第四纪孢粉分析的时间序列与空间模型

论述了第四纪孢粉时间序列和孢粉空间模型在不同尺度上的时空代表性,同时介绍了一些相关的研究方法和主要成果。利用数理统计方法来定量恢复古气候已成为目前第四纪孢粉时间序列研究的一个发展趋势。各种尺度的第四纪孢粉空间模型图可以反映植被对第四纪气候变化的响应。根据孢粉数据与气候变量之间的函数关系还可换算成古气候图。此外,在全球气候模拟和植被模拟中,孢粉数据成为必不可少的诊断工具。     

典型岩溶山坡土壤剖面水分对降雨响应过程研究

为揭示岩溶石山山坡降雨入渗补给机制,选取典型岩溶石山山坡土壤剖面为研究对象,于2015年7-10月期间对不同深度土壤水分进行高分辨率连续监测,研究典型场雨条件下土壤剖面水分对降雨的响应过程,分析土壤剖面水分的动态变化规律及其可能影响因素。研究结果表明:土壤剖面水分对降雨的响应受前期土壤含水量、降雨量、降雨强度的影响,还与土壤所处的地形地貌有关;表层土壤水分对首次次降雨响应的滞后时间与前期土壤含水量有关,响应时间在0.5~4.75 h之间,旱季响应时间比雨季长;降雨阈值是引起土壤水分降雨响应的重要条件,旱季6 mm降雨量是土壤水分响应的降雨阈值。当降雨量补充土壤水分亏缺后,土壤剖面水分对降雨响应迅速,响应时间最小为0.25 h,不同深度土壤水分对降雨的响应时间一致,说明下层土壤水分可能受到优先流或侧向径流补给影响。土壤含水量的变化幅度随土层深度的增加而减小,不同深度土壤水分变化主要受土壤-大气界面、土壤-植被、土壤-基岩界面控制下的气候条件、植被蒸散发和介质渗透性差异影响。      

降雨特征及小气候对秦岭油松林降雨再分配的影响

为了研究降雨特征及小气候对秦岭天然次生油松林冠层降雨再分配的影响,连续3年观测降雨事件发生时油松林林外降雨、穿透降雨、树干茎流以及降雨特征和小气候因子,进行各因子间的相关性和多元回归分析。结果表明:降雨量级是影响林冠降雨再分配的最主要因素,穿透降雨量与降雨量、降雨量和降雨历时交互项、相对湿度呈正相关,与降雨历时和温度呈负相关。树干茎流量与降雨量、降雨量和温度交互项呈正相关,与温度呈负相关。林冠截留量与降雨量、降雨历时和温度呈正相关,与降雨量和降雨历时、温度的交互项呈负相关。雨前干燥期、风向、风速、蒸发速率、光合有效辐射和净辐射与穿透降雨量、树干茎流量和林冠截留量均无相关性。     

红岩煤矿岩溶双重介质对降雨响应特征的研究

根据大量监测资料,研究了矿区岩溶管道和溶孔、溶隙流对降雨的不同响应特征,并概化出本区的岩溶地下水系统结构图。最后应用时间序列分析频谱方法研究了３１年来矿井涌水量对降雨量的响应关系,即全矿涌水量滞后于降雨６ｄ。     

基于时序MODIS NDVI的黑河流域土地覆盖分类研究

归一化植被指数(NDVI)是植被生长状态及植被覆盖度的最佳指示因子,其时序数据也已成为基于生物气候特征开展大区域植被和土地覆盖分类的基本手段。基于时序NDVI数据的土地覆盖分类,即通过提取NDVI时间信号所包含的植被生物学参数,构建起一个包含植被生物学信息的分类特征空间。利用2006年重建得到的MODIS NDVI 16天合成时间序列数据,并结合1 km分辨率的DEM数据、野外实地调查资料等辅助数据,综合分析了不同土地覆盖类型对应的时序NDVI谱线及其第一、二谐波的特征阈值,建立决策树对黑河流域的土地覆盖开展分类研究。结果表明,基于时序MODIS NDVI谱线特征的决策树分类精度为78%,Kappa系数为0.74。利用1 km时序MODIS NDVI时间序列获得较为准确的黑河流域土地覆盖类型是可行的。     

