植被状况指数的改进及在西北干旱监测中的应用

干旱是全球分布最广、发生频率最高、持续时间最长、影响范围最大、造成的经济损失最为严重的一种自然灾害，干旱也是所有自然灾害中影响因子最为复杂、人类了解最少、监测最为困难的一种自然灾害，干旱监测是世界性的难题。干旱可以发生在任何气候带上，但干旱、半干旱地区是全球干旱灾害发生最频繁的地区。干旱发生特征和规律因地区的不同会有很大的差异，不同地区对干旱监测方法不同。目前，世界各国干旱监测主要利用基于气象、水文、农业和卫星遥感等观测资料建立的各种干旱指数开展，已经有150多种干旱指数。植被状况指数VCI是应用最为广泛的一种卫星监测干旱的指数，研究和业务应用结果表明，VCI对全球各地的干旱均有较好的反映，已经应用在美国国家大气海洋局（NOAA）日常干旱监测业务中，中国国家卫星气象中心干旱卫星遥感监测服务产品也是以VCI为基础。 我国干旱半干旱地区主要分布在新疆、甘肃、青海、陕西、宁夏以及内蒙古自治区的中西部，这里降水少且不稳定，降水变率大，是中国干旱发生频率最高的地区。干旱严重制约着当地经济发展和人类生活质量的提高，使本身非常脆弱的生态环境趋于恶化。为了了解条件植被指数VCI对西北地区不同气候区干旱的监测能力，以上述6省（区）为研究区，利用1982—2003年22年NDVI数据，计算了研究区域22年来逐月的VCI，对比分析了不同气候区VCI与降水距平的关系。结果表明，VCI在空间和时间上较好地反映了西北大部分气候干旱发生、发展和空间分布，是干旱监测的较好指标，但在干旱和极端干旱地区，VCI经常出现异常偏高现象，不能反映干旱气候区常年干旱的基本特点。通过对西北不同生态系统之间NDVI特点和各生态系统间NDVI年变化及其年际变化规律的研究，设计了VCI改进方案，提出了改进的条件植被指数RVCI。通过对22年来逐月RVCI与VCI的对比，RVCI客观地反映了干旱气候区常年干旱特点，较VCI有显著改进。      

植被状态指数VCI与几种气象干旱指数的对比——以河南省为例

使用1982-2006年GIMMS AVHRR NDVI数据集与同期的CI、K、Pa、SPI、Z、PDSI等干旱指数做了对比分析, 讨论了河南省植被状态指数VCI对气象干旱的滞后效应及干旱监测能力. 结果表明: VCI指数与气象干旱指数的相关性受不同下垫面的影响较大, 农地的VCI与气象干旱指数相关性要明显高于林地, 农地VCI与气象干旱指数呈现正相关关系. 在河南省不同的作物生长阶段, VCI对气象干旱有着不同的滞后效应, 其中, 3-5月份冬小麦生长期VCI对气象条件的反应滞后1~3个月, 7、9月份夏玉米生长期VCI对气象条件的反应滞后1月. 总体上看, 结合前期的气象数据, VCI对河南省气象干旱有一定的指示作用和监测能力.     

Investigating remote sensing indices to monitor drought impacts on a local scale (case study: Fars province,Iran)

