遥感干旱指数在洛川苹果干旱监测中的适用性分析

目前对苹果干旱研究较少且主要运用站点数据,对空间信息表征有限,遥感干旱指数可用于大范围干旱时空动态监测,但在苹果干旱监测中的适用性还有待研究。基于2014~2018年MODIS反射率、地表温度以及地表覆被数据,结合土壤湿度数据和野外调查资料,分析洛川苹果区温度植被干旱指数（TVDI）、归一化植被水分指数（NDWI）、植被供水指数（VSWI）与10 cm深度土壤湿度（SM）的一致性,探索遥感干旱指标对土壤干湿状况表征能力,并进一步研究遥感干旱指标对干旱响应敏感时段。结果表明：①由增强型植被指数（EVI）计算的VSWI与SM的时空一致性最好,其在2014、2017年表现出的干旱特征与实际旱情相符;②VSWI（EVI）和TVDI（EVI）与SM的相关性分别高于VSWI（NDVI）和TVDI（NDVI）与SM的相关性,使用EVI能提高VSWI和TVDI对干旱的表征能力;③TVDI、NDWI、VSWI对SM存在不同时间的反应滞后,滞后3时相（24 d）的VSWI（EVI）与SM的相关性最高,而NDWI对SM滞后时间短,对干旱响应较及时,结合VSWI（EVI）和NDWI可能更有利于监测苹果干旱;④在不同苹果生育期,遥感指标对土壤湿度敏感性不同,VSWI在不同生育期敏感性差异最明显：新梢旺长期（5、6月）对土壤湿度敏感性高于萌芽开花期、果实膨大期、成熟期;该结果符合洛川县苹果不同生育期需水规律和洛川降水、干旱发生特征。研究结果可为遥感监测苹果干旱提供参考依据。     

TM与MODIS植被供水指数反演及对比分析

为了探讨多源卫星遥感数据针对同一地区同一时刻旱情所得植被供水指数的差异,选择我国华北地区旱灾发生频率较高、影响较广的河北地区为研究区,针对近年来干旱监测应用较为广泛的Landsat TM/ETM+和EOS MODIS数据,分别进行植被供水指数的提取,并进行两者之间的对比分析,得出以下结论:① TM VSWI (Vegetation Supply Water Index) 与MODIS VSWI之间数值上存在一定的差别,变化范围在-0.51~0.20之间。其中负值主要集中在城镇、裸地及水体地表;② 在植被覆盖区,TM的平均VSWI大于MODIS的,但两者差别不大;③ 在各种植被覆盖度条件下,TM VSWI与MODIS VSWI差值的最小值、最大值和均值均表现出随着植被覆盖度的增加,其值逐渐增大的特点。该结论可以为两种遥感数据源干旱监测的差异分析及综合应用提供重要的参考依据。     

苏丹遥感干旱指数及其适用性

针对苏丹地区利用遥感手段进行旱情监测的研究相对缺乏这一问题,该文利用MODIS归一化植被指数和地表温度计算植被条件指数、温度植被干旱指数和归一化植被供水指数,利用AMSR-E土壤湿度数据与3种干旱指数进行相关性分析,选取与土壤湿度相关性最好的干旱指数作为干旱监测的指标,对苏丹典型干湿年份的干旱进行监测。定量分析与实验结果表明:归一化植被供水指数与土壤湿度相关性最高,且与降水量存在滞后关系,3种典型植被覆盖类型下归一化植被供水指数的滞后期均为1个月;苏丹干旱主要发生在北部的撒哈拉沙漠及其边缘地区,且干旱分布受季节变化影响显著,其中春季和冬季是干旱发生的高峰期。     

使用温度植被干旱指数法(TVDI)反演新疆土壤湿度

利用MODIS合成产品数据MOD11A2和MOD13A2获取的归一化植被指数(NDVI)和陆地表面温度(Ts)构建Ts-NDVI特征空间,依据该特征空间计算的温度植被干旱指数(TVDI)作为土壤湿度监测指标,反演了新疆8、9两个月份每16 d的土壤湿度。使用野外与卫星同步采样的土壤湿度数据进行验证,发现TVDI指标与实测土壤湿度数据显著相关,能够较好地反映表层土壤湿度,反映的新疆土壤湿度的空间分布与新疆的年降水量分布、年平均相对湿度分布很吻合;同时表明8、9两个月份期间新疆土壤湿度低的区域在不断扩大。     