青藏高原净生态系统碳交换量的遥感评估模型研究

青藏高原作为世界海拔最高的区域,是全球气候变化的敏感区之一。定量估算这一区域的净生态系统碳交换量(NEE)有利于理解陆地生态系统碳平衡对未来气候变化的响应。本文构建了一个模拟该地区NEE动态变化的净碳收支模型(NCBM)。该模型由来源于MODIS影像的增强型植被指数(EVI)、陆地表面水分指数(LSWI)以及来源于地面观测的空气温度和短波辐射共同驱动,并利用青藏高原地区的3种植被类型(包括高寒灌丛、高寒湿地和高寒草甸)的碳通量长期观测数据对模型进行了校准和验证。结果表明,在模型校准站点年,NCBM模型可以模拟NEE观测值81%的变化,均方根误差(RMSE)为0.03mol C/m~2/d,模型效率(EF)为0.81。在模型验证站点年,NCBM模型可以预测NEE观测值84%的变化,RMSE为0.03mol C/m~2/d,EF为0.81。在大多数情况下,NCBM模型可以清晰地模拟各植被类型的NEE季节和年际变化。此外,NCBM模型因为结构简单,模型驱动变量易于获取等优势,具有在区域尺度上模拟NEE时空变化的潜力。但是该模型还需要进一步的改进和发展,特别需要提高对植被非常稀疏地区NEE变化的模拟能力。     

青藏高原植被动态与环境因子相互关系的研究现状与展望

青藏高原是中国乃至全球对气候变化最敏感的地区之一,是全球平均海拔最高的地理单元,对周边地区起到重要的生态安全屏障作用。近年来,当地植被受到气候变化和人类活动的双重压力。本文基于文献检索分析青藏高原的植被生理、生态特征对气候变化和人为干扰的响应,并利用荟萃分析定量综述植被覆盖度变化对土壤理化性质的影响。在此基础上分析青藏高原植被与环境因子相互关系的研究尺度与方法。结果表明:(1)气温、降水、辐射等自然因素和放牧、农耕、筑路等人为活动均对青藏高原植被的碳交换、水分利用效率、元素含量与分布格局、物候、多样性等指标产生显著影响,植被的变化也同时影响着土壤的水热交换、水文过程和理化性质等;(2)在植被退化过程中,由高覆盖度向中覆盖度转变时对土壤理化性质产生的不利影响强于由中覆盖度转为低覆盖度时,高覆盖度地区的植被保护需要引起更多关注;(3)现有研究更多关注单一要素、单一尺度,未来应关注多要素间的相互耦合,通过合作与共享获取数据,开展多尺度对比和尺度效应研究,系统梳理和分析植被与环境因子的相互关系可为制定科学合理的生态修复策略提供科学依据。     

煤炭开发区植被扰动时空效应及影响范围界定:以宁东矿区为例

煤炭开采是一种具有大规模高强度性质的生态扰动行为,会产生区域地表压占与损毁、植被破坏等生态扰动和环境污染问题。西北干旱荒漠区气候干旱,植被稀疏,生态环境本身极其脆弱,宁东矿区是典型的干旱荒漠煤炭开发区,有重要的研究价值。本文选择宁东矿区以及与矿区自然条件相近的自然植被参照区作为研究对象,收集2008—2019年共276期MODIS归一化植被指数(normalized vegetation index,NDVI)长时间序列遥感数据,通过STL时间序列分解、函数主成分分析(function principal component analysis,FPCA)、像元二分模型植被覆盖度计算等方法,从时间维度上分析了矿区周边区域和参照区NDVI均值在研究期内的总体变化趋势,发现随着开采过程的持续,相比自然参照区植被而言,矿区周边植被生长受到了明显胁迫;从空间维度上分析了不同距离缓冲区NDVI数据的相关性特征,在此基础上通过函数主成分分析得到第一主成分函数,确定矿区生态影响范围边界在7 km左右;本研究还在像元尺度分析了植被覆盖度的变化情况,按照变化的程度进行了分级统计分析,发现矿区周边区域虽然NDVI均值总体长期趋势相对稳定,但植被中度和重度退化区域面积明显增加。     

基于转移函数分析的蒙东地区不同类型植被变化对干旱的响应

为了量化不同类型植被与干旱的响应关系，首先采用回归模式降尺度方法获取内蒙古地区1982-2019年1km分辨率的归一化植被指数（normalizeddifferencevegetationindex,NDVI）数据集，并计算标准化降水蒸发指数（standardizedprecipitationevapotranspirationindex,SPEI）以表征干旱状况；然后，利用转移函数分析（transferfunction analysis,TFA）频域技术进行内蒙古东部不同类型植被变化对干旱响应的存在性、强度和时滞性的研究.发现在年、6个月和3个月尺度上，草地、灌木、阔叶林和针叶林NDVI与SPEI的相干性分别为0.44、0.57、0.31,0.43、0.60、0.32,0.30、0.19、0.14和0.20、0.13、0.10；各类型植被NDVI对干旱的响应强度表现为灌木>草地>阔叶林>针叶林；草地、灌木、阔叶林和针叶林在3个时间尺度上滞后干旱的时间分别为31d、20d、12d,77d、28d、34d,120d、69d、57 d和179 d、103 d、65 d.研...     

