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1.
全国干旱遥感监测运行系统的研制   总被引:11,自引:2,他引:11  
该研究利用1981-1994的NOAA AVHRR 8km分辨率的NDVI资料,以及对应时段全国102个固定农业观测站的20cm深的土壤湿度资料,建立了植被状态指数(VCI)与土壤湿度之间的统计模型,由土壤湿度旱情等级标准来换算出每旬用VCI进行干旱监测的旱情等级标准,以确定出全国的旬旱情分布状况,在此工作的基础上建成了“全国干旱遥感则运行系统”,该运行系统使遥感手段监测全国干旱成为可能,将能提供每年3-9月每旬全国的干旱监测情况,为国家有关决策部门提供干旱减灾的决策依据。  相似文献   

2.
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   

3.
微波植被指数在干旱监测中的应用   总被引:3,自引:0,他引:3  
在植被覆盖区域,归一化植被指数(NDVI)被广泛地应用于干旱遥感监测。和基于光学遥感的植被指数相比,Shi等提出的微波植被指数MVI(Microwave Vegetation Index)被证实能够反映更多的植被生长信息。本文以MVI为基础,利用MVI代替目前比较成熟的温度植被指数TVDI(Temperature Vegetation Index)中的NDVI,构建温度微波植被干旱指数TMVDI(Temperature Microwave Vegetation Index),发展了一种新的干旱监测方法。本文以2006年夏季四川省发生的百年难遇的干旱为研究对象,将基于TMVDI与TVDI的干旱监测结果进行了对比分析。最后,为评估监测结果的准确性,将遥感监测的结果与基于气象站点降雨观测数据构建的标准降雨指数SPI(Standardized Precipitation Index)的计算结果进行了对比分析。结果表明,利用低频降轨微波辐射计数据计算的T MVDI最适合于进行植被覆盖区域的干旱监测。  相似文献   

4.
土壤湿度信息遥感研究   总被引:3,自引:0,他引:3  
土壤湿度是农业生产与应用过程中非常重要的因素,决定农作物的水分供应状况.本文利用MODIS产品数据获取的归一化植被指数(NDVI)和陆面地表温度(Ts)构建Ts-NDVI特征空间,根据温度植被干旱指数(TVDI)的研究原理与方法,对研究区2010年5~8月份土壤湿度分布情况进行遥感监测.结合气象数据与土壤墒情资料对局部...  相似文献   

5.
条件植被温度指数及其在干旱监测中的应用   总被引:93,自引:0,他引:93  
应用NOAA-AVHRR数据,在用条件植被指数、条件温度指数和距平植被指数进行年度间相对干旱程度监测的基础上,提出了条件植被温度指数的概念,它适用于监测某一特定年内某一时期(如旬)区域级的相对干旱程度。条件植被温度指数的定义既考虑了区域内归一化植被指数的变化,又考虑了在归一化植被指数值相同条件下土地表面温度的变化。陕西省关中平原地区2000年3月下旬干旱的监测结果表明,条件植被温度指数能较好地监测该区域的相对干旱程度,并可用于研究干旱程度的空间变化特征,对干旱的监测结果与用土壤热惯量模型反演的土壤表层含水量的结果基本吻合。  相似文献   

6.
干旱是全球范围内影响最广的自然灾害,它不仅威胁着人类赖以生存的自然环境,而且还严重影响着人类社会、经济的可持续发展。华北地区作为我国重要的农业经济区,出现连年干旱情况,是我国最大的干旱区。分析了MODIS干旱指数对干旱响应的敏感性,依据2008~2017年气象降水资料,初步估算了旱情发展过程和空间分布范围旱情发展过程和空间分布范围,从干旱发生的时段和面积分布对MODIS构建的AVI、AWI、VCI、TCI、VHI 5个干旱指数进行比较,对华北区各分区2008~2017年干旱进行了时空分析。旱情监测结果与实际情况较为符合,说明此方法适用于区域旱情的动态监测。  相似文献   

7.
针对鄂尔多斯高原植被覆盖变化受干旱胁迫的状况,该文结合降水和气温的协同变化,以2000-2012年生长季的MODIS-NDVI数据和同期降水、温度和帕尔默干旱指数为依据,采用线性趋势分析、标准偏差分析和相关性分析等方法,对鄂尔多斯高原植被与气候变化的相关关系和干旱异常变化对植被动态的影响进行了研究.结果表明:鄂尔多斯高原生长季及季节(春季、夏季和秋季)植被归一化植被指数主要受降水的控制和干旱的制约,秋季归一化植被指数更多地受到夏季干旱的影响.与气象因子的空间相关分析表明,春季温度上升有利于研究区北部归一化植被指数像元的增加.在荒漠草原和沙漠地区,夏季干旱与归一化植被指数的相关关系最强.秋季降水对典型草原归一化植被指数的提升显著.  相似文献   