As drought occurs in different climates, assessment of drought impacts on parameters such as vegetation cover is of utmost importance. Satellite remote sensing images with various spectral and spatial resolutions represent information about different land covers such as vegetation cover. Hence, the purpose of this study was to investigate the performance of satellite vegetation indices to monitor the agricultural drought on a local scale. In this regard, satellite images including Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Very High Resolution Radiometer (AVHRR) data were used to evaluate vegetation cover and their gradual changes effects on agricultural drought. Fars province in Iran with relatively low precipitation values was selected as the study area. Modified Perpendicular Drought Index (MPDI), MPDI1, Vegetation Condition Index (VCI), Normalized Difference Vegetation Index Anomalies (NDVIA), and Standardized Vegetation Index (SVI), were evaluated to select the remote sensing based index with the best performance in drought monitoring. The performance of such indices were investigated during 13 years (2000–2013) for MODIS and 29 years (1985–2013) for AVHRR. To assess the efficiency of the satellite indices in drought investigation, Standardized Precipitation Index (SPI) data of five selected stations were used for 3, 6, and 9 month periods on August. The results showed that NDVI-based vegetation indices had the highest correlation with SPI in cold climate and long-term timescale (6 and 9 month). The highest correlation values between remote sensing based indices and SPI were acquired, respectively, in 9-month and 6-month time-scales, with the values of 43.5% and 40%. Moreover, VCI showed the highest capability for agricultural drought investigating in different climate regions of the study area. Overall, the results proved that NDVI-based indices can be used for drought monitoring and assessment in a long-term timescale on a local time-scale.

     

The changing characteristics of drought in China from 1982 to 2005

Drought is one of the most detrimental natural disasters. Studying the changing characteristics of drought is obviously of great importance to achieve the sustainable use of water resources at river basin scales. In this paper, the satellite-based Vegetation Condition Index (VCI) and Vegetation Health Index (VH) were firstly calculated by using NDVI and brightness of the Global Vegetation Index dataset derived from Advance Very High Resolution Radiometer for China in growing seasons over 1982–2005. Then, the long-term VCI and VH data were employed to study the variation of droughts in the ten basins covering the whole country. The linear trend of each pixel showed that most parts of China were getting wetter in growing seasons, and the drought areas defined by the number of drought pixels have decreased in most basins. The increasing trend of basin averaged values of VCI and VH also indicates the whole country was generally getting wetter. At last, to better understand the two remote sensing drought indices, the response of the growing-season VCI and VH was compared to that of the Palmer Drought Severity Index and 6-month Standard Precipitation Index. Significant spatial variability of the relationship between the VCI, VH, and the station-based meteorological drought indices was shown, and some more closely related areas were found. The study will be useful for water resources management for each basin in the future.     

基于植被指数和土地表面温度的干旱监测模型

干旱是一种周期性发生的自然现象,其发生过程中有关参数如地表覆盖度、温度和土壤表层含水量等可以通过遥感的途径进行定量反演,而这些参数客观地反映了地表的综合特征。综述了运用遥感反演产品---土地表面温度和归一化植被指数在干旱监测中的应用前景和进展,分析了距平植被指数、条件植被指数、条件温度指数和归一化温度指数等干旱监测方法的优缺点,在前人研究的基础上,提出了条件植被温度指数的干旱监测模型,探讨了其应用前景。     

The relationship between drought activity and vegetation cover in Northwest China from 1982 to 2013

We investigated drought activity and the relationship between drought and vegetation in Northwest China over the period 1982–2013 using the standardized precipitation evapotranspiration index (SPEI) and the normalized difference vegetation index (NDVI). The indexes were, respectively, calculated from ground-based meteorological data and from remotely sensed satellite data. The spatial and temporal distributions of drought (SPEI) and of vegetation cover (NDVI) were compared using annual trends, and the relationships between these trends were analyzed. The results are: (1) Overall, Northwest China had a drought trend during the study period, although some a few regions show a significant wetness trend; (2) the mean annual NDVI fluctuates, but overall shows an increasing trend, particularly in some mountainous areas that have at least adequate water and vegetation cover, while unused land becomes degraded; (3) most regions show a positive correlation between SPEI and NDVI, although the western parts of the Tarim basin, Qaidam basin, and some regions in the southeastern part of study area show a negative correlation; and (4) the various regions respond differently to global climate change, but in general regions with more vegetation cover show increased vegetation growth, while regions with less vegetation cover are becoming degraded and thus more vulnerable to the adverse effects of climate change.     

