基于面向对象影像分析方法的我国西沙珊瑚礁地貌单元信息提取

珊瑚礁地貌单元的空间分布对于理解珊瑚礁生态系统的地质构造过程具有重要作用。然而,基于像素的影像分析方法往往获取不到较高精度的分类结果。本文基于面向对象的影像分析方法,利用Landsat 8卫星影像数据对我国西沙地区的珊瑚环礁进行了地貌单元的遥感信息提取。借鉴于美国千年珊瑚礁测绘项目的工作成果,本文首先针对研究区特点定义了十类珊瑚礁地貌单元类型。然后,基于对象的多层次关系特点,并综合利用对象的光谱、形状、上下文关系等特征,建立合适的分类规则集,获取了研究区较大尺度的珊瑚环礁地貌分区图,其分类精度普遍高于80%。虽然研究结果表明基于面向对象的影像分析方法可以有效的进行珊瑚礁遥感信息提取,但其规则集的可移植性仍需要今后的工作加以改善。     

基于岩石图像深度学习的岩性自动识别与分类方法

岩石岩性的识别与分类对于地质分析极为重要,采用机器学习的方法建立识别模型进行自动分类是一条新的途径。基于Inception-v3深度卷积神经网络模型,建立了岩石图像集分析的深度学习迁移模型,运用迁移学习方法实现了岩石岩性的自动识别与分类。采用此方法对所采集的173张花岗岩图像、152张千枚岩图像和246张角砾岩图像进行了学习和识别分类研究,通过训练学习建立岩石图像深度学习迁移模型,并分别采用训练集和测试集中的岩石图像对模型进行了检验分析。对于训练集中的岩石图像,每组岩石分别用3张图像测试,三种岩石的岩性分类均正确,且分类概率值均达到90%以上,显示了模型良好的鲁棒性;对于测试集中的岩石图像,每组岩石分别采用9张图像进行识别分析,三种岩石的岩性分类均正确,并且千枚岩组图像分类概率均高于90%,但是花岗岩组2张图像和角砾岩组的1张图像分类概率值不足70%,概率值较其他岩石图像低,推测其原因是训练集中相同模式的岩石图像较少,导致模型的泛化能力减小。为了提高识别精确度,对准确率较低的岩石图像进行截取,分别取其中的3张图像加入训练集进行再训练,增加与测试图像具有相同模式的训练样本;在新的模型中,对3张图像进行二次检验,测试概率值均达到85%以上,说明在数据足够的状况下模型具有良好的学习能力。与传统的机器学习方法相比,所提出的岩石图像深度学习方法具有以下优点:第一,模型通过搜索图像像素点提取物体特征,不需要手动提取待分类物体特征;第二,对于图像像素大小,成像距离及光照要求低;第三,采用适当的训练集可获得较好的识别分类效果,并具有良好鲁棒性和泛化能力。     

Geometric-constrained multi-view image matching method based on semi-global optimization

Targeting at a reliable image matching of multiple remote sensing images for the generation of digital surface models, this paper presents a geometric-constrained multi-view image matching method, based on an energy minimization framework. By employing a geometrical constraint, the cost value of the energy function was calculated from multiple images, and the cost value was aggregated in an image space using a semi-global optimization approach. A homography transform parameter calculation method is proposed for fast calculation of projection pixel on each image when calculating cost values. It is based on the known interior orientation parameters, exterior orientation parameters, and a given elevation value. For an efficient and reliable processing of multiple remote sensing images, the proposed matching method was performed via a coarse-to-fine strategy through image pyramid. Three sets of airborne remote sensing images were used to evaluate the performance of the proposed method. Results reveal that the multi-view image matching can improve matching reliability. Moreover, the experimental results show that the proposed method performs better than traditional methods.     