8.
基于遥感技术的河南省农业旱情监测研究   总被引:1,自引:0,他引:1  
干旱的发生不仅影响农业生产,还极大地破坏了生态环境。遥感技术宏观、客观、迅速和廉价的优势及其近年来的飞速发展,为旱情监测开辟了一条新途径。利用RS、GIS、GPS技术,使用MODIS卫星的归一化植被指数( NDVI)数据、地表温度( LST)数据和水文气象数据,结合当前旱情监测模型,以植被指数和地表温度为依托,建立了适合河南省的农业旱情遥感监测模型。  相似文献   

9.
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   

10.
有关春旱的时空特征信息对于许多农业应用和决策都至关重要。本研究利用NOAA/AVHRR的植被状态指数(vegetation condition index,VCI)产品,对1995—2010年间青藏地区的植被干旱情况进行了全面的时空分析。针对VCI作为干旱指标的特点,采用了多种方法,其中包括干旱的频率分析、趋势分析和Mann-Kendall实验。研究表明青藏地区受季风影响较小,横断山脉和祁连山地区干旱发生的频率比较低,且多为轻中旱。根据分析表明,该地区干旱的趋势并不是单向变化的,可以将其分为2个阶段:2000年以前VCI指数较高,且波动相对较大; 2000年之后VCI指数相对较低,且相对稳定。  相似文献   

11.
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   

12.
Early yield assessment at local, regional and national scales is a major requirement for various users such as agriculture planners, policy makers, crop insurance companies and researchers. This current study explored a remote sensing-based approach of predicting sugarcane yield, at district level, using Vegetation Condition Index (VCI), under the FASAL programme of the Ministry of Agriculture & Farmers’ Welfare. 13-years’ historical database (2003–2015) of NDVI was used to derive the VCI. NDVI products (MOD-13A2) of MODIS instrument on board Terra satellite at 16-day interval from first fortnight of June to second fortnight of October (peak growing period) were used to calculate the VCI. Stepwise regression technique was used to develop empirical models between VCI and historical yield of sugarcane over 52 major sugarcane-growing districts in five states of India. For all the districts, the empirical models were found to be statistically significant. A large number of statistical parameters were computed to evaluate the performance of VCI-based models in predicting district-level sugarcane yield. Though there was variation in model performance in different states, overall, the study showed the usefulness of VCI, which can be used as an input for operational sugarcane yield forecasting.  相似文献   

13.
With the development of global changes, researchers from all over the world increasingly pay attention to drought detection, and severe droughts that may have resulted from climate change. In this paper, spatial and temporal variability of drought is evaluated based on precipitation data and remotely sensed images. The standard precipitation index (SPI) and vegetation condition index (VCI) are used to evaluate the spatial and temporal characteristics of meteorological and vegetative drought in Tigray, Northern Ethiopia. Based on the drought critical values of SPI and VCI defining drought, the spatial and temporal extent of droughts in the study area is established. We processed 396 decadal images in order to produce the multi-temporal VCI drought maps. The results of the SPI and VCI analysis reveal that the eastern and southern zones of the study region suffered a recurrent cycle of drought over the last decade. Results further show that there is a time lag between the period of the peak VCI and precipitation values obtained from the meteorological stations across the study area. A significant agreement was observed between VCI values with the current plus last two-months of precipitation. The study demonstrates the utility of the vegetation condition index in semi-arid and arid regions.  相似文献   

14.
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   

15.
Agricultural drought has been a recurrent phenomenon in many parts of India. Remote sensing plays a vital role in real time monitoring of the agricultural drought conditions over large area, there by effectively supplementing the ground mechanism. Conventional drought monitoring is based on subjective data. The satellite based monitoring such as National Agricultural Drought Assessment and Monitoring System (NADAMS) is based on the crop condition, which is an integrated effect of soil, effective rainfall, weather, etc. Drought causes changes in the external appearance of vegetation, which can clearly be identified (by their changed spectral response) and judged using satellite sensors through the use of vegetation indices. These indices are functions of rate of growth of the plants and are sensitive to the changes of moisture stress in vegetation. The satellite based drought assessment methodology was developed based on relationship obtained between previous year’s Normalised Difference Vegetation Index (NDVI) profiles with corresponding agricultural performance available at district/block level. Palar basin, one of the major river basins in Tamil Nadu state was selected as the study area. The basin covers 3 districts, which contain 44 blocks. Wide Image Field Sensor (WiFS) of 188m spatial resolution from Indian Remote Sensing Satellite (IRS) data was used for the analysis. Satellite based vegetation index NDVI, was generated for Samba and Navarai seasons in the years 1998 and 1999. An attempt has been made to estimate the area under paddy. It was also observed that, there was reduction in the crop area as well as vigour in the vegetation in both Samba and Navarai seasons in 1999 when compared with 1998. Drought severity maps were prepared in GIS environment giving blockwise agricultural water deficiency status.  相似文献   

