichuan Plateau.     

Characterization of the July 2007 Swaziland fire disaster using satellite remote sensing and GIS

Data from the NASA'S MODIS (Aqua and Terra) and EUMETSAT'S MSG-SEVIRI satellite sensors is analysed to characterise the geographic and temporal (including diurnal) evolution of the July 2007 fire disaster in the Kingdom of Swaziland using a geographic information system (GIS). Significant fire activity was observed during a three-day period beginning on the 27th July 2007. A total of 1358 and 4365 active fire hotpots were detected by MODIS and MSG-SEVIRI, respectively, mainly concentrated in the Highveld (70.91% for MODIS, 89.89% for MSG) and Middleveld (11.27% for MODIS, 5.23% for MSG) with MSG/MODIS active fire count ratio ranging from a high of 3.69 in the Highveld to a low of 0.06 in the Lubombo Plateau. The results indicate complex differences in spatial fire distribution, behaviour and risk within the country and the effect of sensor differences. A pronounced fire diurnal cycle with a broad afternoon peak centred on 14:00 local time is observed, in general agreement with observations from the region. Despite their limitations, the study demonstrates the importance and usefulness of remotely sensed data and GIS technology for fire disaster and risk assessment for a developing country, where fire monitoring resources are scarce.     

城市绿量测算模式及信息系统

作者提出了以彩红外航片判读和计算机模拟技术测算绿量、建立绿量数据库、及对该数据库的GIS化开发形成绿量信息管理系统的一整套理论技术与方法。     

Estimation of net primary productivity in China using remote sensing data

1 IntroductionAs a major part of terrestrial ecosystem, vegetation plays an important role in the energy, matter and momentum exchange between land surface and atmosphere. Through the process of photosynthesis, land plants assimilate carbon in atmosphere and incorporate into dry matter while part of carbon is emitted into atmosphere again through plant respiration. The remainder of photosynthesis and respiration is called net primary productivity (NPP), which is important in the global carbon…     

基于土壤数据和遥感影像的鄂尔多斯高原北部地貌分类(英文)

Landform classification is commonly done using topographic altitude only.However,practice indicates that locations at a same altitude may have distinctly different landforms,depending on characteristics of soils underneath those locations.The objectives of this study were to:1) develop a landform classification approach that is based on both altitude and soil characteristic;and 2) use this approach to determine landforms within a watershed located in northern Ordos Plateau of China.Using data collected at 134 out of 200 sampling sites,this study determined that D10(the diameter of soil particles 10% finer by weight) and long-term average soil moisture acquired in 2010,which can be estimated at reasonable accuracy from remote sensing imagery,can be used to represent soil characteristics of the study watershed.Also,the sampling data revealed that this watershed consists of nine classes of landforms,namely mobile dune(MD),mobile semi-mobile dune(SMD),rolling fixed semi-fixed dune(RFD),flat sandy land(FD),grassy sandy land(GS),bedrock(BR),flat sandy bedrock(FSB),valley agricultural land(VA),and swamp and salt lake(SW).A set of logistic regression equations were derived using data collected at the 134 sampling sites and verified using data at the remaining 66 sites.The verification indicated that these equations have moderate classification accuracy(Kappa coefficients > 43%).The results revealed that the dominant classes in the study watershed are FD(36.3%),BR(27.0%),and MD(23.5%),while the other six types of landforms(i.e.,SMD,RFD,GS,FSB,VA,and SW) in combination account for 13.2%.Further,the landforms determined in this study were compared with the classes pre-sented by a geologically-based classification map.The comparison indicated that the geo-logically-based classification could not identify multiple landforms within a class that are de-pendent upon soil characteristics.     

Texture-based identification of urban slums in Hyderabad, India using remote sensing data

This paper outlines a methodology to identify informal settlements out of high resolution satellite imagery using the concept of lacunarity. Principal component analysis and line detection algorithms were applied alternatively to obtain a high resolution binary representation of the city of Hyderabad, India and used to calculate lacunarity values over a 60 × 60 m grid. A number of ground truthing areas were used to classify the resulting datasets and to identify lacunarity ranges which are typical for settlement types that combine high density housing and small dwelling size - features characteristic for urban slums in India. It was discovered that the line detection algorithm is advantageous over principal component analysis in providing suitable binary datasets for lacunarity analysis as it is less sensitive to spectral variability within mosaicked imagery. The resulting slum location map constitutes an efficient tool in identifying particularly overcrowded areas of the city and can be used as a reliable source in vulnerability and resilience assessments at a later stage. The proposed methodology allows for rapid analysis and comparison of multi-temporal data and can be applied on many developing urban agglomerations around the world.     

