Landsat长时间序列的阳澄湖湖面围网时空变化

准确提取湖泊围网区域的时空分布信息对湖泊的保护和可持续发展具有重要意义。本文以阳澄湖为研究区域,收集该地区1984年—2017年所有的Landsat 5和Landsat 8影像(共计396景),提出了结合光谱和纹理特征的围网提取新算法,同时利用时间序列滤波消除年际间因数据不一致造成的偏差。以高清影像人工解译作为参考,阳澄湖围网提取结果的生产者精度在72.57%—88.53%,用户者精度在79.79%—98.10%,围网面积变化与文献记录吻合。结果表明,阳澄湖围网经历了"无围网期"(1984年—1994年)、"快速增长期"(1994年—1998年)、"巅峰期"(1999年—2002年)、"快速下降期"(2003年—2006年)和"稳定期"(2007年—2017年)5个阶段,最高达到100 km2,目前稳定在30 km2;通过研究围网区植被指数发现,2002年之后围网区浮水植物的种植面积增大;通过对比水质数据发现,2002年至今持续15年的围网拆除并未使阳澄湖恢复到80年代无围网养殖时期的II类水,其水质依然处于Ⅲ—Ⅳ类。因此在湖泊养殖开发过程中,政府应该坚持可持续发展道路,在不破坏湖泊水质的基础上发展湖泊经济。     

采用DBM方法的时间序列LAI建模与估算

运用DBM(Data Based Mechanistic)方法,使用MODIS数据,建立了遥感观测反射率数据与叶面积指数(LAI)在时间序列上的统计关系模型(LAI_DBM模型),并结合部分Bigfoot站点实测LAI数据进行了模型检验。结果显示,LAI_DBM模型能够较好表达时间序列反射率与LAI的动态变化关系。LAI_DBM模型使用遥感观测数据实时估算得到的LAI,在数据质量和时间连续性上比MODISLAI有改进。     

基于NDVI时间序列影像的张掖市农作物种植结构提取

HJ卫星(环境与灾害监测预报小卫星)数据具有较高的时间和空间分辨率,可以有效地进行农作物种类识别,利用其时间序列数据进行作物信息提取具有很大优势。以甘肃省张掖市为研究区,利用2012年4月~2012年10月15个时相的HJ卫星CCD(电荷耦合元件,charge-coupled device)数据,通过分析玉米、油菜、大麦和小麦农作物在整个生长阶段的时间序列NDVI(归一化植被指数,normalized difference vegetation index)变化特点,提取四类农作物NDVI随时间变化的特征曲线,利用决策树分类方法,对2012年张掖市农作物进行分类,并以外业调查得到的实际地面验证点对分类结果进行验证。验证结果表明,可以有效地识别玉米、油菜、大麦和小麦4类农作物,制图精度分别为94.74%、82.35%、78.95%和90%;总体分类精度达到86.43%。而后提取了张掖市2014年农作物种植面积和分布格局,通过对比分析发现,2012~2014年,张掖市玉米、油菜的种植面积有不同程度的增加,大麦和小麦的种植面积各有一定程度的较少。可以为张掖市主要作物的种植结构调整提供科学依据,还可以为黑河流域农作物信息提取研究提供参考。     

应用时间序列EVI的MERSI多光谱混合像元分解

针对风云3数据的特点,本文将EVI生长曲线引入多光谱混合像元的分解。首先,利用Landsat8 OLI影像,采用支持向量机的分类方法,提取研究区域的耕地信息,利用该信息对风云MERSI数据进行掩膜处理,获得研究区域的耕地影像。接着,利用MERSI时序影像,计算像元EVI值,通过SG滤波,构建农作物(端元)和混合像元的EVI生长曲线。通过实地调查,获取研究区的农作物端元,尤其对主要的农作物玉米,在空间上均匀选取了14个端元。然后,采用传统的方法,将14种玉米端元生长曲线分别与其它端元组合,进行混合像元分解。发现分解的效果差异很大,提取的玉米种植面积从191.90 km2到574.83 km2不等。为提高分解精度,借用光谱匹配(光谱夹角最小)的方法(用生长曲线代替光谱曲线)自适应选择与混合像元EVI曲线最相似的玉米端元作为组合端元,进行混合像元分解。结果得到玉米的种植面积为589.95 km2,比传统方法的最好(相对)精度提高了2%。     

GPS time-series and its response to M S=8.1 Kunlunshan earthquake

In this paper, observation data in 25 GPS reference stations of China have been analyzed by calculating GPS position coordinate time-series with GIPSY. Result shows there is an obvious trend variation in such time-series. The trend variations of time series along the longitude and latitude coordinate reflect the motion of each position in the global-plate, in which the trend variation in the vertical direction reveals some large-scale construction information or reflects the local movement around the positions. The analysis also shows that such time-series have a variation cycle of nearly 1.02 a, but the reason still remains to be further studied. At the end of this paper, response of the time-series of M _S=8.1 Kunlunshan earthquake was analyzed, and the seismogenic process of M _S=8.1 Kunlunshan earthquake, according to the time proceeding and the feature of anomaly, was divided into 3 phases—changes in blocks with forces, strain accumulation, quick accumulation and slow release of energy. At the initial stage of seismogenic process of M _S=8.1 earthquake and at the imminent earthquake, coseismic process as well as during the post earthquake recovery, anomaly in vertical direction is always in a majority. The anomalous movement in vertical direction at the initial stage resulted in a blocking between faults, while at the middle stage of seismogenic process, the differential movement between blocks are in a majority, which is the major reason causing energy accumulating at the blocking stage of faults. Foundation item: National Natural Science Foundation of China (40074024 and 40304002).     

Differencing Reveals Hidden Changes in Baseline Length Time-series

In order to make successful earthquake predictions, detection and monitoring of baseline changes are important for investigating their origins, including precursory crustal deformations in tectonically active areas. In this study, differencing two baselines that run approximately parallel to each other and normal to the expected crustal deformations, and that share a station is proposed for analysis. Differencing reduces common systematic baseline errors, thereby enabling detection of subtle transient systematic changes in the baseline time-series that are otherwise buried in the measurement noise. Mean shift analysis, a well-known statistical technique to determine hether the mean of a stochastic process has shifted using cumulative sum charts, can then be used to locate the change points in the time-series. The application of this method to the differences of concurrently observed very long baseline interferometry (VLBI) and global positioning system (GPS) baselines in the Japanese Keystone project, where periodic and persistent baseline changes are removed, revealed transient variations in the baseline lengths several months prior to the seismic activity in the Izu Islands that started on June 26, 2000. Reproduction of the results using GPS and VLBI, two alternative baseline measurement techniques, validated the accuracy of the proposed approach for detecting previously hidden transient changes in the baseline lengths.