星地多源数据的区域土壤有机质数字制图

土壤有机质(SOM)是全球碳循环、土壤养分的重要组成部分,精确估算土壤有机质含量具有重要意义。本文以中国东北—华北平原为研究区,收集了1078个土壤样本,以遥感数据(MODIS,TRMM和STRM数据)与土壤地面光谱数据为预测因子,运用基于树形结构的数据挖掘技术构建土壤有机质-环境预测因子模型进行数字土壤制图。通过不同建模样本数建模精度比较,选择300个样本数时的模型为最优模型。建模结果表明土壤光谱和气候因子是研究区SOM变异的主控因子,生物因子次之,而地形因子影响最小。预测结果经检验,RMSE为7.25,R2为0.69,RPD为1.53制图结果与基于第二次全国土壤普查数据的土壤有机质地图具有相似的分布规律,呈现SOM自东北向西南递减的趋势。通过比较分析发现,经过20年左右的土地开发与利用,研究区低SOM和高SOM含量土壤面积减少,而中等SOM含量土壤面积增加。     

Sentinel-3 OLCI数据的内陆湖泊有机悬浮物浓度遥感估算

有机悬浮物OSM (Organic Suspended Matter)是湖泊有机碳库的重要组成成分,对研究湖泊生态环境和初级生产力具有重要意义.本研究以太湖、巢湖、涌湖、小兴凯湖、滇池、洪泽湖、呼伦湖和南漪湖8个内陆湖泊为研究区,发展了适合内陆水体的有机悬浮物浓度遥感估算方法.基于B6、B7波段的斜率和B10、B11波...     

Multiresolution fusion of remote sensing images based on resolution degradation model

A new method based on resolution degradation model is proposed to improve both spatial and spectral quality of the synthetic images. Some ETM panchromatic and multispectral images are used to assess the new method. Its spatial and spectral effects are evaluated by qualitative and quantitative measures and the results are compared with those of IHS, PCA, Brovey, OWT(Orthogonal Wavelet Transform) and RWT (Redundant Wavelet Transform). The results show that the new method can keep almost the same spatial resolution as the panchromatic images, and the spectral effect of the new method is as good as those of waveletbased methods.     

Re-parameterization of a quasi-analytical algorithm for colored dissolved organic matter dominant inland waters

Quasi-Analytical Algorithms (QAAs) are based on radiative transfer equations and have been used to derive inherent optical properties (IOPs) from the above surface remote sensing reflectance (R_rs) in aquatic systems in which phytoplankton is the dominant optically active constituents (OACs). However, Colored Dissolved Organic Matter (CDOM) and Non Algal Particles (NAP) can also be dominant OACs in water bodies and till now a QAA has not been parametrized for these aquatic systems. In this study, we compared the performance of three widely used QAAs in two CDOM dominated aquatic systems which were unsuccessful in retrieving the spectral shape of IOPS and produced minimum errors of 350% for the total absorption coefficient (a), 39% for colored dissolved matter absorption coefficient (a_CDM) and 7566.33% for phytoplankton absorption coefficient (a_phy). We re-parameterized a QAA for CDOM dominated (hereafter QAA_CDOM) waters which was able to not only achieve the spectral shape of the OACs absorption coefficients but also brought the error magnitude to a reasonable level. The average errors found for the 400–750 nm range were 30.71 and 14.51 for a, 14.89 and 8.95 for a_CDM and 25.90 and 29.76 for a_phy in Funil and Itumbiara Reservoirs, Brazil respectively. Although QAA_CDOM showed significant promise for retrieving IOPs in CDOM dominated waters, results indicated further tuning is needed in the estimation of a(λ) and a_phy(λ). Successful retrieval of the absorption coefficients by QAA_CDOM would be very useful in monitoring the spatio-temporal variability of IOPS in CDOM dominated waters.     

