地形坡面对被动微波遥感影响的试验研究

地表起伏所形成的倾斜表面,特别是在山区,受地形坡度和坡向变化的影响,地表的微波辐射特征较之平坦地表发生明显变化。基于地基微波辐射地形试验,模拟星载被动微波辐射计AMSR\|E的观测参数,通过建立地形坡面的地貌微缩景观进行观测,探索地表斜坡对被动微波辐射特征的影响,用AIEM模型 和 Fresnel 方程分别模拟裸土地形坡面的微波辐射特征。结果表明,倾斜坡面对被动微波辐射的亮度温度产生了10~15 K的偏差,由坡度形成的本地入射角改变了地表的有效发射率,并随坡向的变化发生微波极化旋转。经试验数据和模型模拟结果对比,认为AIEM 在考虑了表面粗糙度影响时可以较好地模拟地形坡面的被动微波辐射特征。     

Land surface phenology of North American mountain environments using moderate resolution imaging spectroradiometer data

Monitoring and understanding plant phenology is becoming an increasingly important way to identify and model global changes in vegetation life cycle events. High elevation biomes cover twenty percent of the Earth's land surface and provide essential natural resources. These areas experience limited resource availability for plant growth, development, and reproduction, and are one of the first ecosystems to reflect the harmful impact of climate change. Despite this, the phenology of mountain ecosystems has historically been understudied due to the rough and variable terrain and inaccessibility of the area. In addition, although numerous studies have used synoptically sensed data to study phenological patterns at the continental and global scales, relatively few have focused on characterizing the land surface phenology in mountainous areas. Here we use the MODIS/Terra + Aqua satellite 8-day 500 m Nadir BRDF Adjusted Reflectance product to quantify the land surface phenology. We relate independent data for elevation, slope, aspect, solar radiation, and temperature as well as longitude and latitude with the derived phenology estimates. We present that satellite derived SOS can be predicted based on topographic and weather variables with a significant R²adj between 0.56 and 0.62 for the entire western mountain range. Elevation and latitude exhibit the most significant influences on the timing of SOS throughout our study area. When examined at both the local and regional scales, as well as when accounting for aspect and temperature, SOS follows closely with Hopkins' Bioclimatic Law with respect to elevation and latitude.     

Snow Cover Change Analysis within the Year of Typical Area in Tianshan Mountains

Using the observation snow cover data from Landsat TM and ETM+ from January 2000 to May 2001, the inter annual temporal and spatial characteristics of snow cover over middle Tianshan mountains are analyzed. Combining with digital elevation model (DEM) data, the distribution of snow cover in different terrain conditions and different altitude per-month are acquired. After analyzing the spatial distribution and temporal variation regulation of snow cover, it comes to a conclusion that the snow cover within year is correlated with altitude, aspect and slope. On the whole, the ratio of snow cover within year increases when the altitude increases and it decreases when the slope increases. The average height of snow cover boundary is high in summer and autumn but low in spring and winter. The difference of snow cover in aspect west and east is obvious in certain times, but the difference is less than that of the aspect north and south. This study provides a scientific support for utilization of water resource and the research of climate and environment in Tianshan Mountains.     

Field-based spectral reflectance measurements of seasonal snow cover in the Indian Himalaya

In the present study, spectroradiometer (350–2500 nm) experiments are carried out in the field to understand the influence of snow grain size, contamination, moisture, ageing, snow depth, slope / aspect on spectral reflectance and to determine the sensitive wavelengths for mapping of snow and estimation of snow characteristics using satellite data. The observations suggest that, due to ageing and grain-size variation, the maximum variations in reflectance are observed in the near-infrared region, i.e. around 1040–1050 nm. For varying contamination and snow depth, the maximum variations are observed in the visible region, i.e. around 470 and 590 nm, respectively. For the moisture changes, the maximum variations are observed around 980 and 1160 nm. Based on the spectral signatures of seasonal snow, the normalized difference snow index (NDSI) is studied, and snow indexes, such as grain and contamination indexes, are proposed. The study also suggests that the NDSI increases with ageing, grain size and moisture content. The NDSI values remain constant with variations in slope and aspect. Attempts are made to estimate seasonal snow characteristics using multispectral Advanced Wide Field Sensor (AWiFS) Indian Remote Sensing (IRS-P6) and Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite data and validated with snow-meteorological observatory data of the study area.     