Desertification Risk Monitoring for North Shaanxi Province, China,Using Normalized Difference Vegetation Index（NDVI）

In this study,the remote sensing is applied to the examination of the relationship between desertification and normalized difference vegetation index(NDVI) in the context of northern Shaanxi Province.This relationship is also examined using spatial analysis methods.A strong negative correlation is found in the largest area desert,indicating that the relationship between desert and NDVI is not a sim-ple linear one and that the correlation coefficient between NDVI and vegetation abundance is significant.The normalized difference vegetation index(NDVI) was compared with other vegetation index-based methodologies.NDVI is a valuable first-cut indicator for such systems, although the analysis and inter-pretation of its relationship to desertification are complex and also based on the detailed analysis of its re-lationship to ecological zone,vegetation type and season.Conclusions thus made would help to upgrade the methodology as an effective tool for early-warning desertification in the northern Shaanxi Province where a drought is a recurring threat.This methodology includes the integration of NDVI with other socio-economic and bio-physical indicators in GIS ,the complementation of desert area data with satellite data,and the analysis of the relationship between NDVI and specific climatic zones,for each season and vegetation type.     

Identifying Water Storage Variation in Krishna Basin,India from <Emphasis Type="Italic">in situ</Emphasis> and Satellite based Hydrological Data

Terrestrial water storage (TWS), a sum total of water stored on or beneath the earth’s surface, transits in response to hydroclimatic processes such as precipitation, evapo-transpiration, runoff etc. and serves an indicator of hydrological condition of a region. We analyse spatio-temporal variance of water storage in Krishna Basin, India, derived from in-situ groundwater data and Gravity Recovery and Climate Experiment (GRACE) satellite data in order to determine physical causes of variations, and compare the variance with climatic factors such as Cumulative Rainfall Departure (CRD) and drought index i.e. Standardized Precipitation Index (SPI). GRACE satellite based TWS is found to reflect insitu groundwater changes and also shows a relationship with drought patterns as indicated by a good correlation with SPI. The largest part of TWS represents seasonal flux, and at an interannual scale, TWS depicts spatio-temporal variability in response to drought index viz. SPI. We infer that the groundwater storage derived from GRACE time-variable gravity solutions can be utilised to complement in-situ observations at basin scale and it reflects climatic forcing quite well.     

Drought Monitoring Using Data Mining Techniques: A Case Study for Nebraska, USA

Drought has an impact on many aspects of society. To help decision makers reduce the impacts of drought, it is important to improve our understanding of the characteristics and relationships of atmospheric and oceanic parameters that cause drought. In this study, the use of data mining techniques is introduced to find associations between drought and several oceanic and climatic indices that could help users in making knowledgeable decisions about drought responses before the drought actually occurs. Data mining techniques enable users to search for hidden patterns and find association rules for target data sets such as drought episodes. These techniques have been used for commercial applications, medical research, and telecommunications, but not for drought. In this study, two time-series data mining algorithms are used in Nebraska to illustrate the identification of the relationships between oceanic parameters and drought indices. The algorithms provide flexibility in time-series analyses and identify drought episodes separate from normal and wet conditions, and find relationships between drought and oceanic indices in a manner different from the traditional statistical associations. The drought episodes were determined based on the Standardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI). Associations were observed between drought episodes and oceanic and atmospheric indices that include the Southern Oscillation Index (SOI), the Multivariate ENSO Index (MEI), the Pacific/North American (PNA) index, the North Atlantic Oscillation (NAO) Index, and the Pacific Decadal Oscillation (PDO) Index. The experimental results showed that among these indices, the SOI, MEI, and PDO have relatively stronger relationships with drought episodes over selected stations in Nebraska. Moreover, the study suggests that data mining techniques can help us to monitor drought using oceanic indices as a precursor of drought.     

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.     

基于SPEI指数的兰州干旱特征与气候指数的关系

基于1961～2012年逐日气象及同期4个气候因子资料系列,采用标准化降水蒸散发指数(SPEI)定量描述兰州地区干旱状况,利用M-K检验分析了该地干旱变化趋势,采用皮尔逊相关系数法以及交叉小波变换法研究了SPEI与北大西洋涛动(NAO)、北极振荡(AO)、太平洋十年涛动(PDO)以及厄尔尼诺-南方涛动(ENSO)四个气...     