使用温度植被干旱指数法(TVDI)反演新疆土壤湿度

利用MODIS合成产品数据MOD11A2和MOD13A2获取的归一化植被指数(NDVI)和陆地表面温度(Ts)构建Ts—NDVI特征空间，依据该特征空间计算的温度植被干旱指数(TVDI)作为土壤湿度监测指标，反演了新疆8、9两个月份每16d的土壤湿度。使用野外与卫星同步采样的土壤湿度数据进行验证，发现TVDI指标与实测土壤湿度数据显著相关，能够较好地反映表层土壤湿度，反映的新疆土壤湿度的空间分布与新疆的年降水量分布、年平均相对湿度分布很吻合；同时表明8、9两个月份期间新疆土壤湿度低的区域在不断扩大。     

基于温度植被干旱指数的印度和巴基斯坦干旱监测

针对印度和巴基斯坦近年干旱频发的问题,该文使用温度植被干旱指数对印巴地区2009~2014年干季(3~5月)实现遥感干旱监测,利用多年同期MODIS卫星数据构建印巴地区归一化植被指数-陆地表面温度的特征空间,拟合特征空间中的干、湿边方程,进一步反演温度植被干旱指数,对该区土地利用和地形作了统计与分析,对温度植被干旱指数划分等级,并利用印巴气象站点的实测降水量以及标准降水指数进行验证。结果表明:1)从干旱等级面积统计来看,印巴地区干季主要以中旱为主,其他等级面积所占比例较小;2)从土地利用类型来看,全区土地覆盖良好,温度植被干旱指数作为印巴地区旱情评价指标具有一定的合理性;3)从气象站点数据来看,归一化植被指数-陆地表面温度特征空间反演的温度植被干旱指数与降水具有密切相关性。     

农业干旱遥感监测业务化运行方法研究

研究一种基于MODIS遥感数据的快速且易于实际应用的农业旱情监测方法及其系统实现。监测方法基于植被供水指数的思想,利用NDVI进行植被盖度分级来计算,标准化作物供水指数,再耦合近8旬的综合降水距平指数,由此实现对旱情的监测。在介绍监测方法的同时,又针对应用数据的特点,设计了有效的数据管理系统,为高效管理各种数据而服务。     

仪征地区农田深层土壤湿度遥感反演初探

利用MODIS合成产品数据MOD11A2和MOD13A2获取的陆地表面温度(Ts)和归一化植被指数(NDVI)构建Ts/NDVI特征空间,依据该特征空间计算温度植被干旱指数(TVDI),进而反演了仪征地区不同季节的40 cm土壤相对湿度。使用野外同步实测数据进行验证,结果显示,总体平均相对误差为11.83%,2004年11月误差最小,为4.30%。遥感反演的仪征地区土壤湿度分布图表明该地区存在两个土壤湿度高值区,分别位于仪征南部的长江冲积平原和西北部的谷底平原地带,并且土壤平均相对湿度越大,其高值区与低值区之间的差异越小。     

旱灾灾情监测中的遥感应用综述

旱灾是我国影响范围最广的农业自然灾害。遥感是对干旱进行大面积、实时动态监测的有效技术手段。对遥感技术在干旱旱情监测中的传统方法进行了概括和汇总,应用较多的干旱旱情遥感监测方法主要有热惯量法、蒸散法、植被指数法,其中植被指数法又分为距平植被指数、条件植被指数、植被指数差异、植被供水指数、温度植被干旱指数等方法。分析了不同方法的优缺点以及它们各自的适用范围,结合当前研究的热点问题,指出随着干旱机理和MODIS数据的应用,干旱旱情的遥感监测将得到更广泛、更深入的应用。     