Rice crop phenology mapping at high spatial and temporal resolution using downscaled MODIS time-series

Satellite data holds considerable potential as a source of information on rice crop growth which can be used to inform agronomy. However, given the typical field sizes in many rice-growing countries such as China, data from coarse spatial resolution satellite systems such as the Moderate Resolution Imaging Spectroradiometer (MODIS) are inadequate for resolving crop growth variability at the field scale. Nevertheless, systems such as MODIS do provide images with sufficient frequency to be able to capture the detail of rice crop growth trajectories throughout a growing season. In order to generate high spatial and temporal resolution data suitable for mapping rice crop phenology, this study fused MODIS data with lower frequency, higher spatial resolution Landsat data. An overall workflow was developed which began with image preprocessing, calculation of multi-temporal normalized difference vegetation index (NDVI) images, and spatiotemporal fusion of data from the two sensors. The Spatial and Temporal Adaptive Reflectance Fusion Model was used to effectively downscale the MODIS data to deliver a time-series of 30 m spatial resolution NDVI data at 8-day intervals throughout the rice-growing season. Zonal statistical analysis was used to extract NDVI time-series for individual fields and signal filtering was applied to the time-series to generate rice phenology curves. The downscaled MODIS NDVI products were able to characterize the development of paddy rice at fine spatial and temporal resolutions, across wide spatial extents over multiple growing seasons. These data permitted the extraction of key crop seasonality parameters that quantified inter-annual growth variability for a whole agricultural region and enabled mapping of the variability in crop performance between and within fields. Hence, this approach can provide rice crop growth data that is suitable for informing agronomic policy and practice across a wide range of scales.     

Fusing MODIS with Landsat 8 data to downscale weekly normalized difference vegetation index estimates for central Great Basin rangelands,USA

Data fused from distinct but complementary satellite sensors mitigate tradeoffs that researchers make when selecting between spatial and temporal resolutions of remotely sensed data. We integrated data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the Terra satellite and the Operational Land Imager sensor aboard the Landsat 8 satellite into four regression-tree models and applied those data to a mapping application. This application produced downscaled maps that utilize the 30-m spatial resolution of Landsat in conjunction with daily acquisitions of MODIS normalized difference vegetation index (NDVI) that are composited and temporally smoothed. We produced four weekly, atmospherically corrected, and nearly cloud-free, downscaled 30-m synthetic MODIS NDVI predictions (maps) built from these models. Model results were strong with R² values ranging from 0.74 to 0.85. The correlation coefficients (r ≥ 0.89) were strong for all predictions when compared to corresponding original MODIS NDVI data. Downscaled products incorporated into independently developed sagebrush ecosystem models yielded mixed results. The visual quality of the downscaled 30-m synthetic MODIS NDVI predictions were remarkable when compared to the original 250-m MODIS NDVI. These 30-m maps improve knowledge of dynamic rangeland seasonal processes in the central Great Basin, United States, and provide land managers improved resource maps.     

Single Zircon LA-ICP-MS U-Pb Dating of the Guandimiao and Wawutang Granitic Plutons in Hunan, South China and Its Petrogenetic Significance

1 Introduction The South China Block (SCB), located between the Qinling-Dabie and Songma Indosinian sutures, experienced successively two important tectonic movements during the Mesozoic, i.e. the Indosinian movement (early Mesozoic) and the Yanshanian movement (late Mesozoic). Therefore, the generally accepted viewpoint is that the key geological problems during the Mesozoic are essentially the dynamics and material expression of these two tectonic movements in South China (Chen et al.…     

黄土丘陵沟壑区典型村域土地利用变化及对区域乡村转型发展的启示

深入开展乡村地域土地利用变化和聚落发展规律的研究对于探究乡村地域系统优化、推进城乡融合与乡村可持续发展具有重要意义。论文以延安市碾庄流域为例,基于ENVI和GIS等软件技术,结合Landsat卫星影像、马尔科夫链模型和实地调查,从土地利用转移与交换变化、建筑用地空间转移、社会响应等角度探讨了黄土丘陵沟壑区典型村域土地利用变化特征以及对区域乡村发展转型的影响。研究表明：① 在一系列生态工程措施作用下,碾庄流域生态覆被发生明显改观,主要表现为大量的坡耕地及稀疏生态用地转化为林地,其中,林地面积占比由32.34%(2009年)增加至50.88%(2018年);② 在社会经济发展和延安新城“边缘效应”的影响下,碾庄建设用地呈现向流域的东南和西南方向拓展的趋势,10 a间建设用地面积增加了近75%;③ 在人类活动的主导作用下,黄土丘陵沟壑区的乡村正在朝着生态化和集约化的方向转型发展。研究结果有望为深入理解黄土丘陵沟壑区乡村地域系统结构和优化提供新参考。     

