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1.
海冰变化与全球气候、 生态系统和人类活动密切相关, 海冰厚度是海冰变化研究的重要参数之一。全面立体高精度观测海冰厚度的最有效手段是航空遥感, 而冰桥计划(IceBridge)是当前南北极最大的航空遥感工程。基于2009 - 2014年冰桥计划的激光雷达高程数据和数字测图系统相机光学影像对南极别林斯高晋海的海冰厚度进行研究, 并结合降雪量等气象数据探讨该区域海冰厚度变化的原因。研究发现该海域的海冰厚度在2009 - 2014年间整体呈微弱增长趋势(0.07 m·a-1), 但是在95%置信水平下不具有显著性。2009 - 2011年呈现先增加后减少的大幅度变化, 其中2010年达到极大值2.42 m, 之后开始缓慢增加。海冰厚度的年际变化与降雪和近地表温度等气象要素相关, 二者相比较而言降雪为主要影响因素。  相似文献   
2.
Near-surface remote sensing (e.g., digital cameras) has played an important role in capturing plant phenological metrics at either a focal or landscape scale. Exploring the relationship of the digital image-based greenness index (e.g., Gcc, green chromatic coordinate) with that derived from satellites is critical for land surface process research. Moreover, our understanding of how well Gcc time series associate with environmental variables at field stations in North American prairies remains limited. This paper investigated the response of grass Gcc to daily environmental factors in 2018, such as soil moisture (temperature), air temperature, and solar radiation. Thereafter, using a derivative-based phenology extraction method, we evaluated the correspondence between key phenological events (mainly including start, end and length of growing season, and date with maximum greenness value) derived from Gcc, MODIS and VIIRS NDVI (EVI) for the period 2015-2018. The results showed that daily Gcc was in good agreement with ground-level environmental variables. Additionally, multivariate regression analysis identified that the grass growth in the study area was mainly affected by soil temperature and solar radiation, but not by air temperature. High frequency Gcc time series can respond immediately to precipitation events. In the same year, the phenological metrics retrieved from digital cameras and multiple satellites are similar, with spring phenology having a larger relative difference. There are distinct divergences between changing rates in the greenup and senescence stages. Gcc also shows a close relationship with growing degree days (GDD) derived from air temperature. This study evaluated the performance of a digital camera for monitoring vegetation phenological metrics and related climatic factors. This research will enable multiscale modeling of plant phenology and grassland resource management of temperate prairie ecosystems.  相似文献   
3.
Phenology is a sensitive and critical feature of vegetation and is a good indicator for climate change studies. The global inventory modelling and mapping studies (GIMMS) normalized difference vegetation index (NDVI) has been the most widely used data source for monitoring of the vegetation dynamics over large geographical areas in the past two decades. With the release of the third version of the NDVI (GIMMS NDVI3g) recently, it is important to compare the NDVI3g data with those of the previous version (NDVIg) to link existing studies with future applications of the NDVI3g in monitoring vegetation phenology. In this study, the three most popular satellite start of vegetation growing season (SOS) extraction methods were used, and the differences between SOSg and SOS3g arising from the methods were explored. The amplitude and the peak values of the NDVI3g are higher than those of the NDVIg curve, which indicated that the SOS derived from the NDVIg (SOSg) was significantly later than that derived from the NDVI3g (SOS3g) based on all the methods, for the whole northern hemisphere. In addition, SOSg and SOS3g both showed an advancing trend during 1982–2006, but that trend was more significant with SOSg than with SOS3g in the results from all three methods. In summary, the difference between SOSg and SOS3g (in the multi-year mean SOS, SOS change slope and the turning point in the time series) varied among the methods and was partly related to latitude. For the multi-year mean SOS, the difference increased with latitude intervals in the low latitudes (0–30°N) and decreased in the mid- and high-latitude intervals. The GIMMS NDVI3g data-sets seemed more sensitive than the GIMMS NDVIg in detecting information about the ground, and the SOS3g data were better correlated both with the in situ observations and the SOS derived from the Moderate Resolution Imaging Spectroradiometer NDVI. For the northern hemisphere, previous satellite measures (SOS derived from GIMMS NDVIg) may have overestimated the advancing trend of the SOS by an average of 0.032 d yr–1.  相似文献   
4.
地震数据是利用地震学方法探测地下结构的基础条件,然而传统地震仪器难以获得极端环境地区(水下、高原等)的长时间、高密度连续数据。较之国际仪器厂商,国内的DAS研制相对较晚。自2016年起,国产DAS逐步应用于石油测井和城市区域地下结构探测,而运用在极端环境下的探测工作尚未见报道。中国科学院半导体研究所与青藏高原研究所经过多年合作研究,于2021年4月将自主研发的DAS系统首次应用于青藏高原的野外数据采集。本次试验同时记录了地面和水下的连续背景噪声和重锤数据。该研究利用背景噪声成像技术,获得了西藏易贡湖地区地表70 m以内的横波速度结构。本次研究为极端环境下的低成本、高密度数据采集和地下结构探测提供了理论和试验依据。  相似文献   
5.