The Study of Spatial-Temporal Characteristics for Chlorophyll Concentration derived from Remote Sensing Image in Xinfengjiang Reservoir

By investigating the law of radiative transfer and the process of scattering and absorption from suspended sediment，chlorophyll and oxygen\|consuming organics，this paper builds the model，it formulate the functional relationship between the reflection and the concentration of this three kinds of water quality parameters，therefore retrieve the concentration.With this model，the chlorophyll concentration in Xinfengjiang Reservoir can be inversed，then using the measured data to verify the inversion result，the correlation coefficient between them equals 0.94，and the average relative error equals 66.67%.By analyzing the characteristics of the chlorophyll spatial structure and its time distribution based on the result，we find out that the lowest concentration of the chlorophyll is always existing in the center area during the whole year，and the area near Xinfengjiang River and Zhongxinshui River has the highest concentration，associated with cage culture.Multiple factors has been considered in the model building in this paper，and hence multi\|spectral remote sensing data were successfully applied to improve the calculation accuracy.     

低空间分辨率多源遥感数据的空间一致性分析和相对几何校正

多源低空间分辨率遥感数据在空间上的一致性对于其在全球变化研究中的集成使用有非常重要的意义。对此,以公认几何精度较高的MODIS数据为基准,对NOAA/AVHRR、FY-3/VIRR、FY-3/MERSI、FY-2/VISSR这4类国内外常用的低空间分辨率传感器的L1B数据进行了一系列相对几何精度评价和多项式相对几何校正的实验。相对几何精度评价的结果表明:MODIS数据与这4类L1B数据在几何精度上的偏差都比较大。在此基础上,选取少量均匀分布的控制点并采用不同阶数的多项式几何校正模型对多源数据进行空间一致性校正。校正结果表明:低阶的多项式几何校正模型就能对各种待校正数据的几何精度有显著的提升,使其与基准数据在空间上达到一致,满足全球变化研究对低分辨率多源遥感数据在空间一致性上的需求。     

一种融合遥感和地面观测资料的雪深空间插值方法

针对积雪观测站点稀少的问题,提出一种考虑海拔影响,能够融合MODIS积雪面积产品和站点观测的雪深空间插值方法,该方法利用去云后MODIS积雪面积产品构建的无积雪“虚拟站点”弥补站点分布不均匀和稀少的不足,利用泛协克里金插值方法考虑海拔对雪深的影响。利用北疆地区50个气象站点的逐日雪深观测资料、逐日MODIS积雪面积产品和AMSR-E被动微波雪水当量和雪深产品,对普通克里金、泛克里金、普通协克里金和泛协克里金插值结果进行了比较研究。研究结果表明:积雪覆盖范围较大时,站点雪深与海拔之间相关系数较大,利用泛协克里金插值结果精度高且稳定;否则利用普通克里金插值精度较高且稳定。通过增加“虚拟站点”,能够提高雪深插值精度,并在一定程度上修正了克里金插值中存在的平滑效应。
     

Technical Note: DEM from IRS-1C PAN stereo coverages over Himalayan glaciated region—accuracy and its utility

Satellite photogrammetric technique has been used for monitoring of fluctuations of Himalayan glaciers and the resulting changes in the elevations of glacier snouts. Two across-track stereo pairs from the Indian Remote Sensing Satellite (IRS)-1C covering parts of Basapa valley, a high altitude Himalayan glaciated terrain, were processed for generation of digital elevation models (DEM) and orthoimages using a softcopy photogrammetry workstation. Two glacier regions, viz., Janapa Garang and Shaune Garang glacier valley, were taken up for the study. For one glacier region, the stereo pair was generated in a workstation by replacing an image of one pair with an image from the other pair. Interchanging input image and reference image in the new pair has resulted in improvement in image matching. Accuracies related to location (in terms of latitude and longitude) and elevation of image features in the accumulation zone, ablation zone and nonglaciated regions with respect topographical map were checked. Based on geographical location and elevation of the snout derived from a topographical map of 1962 and the DEM and orthoimage of 1997, the two glaciers have been observed to have a retreat of about 690?m and 925?m, respectively.     

