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1.
基于中国西南地区5个省(市)2001年—2010年期间由中分辨率成像光谱仪MODIS影像资料反演得到的归一化植被指数NDVI产品数据和区内气象站点的连续观测资料,提取了研究区内各气象站点印迹区的NDVI值,计算了降水距平百分率Pa和D指数(降水量与潜在蒸散量之差)这两种气象干旱指数。依据全国植被类型图(2000年版),对研究区内的主要植被类型在季节时间尺度上开展了这两种气象干旱指数与距平NDVI的相关性分析。研究结果表明:距平NDVI对D指数的最大响应滞后约一个月,在此尺度上表现出明显的线性相关性,所选取的6个季度的相关系数均接近或大于0.7,显著性水平小于0.01;对干旱敏感的植被类型如旱地和草地等,表现出更显著的相关性,其相关系数分别达到了0.83和0.71(平均);在干旱季节,D指数与距平NDVI表现出较为一致的空间分异规律,而Pa指数仅在旱情比较严重的情况下或对干旱比较敏感的植被类型区与距平NDVI表现出一致性分布。  相似文献   

2.
基于TRMM降雨数据的中国黄淮海地区干旱监测分析   总被引：3，自引：0，他引：3  
热带降雨测量卫星(tropical rainfall measuring mission,TRMM)的降雨数据覆盖范围广,时间分辨率高,是区域干旱监测的一种有效数据源。将0.25°空间分辨率的TRMM 3B43数据降尺度处理成0.05°空间分辨率数据,用以构建降水量距平百分率(Pa指数)和Z指数,对黄淮海地区2010年冬季到2011年春季的干旱时空演化特征进行监测与分析,并计算同期的标准化降水指数(standardized precipitation index,SPI)对监测结果进行验证。研究结果表明,降尺度数据具有较高的可靠性,与实测数据的拟合结果 R20.76;Pa指数突出降水盈亏程度,能够有效监测区域尺度干旱,但缺乏空间分布规律;Z指数以Person-Ⅲ型分布拟合降水量,能够很好地监测干旱的时空演化特征,但干旱等级划分相对困难;利用Pa指数对Z指数干旱等级划分进行修正,其结果与SPI相关程度R20.75,表明Pa和Z指数用于干旱监测的有效性,为区域尺度干旱监测提供了一种切实可行的方法。  相似文献   

3.
利用2015—2020年金沙江流域MODIS数据和流域内29个气象站1991—2020年月降水、气温资料,研究不同遥感干旱指数在金沙江流域的适用性,这些指数包括温度状态指数(temperature condition index, TCI)、温度植被干旱指数(temperature vegetation dryness index, TVDI)、植被状态指数(vegetation condition index, VCI)、植被供水指数(vegetation supply water index, VSWI)和标准化降水蒸散指数(standardized precipitation evapotranspiration index, SPEI)。结果表明：TCI与TVDI、VSWI与TCI、VSWI与TVDI、VSWI与VCI各月的相关性均较为显著。TVDI与SPEI和TCI与SPEI全年相关性较好。SPEI与VSWI相关性在1月、10月较低,其余月份均相关性较好。SPEI与VCI在1—3月相关性较低,其余月份均相关性较好。根据4种遥感干旱指数与SPEI的相关性分析,建议金沙江上游地区...  相似文献   

4.
基于TRMM数据与SPI指数的广西地区旱涝演变分析   总被引：1，自引：0，他引：1  
干旱是一种影响大、受灾重且恢复周期长的自然灾害,广西是农业大省,对广西地区进行干旱情况分析及预测对该地防灾减灾具有重要意义。通过对广西地区1998—2019年的降雨情况进行分析,并引入标准化降水指数(standardized precipitation index,SPI),验证了热带降雨测量卫星(tropical rainfall measuring mission,TRMM)数据在广西地区的适用性,研究了广西地区22 a间旱涝演变情况,并对未来广西地区旱涝变化趋势做出预测。结果表明:(1)TRMM 3B43降雨数据与地面台站实测数据具有高度相关性,适用于广西地区的干旱监测;(2)广西地区旱涝灾害频繁,平均每6 a就会有范围较大的洪涝事件发生;每2～3 a就会有范围较大的严重的干旱事件发生;(3)广西地区夏季降雨量最大,冬季最小,且降雨总体呈现"东多西少"的格局;(4)根据结果可以预测,2020年广西地区整体没有较大的干旱和洪涝事件发生,部分城市将会出现轻度洪涝和轻度干旱的情况。  相似文献   