雅鲁藏布江干流河宽时空变化遥感监测及水文气象响应

河宽作为河流形态的基本参数之一,对于理解地表水过程和河流生态系统功能至关重要。雅鲁藏布江是全球具有典型地域特色的高原河流,也是重要的国际河流。雅鲁藏布江地处偏远山区,其地形环境条件恶劣、测量站分布稀疏,严重限制了对雅鲁藏布江河流水文动态变化特征的科学理解。遥感卫星通过提供多时相、长时序观测影像数据,使雅鲁藏布江河宽长期动态变化监测和水文特征分析成为可能。本文基于全球地表水变化数据集（GLAD）,利用水体边界水淹频率阈值分割法重建了2000—2020年雅鲁藏布江逐月完整的水域范围,进而提取和解析雅鲁藏布江干流河宽的时空变化特征。研究结果表明：2000—2020年期间,受年内气温和降水季节性差异等影响,雅鲁藏布江干流河宽呈现出显著的季节性变化特征,中游河段的季节性变幅最大（453.6 m）,下游河段季节性变幅最小（90.3 m）;雅鲁藏布江干流河道受气候和地形的影响,空间分布差异大,河道可观察到的最窄处约30 m（即Landsat卫星影像的最小空间分辨率）,中下游辫状河流有效河宽最大可达6000 m,全程约50%长度的河道宽度小于150 m,仅2.0%的河道宽度大于2000 m;2000—2020年雅鲁藏布江干流河道的年平均河宽呈现先下降、后上升、再下降的变化特征,雅鲁藏布江全程平均河宽与降水、气温之间呈现较显著的正相关关系（通过p<0.01的显著性检验）,相关性系数R值均为0.7。此外,本文利用10 m分辨率Sentinel-2影像数据目视解译提取的河宽信息与本文基于GLAD重建的河宽结果进行对比验证,两者的相对偏差低于2%,表明本文雅鲁藏布江河宽的提取结果总体可信。     

塔里木盆地南缘和田地区土地利用变化的遥感研究

中国西部干旱区土地利用变化显著,是全球土地变化科学研究的热点区,为此论文基于1990—2016年4个时段的遥感卫星数据,采用面向对象的分层分类影像解译方法完成了塔里木盆地南缘和田地区(简称和田塔里木地区)土地利用调查,重点分析土地利用变化特征、发展模式和区域差异性。结果表明：1990—2016年,和田塔里木地区耕地持续加速扩张(增长率为2.9%/a),呈现渐进式扩张和骤变式开垦2种发展模式;建设用地面积增加(12.1%/a),主要表现为城市化发展、农村居民用地和交通用地的增加;耕地和建设用地扩张导致林灌草地和未利用地面积减少;和田地区县域土地利用发展不均衡,和田市建设用地比例最高,和田县与墨玉县的农业和建设用地扩张总量和速率最大,其次是洛浦县和于田县,皮山县、策勒县和民丰县农业和建设用地增长相对缓慢;总体上,和田塔里木地区耕地和建设用地的扩张在新疆处于一个较快的发展水平,今后一段时期快速的土地利用变化可能引起的生态环境问题需要重点关注。     

Mapping and monitoring of land use changes in post-Soviet western Ukraine using remote sensing data

While agriculture is expanded and intensified in many parts of the world, decreases in land use intensity and farmland abandonment take place in other parts. Eastern Europe experienced widespread changes of agricultural land use after the collapse of the Soviet Union in 1991, however, rates and patterns of these changes are still not well understood. Our objective was to map and analyze changes of land management regimes, including large-scale cropland, small-scale cropland, and abandoned farmland. Monitoring land management regimes is a promising avenue to better understand the temporal and spatial patterns of land use intensity changes. For mapping and change detection, we used an object-based approach with Superpixel segmentation for delineating objects and a Random Forest classifier. We applied this approach to Landsat and ERS SAR data for the years 1986, 1993, 1999, 2006, and 2010 to estimate change trajectories for this time period in western Ukraine. The first period during the 1990s was characterized by post-socialist transition processes including farmland abandonment and substantial subsistence agriculture. Later on, recultivation processes and the recurrence of industrial, large-scale farming were triggered by global food prices that have led to a growing interest in this region.     