Three Decades of Sea-Ice Variability in Jiaozhou Bay Revealed by Landsat Observations

In this study, we used Landsat images and meteorological data to examine the spatiotemporal distribution and variability of sea ice in Jiaozhou Bay(JZB) between 1986 and 2016. The results show that JZB is not always covered by sea ice in winter, but in some extreme cases, sea ice has covered more than one-third of the sea area of the bay. Sea ice in JZB has generally formed between January 1 and February 5, primarily along the coast, and gradually expanding to the central area of the bay. Both meteorological and artificial factors have played important roles in modulating the sea ice distribution. We found sea ice coverage to have been strongly correlated with the accumulated freezing-degree days nine days before the occurrence of sea ice(R2 = 0.767). North-northwest surface winds have dominated the freezing period of sea water in the JZB, and wind speed has exerted a more significant influence on the formation of sea ice when the sea ice coverage has been generally small. Additionally, artificial factors began to affect the expansion of sea ice in JZB since 2007. The construction of the Jiao-Zhou-Bay Bridge(JZBB) is believed to have retarded water flow and reduced the tidal prism, thereby leading to the formation of an ice bridge along the JZBB, which effectively prevents the southward expansion of sea ice.     

Mapping of moraine dammed glacial lakes and assessment of their areal changes in the central and eastern Himalayas using satellite data

The relatively rapid recession of glaciers in the Himalayas and formation of moraine dammed glacial lakes(MDGLs) in the recent past have increased the risk of glacier lake outburst floods(GLOF) in the countries of Nepal and Bhutan and in the mountainous territory of Sikkim in India. As a product of climate change and global warming, such a risk has not only raised the level of threats to the habitation and infrastructure of the region, but has also contributed to the worsening of the balance of the unique ecosystem that exists in this domain that sustains several of the highest mountain peaks of the world. This study attempts to present an up to date mapping of the MDGLs in the central and eastern Himalayan regions using remote sensing data, with an objective to analyse their surface area variations with time from 1990 through 2015, disaggregated over six episodes. The study also includes the evaluation for susceptibility of MDGLs to GLOF with the least criteria decision analysis(LCDA). Forty two major MDGLs, each having a lake surface area greater than 0.2 km2, that were identified in the Himalayan ranges of Nepal, Bhutan, and Sikkim, have been categorized according to their surface area expansion rates in space and time. The lakes have been identified as located within the elevation range of 3800 m and6800 m above mean sea level(a msl). With a total surface area of 37.9 km2, these MDGLs as a whole were observed to have expanded by an astonishing 43.6% in area over the 25 year period of this study. A factor is introduced to numerically sort the lakes in terms of their relative yearly expansion rates, based on their interpretation of their surface area extents from satellite imageries. Verification of predicted GLOF events in the past using this factor with the limited field data as reported in literature indicates that the present analysis may be considered a sufficiently reliable and rapid technique for assessing the potential bursting susceptibility of the MDGLs. The analysis also indicates that, as of now, there are eight MDGLs in the region which appear to be in highly vulnerable states and have high chances in causing potential GLOF events anytime in the recent future.     

一种高光谱遥感图像快速谱聚类算法

为获得分类效果更优良的遥感图像分类方式并解决高光谱遥感图像分类运算速度缓慢的问题,集成Lanczos算法与谱聚类算法,探讨了高光谱遥感图像谱聚类算法应用于遥感图像分类的可行性,提出了一种面向高光谱遥感图像的快速谱聚类算法;通过对比美国圣地亚哥机场高光谱遥感图像K-均值算法与谱聚类算法的分类结果,发现面向高光谱遥感图像的谱聚类算法易于识别线性地物,且分类的速度能得到较大提升。