5.
小麦生物量和真实叶面积指数的高光谱遥感估算模型   总被引：5，自引：0，他引：5  
利用大田小麦的参数数据和冠层光谱数据,基于光谱一阶微分技术和光谱响应函数,构建等效MODIS植被指数,建立小麦生物量(本文指总干生物量,下同)和真实叶面积指数的高光谱遥感估算模型.结果表明:①小麦生物量与冠层光谱在552 nm,721 nm处呈现最显著相关关系,叶面积指数与冠层光谱的相关性在400～1100 nm范围内较显著;②红边位置与生物量的关系最为显著,相关系数R为0.818;③6种等效MODIS植被指数中,增强型植被指数对生物量最为敏感;④红边位置估算小麦总生物量的指数模型最优,决定系数R2为0.829;⑤增强型植被指数与小麦叶面积指数的指数模型拟合度最强,决定系数R2为0.94.利用实测光谱模拟MODIS等效反射率构建植被指数反演小麦参数的方法,可为利用卫星数据进行大面积、无破坏和及时获取地面植被信息研究提供重要手段.  相似文献   

6.
以湖北省输电线路走廊地区作为研究区,利用2013年1~9月MODIS卫星影像数据,处理得到月尺度的归一化植被指数(Normalized Differential Vegetation Index,NDVI)与地表温度(Land Surface Temperature,LST)数据,构建NDVI-Ts特征空间,计算得到温度植被干旱指数(Temperature Vegetation Dryness Index,TVDI),用TVDI监测结果分析湖北省输电线路走廊区域2013年干旱时空分布情况。结果表明,湖北省输电线路走廊地区TVDI和土壤含水量之间存在显著的负相关,相关系数达到0.525(p0.05),由MODIS卫星影像计算得到TVDI影像可以有效表明湖北省输电线路走廊地区的土壤含水情况。  相似文献   

7.
使用鲁西北地区24个国家气象观测站1981—2017年的气温及降水月值数据,主要通过计算年尺度SPEI指数,采用线性回归、两种突变检验方法以及小波能量谱分析等方法深入分析鲁西北地区干旱的变化规律。鲁西北地区实际发生的干旱事件与同期同时长SPEI值表征的干旱状态较吻合,表明SPEI指数在该地区具有较好的适用性;鲁西北地区整体上呈不显著的湿润化趋势发展,2008年为研究时间段内干旱情况的突变年;鲁西北地区SPEI12指数多年平均值为正常状态,最小值和最大值分别出现在1990年和2002年。鲁西北地区整体上出现轻旱、中旱、重旱,年份数分别为5次、8次、1次,所有年份均未发生特旱;鲁西北地区不同地区发生不同等级干旱灾害的频率差异较大,整体上干旱灾害的发生频率为轻旱>中旱>重旱>特旱;鲁西北地区年尺度干旱的小波波动能量中心共有3个,中心尺度分别为5 a、9～10 a和3 a。  相似文献   

8.
以河南省为研究区,利用2005—2014年间的EOS-MODIS地表温度产品MOD11A2、植被指数产品MOD13A3以及热带降水测量任务(tropical rainfall measuring mission,TRMM)的月降水速率数据集TRMM3B43,计算了植被状态指数(vegetation condition index,VCI)、温度状态指数(temperature condition index,TCI)以及降水状态指数(tropical rainfall condition index,TRCI),同时结合土地利用类型数据及气象站点数据,通过层次分析法确定权重,构建了农业干旱指数监测模型。在此基础上,利用标准化降水指数(standardized precipitation index,SPI)对模型进行验证,并根据SPI的等级划分确定构建的农业干旱指数监测模型的划分等级。以2014年为例,应用构建的农业干旱指数对河南省干旱情况进行时空分析。结果表明,构建的农业干旱指数监测模型能够有效监测河南省干旱时空变化特征,具有较好的监测效果。  相似文献   