Application Progress on Goldstone Solar System Radar and Its Inspiration for Deep Space Exploration in China

Goldstone Solar System Radar(GSSR) has been played an important role in international deep space exploration and widely used in lunar terrain mapping，Mars exploration，asteroids orbit determination，deep space aircraft measurement or control，etc.We reviewed the background and summarized the present development situation of the GSSR system which is the only fully steerable imaging radar system in the world for planetary and small\|body targets.Then，we analyzed the composition of the GSSR system and its imaging principle of the near\|Earth objects in details.In addition，we emphatically introduced the new applications of GSSR in deep space exploration.GSSR has provided an inspiration for the deep space exploration in China and given a valuable reference to Lunar\|based Synthetic Aperture Radar(SAR) for Earth observation.     

The Comparison of Reflectance based on Different Terrain Correction

Selecting the Xinglong Mountain which locates in the southeast of Lanzhou city，GanSu province as an example.Using the Landsat8 satellite image as the data source，the Cosine method，C and the modified Minnaert methods were used for each band in the study area.Comparing with the results of the field measurement reflectance and the statistical characteristics of image，the result showed that the cosine method has a perfect correction in the visible and short wave infrared wavelength，the C correction has a serious over\|correct，however.In the Near Infrared Wavelength，the better result obtained by C correction，and the cosine method has over\|correct otherwise.Comparing with the correct effect of whole bands，the modified Minnaert method has an ideal correct effect.The comparison of before and after correction we found that there is a smaller difference for three methods in the smaller slope，and the over correct is mostly in the south.What’s more，with the increase of the slope，the over correct is more obviously，but，there is a little over correct which used the modified Minnaert method in the whole area，it’s more suitable in large slope and the complicated area.     

Application to GF-2 Satellite for Road Landslides Monitoring

Global warming has profoundly changed extreme weather events,and remote sensing technology is gradually being applied to the monitoring of ecological and environmental disasters.China is one of the countries with most serious natural disasters in the world.With the development of human society and the improvement of people’s awareness of disaster risk,geological disaster monitoring and risk management has attracted more and more attention.Taking the Adjacent Area of Changsha \| Xiangtan(CXAA),which is the main part of Xiangtan jiuhua economic development zone,as the research area,the road slope and the ecological environment in the area were monitored by using the fusion image of high spatial resolution remote sensing of GF\|2 made in China on March 27,2016.Taking normalized difference vegetation index(NDVI),terrain slope index,soil index and other parameters as inputs,the comprehensive evaluation of ecological environment in CXAA was obtained by simulating the comprehensive factors of ecological environment with the comprehensive index method.We found that the ecological environment of 78.75 % of the study area was good,which indicated that the natural ecological environment on both sides of the road and the surrounding areas was basically not damaged.The road surface,water area(such as Xiangjiang river),construction land(such as Xiangtan high\|speed railway north station) and industrial areas(such as Geely automobile,Tidfore enterprise group,etc.) and other regions of the ecological environment comprehensive index is poor,on both sides of the road in some slope sections still exist the potential risk of landslide.Therefore,we suggest that during the rainy season,there is a need for more time\|phase high spatial resolution of GF-2 remote sensing satellite and other domestic GF satellite continuous monitoring,in order to more fully understand the risk of road slope landslide and provide early warning.     