海南岛干旱特征遥感识别及时空变化研究

海南岛是我国重要的湿热带宝地，受自然地理环境和条件等因素影响，岛上干旱频发，旱涝严重，对农业生产和人民生活造成了重大的经济损失。基于MODIS数据，计算了归一化植被指数NDVI和陆地表面温度LST，进而构建了植被供水指数模型VSWI，分析了海南岛2004—2020年干旱特征和时空变化分布演变规律，结论如下：①2004—2020年期间海南岛以2004、2005、2010、2015年整体干旱偏严重，2005年海南岛旱情最为严重，干旱面积分布可达总面积的56.76%，其中重旱、中旱、轻旱所占的面积比例分别为7.37%、20.75%、28.64%，旱情影响较为广泛。②海南岛VSWI年内指数变化整体呈现先减小后增加的单峰型趋势，1—5月呈下降趋势，干旱随着时间推移不断加重，4月和5月旱情达到高峰，6—12月受气候因素影响干旱略有缓解。2005年5月旱情最为严重，整个区域的84.27%均处于不同程度的干旱，受灾严重区域集中在西南部地区，儋州市受灾最为严重，特旱面积可达35.57%，无旱面积仅为2.31%，空间范围上广泛受灾。③受地理因子和气候因素影响，不同土地利用类型年内VSWI值变化趋于一致，林地和草地受干旱影响程度较轻，耕地和城镇因植被稀疏受干旱影响较强，月均值最小值皆在4月。④2004—2020年海南岛VSWI空间分布具有明显的季节性差异，海南岛主要以冬旱和春旱为主，夏旱和秋旱也时有发生，各市县干旱具有明显的地域差异和季节差异，沿海重于内陆，四周重于中间，南部重于北部，西部重于南部。⑤海南岛VSWI与降雨和气温因子关系较为密切，其中降雨与植被供水指数VSWI的相关性最高，且降雨因子影响所占的面积比例较大，因此，海南岛干旱主要受气象因子降雨的影响。研究结果可以为海南岛干旱预警提供参考依据。     

Soil moisture retrieval from MODIS data in Northern China Plain using thermal inertia model

Soil moisture plays an important role in surface energy balances, regional runoff, potential drought and crop yield. Early detection of potential drought or flood is important for the local government and people to take actions to protect their crop. Traditionally measurement of soil moisture is a time‐consuming job and only limited samples could be collected. Many problems would be results from extending those point measurements to 2D space, especially for a regional area with heterogeneous soil characteristics. The emergency of remote‐sensing technology makes it possible to rapidly monitor soil moisture on a regional scale. Thermal inertia represents the ability of a material to conduct and store heat, and in the context of planetary science, it is a measure of the subsurface's ability to store heat during the day and reradiate it during the night. One major application of thermal inertia is to monitor soil moisture. In this paper, a thermal inertia model was developed to be suitable in situations whether or not the satellite overpass time coincides with the local maximum and minimum temperature time. Besides, the sensibilities of thermal inertia with surface albedo and the surface temperature difference were discussed. It shows that the surface temperature difference has more effects on the thermal inertia than the surface albedo. When the temperature difference is less than 10 Kelvin degrees, 1 Kelvin degree error of temperature difference will lead to a big fluctuation of thermal inertia. When the temperature difference is more than 10 Kelvin degrees, 1 Kelvin degree error of temperature difference will cause a small change of thermal inertia. The temperature difference should be larger than 10 Kelvin degrees when the thermal inertia model is selected to derive soil moisture or other applications. Based on this thermal inertia model, the soil moisture map was obtained for North China Plain. It shows that the averaged difference between the soil moisture values derived from MODIS data and in situ measured soil moisture data is 4.32%. This model is promising for monitoring soil moisture on a large regional scale.     

重庆市墒情分析评价预测系统的设计与实现

结合重庆市墒情、水雨情等自动监测系统,考虑主要作物种类、分布区域、播种面积、耕作制度、生育期间各生长发育指标,以及不同区域、深度的田间持水量,对已建立土壤墒情监测点的地区,采用土壤相对湿度评估农业墒情;对于尚未建立墒情监测站但已建立雨量监测站点的雨养农业区,采用降水量距平法或连续无雨日数法,进行墒情分析评价,用衰减系数法预测墒情的变化趋势。采用B/S开发模式,利用Flex通过天地图在线服务进行地图显示,采取IIS发布模式,基于Web Services的数据服务模式,设计一套基于Web GIS的墒情监测分析评价预测系统,通过相关评价指标反映农林作物土壤的干旱情况,并能结合天气情况预测未来墒情数据,为安排农业用水提供技术支撑,减少干旱灾害损失。     

Assessing vegetation response to drought in the northern Great Plains using vegetation and drought indices