9.
FY-3A MERSI数据干旱监测能力评价   总被引：3，自引：0，他引：3  
对FY-3A MERSI数据进行辐射定标、几何定位预处理,与同期MODIS数据预处理结果进行对比;选用温度植被干旱指数法对两种数据进行监测,分析了监测结果的相对精度。实验结果表明,FY-3A MERSI数据的干旱监测结果精度与MODIS数据基本一致,且在空间分辨率及光谱分辨率方面有较大的提高。  相似文献   

10.
为提高农业干旱监测效果和精度,在对传统干旱监测模型对比分析基础上,本文提出将温度植被干旱指数(TVDI)和植被供水指数(VSWI)加权联合构建温度供水干旱指数(TSWDI)的研究思路。以京津冀2006—2012年5月份数据作为实验统计数据,以京津冀2006—2016年3—5月份春旱监测为例进行了模型实验。实验结果证实,TSWDI指数相对其他两个指数与10、20和50 cm深处的土壤水分相关性更高,能够更精准地反映农业干旱状况。TSWDI计算结果显示,京津冀干旱分布具有如下特征:从时间角度看,2006—2016年整体干旱状况逐渐缓解,特别是自2010年至今,研究区域干旱程度逐步减轻;从空间角度看,京津冀区域整体干旱面积逐步减少。  相似文献   

11.
ABSTRACT

Agricultural drought threatens food security. Numerous remote-sensing drought indices have been developed, but their different principles, assumptions and physical quantities make it necessary to compare their suitability for drought monitoring over large areas. Here, we analyzed the performance of three typical remote sensing-based drought indices for monitoring agricultural drought in two major agricultural production regions in Shaanxi and Henan provinces, northern China (predominantly rain-fed and irrigated agriculture, respectively): vegetation health index (VHI), temperature vegetation dryness index (TVDI) and drought severity index (DSI). We compared the agreement between these indices and the standardized precipitation index (SPI), soil moisture, winter wheat yield and National Meteorological Drought Monitoring (NMDM) maps. On average, DSI outperformed the other indices, with stronger correlations with SPI and soil moisture. DSI also corresponded better with soil moisture and NMDM maps. The jointing and grain-filling stages of winter wheat are more sensitive to water stress, indicating that winter wheat required more water during these stages. Moreover, the correlations between the drought indices and SPI, soil moisture, and winter wheat yield were generally stronger in Shaanxi province than in Henan province, suggesting that remote-sensing drought indices provide more accurate predictions of the impacts of drought in predominantly rain-fed agricultural areas.  相似文献   

12.
The hard-rock hilly Aravalli terrain of Rajasthan province of India suffers with frequent drought due to poor and delayed monsoon, abnormally high summer-temperature and insufficient water resources. In the present study, detailed analysis of meteorological and hydrological data of the Aravalli region has been carried out for the years 1984–2003. Standardised Precipitation Index (SPI) has been used to quantify the precipitation deficit. Standardised Water-Level Index (SWI) has been developed to assess ground-water recharge-deficit. Vegetative drought indices like Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) and Vegetation Health Index (VHI) have been computed using NDVI values obtained from Global Vegetation Index (GVI) and thermal channel data of NOAA AVHRR satellite. Detailed analyses of spatial and temporal drought dynamics during monsoon and non-monsoon seasons have been carried out through drought index maps generated in Geographic Information Systems (GIS) environment. Analysis and interpretation of these maps reveal that negative SPI anomalies not always correspond to drought. In the Aravalli region, aquifer-stress shifts its position time to time, and in certain pockets it is more frequent. In comparison to hydrological stress, vegetative stress in the Aravalli region is found to be slower to begin but quicker to withdraw.  相似文献   

