关键时相长势—环境和景观特征对河北省县级尺度冬小麦单产估算精度影响分析

区域尺度上精准、快速的作物单产估算可以有效地为国家粮食安全相关政策的制定提供数据支撑。本文针对县级估产时相和特征类型选择问题,基于遥感、气象和统计等多源数据,通过不同时相和特征要素之间的组合分析来探索其对于县级尺度冬小麦单产估算的影响。特征要素主要考虑作物长势、环境（水分和光温条件）和农田景观3个类型;时相主要考虑由冬小麦生长过程NDVI（Normalized Difference Vegetation Index）曲线特征提取的5个关键时段（P1—P5）。利用不同时相与类型特征的组合与统计单产构建随机森林回归模型,根据精度评价结果分析各组合的优劣。2014年—2017年的数据用来建模,2018年数据用来验证。对于单时相,P2、P3、P4的表现明显好于P1和P5;多时相的准确度明显优于单时相,其中P2、P4的组合效果最佳。对于不同类型的特征要素,作物长势特征参量对估产精度的影响最大,而水分影响和光温条件等环境因子的加入对估产准确性并没有明显提升,农田景观参数的加入能够有效提升估产的准确性。在最优组合的基础上,剔除冗余变量优选出5个重要的指标因子（PROP、NDVI_P2、B2_P2、ED、B1_P4）,并建立单产估算模型获取2018年河北省冬小麦县级尺度单产。结果表明,平均相对误差（MRE）仅为2.85%,决定系数（R ²）为0.83,均方根误差（RMSE）为253.25 kg/ha,归一化均方根误差（NRMSE）为4.09%。研究结果为全国县级冬小麦单产估算提供了新的思路和方法参考。     

Dating lava flows of tropical volcanoes by means of spatial modeling of vegetation recovery

The age of past lava flows is crucial information for evaluating the hazards and risks posed by effusive volcanoes, but traditional dating methods are expensive and time‐consuming. This study proposes an alternative statistical dating method based on remote sensing observations of tropical volcanoes by exploiting the relationship between lava flow age and vegetation cover. First, the factors controlling vegetation density on lava flows, represented by the normalized difference vegetation index (NDVI), were investigated. These factors were then integrated into pixel‐based multi‐variable regression models of lava flow age to derive lava flow age maps. The method was tested at a pixel scale on three tropical African volcanoes with considerable recent effusive activity: Nyamuragira (Democratic Republic of Congo), Mt Cameroon (Cameroon) and Karthala (the Comoros). Due to different climatic and topographic conditions, the parameters of the spatial modeling are volcano‐specific. Validation suggests that the obtained statistical models are robust and can thus be applied for estimating the age of unmodified undated lava flow surfaces for these volcanoes. When the models are applied to fully vegetated lava flows, the results should be interpreted with caution due to the saturation of NDVI. In order to improve the accuracy of the models, when available, spatial data on temperature and precipitation should be included to directly represent climatic variation. Copyright © 2017 John Wiley & Sons, Ltd.     

基于小波分析的NDVI与环境因子空间尺度依存关系研究(英文)

本文通过多尺度分解途径分析了NDVI与环境因子如地形与气候之间的空间尺度依存关系。为了揭示两者关系的尺度效应,选取青藏高原北纬32.5度作为研究样带,应用小波变换分析了不同空间尺度下的小波一致性和相位关系。研究结果表明:在青藏高原小于80km空间尺度上,气候变量如降水和气温不是控制NDVI的主导因素;而大于这个尺度,在一些生态区可以发现NDVI和气候因子具有显著的小波一致性。作为一个分异因子,海拔高度在青藏高原东南缘的纵向岭谷区对NDVI有着显著影响。通过这一研究发现,小波变换是研究NDVI与影响因素之间多尺度关系的一个有力途径。     