Trends and variability of meteorological drought over the districts of India using standardized precipitation index

Meteorological drought during the southwest monsoon season and for the northeast monsoon season over five meteorological subdivisions of India for the period 1901–2015 has been examined using district and all India standardized precipitation index (SPI). Whenever all India southwest monsoon rainfall was less than ?10% or below normal, for those years all India SPI was found as ?1 or less. Composite analysis of SPI for the below normal years, viz., less than ?15% and ?20% of normal rainfall years indicate that during those years more than 30% of country’s area was under drought condition, whenever all India southwest monsoon rainfall was –15% or less than normal. Trend analysis of monthly SPI for the monsoon months identified the districts experiencing significant increase in drought occurrences. Significant positive correlation has been found with the meteorological drought over most of the districts of central, northern and peninsular India, while negative correlation was seen over the districts of eastern India with NINO 3.4 SST. For the first time, meteorological drought analysis over districts and its association with equatorial pacific SST and probability analysis has been done for the northeast monsoon over the affected regions of south peninsular India. Temporal correlation of all India southwest monsoon SPI and south peninsular India northeast monsoon SPI has been done with the global SST to identify the teleconnection of drought in India with global parameters.     

Analysing the relationship between drought and soil erosion using vegetation health index and RUSLE models in Godavari middle sub-basin,India

Drought is a natural phenomenon posing severe implications for soil, groundwater and agricultural yield. It has been recognized as one of the most pervasive global change drivers to affect the soil. Soil being a weakly renewable resource takes a long time to form, but it takes no time to degrade. However, the response of soil to drought conditions as soil loss is not manifested in the existing literature. Thus, this study makes a concerted effort to analyze the relationship between drought conditions and soil erosion in the middle sub-basin of the Godavari River in India. MODIS remote sensing data was utilized for driving drought indices during 2000–2019. Firstly, we constricted Temperature condition index (TCI) and Vegetation Condition Index (VCI) from Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI) derived from MODIS data. TCI and VCI were then integrated to determine the Vegetation Health Index (VHI). Revised Universal Soil Loss Equation (RUSLE) was utilized for estimating soil loss. The relationship between drought condition and vegetation was ascertained using the Pearson correlation. Most of the northern and southern watersheds experienced severe drought condition in the sub-basin during 2000–2019. The mean frequency of the drought occurrence was 7.95 months. The average soil erosion in the sub-basin was estimated to be 9.88 t ha^?1 year^?1. A positive relationship was observed between drought indices and soil erosion values (r value being 0.35). However, wide variations were observed in the distribution of spatial correlation. Among various factors, the slope length and steepness were found to be the main drivers of soil erosion in the sub-basin. Thus, the study calls for policy measures to lessen the impact of drought and soil erosion.     

Evaluation of drought and wetness episodes in a cold region (Northeast China) since 1898 with different drought indices

Drought identification and drought severity characterization are crucial to understand water scarcity processes. Evolution of drought and wetness episodes in the upper Nen River (UNR) basin have been analyzed for the period of 1951–2012 using meteorological drought indices and for the period of 1898–2010 using hydrological drought indices. There were three meteorological indices: one based on precipitation [the Standardized Precipitation Index (SPI)] and the other two based on water balance with different formulations of potential evapotranspiration (PET) in the Standardized Precipitation Evapotranspiration Index (SPEI). Moreover, two hydrological indices, the Standardized Runoff Index and Standardized Streamflow Index, were also applied in the UNR basin. Based on the meteorological indices, the results showed that the main dry period of 1965–1980 and wet periods of 1951–1964 and 1981–2002 affected this cold region. It was also found that most areas of the UNR basin experienced near normal condition during the period of 1951–2012. As a whole, the UNR basin mainly had the drought episodes in the decades of 1910, 1920, 1970 and 2000 based on hydrological indices. Also, the severity of droughts decreased from the periods of 1898–1950 to 1951–2010, while the severity of floods increased oppositely during the same periods. A correlation analysis showed that hydrological system needs a time lag of one or more months to respond to meteorological conditions in this cold region. It was also found that although precipitation had a major role in explaining temporal variability of drought, the influence of PET was not negligible. However, the sole temperature driver of PET had an opposite effect in the UNR basin (i.e., misestimating the drought detection) and was inferior to the SPI, which suggests that the PET in the SPEI should be determined by using underlying physical principles. This finding is an important implication for the drought research in future.     