13.
Developing a robust drought monitoring tool is vital to mitigate the adverse impacts of drought. A drought monitoring system that integrates multiple agrometeorological variables into a single drought indicator is lacking in areas such as Ethiopia, which is extremely susceptible to this natural hazard. The overarching goal of this study is to develop a combined drought indicator (CDI-E) to monitor the spatial and temporal extents of historic agricultural drought events in Ethiopia. The CDI-E was developed by combining four satellite-based agrometeorological input parameters – the Standardized Precipitation Index (SPI), Land Surface Temperature (LST) anomaly, Standardized Normalized Difference Vegetation Index (stdNDVI) and Soil Moisture (SM) anomaly – for the period from 2001 to 2015. The method used to combine these indices is based on a quantitative approach that assigns a weight to each input parameter using Principal Component Analysis (PCA). The CDI-E results were evaluated using satellite-based gridded rainfall (3-month SPI) and crop yield data for 36 intra-country crop growing zones for a 15-year period (2001 to 2015). The evaluation was carried out for the main rainfall season, Kiremt (June-September), and the short rainfall season, Belg (February-May). The results showed that moderate to severe droughts were detected by the CDI-E across the food insecure regions reported by FEWS NET during Kiremt and Belg rainfall seasons. Relatively higher correlation coefficient values (r > 0.65) were obtained when CDI-E was compared with the 3-month SPI across the majority of Ethiopia. The spatial correlation analyses of CDI-E and cereal crop yields showed relatively good correlations (r > 0.5) in some of the crop growing zones in the northern, eastern and southwestern parts of the country. The CDI-E generally mapped the spatial and temporal patterns of historic drought and non-drought years and hence the CDI-E could potentially be used to develop an agricultural drought monitoring and early warning system in Ethiopia. Moreover, decision makers and donors may potentially use CDI-E to more accurately monitor crop yields across the food-insecure regions in Ethiopia.  相似文献   

14.
We used RapidEye and Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra data to study terrain illumination effects on 3 vegetation indices (VIs) and 11 phenological metrics over seasonal deciduous forests in southern Brazil. We applied TIMESAT for the analysis of the Enhanced Vegetation Index (EVI) and the Normalized Difference Vegetation Index (NDVI) derived from the MOD13Q1 product to calculate phenological metrics. We related the VIs with the cosine of the incidence angle i (Cos i) and inspected percentage changes in VIs before and after topographic C-correction. The results showed that the EVI was more sensitive to seasonal changes in canopy biophysical attributes than the NDVI and Red-Edge NDVI, as indicated by analysis of non-topographically corrected RapidEye images from the summer and winter. On the other hand, the EVI was more sensitive to terrain illumination, presenting higher correlation coefficients with Cos i that decreased with reduction in the canopy background L factor. After C-correction, the RapidEye Red-Edge NDVI, NDVI, and EVI decreased 2%, 1%, and 13% over sunlit surfaces and increased up to 5%, 14%, and 89% over shaded surfaces, respectively. The EVI-related phenological metrics were also much more affected by topographic effects than the NDVI-derived metrics. From the set of 11 metrics, the 2 that described the period of lower photosynthetic activity and seasonal VI amplitude presented the largest correlation coefficients with Cos i. The results showed that terrain illumination is a factor of spectral variability in the seasonal analysis of phenological metrics, especially for VIs that are not spectrally normalized.  相似文献   

15.
ABSTRACT

We designed a unique hyperspectral experiment from the Earth Observing One (EO-1) orbit change to evaluate solar illumination effects over tropical forests in Brazil. Ten nadir-viewing Hyperion images collected over a fixed site and period of the year (July to August) were selected for analysis. We evaluated variations in reflectance and in 16 narrowband vegetation indices (VIs) with increasing solar zenith angle (SZA) from the pre-drift (2004–2008) to the EO-1 drift period (2011–2016). To detect changes in reflectance and shadows, we applied spectral mixture analysis (SMA) and principal component analysis (PCA) and calculated the similarity spectral angle (θ) between the vegetation spectra measured with variable SZA. The magnitude of the illumination effects was also evaluated from change-point analysis and nonparametric Mann-Whitney U tests applied over the time series. Finally, we complemented our experiment using the PROSAIL model to simulate the VIs variation with increasing SZA resultant from satellite drift. The results showed significant changes in Hyperion reflectance and VIs, especially when the EO-1 crossed the study area at earlier times and larger SZA in 2015 (9:05 a.m.; SZA = 59°) and 2016 (8:30 a.m.; SZA = 67°). Compared to the pre-drift period (10:30 a.m.; SZA = 45°), the SZA differences of 14° (2015) and 22° (2016) increased the shade fractions and decreased the vegetation brightness. PCA separated the pre-drift and drift reflectance datasets, showing shifts in scores due to changes in brightness. θ increased with SZA, indicating changes in the shape of the vegetation spectra with drift. For most VIs, the change-point analysis indicated 2015 (SZA = 59°) as the predominant year of detected changes. Compared to the EO-1 original orbit, the Plant Senescence Reflectance Index (PSRI), Anthocyanin Reflectance Index (ARI) and Structure Insensitive Pigment Index (SIPI) presented the largest positive changes during drift, while the Photochemical Reflectance Index (PRI), Visible Atmospherically Resistant Index (VARI) and Enhanced Vegetation Index (EVI) had the largest negative changes. The effect size of the illumination geometry on these VIs was large, as indicated by increasing values of the Cohen’s r metric toward 2016. The anisotropy of the Hyperion VIs was generally consistent with that from PROSAIL in the simulated pre-drift and drift periods. Focusing on structural indices, it affected the relationships between VIs and simulated leaf area index (LAI) at large SZA.  相似文献   