岩溶关键带土壤—洞穴系统CO2运移的时空变化——以河南鸡冠洞为例

为了了解豫西鸡冠洞岩溶区不同尺度下水-土-气的中CO2的变化特征,探究CO2在岩溶关键带系统的运移关系,2019年5月至2020年10月,利用固态传感器对河南鸡冠洞上覆土壤取样点进行高时间分辨率监测,每隔15 min采集一次数据。结合每月采集洞内空气CO2浓度数据、每月测定洞穴水水化学指标数据及每月监测的降水、气温数据进行全面系统地分析。结果表明:①土壤CO2浓度、洞内空气CO2浓度和洞穴水水化学指标具有明显的季节性变化特征,均表现为夏秋高冬春低;②土壤CO2浓度在昼夜尺度下,白天高于夜晚,夏季的昼夜差值最大,冬季的昼夜差值最小,且昼夜变化滞后气温、土温变化约6 h;③洞内CO2浓度变化、洞穴水离子浓度和水化学指标在昼夜变化上具有同步性;④强降雨条件下（单场降雨量为42.2mm）,土壤水分和土壤温度能及时响应降雨变化,而土壤CO2浓度对降雨的响应滞后2 h。洞穴水、洞穴CO2浓度对降雨的响应与土壤CO2具有相似性;⑤基于月均值的土壤CO2浓度与土壤温度、土壤湿度的相关系数分别为0.67、0.031。垂直方向上,CO2浓度变化依次为土壤>洞穴>空气。昼夜尺度上,土壤CO2浓度变化滞后于气温、土壤温度变化,其原因是受上覆植被光合作用强度影响。CO2在洞穴水运移中以脱气沉积为主,补给洞内空气CO2浓度。在强降雨过程中,土壤CO2浓度变化受控土壤的温度和湿度;而在更长时间尺度上,土壤CO2浓度变化更多地受土壤温度影响,土壤湿度对其影响较小。      

基于FY-3 A/VIRR数据的藏西北干旱遥感监测研究

藏西北地区生态环境脆弱,由于地形复杂、气候独特,该区的观测资料非常缺乏。利用遥感技术开展藏西北地区的干旱监测,能获取在空间上连续变化的地表干旱情况,对于指导该区农牧业生产具有重要的意义。基于FY-3A/VIRR的一级数据和标准旬产品（地表温度、植被指数）,采用温度植被干旱指数（TVDI）进行藏西北地区的干旱监测研究,并将监测结果分别与基于EOS/MODIS数据监测的结果、同期的野外实测土壤水分数据以及气象站点的降水量数据进行了对比分析。结果表明：利用FY-3A/VIRR数据的TVDI遥感监测结果与实测土壤水分、气象站累计降水量数据均呈显著的负相关关系,通过了0.01水平的显著性检验;利用FY-3A/VIRR数据与EOS/MODIS数据估算的TVDI干旱等级空间分布特征基本一致,FY-3A/VIRR数据可以代替EOS/MODIS数据在藏西北地区开展干旱遥感监测,可为指导藏西北地区农牧业生产提供数据支持。     

Recent trends of temperature and precipitation proxies in Saudi Arabia: implications for climate change

The objective of the present study was to reconstruct a short-term (12–14 years) trend of surface temperature and precipitation patterns using their surrogates as provided by satellite images for selected locations along the Red Sea mountains in Saudi Arabia. Time series land surface temperature (LST) and normalized difference vegetation index (NDVI) data acquired from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite were temporally plotted to delineate the trend and the decadal rates of change of both parameters. Results showed that real climate change is reported in the study area during the study period. There is a net increasing in the surface temperatures by 0.45 to 1.2 °C/decade and a net decrease in annual rainfall between 2001 and 2014. Findings of the present study show that the region is under a warming of the climate and a declining of wetness, which coincide with the air temperature and rainfall trends obtained from meteorological stations.     