融入空间关系的二型模糊模型高分辨率遥感影像分割

为解决高分辨率遥感影像分割中,由光谱测度的空间复杂性、相同类型地物目标异质性增大带来的类属不确定性以及分割决策不确定性等引起的分割精度下降问题,提出一种融入空间关系的区间二型模糊模型高分辨率遥感影像监督分割方法。(1)建立高斯函数模型作为一型模糊模型,用来刻画像素类属的不确定性;(2)模糊化一型模糊模型中的均值或标准差,建立区间二型模糊模型,以强化类属的不确定表达和增加分割决策信息;(3)综合一型模糊模型及区间二型模糊模型的上、下隶属函数建模模糊决策模型;(4)融入邻域像素关系,使用待分像素及其邻域像素在模糊决策模型中的隶属度共同决定像素的类属。采用本文算法分别对真实高分辨遥感影像及合成影像进行分割,并对测试结果进行定性和定量分析。结果表明,本文算法可以得到更高的分割精度。     

基于Sentinel-2影像的雄安新区2016—2019年土地利用分析

雄安新区是国家层面打造的又一个具有重要战略意义的新区,及时准确掌握该地区的土地利用详情具有重要意义。本文利用10 m分辨率的Sentinel-2影像对雄安新区2016—2019年的土地利用进行分类,进而分析该地区的土地利用时空演变。共测试了决策树、随机森林和支持向量机3种分类器,进而获得最高精度的土地分类结果图;同时,利用随机森林的特征排序功能分析了不同特征的重要性。结果表明,雄安新区的耕地、林地、水生植物面积总体均呈显著减少趋势,建设用地面积变化最为显著,表明雄安新区正在进行中、快速的城市化发展。本研究得到的10 m分辨率土地利用专题图和分析结果对于雄安新区的及时监测与规划有着重要参考意义。     

Indoor scene texturing based on single mobile phone images and 3D model fusion

Realistic texture mapping and coherent up-to-date rendering is one of the most important issues in indoor 3-D modelling. However, existing texturing approaches are usually performed manually during the modelling process, and cannot accommodate changes in indoor environments occurring after the model was created, resulting in out-dated and misleading texture rendering. In this study, a structured learning-based texture mapping method is proposed for automatic mapping a single still photo from a mobile phone onto an already-constructed indoor 3-D model. The up-to-date texture is captured using a smart phone, and the indoor structural layout is extracted by incorporating per-pixel segmentation in the FCN algorithm and the line constraints into a structured learning algorithm. This enables real-time texture mapping according to parts of the model, based on the structural layout. Furthermore, the rough camera pose is estimated by pedestrian dead reckoning (PDR) and map information to determine where to map the texture. The experimental results presented in this paper demonstrate that our approach can achieve accurate fusion of 3-D triangular meshes with 2-D single images, achieving low-cost and automatic indoor texture updating. Based on this fusion approach, users can have a better experience in virtual indoor3-D applications.     

Spatial and semantic effects of LUCAS samples on fully automated land use/land cover classification in high-resolution Sentinel-2 data

In this study, we test the use of Land Use and Coverage Area frame Survey (LUCAS) in-situ reference data for classifying high-resolution Sentinel-2 imagery at a large scale. We compare several pre-processing schemes (PS) for LUCAS data and propose a new PS for a fully automated classification of satellite imagery on the national level. The image data utilizes a high-dimensional Sentinel-2-based image feature space. Key elements of LUCAS data pre-processing include two positioning approaches and three semantic selection approaches. The latter approaches differ in the applied quality measures for identifying valid reference points and by the number of LU/LC classes (7–12). In an iterative training process, the impact of the chosen PS on a Random Forest image classifier is evaluated. The results are compared to LUCAS reference points that are not pre-processed, which act as a benchmark, and the classification quality is evaluated by independent sets of validation points. The classification results show that the positional correction of LUCAS points has an especially positive effect on the overall classification accuracy. On average, this improves the accuracy by 3.7%. This improvement is lowest for the most rigid sample selection approach, PS₂, and highest for the benchmark data set, PS₀. The highest overall accuracy is 93.1% which is achieved by using the newly developed PS₃; all PS achieve overall accuracies of 80% and higher on average. While the difference in overall accuracy between the PS is likely to be influenced by the respective number of LU/LC classes, we conclude that, overall, LUCAS in-situ data is a suitable source for reference information for large scale high resolution LC mapping using Sentinel-2 imagery. Existing sample selection approaches developed for Landsat imagery can be transferred to Sentinel-2 imagery, achieving comparable semantic accuracies while increasing the spatial resolution. The resulting LC classification product that uses the newly developed PS is available for Germany via DOI: https://doi.org/10.15489/1ccmlap3mn39.     