The control of wind strength on the barchan to parabolic dune transition

The evolution of barchan-to-parabolic dunes can be driven by vegetation establishment, which may be linked to climate change and/or human activity. However, little is known of the impact of changes in wind strength on vegetation development and the resulting impacts on the evolution of dune morphology and sedimentological characteristics. To address this issue, we studied the morphology and grain-size characteristics of barchan, barchan-to-parabolic and parabolic dunes in the Mu Us Desert in north China, which was combined with an analysis of changes in normalized difference vegetation index (NDVI) and climatic variables during 1982–2018. The results reveal a trend of increasing growing-season NDVI which was related to a significant decrease in drift potential (DP). Therefore, we suggest that the initiation of dune transformation was caused by the reduced wind strength which favored the establishment and development of vegetation. To reveal the response of sedimentological reorganization during the processes of dune transformation, grain-size characteristics along the longitudinal profile of the three different types of dunes were examined. The decreasing wind strength led to the transport of fine sands on the upper part of the windward face of the dunes, resulting in a progressive coarsening of the grain-size distribution (GSD) and a reduction in dune height at the crest area. No distinct trend in sorting and mean grain-size was observed on the windward slope of the barchan-to-parabolic dune, indicating that the sand in transit had little influence on the GSD. Conversely, progressive sorting and coarsening of the sand occurred towards the crest of the parabolic dune. This indicates that vegetation development limited the transport of sand from upwind of the dune, and affected a shift in the dune source material to the underlying source deposits, or to reworked pre-existing aeolian deposits, and resulted in the trapping of sand in the crest area. © 2020 John Wiley & Sons, Ltd.     

基于海岸带成像仪CZI的连云港紫菜养殖动态监测

连云港海域的紫菜养殖遥感监测对于规划紫菜养殖空间分布具有重要意义。基于50m空间分辨率的海洋一号C卫星（HY-1C）海岸带成像仪（Coastal Zone Imager, CZI）数据,利用归一化植被指数(NDVI)和人工目视解译,获取了2018年10月-2020年4月连云港沿岸的紫菜养殖遥感监测面积,并分析了紫菜养殖的季节变化特征。结果显示,连云港紫菜养殖区主要分布于海州湾和连岛附近海域;养殖区自9月至次年5月在CZI图像上可见,紫菜养殖遥感监测面积呈先增加后减少的趋势,1-2月其遥感监测面积通常达到一个养殖周期的最大值,3月初面积迅速减少;基于CZI影像的2019年度遥感监测面积为123km2,2020年为160km2。建立HY-1C与哨兵二号(10m)、高分一号(16m)和Landsat-8(30m)监测结果的线性模型,以Google Earth影像目视解译的紫菜养殖区遥感面积作为真实值,并将哨兵二号监测值转换为真实值。换算成真实值的2020年度紫菜养殖区真实面积为94km2,较2015年度的42km2增长了一倍多。本研究展示,CZI可用于紫菜养殖区的业务化观测,本文同时建议,利用其1-2月份的多期遥感影像监测结果作为年度紫菜养殖区遥感监测面积的基准。     

京津风沙源区2000—2015年植被覆盖状况的区域差异研究

植被覆盖状况是监测与表征区域生态建设成效的重要指标。以往研究注重区域植被覆盖状况的整体变化分析,对长时期区域内部植被覆盖变化及其差异研究较少。文中基于京津风沙源区遥感影像数据,采用GIS空间分析技术,重点评估了2000—2015年植被覆盖度的年际变化及其区域差异。研究结果表明,2000—2015年京津风沙源区植被覆盖度变化为35%~45%,且随年份变化呈波动增加趋势,年均增速为0.4%(P<0.05),生态治理取得明显植被恢复成效。8个治理分区植被覆盖均有所增加,但区域差异明显,晋北山地丘陵亚区和燕山丘陵山地水源保护亚区植被覆盖度年均增速超过0.6%,浑善达克沙地亚区与荒漠草原亚区植被覆盖度年均增速不及0.2%,这与区域地表组成和气候背景有关。从地市来看,北京、天津和承德植被覆盖度较高,但朔州和张家口植被覆盖度增速明显,而乌兰察布和包头植被覆盖度年均增速低于0.1%。相比2000年,2015年京津风沙源区有51%的区域植被覆盖度增加,49%区域植被覆盖度未变或降低,主要集中在京津风沙源区的中部和西部县市(旗),未来生态治理过程中应加以重点关注。     