Currently there is a lack of knowledge on spatio-temporal patterns of land surface dynamics at medium spatial scale in southern Africa, even though this information is essential for better understanding of ecosystem response to climatic variability and human-induced land transformations. In this study, we analysed vegetation dynamics across a large area in southern Africa using the 14-years (2000–2013) of medium spatial resolution (250 m) MODIS-EVI time-series data. Specifically, we investigated temporal changes in the time series of key phenometrics including overall greenness, peak and timing of annual greenness over the monitoring period and study region. In order to specifically capture spatial and per pixel vegetation changes over time, we calculated trends in these phenometrics using a robust trend analysis method. The results showed that interannual vegetation dynamics followed precipitation patterns with clearly differentiated seasonality. The earliest peak greenness during 2000–2013 occurred at the end of January in the year 2000 and the latest peak greenness was observed at the mid of March in 2012. Specifically spatial patterns of long-term vegetation trends allowed mapping areas of (i) decrease or increase in overall greenness, (ii) decrease or increase of peak greenness, and (iii) shifts in timing of occurrence of peak greenness over the 14-year monitoring period. The observed vegetation decline in the study area was mainly attributed to human-induced factors. The obtained information is useful to guide selection of field sites for detailed vegetation studies and land rehabilitation interventions and serve as an input for a range of land surface models.  相似文献   
6.
Wang  Chenzhi  Zhang  Zhao  Zhang  Jing  Tao  Fulu  Chen  Yi  Ding  Hu 《地理学报(英文版)》2019,29(2):287-305
Journal of Geographical Sciences - Rice (Oryza sativa L.) is the most important staple crop of China, and its production is related to both natural condition and human activities. It is fundamental...  相似文献   
7.
Qi  Miaomiao  Yao  Xiaojun  Li  Xiaofeng  Duan  Hongyu  Gao  Yongpeng  Liu  Juan 《地理学报(英文版)》2019,29(1):115-130
Journal of Geographical Sciences - Lake ice phenology is considered a sensitive indicator of regional climate change. We utilized time series information of this kind extracted from a series of...  相似文献   
8.
利用AIRS产品分析中国地区近地面甲烷浓度时空特性   总被引:1,自引:0,他引:1  
甲烷(CH4)作为仅次于二氧化碳(CO2)的第二大温室气体,不仅在全球和区域尺度光化学反应中起着重要作用,而且在能量收支平衡及气候变化方面有着重要的影响。2013年,Auqa/EOS的大气红外探测仪(AIRS)热红外近地表CH4产品在AIRS Version6.0产品中发布,其结果尚未在中国进行验证,利用热红外传感器分析中国近地表CH4浓度的时空分布还处于初始阶段。本文利用中国青海瓦里关(WLG)、中国台湾鹿林山(LLN)及蒙古乌兰乌勒(UUM)地基观测资料对AIRS V6.0近地面CH4浓度产品进行了验证,误差在2%以内,二者相关系数r分别为0.68、0.5、0.69,变化趋势一致,进而从地域、季节变化和年际变化3个方面探讨了2003年—2013年中国地区近地面CH4浓度的时空分布特征。结果表明:CH4浓度最低值位于西藏地区(1800 ppbv),高值区位于新疆维吾尔自治区北部、内蒙古自治区及黑龙江北部(1920 ppbv);夏季高,冬季低,季节性变化明显,年际变化基本上呈增长趋势。  相似文献   
9.
一次暴雪过程前后近地层物理量场特征分析   总被引:2,自引:1,他引:1  
利用铁塔风梯度观测资料和超声风温仪观测资料,对2008年1月18—21日暴雪前后,湖北黄石长江岸边近地层风场和湍流作了计算分析,探索其异常变化特征,为认识黄石地区暴雪近地层发生发展的物理过程提供依据。结果表明,暴雪前,风向转变,水平风速和垂直风速明显增大,湍流通量的输送较活跃,湍流动能和湍流强度有显著峰值出现;降雪过程结束后,湍流动能再次增大后缓慢减弱。可见此次暴雪过程前后近地层物理量场有异常变化  相似文献   
10.
The study developed a feasible method for large-area land cover mapping with combination of geographical data and phenological characteristics, taking Northeast China (NEC) as the study area. First, with the monthly average of precipitation and temperature datasets, the spatial clustering method was used to divide the NEC into four ecoclimate regions. For each ecoclimate region, geographical variables (annual mean precipitation and temperature, elevation, slope and aspect) were combined with phenological variables derived from the moderate resolution imaging spectroradiometer (MODIS) data (enhanced vegetation index (EVI) and land surface water index (LSWI)), which were taken as input variables of land cover classification. Decision Tree (DT) classifiers were then performed to produce land cover maps for each region. Finally, four resultant land cover maps were mosaicked for the entire NEC (NEC_MODIS), and the land use and land cover data of NEC (NEC_LULC) interpreted from Landsat-TM images was used to evaluate the NEC_MODIS and MODIS land cover product (MODIS_IGBP) in terms of areal and spatial agreement. The results showed that the phenological information derived from EVI and LSWI time series well discriminated land cover classes in NEC, and the overall accuracy was significantly improved by 5.29% with addition of geographical variables. Compared with NEC_LULC for seven aggregation classes, the area errors of NEC_MODIS were much smaller and more stable than that of MODIS_IGBP for most of classes, and the wall-to-wall spatial comparisons at pixel level indicated that NEC_MODIS agreed with NEC_LULC for 71.26% of the NEC, whereas only 62.16% for MODIS_IGBP. The good performance of NEC_MODIS demonstrates that the methodology developed in the study has great potential for timely and detailed land cover mapping in temperate and boreal regions.  相似文献   
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