基于GIS与遥感影像的银行ATM机网点选址方法研究

本文针对当前影响ATM机布点的因素,提出了基于矢量图和遥感影像的可视化平台。首先应用门槛分析模型将区域划分为潜力区域(含有ATM机但还有布放潜力的区域)和空白区域(不含ATM机的区域),从宏观上分析区域布放的可行性,并通过计算潜力区域和空白区域内的网点消费潜力,得出适合布放ATM机的区域,然后通过点位评估模型来分析这些区域内的网点,最后评估出可以布放ATM机的网点,并以北京某公司ATM机布点选址规划应用本文的选址方法进行了实践,取得了很好的效果。     

利用Sentinel-2A多光谱成像仪与Landsat8陆地成像仪影像进行普陀山岛植被分类效果比较

卫星遥感技术可用于海岛资源调查。Sentinel-2A与Landsat 8两颗卫星都可免费提供空间分辨率较高的多光谱遥感影像,在海岛调查中的应用潜力较大。本文以浙江舟山普陀山岛为例开展了针对这两种影像在海岛植被分类中的应用效果的研究,分别利用Sentinel-2A多光谱成像仪（MSI）和Landsat 8陆地成像仪（OLI）影像基于最大似然法分类获得了该岛阔叶林、针阔混交林、针叶林、灌丛、草丛等植被及其他地物的分布情况,并进行了精度检验,结果表明MSI的总体分类精度略高于OLI。     

Sentinel-2密集时间序列数据和Google Earth Engine的潮间带湿地快速自动分类

潮间带湿地是滨海湿地的重要组成部分,具有维持生物多样性、促进碳汇等重要生态功能.及时、准确地掌握潮间带湿地现状是实现潮间带湿地可持续管理目标的基础.先前的潮间带湿地分类研究依赖于训练样本、人工设定阈值或后处理等,本研究基于GEE (Google Earth Engine)平台开发一种自动、快速、高精度的潮间带湿地分类方...     

基于Sentinel-2A/B的新疆典型城市不透水面提取及空间差异分析

随着城市化进程加快,自然地表物理结构及属性的变化使得城市不透水面不断增加,进而造成城市土地覆盖类型剧烈变化,极大地影响着其环境质量和生态循环。因此,探讨不透水面的空间变化规律,对建设生态、和谐、宜居城市变得极为重要。本文选取新疆维吾尔自治区（简称新疆）典型城市（乌鲁木齐、喀什、哈密及克拉玛依）主城区为研究区,通过对Sentinel-2A/B影像L2范数归一化处理,结合增强型归一化差值不透水面指数ENDISI（Enhanced Normalized Difference Impervious Surface Index）,采用最大类间方差法（OTSU）自适应确定阈值,提取2017年和2019年新疆典型城市不透水面。结果表明：L2范数归一化处理与ENDISI结合能较好的突显不透水面与非不透水面的差异;OTSU自适应确定的阈值能够很好的区分不透水面,经示例验证（2019年乌鲁木齐主城区）,不透水面提取结果总体精度为86.60%,Kappa系数为0.73。通过对不透水面空间差异分析可知：从剖面线角度分析得出乌鲁木齐北部、喀什中部和北部及哈密中东部和北部ENDISI指数值均显著增加,而克拉玛依北部和中西部区域ENDISI指数值增加较少;从不透水面盒维数分析中得出,新疆典型城市的盒维数值均呈增加趋势,城市结构复杂度不断增强,其中哈密盒维数值最大,乌鲁木齐盒维数值最低,且哈密的盒维数值变化幅度最大,克拉玛依的盒维数值变化最小。本文可为新疆典型城市内涵式发展提供科学指导,为干旱区城市生态环境保护提供理论依据。     

基于光谱和纹理特征的山区高分辨率遥感影像分类

本文在只做阴影补偿而不做地形校正的情况下,使用光谱和纹理特征相结合的方法进行山区高分辨率遥感影像分类。实验取得了78%的分类精度,表明该方法合理可行,具有一定的实用性。     

基于星载激光雷达的高原堰塞湖水文要素反演与变化特征分析

针对帕米尔高原堰塞湖——萨雷兹湖的安全问题及水文站点资料获取困难,缺乏时段固定、精度统一的准实时湖泊水位信息等问题,本文提出了基于星载激光雷达测高数据(ICESat-1/2)的高原湖泊水位综合反演.开展了近20年(2003—2019年)的水位变化遥感调查和时序重建研究,并采用趋势分析和Mann Kendall(M-K)...     

Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3

Sentinel-2 is planned for launch in 2014 by the European Space Agency and it is equipped with the Multi Spectral Instrument (MSI), which will provide images with high spatial, spectral and temporal resolution. It covers the VNIR/SWIR spectral region in 13 bands and incorporates two new spectral bands in the red-edge region, which can be used to derive vegetation indices using red-edge bands in their formulation. These are particularly suitable for estimating canopy chlorophyll and nitrogen (N) content. This band setting is important for vegetation studies and is very similar to the ones of the Ocean and Land Colour Instrument (OLCI) on the planned Sentinel-3 satellite and the Medium Resolution Imaging Spectrometer (MERIS) on Envisat, which operated from 2002 to early 2012. This paper focuses on the potential of Sentinel-2 and Sentinel-3 in estimating total crop and grass chlorophyll and N content by studying in situ crop variables and spectroradiometer measurements obtained for four different test sites. In particular, the red-edge chlorophyll index (CI_red-edge), the green chlorophyll index (CI_green) and the MERIS terrestrial chlorophyll index (MTCI) were found to be accurate and linear estimators of canopy chlorophyll and N content and the Sentinel-2 and -3 bands are well positioned for deriving these indices. Results confirm the importance of the red-edge bands on particularly Sentinel-2 for agricultural applications, because of the combination with its high spatial resolution of 20 m.     

高分辨率遥感卫星立体影像RPC模型定位的算法及其优化

介绍了高分辨率遥感卫星影像的RPC模型,重点探讨了基于RPC模型的立体定位算法,并给出了补偿RPC模型系统误差的物方方案和像方方案.针对IKONOS卫星数据的实验结果表明,这些方案能有效地消除RPC模型的系统误差,达到的定位精度能满足1:10000比例尺的地形图测绘要求.     

利用3S技术综合研究新疆塔里木河流域中下游11年生态环境变化与成因

介绍了综合运用RS、GIS和GPS（3S）技术对新疆塔里木河流域中下游土地覆盖与土地利用、植被指数、人口经济等主要生态环境要素的遥感时序信息提取、GIS数据分析和GPS野外定点检测。总结出塔里木河流域中下游地区从1990-2000年的11年间农业用地面积增加了505.433km^2，整个自然/半自然植被的面积减少了943.089km^2，水体面积增加了80.477km^2，塔河中下游天然植被大面积衰败和死亡，尤其是胡杨林面积锐减，致使沙漠化面积不断扩大。初步提出了生态环境修复和治理建议。通过研究还建立了新疆塔里木河流域中下游3S生态环境动态监测系统。     

三维七参数与二维七参数坐标转换的研究

为了验证三维七参数和二维七参数坐标转换模型的可靠性,严格推导三维七参数及二维七参数转换模型,并用IGS站数据进行检验。结果表明,由三维七参数和二维七参数转换模型求出的坐标参数与布尔沙模型求出的坐标参数存在着明显差异,证明用前两种模型求解的坐标转换参数只是普通的回归参数,它们不再具有坐标旋转、平移、缩放的实际意义,但均可以用于大区域坐标转换。     

城市倾斜摄影实景三维模型数据质量检查方法研究与实践

基于倾斜摄影可以快速获得高精度的城市实景三维模型,分析了实景三维模型数据的特点,探讨了实景三维模型数据质量检查的重点内容和质量元素,结合北京市大规模倾斜摄影实景三维数据质量检查实例,对实景三维数据质检问题与内容进行了总结,最后提出了实景三维模型数据的质量检查方法。     

WorldView-2影像林地信息提取的研究与实现

林地信息的获取具有重要意义,可广泛应用于城市规划编制、林地资源分析、水土流失治理等领域。本文基于WorldView-2影像,在研究分割与对象特征的基础上,采用面向对象方法,实现了林地信息提取,其用户精度达到94%,制图精度达到97.2%。然后,将像元二分模型应用于林地类对象,计算其植被覆盖度。试验表明,面向对象方法能高效、准确、经济地提取林地信息;基于林地类对象计算的植被覆盖度能较好地表征植被覆盖情况。