16.
长江中下游地区是中国最重要的粮食产区之一,近年来,由于极端天气影响,长江中下游地区的农业生产时常受到干旱灾害威胁。利用植被条件指数(vegetation condition index, VCI)、温度条件指数(temperature condition index, TCI)及植被健康指数(vegetation health index, VHI)对2001—2019年长江中下游地区农业干旱的时空演变情况进行监测,探究长江中下游地区VCI、TCI在VHI指数中的最优权重比例,挖掘不同植被对干旱的敏感性差异,同时基于气候变化背景分析长江中下游六省一市的干旱趋势。结果表明,VCI和TCI指数能够分别反映地区植被生长异常和热量异常;当VCI和TCI的权重分配比为7∶3时,VHI指数能够结合两种指数的特点,在长江中下游地区农业干旱监测上更有优势;不同植被对干旱的敏感性不同,在长江中下游地区,农作物对干旱的敏感性最高,森林最低,草地介于二者之间;在气候变化背景下,近20年来,长江中下游地区呈现逐渐湿润的趋势,干旱风险逐步降低,其中湖北、湖南、安徽、江西和浙江等地湿润趋势明显,而江苏和上海地区湿润趋势较弱,在极端气候下仍存在一定的干旱风险。相关结果能够为长江中下游地区各省市旱情预警及抗旱措施制定、区域农业生产管理提供参考。  相似文献   

17.
Satellite-based remote sensed phenology has been widely used to assess global climate change. However, it is constrained by uncertain linkages with photosynthesis activity. Two dynamic threshold methods were employed to retrieve spring phenology metrics from four Moderate Resolution Imaging Spectroradiometer (MODIS) products, including fraction of Absorbed Photosynthetically Active Radiation (fAPAR), Leaf Area Index (LAI), Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) for three temperate deciduous broadleaf forests in North America between 2001 and 2009. These MODIS-based spring phenology metrics were subsequently linked to the photosynthetic curves (daily gross primary productivity, GPP) measured by an eddy covariance flux tower. The 20% dynamic threshold spring onset metrics from MODIS products were closer to the photosynthesis onset metrics at the date of 2% GPP increase for NDVI and fAPAR, and closer to the date of 5% and 10% increase of GPP for EVI and LAI, respectively. The 50% dynamic threshold onset metrics were closer to the photosynthesis onset metrics at the date of 10% GPP increase for NDVI, and closer to the date of 20% GPP increase for fAPAR, LAI and EVI, respectively. These results can improve our knowledge on the photosynthesis activity status of remotely sensed spring phenology metrics.  相似文献   

18.
Monthly time series, from 2001 to 2016, of the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI) from MOD13Q1 products were analyzed with Seasonal Trend Analysis (STA), assessing seasonal and long-term changes in the mangrove canopy of the Teacapan-Agua Brava lagoon system, the largest mangrove ecosystem in the Mexican Pacific coast. Profiles from both vegetation indices described similar phenological trends, but the EVI was more sensitive in detecting intra-annual changes. We identified a seasonal cycle dominated by Laguncularia racemosa and Rhizophora mangle mixed patches, with the more closed canopy occurring in the early autumn, and the maximum opening in the dry season. Mangrove patches dominated by Avicennia germinans displayed seasonal peaks in the winter. Curves fitted for the seasonal vegetation indices were better correlated with accumulated precipitation and solar radiation among the assessed climate variables (Pearson’s correlation coefficients, estimated for most of the variables, were r ≥ 0.58 p < 0.0001), driving seasonality for tidal basins with mangroves dominated by L. racemosa and R. mangle. For tidal basins dominated by A. germinans, the maximum and minimum temperatures and monthly precipitation fit better seasonally with the vegetation indices (r ≥ 0.58, p < 0.0001). Significant mangrove canopy reductions were identified in all the analyzed tidal basins (z values for the Mann-Kendall test ≤ ?1.96), but positive change trends were recorded in four of the basins, while most of the mangrove canopy (approximately 87%) displayed only seasonal canopy changes or canopy recovery (z > ?1.96). The most resilient mangrove forests were distributed in tidal basins dominated by L. racemosa and R. mangle (Mann-Kendal Tau t ≥ 0.4, p ≤ 0.03), while basins dominated by A. germinans showed the most evidence of disturbance.  相似文献   