适用于遥感影像的水生态空间多功能分类体系研究

水生态空间分类体系是研究水生态空间变化的重要前提。目前,水生态空间分类体系一般都基于特定的研究或者管理目的,没有相对统一的划定标准。因此,这些水生态空间分类体系间的可比性及可操作性就存在一定的局限。鉴于此,论文结合遥感观测技术,基于系统论提出了适用于遥感影像的水生态空间多功能分类体系。该分类体系具有一定的理论基础,同时也兼具遥感技术的可操作性和可比性,能为研究水生态空间的面积动态变化提供理论基础和技术保障。此外,研究还结合生产管理经验和专家咨询等方法,建立了适用于Landsat卫星遥感数据的各类水生态空间的解译标志。最后,以中国为例,运用2015年的Landsat卫星遥感数据,划定了中国各类水生态空间的分布,并得到了不同水生态空间类型所占的面积比,这为进一步研究中国水生态空间的演化规律奠定了坚实基础。     

基于多源遥感数据的中山站附近地区冰架和冰川变化监测

南极冰架和冰川的变化是全南极动态变化的主要过程之一。利用MODIS L1B级250 m分辨率数据和Landsat陆地卫星15 m分辨率数据,针对不同尺度试验区域,分别监测2000—2016年间中山站附近地区的埃默里冰架、极时代冰川、极记录冰川和达尔克冰川的动态变化过程,并对试验区的动态变化进行分析。结果表明,埃默里冰架在近16年间一直处于向外扩展状态,前缘年扩展速率和扩展面积量较为稳定;极时代和极记录冰川不断向海洋流动,极时代冰川于2007年发生大型崩解,而极记录冰川前端的冰山在2014年发生崩解,冰山面积逐年递减,于2016年完全漂离冰川前缘;达尔克冰川则在监测年份内呈现出了交替性扩展和崩解的变化规律。     

基于MODIS数据新疆土壤干旱特征分析

干旱是一种常见的自然灾害,严重影响着新疆的农业生产。利用中分辨率成像光谱仪MODIS影像MOD11A2数据和MOD13A2数据,数字高程模型(DEM)对Ts进行了纠正,提取归一化植被指数(NDVI)和地表温度(Ts)构建NDVI-Ts特征空间,并依据特征空间计算的温度植被干旱指数(TVDI)作为监测土壤湿度指标,反演了新疆2013年5、6、7三个月每16 d的土壤湿度。较好地反映地表图层土壤湿度,分析了新疆土壤湿度的时空分布特征,新疆北部地区土壤湿度高于南部,西部的土壤湿度高于东部,且土壤湿度由西北向东南逐步减小,依次表现为湿润>正常>轻旱>中旱>重旱>极旱;由5月到7月土壤湿度不断增大,这与新疆降水量分布和实地土壤含水率十分吻合,监测结果可信,能够为决策部门防旱抗旱提供有力的信息支持。     

卫星遥感检测高原湖泊水面变化及与气候变化分析

对西藏西部的玛旁雍错、中部的纳木错和南部的普莫雍错三大湖泊地区,采用中巴资源卫星自1999年至2007年长时间序列的影像数据,通过最佳波段组合和时相的选取,高精度几何配准和镶嵌以及进行边缘信息提取等处理,绘制湖面变化解译图。并用一景同期ETM 图像作为辅助数据计算湖区地物光谱反射率曲线以辅助分类。为避免个别年份湖面变化出现偶然性,采用几个相邻年份湖面求取平均值的方法统计近年湖面面积。其结果与1984年中国科学院青藏高原综合科学考察队的数字对比表明,西藏南部的普莫雍错和中部的纳木错湖面有明显扩张,分别扩张了大约4.01%和4.55%;而西部的玛旁雍错近年间变化不大,甚至略有萎缩趋势,相比1984年也仅增长了1.31%。为研究西部地区和中东部地区出现不同变化的主要原因,通过对水位数据和气象特征因子的相关性分析,及对三地区近34年的气象资料,包括年均温度、年均降雨量、年均蒸发量等进行距平均值曲线拟合,发现中东部年均温和降雨量均呈显著增加趋势,而西部降雨量则呈微弱减少趋势。这说明近期湖面的扩张与气象资料分析的变化情况具有很好的一致性,反映遥感方法在湖泊水域变化检测方面具有较高的可用性。     