基于FY-4A/AGRI时空特征融合的新疆地区积雪判识

高时间分辨率的积雪判识对于新疆牧区农牧业发展和雪灾预警具有重要作用,针对已有积雪产品易受复杂地形地貌,下垫面类型以及云遮蔽的影响,导致积雪判识精度降低的问题,提出一种利用深度学习方法对风云4号A星多通道辐射扫描计（AGRI）数据与地理信息数据进行多特征时序融合的积雪判识方法：以多时相FY-4A/AGRI多光谱遥感数据,以及高程、坡向、坡度和地表覆盖类型等地形地貌信息作为模型输入,以Landsat 8 OLI提取的高空间分辨率积雪覆盖图作为“真值”标签,构建并训练基于卷积神经网络的积雪判识模型,从而有效区分新疆复杂地形与下垫面地区的云、雪以及无雪地表,最终得到逐小时积雪覆盖范围产品。经数据集和2019年地面气象站实测雪盖验证,该方法精度高于国际主流MODIS逐日积雪产品MOD10A1和MYD10A1,显著降低云雪误判率。     

基于多源数据的阿勒泰地区雪深反演研究

利用阿勒泰地区 2010~2012年冬季(11月~次年2月)3类积雪数据:风云三号微波成像仪(FY\|3/MWRI)反演的雪深数据、美国人机交互式多仪器冰雪制图系统(IMS)积雪面积数据、阿勒泰及周边地区实测雪深数据,进行积雪深度的反演研究。通过结合3类积雪数据的各自优势,建立修正模型,最终得到较准确的研究区雪深数据。同时通过编程实现了相应模型的操作平台,为今后研究区积雪业务化监测做好准备。结果表明:模型提高了FY\|3/MWRI数据反演阿勒泰地区积雪深度的准确性,改善了FY\|3/MWRI数据在阿勒泰地区雪深反演偏低的缺点,使微波与实测平均雪深误差由修正前的21.7~12.1 cm缩小为修正后的3.7~1.5 cm。     

基于AMSR2和MODIS数据融合的雪深降尺度算法研究—以北疆地区为例

高空间分辨率雪深数据对于区域气候、水文研究具有重要的意义。利用10 km空间分辨率的AMSR2 L1B亮度温度数据,结合500 m空间分辨率的MODIS逐日无云积雪面积比例数据,发展了一种多源数据融合的空间动态降尺度雪深反演算法（SDD）。基于该算法获取了北疆地区500 m空间分辨率的雪深数据（SDDsd）,并利用研究区30个气象台站和野外实测的雪深数据对该算法反演雪深的精度进行了评估。结果表明：基于SDD方法获取的雪深数据与实测雪深数据之间的决定系数R²为0.74,均方根误差RMSE为3.47 cm;雪深反演的精度与下垫面类型密切相关,草地精度最高,城镇和建设用地次之,耕地相对较差;雪深反演的精度也会受到地形的影响,精度随坡度的增加而降低。相对于微波遥感雪深数据直接重采样结果,新的算法有效提高了浅雪区雪深反演精度,同时能更精细地描述积雪的空间分布,为理解区域气候变化、水文循环提供了可靠的数据支撑。此外,随着长时间序列全球尺度逐日无云FSC数据的生产,结合现有的长时间序列全球尺度AMSR2数据,该算法有望制备全球的降尺度雪深产品。     

基于MODIS的青藏高原雪线高度遥感监测

雪线作为区分积雪覆盖区与无雪区的边界线,是冰冻圈各要素中对气候变化最为敏感的指示器。利用去云后的MODIS积雪面积比例产品并结合DEM数据,通过雪线像元及其高度的提取、雪线高度场的建立,对青藏高原近12a(2000~2011年)雪线高度的时空变化特征进行了分析。结果表明:青藏高原雪线高度的分布受地形的影响,高原内部的雪线高度明显高于周围山区;在近12a中,青藏高原的雪线高度变化虽然没有明显的年际变化趋势(升高或者降低),但是体现出较高的年内和年际波动特征,特别是青藏高原的东部和南部地区由于受西南季风的影响,夏季雪线高度的年际变化尤为强烈。提出基于MODIS的雪线高度提取方法具有较好的应用潜力,能够适用于其他地方雪线高度的遥感监测。     