利用MODIS数据产品进行全国干旱监测的研究

利用MODIS植被指数和陆地表面温度产品建立全国3个农业气候区NDVI-Ts、NDVI-ΔT和NDVI-ATI空间,并由NDVI-Ts、NDVI-ΔT和NDVI-ATI空间分别建立温度植被干旱指数(TVDI)、温差植被干旱指数(DTVDI)和表观热惯量植被干旱指数(AVDI)3个干旱评价指标研究全国干旱分布,利用实测土壤含水量对3个干旱指标进行检验评价.NDVI-ΔT空间中的湿边基本与横坐标平行,表明当土壤水分处于饱和状态或植被完全无水分胁迫条件下,植被和土壤对缓冲环境温度变化的能力大体相当;由NDVI-ATI空间看出,随着植被覆盖增加,表观热惯量有增加的趋势.对比3个干旱评价指标表明:当监测范围较大,区域内地形复杂时,由NDVI-Ts空间计算的TVDI评价干旱最合理,由NDVI-ΔT空间计算的DTVDI在干旱监测中也具有一定的价值,而由NDVI-ATI空间计算的AVDI已经不能合理评价干旱.     

Spatial and temporal analysis of drought based on a combined index using copula

Drought as a natural disaster impresses people living. The main tool in better management of such phenomena is to explain its characteristics, using drought indices. The indices use precipitation, temperature, streamflow, and other hydrological variables to explain such events. In this study, standardized precipitation index (SPI) and stream-flow drought index (SDI) were used to develop a new combined drought index (CDI) based on copula functions. The proposed index function was evaluated in Khuzestan, Yazd and Golestan provinces of Iran from 1982 to 2012. These areas introduce different climate conditions. The index was analyzed temporally and spatially. In the temporal analysis, CDI was calculated separately for each station and the finest index was chosen by Kolmogorov–Smirnov and Chi-squared tests. In the spatial analysis, CDI was computed for two main scenarios and twenty sub-scenarios for the whole area of Golestan Province. The optimum index was chosen based on comparison with initial SPI and SDI. The results showed that CDI is more meticulous than both singular SPI and SDI, as it can trace a drought onset earlier and drought duration more accurate than the two individual indices and obviously display extreme states.     

多尺度干旱指数在江淮流域的适应性研究

利用1960-2010年江淮流域34个地面气象观测站的逐日降水、日平均气温、相对湿度等实测资料, 分别计算了江淮流域的Z指数、降水距平百分率、相对湿润指数、标准化降水指数以及CI指数, 经与江淮流域干旱记录对比分析, 结果表明: 月尺度的Z指数在5种干旱指数中应用效果最好, 符合率达70%以上;在时间域上, 月尺度的Z指数仅在春季吻合率稍差, 其余月份均在70%以上;月尺度的SPI指数在冬季吻合率较差, 其余月份同Z指数总体相当;MI指数效果最差;日尺度的CI指数应用效果存在时空差异, 在河南最好, 在山东最差, 夏季效果最好, 春季、冬季最差.     