夜间灯光遥感数据应用综述和展望

在遥感应用研究中,夜间灯光遥感作为发展活跃的一个重要分支,近年来受到越来越多来自自然科学领域和社会经济领域的关注。与传统的光学遥感卫星获取地物辐射信息不同,夜间灯光遥感是获取夜间无云条件下地表发射的可见光-近红外电磁波信息。相比于普通的遥感卫星影像,夜间灯光遥感所使用的夜间灯光影像记录的地表灯光强度信息更直接反映人类活动差异,因而被广泛应用于城市化进程研究、不透水面提取、社会经济指标空间化估算、重大事件评估、生态环境评估等领域。目前,虽然基于夜间灯光数据的应用研究成果正在不断积累,但对成果的系统性总结、整理的研究目前存在着覆盖面不全、时效性不强等不足。基于此,论文通过对近几十年来有关夜间灯光数据的研究成果的详细梳理,从数据处理与技术方法、应用研究等方面进行归纳总结。最后,文章从多源数据融合、应用领域拓展和短周期地表灯光监测3个方面指出了未来的研究热点。     

Grassland degradation in Northern Tibet based on remote sensing data

This study selected vegetation cover as the main evaluation index, calculated the grassland degradation index (GDI) and established the remote sensing monitoring and evaluation system for grassland degradation in Northern Tibet, according to the National Standard (GB19377-2003), based on the remote sensing data such as NDVI data derived from NOAA/AVHRR with a spatial resolution of 8 km of 1981-2000, from SPOT/VGT with a spatial resolution of 1 km of 2001 and from MODIS with a spatial resolution of 0.25 km of 2002-2004 respectively in this area, in combination with the actual condition of grassland degradation. The grassland degradation processes and their responses to climate change during 1981-2004 were discussed and analyzed in this paper. The result indicated that grassland degradation in Northern Tibet is very serious, and the mean value of GDI in recent 20 years is 2.54 which belongs to the serious degradation grade. From 1981 to 2004, the GDI fluctuated distinctly with great interannual variations in the proportion of degradation degree and GDI but the general tendency turned to severe-grade during this period with the grassland degradation grade changed from light degraded to serious degraded in Northern Tibet. The extremely serious degraded and serious degraded grassland occupied 1.7% and 8.0% of the study area, the moderate and light degraded grassland accounted for 13.2% and 27.9% respectively, and un-degraded grassland occupied 49.2% of the total grassland area in 2004. The grassland degradation was serious, especially in the conjunctive area of Naqu, Biru and Jiali counties, the headstream of the Yangtze River lying in the Galadandong snow mountain and glaciers, the area along the Qinghai-Tibet highway and railway, and areas around the Tanggula and Nianqingtanggula snow mountains and glaciers. So the snow mountains and glaciers as well as their adjacent areas in Northern Tibet were sensitive to climate change and the areas along the vital communication line with frequent human activities experienced relatively serious grassland degradation.     

Image data fusion for the remote sensing of freshwater environments

Remote sensing based mapping of diverse and heterogeneous freshwater environments requires high-resolution images. Data fusion is a useful technique for producing a high-resolution multispectral image from the merging of a high-resolution panchromatic image with a low-resolution multispectral image. Given the increasing availability of images from different satellite sensors that have different spectral and spatial resolutions, data fusion techniques that combine the strengths of different images will be increasingly important to Geography for land-cover mapping. Different data fusion methods however, add spectral and spatial distortions to the resultant data depending on the geographical context; therefore a careful selection of the fusion method is required. This paper compares a technique called subtractive resolution merge, which has not previously been formally tested, with conventional techniques such as Brovey transformation, principal component substitution, local mean and variance matching, and optimised high pass filter addition. Data fusion techniques are grouped into spectral and spatial centric methods. Subtractive resolution merge belongs to a new class of data fusion techniques that uses a mix of both spatial and spectral centric approaches. The different data fusion techniques were applied to a QuickBird image of a semi-aquatic freshwater environment in New Zealand. The results were compared both qualitatively and quantitatively using spectral and spatial error metrics. This research concludes that subtractive resolution merge performed better than all the other techniques and will be a valuable technique for enhancing images for freshwater land-cover mapping.     

藏北地区草地退化的时空分布特征

1 Introduction Commonly known as the “Weather System Sensitive Spot”, “Watertower of China” and “Rivershed”, the Naqu Prefecture of Northern Tibet is the source region of such major rivers as the Yangtze, the Nujiang and the Lancang in China (Gansu