地形对高山区TM积雪定量遥感的影响

高山区积雪的辐射特性受到高度迅速变化和地形强烈分异的显著影响,必须对图像进行辐射纠正和地形纠正以得到标准化的图像。利用大气纠正模型和对太阳辐照入射度的模拟,在高精度数字高程模型和实验区气象观测资料的支持下,通过计算光谱反射比而实现地形标准化,是一条行之有效的方法。这一方法在天山乌鲁木齐河上游冰川区得到了实际检验,被证明是实现积雪定量遥感,提高积雪区地物分类精度的重要前提。并对这一方法的局限性进行了讨论。     

冰雪反照率测量和反演及其应用研究进展

总结了反照率的相关概念和2种主要的测量方法,分析了诸如雪粒径、含水量、烟尘、雪密度、雪深、太阳天顶角、大气状况和新降雪等因素对反照率的影响,介绍了遥感反演反照率通用的基本方法步骤,包括辐射校正、大气校正、各向异性校正和窄带转宽带反照率。最后阐述了反照率的研究动态和研究应用,如地表能量平衡、冰雪面积制图、确定雪粒径和反演雪线等。     

Spatiotemporal Change of Water Storage and Its Influencing Factorsin the Ili-Balkhash Basin based on GRACE Data

Climate change and human activities significantly influence regional distribution of water resources and socio\|economic and environmental sustainability.The separation of water formation and dissipation in the arid region leads to a challenge for regional water resources management.A clear insight view on regional water storage variation lacks due to the scarcity of ground observation data in the region.This study applied the satellite data to investigate regional water storage variation in the Ili\|Balkhash Basin.The water storage variation data derived from UTCSR\|RL05 L\|2 data with 1°×1° was compared with the data from GLDAS within a period from January 2003 to May 2014，then applied to investigate the temporal and spatial characteristics of water storage variation as well as their influencing factors in the Basin.The results indicated that water storage increased from every November to April of the next year，and decreased from May to October.Among the factors influencing water storage change in the basin，bias between precipitation and evaporation(BPE) is a most important factor to influence regional water storage change，followed by evaporation.Spatially，the factors influencing water storage change differ in water formation and dissipation region.Water storage change is most influenced by precipitation in the water formation region，but by BPE in the water dissipation region，and the impact of evaporation on water storage change in the water dissipation region is greater than that in the water formation region.     

Learning sequences of sparse correlated patterns using small-world attractor neural networks: An application to traffic videos

The goal of this work is to learn and retrieve a sequence of highly correlated patterns using a Hopfield-type of attractor neural network (ANN) with a small-world connectivity distribution. For this model, we propose a weight learning heuristic which combines the pseudo-inverse approach with a row-shifting schema. The influence of the ratio of random connectivity on retrieval quality and learning time has been studied. Our approach has been successfully tested on a complex pattern, as it is the case of traffic video sequences, for different combinations of the involved parameters. Moreover, it has demonstrated to be robust with respect to highly variable frame activity.     

基于MODIS数据的我国天山典型区积雪特征研究

准确监测天山地区积雪面积和积雪日数对合理利用水资源及分析区域气候变化有重要意义。MODIS每日积雪产品可以为大面积快速积雪制图与监测提供依据,但因云量较高成为其应用的瓶颈。利用结合MODIS产品的时间与空间信息有效地减少了云对MODIS积雪产品的影响,并利用改进的MODIS积雪数据和DEM分析2002~2009年天山地区积雪面积和积雪日数的变化特征。结果表明:积雪频率总体上随着海拔升高而增大;不同坡向积雪面积差异明显,西北坡积雪覆盖率最高,北坡、西坡和东北坡次之,南坡和东南坡的积雪覆盖率最低;2006~2008年研究区积雪面积出现低值,年内最大积雪面积呈逐年减少的趋势;随着海拔下降,积雪日数逐渐变小,天山南部地区积雪日数仅为40 d以下;积雪日数大的区域年际积雪日数变化相对稳定,积雪日数少于40 d的区域积雪日数的变异系数最大,年际积雪日数变化不稳定。