19.
The main purpose of this study is to explore the relationship between three field-based fire severity indices (Composite Burn Index-CBI, Geometrically structure CBI, weighted CBI) and spectral indices derived from Sentinel 2A and Landsat-8 OLI imagery on a recent large fire in Thasos, Greece. We employed remotely sensed indices previously used from the remote sensing fire community (Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), differenced NDVI, differenced NBR, relative differenced NBR, Relativized Burn Ratio) and seven Sentinel 2A-specific indices considering the availability of spectral information recorded in the red-edge spectral region. The statistical correlation indicated a slightly stronger relationship between the differenced NBR and the GeoCBI for both Sentinel 2A (r = 0.872) and Landsat-8 OLI (r = 0.845) imagery. Predictive local thresholds of dNBR values showed slightly higher classification accuracy for Sentinel 2A (73.33%) than Landsat-8 OLI (71.11%), suggesting the adequacy of Sentinel 2A for forest fire severity assessment and mapping in Mediterranean pine ecosystems. The evaluation of the classification thresholds calculated in this study over other fires with similar pre-fire conditions could contribute in the operational mapping and reconstruction of the historical patterns of fire severity over the Eastern Mediterranean region.  相似文献   

20.
Monitoring agricultural drought effectively and timely is important to support drought management and food security. Effective drought monitoring requires a suite of drought indices to capture the evolution process of drought. Thermal infrared signals respond rapidly to vegetation water stress, thus being regarded useful for drought monitoring at the early stage. Several temperature-based drought indices have been developed considering the role of land surface temperature (LST) in surface energy and water balance. Here, we compared the recently proposed Temperature Rise Index (TRI) with several agricultural drought indices that also use thermal infrared observations, including Temperature Condition Index (TCI), Vegetation Health Index (VHI) and satellite-derived evapotranspiration ratio anomaly (ΔfRET) for a better understanding of these thermal infrared drought indices. To do so, we developed a new method for calculating TRI directly from the top-of-atmosphere brightness temperatures in the two split-window channels (centered around ∼11 and 12 μm) rather than from LST. TRI calculated using the Himawari-8 brightness temperatures (TRI_BT) and LST retrievals (TRI_LST), along with the other LST-based indices, were calculated for the growing season (July–October) of 2015−2019 over the Australian wheatbelt. An evaluation was conducted by spatiotemporally comparing the indices with the drought indices used by the Australian Bureau of Meteorology in the official drought reports: the Precipitation Condition Index (PCI) and the Soil Moisture Condition Index (SMCI). All the LST-based drought indices captured the wet conditions in 2016 and dry conditions in 2019 clearly. Ranking of Pearson correlations of the LST-based indices with regards to PCI and SMCI produced very similar results. TRI_BT and TRI_LST showed the best agreement with PCI and SMCI (r > 0.4). TCI and VHI presented lower consistency with PCI and SMCI compared with TRI_BT and TRI_LST. ΔfRET had weaker correlations than the other LST-based indices in this case study, possibly because of outliers affecting the scaling procedure. The capability of drought early warning for TRI was demonstrated by comparing with the monthly time series of the greenness index Vegetation Condition Index (VCI) in a case study of 2018 considering the relatively slow response of the greenness index to drought. TRI_BT and TRI_LST had a lead of one month in showing the changing dryness conditions compared with VCI. In addition, the LST-based indices were correlated with annual wheat yield. Compared to wheat yields, all LST-based indices had a peak correlation in September. TRI_BT and TRI_LST had strong peak and average correlations with wheat yield (r ≥ 0.8). We conclude that TRI has promise for agricultural drought early warning, and TRI_BT appears to be a good candidate for efficient operational drought early warning given the readily accessible inputs and simple calculation approach.  相似文献   

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