Assessing the consistency between AVHRR and MODIS NDVI datasets for estimating terrestrial net primary productivity over India

This study examines the consistency between the AVHRR and MODIS normalized difference vegetation index (NDVI) datasets in estimating net primary productivity (NPP) and net ecosystem productivity (NEP) over India during 2001–2006 in a terrestrial ecosystem model. Harmonic analysis is employed to estimate seasonal components of the time series. The stationary components (representing long-term mean) of the respective NDVI time series are highly coherent and exhibit inherent natural vegetation characteristics with high values over the forest, moderate over the cropland, and small over the grassland. Both data exhibit strong semi-annual oscillations over the cropland dominated Indo-Gangetic plains while annual oscillations are strong over most parts of the country. MODIS has larger annual amplitude than that of the AVHRR. The similar variability exists on the estimates of NPP and NEP across India. In an annual scale, MODIS-based NPP budget is 1.78 PgC, which is 27% higher than the AVHRR- based estimate. It revealed that the Indian terrestrial ecosystem remained the sink of atmospheric CO ₂ during the study period with 42 TgC y ^?1 NEP budget associated with MODIS-based estimate against 18 TgC y ^?1 for the AVHRR-based estimate.     

Remote sensing monitoring the spatio-temporal changes of aridification in the Mongolian Plateau based on the general Ts-NDVI space, 1981–2012

This paper has developed a general Ts-NDVI triangle space with vegetation index time-series data from AVHRR and MODIS to monitor soil moisture in the Mongolian Plateau during 1981–2012, and studied the spatio-temporal variations of drought based on the temperature vegetation dryness index (TVDI). The results indicated that (1) the developed general Ts-NDVI space extracted from the AVHRR and MODIS remote sensing data would be an effective method to monitor regional drought, moreover, it would be more meaningful if the single time Ts-NDVI space showed an unstable condition; (2) the inverted TVDI was expected to reflect the water deficit in the study area. It was found to be in close negative agreement with precipitation and 10 cm soil moisture; (3) in the Mongolian Plateau, TVDI presented a zonal distribution with changes in land use/land cover types, vegetation cover and latitude. The soil moisture is low in bare land, construction land and grassland. During 1981–2012, drought was widely spread throughout the plateau, and aridification was obvious in the study period. Vegetation degradation, overgrazing, and climate warming could be considered as the main reasons.     

基于MODIS数据的西藏干旱自动监测系统实现的关键技术研究

干旱是一种危害较大的自然灾害, 影响范围大、持续时间长. 随着经济发展和人口的增加, 水资源短缺现象日益严重, 这也导致了干旱范围的扩大和干旱化程度加重. 为降低业务人员负担, 提高业务工作效率, 探讨了基于MODIS遥感数据的西藏干旱监测系统实现的关键技术. 首先, 阐述了MODIS 轨道数据快速投影处理的正向投影处理技术原理, 然后分析了温度植被干旱指数算法(TVDI)及其实现, 最后, 将干旱监测方法集成到业务系统软件, 最终实现西藏全区的干旱遥感监测业务工作. 通过与传统手工干旱监测方法进行对比, 发现干旱自动监测系统具有速度快、自动化等优点, 具有十分重要的实践意义.     

Dynamic monitoring of drought using HJ-1 and MODIS time series data in northern China

From early November 2008 to February 2009, lack of rainfall led to severe drought in northern China. More than 9.3 million ha of wheat in six major crop production provinces, including Henan, Anhui, Shandong, Shanxi, Gansu, and Shaanxi, were hit by drought. Supported by Chinese HJ-1 satellite images together with NASA Moderate Resolution Imaging Spectroradiometer (MODIS) data, dynamic monitoring of the drought was conducted. HJ-1 CCD data with 30-m resolution were used to identify cropland information. Spatial–temporal variation of drought was detected using Vegetation Index and Water Index time series data derived from MODIS visible, infrared, and short-wave infrared bands. The influences of drought were classified into five levels based on MODIS-derived 8-day composite Anomaly Water Index (AWI) and field survey data. The results indicated that the drought deteriorated beginning in November 2008 and became most serious in late January 2009. HJ-1 data together with MODIS data proved to be valuable data sources for monitoring soil moisture and drought at a both regional and national scale.     