2000年以来朝鲜植被覆盖变化及其与气候因子的相关性研究

生态环境的可持续与人类福祉和生态系统服务息息相关,研究植被覆盖变化及其与气候因子的相关性,探讨植被覆盖时空变化规律,探究气候因子对植被变化的驱动机制,对预见气候因子对生态系统影响、制定生态环境可持续保护策略具有深远意义。基于此,利用美国国家航空航天局发布的MODIS NDVI数据并结合相关的气候资料,通过对像元信息进行提取与分析,采用最大合成法、克里金插值法、相关分析法等方法,对2000-2016年朝鲜全境植被覆盖变化及其与气候因子的相关性进行了研究。结果表明：朝鲜全境植被覆盖空间分布不均,北部盖马高原、东北部咸镜山区,中、东部山地丘陵区为高值区;西、南部平原地区,东部沿海地带为低值区。NDVI值整体上增加,局部减少,空间差异明显。植被生长受气温和降水双重驱动,其中,气温对植被年内生长变化比降水作用更大;而气温因素中,年平均气温对植被生长的影响程度略大,NDVI对降水的响应存在明显滞后效应;NDVI对温度和降水的响应程度与空间地理位置、高程有关。区域植被NDVI年际变化主要受年最低气温和人类活动的影响。     

The Effect of Higher Warming on Vegetation Indices and Biomass Production is Dampened by Greater Drying in an Alpine Meadow on the Northern Tibetan Plateau

In order to understand whether or not the response of vegetation indices and biomass production to warming varies with warming magnitude, an experiment of field warming at two magnitudes was conducted in an alpine meadow on the northern Tibetan Plateau beginning in late June, 2013. The normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI) and soil adjusted vegetation index (SAVI) data were obtained using a Tetracam Agricultural Digital Camera in 2013-2014. The gross primary production (GPP) and aboveground plant biomass (AGB) were modeled using the surface measured NDVI and climatic data during the growing seasons (i.e. June-September) in 2013-2014. Both low and high warming significantly increased air temperature by 1.54 and 4.00°C, respectively, and significantly increased vapor pressure deficit by 0.13 and 0.31 kPa, respectively, in 2013-2014. There were no significant differences of GNDVI, AGB and ANPP among the three warming treatments. The high warming significantly reduced average NDVI by 23.3% (-0.06), while the low warming did not affect average NDVI. The low and high warming significantly decreased average SAVI by 19.0% (-0.04) and 27.4% (-0.05), respectively, and average GPP by 24.2% (i.e. 0.21 g C m^-2 d^-1) and 44.0% (i.e. 0.39 g C m^-2 d^-1), respectively. However, the differences of the average NDVI, SAVI, and GPP between low and high warming were negligible. Our findings suggest that a greater drying may dampen the effect of a higher warming on vegetation indices and biomass production in alpine meadow on the northern Tibetan Plateau.     

The response of vegetation growth to shifts in trend of temperature in China

Though many studies have focused on the causes of shifts in trend of temperature, whether the response of vegetation growth to temperature has changed is still not very clear. In this study, we analyzed the spatial features of the trend changes of temperature during the growing season and the response of vegetation growth in China based on observed climatic data and the normalized difference vegetation index (NDVI) from 1984 to 2011. An obvious warming to cooling shift during growing season from the period 1984–1997 to the period 1998–2011 was identified in the northern and northeastern regions of China, whereas a totally converse shift was observed in the southern and western regions, suggesting large spatial heterogeneity of changes of the trend of growing season temperature throughout China. China as a whole, a significant positive relationship between vegetation growth and temperature during 1984 to 1997 has been greatly weakened during 1998–2011. This change of response of vegetation growth to temperature has also been confirmed by Granger causality test. On regional scales, obvious shifts in relationship between vegetation growth and temperature were identified in temperate desert region and rainforest region. Furthermore, by comprehensively analyzing of the relationship between NDVI and climate variables, an overall reduction of impacts of climate factors on vegetation growth was identified over China during recent years, indicating enhanced influences from human associated activities.     

基于NDVI先验知识的LAI地面采样方法

针对非均质中低分辨率像元的叶面积指数LAI验证中如何布设基本采样单元ESU的问题,提出基于NDVI先验知识的ESU布设方法,并采用不同植被类型、不同均匀程度的地表作为模拟场,分析对比了方法的精度及稳定性。结果显示,本文方法用NDVI先验知识描述植被的生长空间分布信息,能相对准确地划分植被的不同生长水平,有效降低层内方差。在草地和森林地区的试验中,精度与稳定性均优于传统的随机采样、均匀采样和基于分类图的3种采样方法。因此,本文提出的采样方法为大尺度非均质区域LAI地面验证的采样方案提供了新的设计思路。