16.
Although poor precipitation due to delayed arrival and/or early retreat of the southwest monsoon is considered the chief architect of drought in India, heat waves may also play a crucial role in the intensification of droughts. In the Indian subcontinent, occurrence of heat waves during the pre-monsoon and high air-temperature in the subsequent monsoon season imparts thermal stress on vegetation causing degradation of vegetation health (VH). In the present study, various vegetation indices and land-use/land-cover data derived from multi-sensor satellite have been used to assess VH and agricultural drought in Gujarat during 1981–2010. This Geographical Information Systems-based study has also used heat wave and temperature data to analyze the adverse effects of high temperature on VH. The time series of Vegetation Condition Index and Temperature Condition Index (TCI) has shown that the combined influence of moisture-stress and thermal stress determines the occurrence and severity of drought, which is reflected in the Vegetation Health Index (VHI). A strong correlation among aboveground air-temperature, the TCI and the VHI indicates definite influence of thermal stress on VH. Further, a systematic variation and strong resemblance between temperature, crop yield, TCI and VHI has established the impact of thermal stress on agricultural productivity.  相似文献   

17.
Availability of reliable, timely and accurate rainfall data is constraining the establishment of flood forecasting and early warning systems in many parts of Africa. We evaluated the potential of satellite and weather forecast data as input to a parsimonious flood forecasting model to provide information for flood early warning in the central part of Nigeria. We calibrated the HEC-HMS rainfall-runoff model using rainfall data from post real time Tropical Rainfall Measuring Mission (TRMM) Multi satellite Precipitation Analysis product (TMPA). Real time TMPA satellite rainfall estimates and European Centre for Medium-Range Weather Forecasts (ECMWF) rainfall products were tested for flood forecasting. The implication of removing the systematic errors of the satellite rainfall estimates (SREs) was explored. Performance of the rainfall-runoff model was assessed using visual inspection of simulated and observed hydrographs and a set of performance indicators. The forecast skill was assessed for 1–6 days lead time using categorical verification statistics such as Probability Of Detection (POD), Frequency Of Hit (FOH) and Frequency Of Miss (FOM). The model performance satisfactorily reproduced the pattern and volume of the observed stream flow hydrograph of Benue River. Overall, our results show that SREs and rainfall forecasts from weather models have great potential to serve as model inputs for real-time flood forecasting in data scarce areas. For these data to receive application in African transboundary basins, we suggest (i) removing their systematic error to further improve flood forecast skill; (ii) improving rainfall forecasts; and (iii) improving data sharing between riparian countries.  相似文献   

18.
Drought is one of the most frequent climate-related disasters occurring in Southwest China, where the occurrence of drought is complex because of the varied landforms, climates and vegetation types. To monitor the comprehensive information of drought from meteorological to vegetation aspects, this paper intended to propose the optimized meteorological drought index (OMDI) and the optimized vegetation drought index (OVDI) from multi-source satellite data to monitor drought in three bio-climate regions of Southwest China. The OMDI and OVDI were integrated with parameters such as precipitation, temperature, soil moisture and vegetation information, which were derived from Tropical Rainfall Measuring Mission (TRMM), Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST), AMSR-E Soil Moisture (AMSR-E SM), the soil moisture product of China Land Soil Moisture Assimilation System (CLSMAS), and MODIS Normalized Difference Vegetation Index (MODIS NDVI), respectively. Different sources of satellite data for one parameter were compared with in situ drought indices in order to select the best data source to derive the OMDI and OVDI. The Constrained Optimization method was adopted to determine the optimal weights of each satellite-based index generating combined drought indices. The result showed that the highest positive correlation and lowest root mean square error (RMSE) between the OMDI and 1-month standardized precipitation evapotranspiration index (SPEI-1) was found in three regions of Southwest China, suggesting that the OMDI was a good index in monitoring meteorological drought; in contrast, the OVDI was best correlated to 3-month SPEI (SPEI-3), and had similar trend with soil relative water content (RWC) in temporal scale, suggesting it a potential indicator of agricultural drought. The spatial patterns of OMDI and OVDI along with the comparisons of SPEI-1 and SPEI-3 for different months in one year or one month in different years showed significantly varied drought locations and areas, demonstrating regional and seasonal fluctuations, and suggesting that drought in Southwest China should be monitored in seasonal and regional level, and more fine distinctions of seasons and regions need to be considered in the future studies of this area.  相似文献   

19.
鄱阳湖地区洪涝灾害遥感分析   总被引:3,自引:0,他引:3  
鄱阳湖是一个吞吐型,季节性的浅淡水湖,高水湖相,低水河相。有“高水是湖,低水似河”,“洪水一片,枯水一线”的独特景观。洪涝灾害发生时,给周边地区造成巨大损失。利用TM遥感卫星图片,以特征最明显的1998年特大洪涝灾害为例,对鄱阳湖地区洪涝灾害症结和防洪策略提出几点见解。  相似文献   

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