A composite index for drought hazard assessment using CPC rainfall time series data

Hazard analysis is the first step in any disaster management activity. Drought is a serious environmental hazard strongly limiting the agricultural production in the tropical countries like India. A comprehensive drought hazard map is useful for multiple perspectives such as agriculture, environment and hydrology. In this study, daily rainfall data of the Climate Prediction Centre during the south-west monsoon season (June–September) of 12 years, over India was analysed. Based on rainfall and rainy days, six indicators of drought were generated which were then synthesized into a composite index of drought hazard for every 10 × 10 km pixel. The weights for the composite index were generated through variance approach. The index has effectively captured the spatial variations in meteorological drought across India by showing a typical pattern with increasing hazardous area from east to west. The drought hazard map also shows considerable agreement with the climate classification map and the drought proneness map reported by other studies. Thus, the current study presents a simple and novel approach for drought hazard analysis, using the routinely available geospatial rainfall data products. The methodology can be extended to other geographies and disasters too. Use of time series data of longer period would improve the reliability of the composite drought hazard index.     

The assessment of drought relief by typhoon Saomai based on MODIS remote sensing data in Shanghai,China

Typhoons are one of the major natural hazards occurring frequently in Shanghai. The comprehensive assessment of drought relief by typhoon has become a major concern of scientists and government agencies in Shanghai, China. In this article, with the support of remote sensing data and the available data from local meteorological stations, the regional drought relief was investigated and the change of drought intensity was quantified by the typhoon “Saomai” between 5 and 8 August 2005. The precipitation anomaly calculated on the basis of recorded rainfall was adopted to analyze drought condition changes before and after the typhoon. Then, vegetation supply water index (VSWI) and normalized difference vegetation index (NDVI) were used to monitor the drought relief due to the consecutive shortage of summer rainfall. Impact of typhoon on drought was compared by VSWI before and after typhoon Saomei. The results showed that the typhoon alleviated the drought of the vegetation by more than 70 %, based on the spatial and temporal distribution of precipitation, the ground temperature, relative humidity, high temperature, NDVI from Shanghai area. The result shows that MODIS remote sensing data are a useful quantitative monitoring tool in drought relief by local typhoons. More strategies are necessary to be adopted for prevention and mitigation of meteorological disaster in Shanghai in recent years.     

The characteristics of the Mocoa compound disaster event,Colombia

A rainfall-induced compound disaster happened in Mocoa in the pre-dawn hours of 1 April 2017. More than 300 people were killed, and a large number of houses and roads were destroyed in the worst catastrophe in the history of Mocoa. To investigate this disaster, a detailed interpretation was carried out using high-resolution images. Analysis of disaster characteristics based on satellite image revealed that the disaster could be identified as a consequence of compound mountain hazards including landslides, debris flows, and mountain torrents. The mountain hazards converged in the mountain watershed, which amplified the disaster’s effects. Analysis considers that this disaster is the result of heavy rainfalls. Moreover, in-depth interpretation of rainfall data and satellite images spanning over 16 years reveals that the previous El Niño event (2014–2016) also played an important role, which caused reduced rainfall and vegetation coverage. The long period of drought brought by El Niño affected the growth of vegetation and reduced the ability of vegetation to cope with heavy rainfalls. The results reveal that both antecedent rainfalls and climate impact need to be taken into consideration for mountain hazard analysis.     

Application of meteorological and vegetation indices for evaluation of drought impact: a case study for Rajasthan, India

Drought is a serious climatic condition that affects nearly all climatic zones worldwide, with semi-arid regions being especially susceptible to drought conditions because of their low annual precipitation and sensitivity to climate changes. Drought indices such as the standardized precipitation index (SPI) using meteorological data and vegetation indices from satellite data were developed for quantifying drought conditions. Remote sensing of semi-arid vegetation can provide vegetation indices which can be used to link drought conditions when correlated with various meteorological data based drought indices. The present study was carried out for drought monitoring for three districts namely Bhilwara, Kota and Udaipur of Rajasthan state in India using SPI, normalized difference vegetation index (NDVI), water supply vegetation index (WSVI) and vegetation condition index (VCI) derived from the Advanced Very High resolution Radiometer (AVHRR). The SPI was computed at different time scales of 1, 2, 3, 6, 9 and 12 months using monthly rainfall data. The NDVI and WSVI were correlated to the SPI and it was observed that for the three stations, the correlation coefficient was high for different time scales. Bhilwara district having the best correlation for the 9-month time scale shows late response while Kota district having the best correlation for 1-month shows fast response. On the basis of the SPI analysis, it was found that the area was worst affected by drought in the year 2002. This was validated on the basis of NDVI, WSVI and VCI. The study clearly shows that integrated analysis of ground measured data and satellite data has a great potential in drought monitoring.