青藏高原高寒草地植被指数变化与地表温度的相互关系

为了解脆弱的高原生态环境对升温过程的响应, 利用1982-2006年国家标准地面气象站地表温度和GIMMS-NDVI数据集, 探讨了青藏高原高寒草地植被指数和地表温度的变化特征及其相互关系. 结果表明:1982-2006年, 高寒草地NDVI、地表温度整体均呈现增加趋势, 年均NDVI、生长季NDVI、年最大NDVI(NDVI_max)与年均地表温度、生长季地表温度的上升趋势分别为0.007 (10a)^-1、0.011 (10a)^-1、0.007 (10a)^-1与0.60 ℃·(10a)^-1、0.43 ℃·(10a)^-1; NDVI_max与地表温度显著相关的地区达70.49%. 但是高原地形、气候、水文环境的空间差异性导致高寒草地NDVI与地表温度的相关关系十分复杂. NDVI_max与年均地表温度的相关性最为显著; 在返青期和枯萎期, NDVI与地表温度均为显著正相关. 不同的植被覆盖条件下, NDVI对地表温度的响应不同:植被覆盖差以及退化严重的地区, NDVI_max与地表温度呈负相关性; 反之, NDVI_max与地表温度主要表现为正相关.     

Application of the self-calibrated palmer drought severity index and standardized precipitation index for estimation of drought impact on maize grain yield in Pannonian part of Croatia

Recent global warming and more frequent droughts are causing significant damage to maize production. A reliable estimate of drought intensity and duration is essential for testing maize hybrids to drought tolerance. For this purpose, the self-calibrating 10-day palmer drought severity index (scPDSI) and standardized precipitation index (SPI) for 1, 2, 3, 6, 9, 18, 27, and 36 10-day scales were used to estimate the effects of drought on grain yield of 32 maize hybrids evaluated in 2017 and 2018 at eight experimental locations in the Pannonian part of Croatia. Time series of observed 10-day mean air temperature, relative humidity, and precipitation totals for a set of “reference” weather stations of the croatian meteorological and hydrological service (DHMZ) for the period 1981–2018 were used to calculate the scPDSI and SPI indices. According to the 10-day scPDSI and SPI for different time scales, 2018 proved to be a “normal year,” while 2017 experienced a “mild to moderate drought,” which resulted in a 13% reduction in maize grain yield at eight experimental locations compared to 2018. The correlation between grain yield and drought indices for summer months was the highest for the 10-day scPDSI. To some extent, correlations between summer months’ SPI for the 3 10-day time scale and maize grain yield were comparable to the corresponding correlations for the 10-day scPDSI. However, for other SPI time scales considered, the corresponding correlations were weaker and less informative. The dependence of grain yield on scPDSI values was not the same for all hybrids, indicating their different tolerance to drought. The reduction in grain yield due to drought was primarily caused by insufficient grain filling (lower 1000-grain weight) and, to some extent, by a reduction in the number of grains. In this study, application of 10-day scPDSI data proved to be more relevant in detecting effects of drought on agronomic traits than application of SPI data for the most time scales.

     

Identifying spatial patterns of synchronization between NDVI and climatic determinants using joint recurrence plots

Ten-day series of the Normalized Difference Vegetation Index (NDVI) derived from multi-temporal satellite imagery (1998–2008) was employed as a surrogate for the surface vegetation cover to investigate synchronization of the climatic determinants and its spatial patterns in China. The results, both of the spatiotemporal patterns of joint probability of recurrence (JPR) index and lag time of maximal JPR, clearly suggest that the synchronous relationships of NDVI–climate are site specific and spatially heterogeneous. Higher JPR values of NDVI–temperature are found in Northern China, indicating stronger synchronization in these areas, while higher JPR values of NDVI–precipitation are found in semi-arid and semi-humid regions, which suggest that the moisture factor has a significant influence on NDVI in these areas. Whether lagged or advanced relationship, the phase difference of NDVI–temperature is smaller in Southern China, while is bigger in Northern China. In contrast, the phase difference of NDVI–precipitation is smaller in the semi-arid and sub-humid areas, which means that precipitation has a significant and immediate influence on vegetation in these areas. Overall, the JPR values for NDVI–temperature are higher than those for NDVI–precipitation, suggest that the synchronization between NDVI and temperature is stronger than that between NDVI and precipitation in most areas of China. The results indicate that joint recurrence quantification analysis is a good candidate method for identifying the synchronization between NDVI and climatic determinants.