The Normalized Difference Vegetation Index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR) has been widely used to monitor moisture-related vegetation condition. The relationship between vegetation vigor and moisture availability, however, is complex and has not been adequately studied with satellite sensor data. To better understand this relationship, an analysis was conducted on time series of monthly NDVI (1989-2000) during the growing season in the north and central U.S. Great Plains. The NDVI was correlated to the Standardized Precipitation Index (SPI), a multiple-time scale meteorological-drought index based on precipitation. The 3-month SPI was found to have the best correlation with the NDVI, indicating lag and cumulative effects of precipitation on vegetation, but the correlation between NDVI and SPI varies significantly between months. The highest correlations occurred during the middle of the growing season, and lower correlations were noted at the beginning and end of the growing season in most of the area. A regression model with seasonal dummy variables reveals that the relationship between the NDVI and SPI is significant in both grasslands and croplands, if this seasonal effect is taken into account. Spatially, the best NDVI-SPI relationship occurred in areas with low soil water-holding capacity. Our most important finding is that NDVI is an effective indicator of vegetation-moisture condition, but seasonal timing should be taken into consideration when monitoring drought with the NDVI.     

Comparison of remotely sensed and meteorological data-derived drought indices in mid-eastern China

Numerous drought indices have been developed and applied to monitor the severity of drought. It has been demonstrated that the evaluation of the indices is very important for further utilization of remotely sensed and meteorological information. The objective of this article is to investigate and compare the different methods derived from satellite/meteorological data for drought monitoring during the typical dry year (2006) in mid-eastern China. The compared six drought indices include the vegetation condition index (VCI), percent of average seasonal greenness (PASG), temperature condition index (TCI), vegetation supply water index (VSWI), percentage of precipitation anomalies (PPA) and standardized precipitation index (SPI). These indices are calculated based on different data sources including reflective data, thermal data, the combination of reflective and thermal data and meteorological data. The correlation matrix and regression relationships among the integrals under all drought indices, the integral under the relative air humidity (RAH) curve and cumulative rainfall at the location of 11 agro-meteorological stations for 2006 were calculated. Spatial comparison analysis among the drought indices reveals that all the indices have certain coincidence in the detected regional-scale distribution of drought especially those derived from the same data set, while obviously local-scale distribution differences were found among the different groups of indices. Compared to curves of the reflective and thermal indices, the overall trend of VSWI series has better consistence with the PPA curve. Based on correlation and regression analysis, it is demonstrated that VSWI can better reflect both the amount of precipitation and the severity of drought due to lack of rainfall. Furthermore, land surface temperature (LST) contributes more to the result of hybrid index (VSWI) than reflective information. There is logarithmic relationship between integral of VSWI and cumulative precipitation, while obvious linear correlations were found between integral under VSWI curve and integral under the RAH/TCI/PASG curves. According to the filed observation of droughts from agro-meteorological stations in the study area, it can be concluded that any single index is not sufficient to precisely depicting drought characteristics. The combined use of different indices at the same time or indices which integrate various sources of information may obtain more consistent results with the actual situation.     

Drought monitoring of the wetland in the Tumen River Basin between 1991 and 2016 using Landsat TM/ETM+

Wetland areas are known as ‘the kidneys of the Earth’ because they provide important functions towards stabilizing the environment, long-term protection of water sources, effectively minimizing sediment loss, purifying surface water from industrial and agricultural pollutants, and enhancing aquifer recharge. The condition of water supply in wetlands directly affects the growth of wetland plants and local biodiversity. Therefore, drought monitoring is vital in wetlands. In this study, Vegetation Temperature Condition Index (VTCI) derived from normalized difference vegetation index (NDVI) and land surface temperature (LST) is used to observe the drought status of the wetland in the cross-border (China and North Korea) Tumen River Basin from 1991 to 2016. For this purpose, the Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) data for six periods were used for the analysis. Soil moisture maps acquired from the China Meteorological Administration Land Data Assimilation System Version 1.0 (CLDAS-V1.0) were then introduced for validating the reliability of the drought monitoring method. The results showed that most areas with a normal moisture level (decreased 25.8%) began experiencing slight drought (increased 29.7%). The coefficient of determination (R²) between VTCI and soil moisture showed values of 0.69, 0.32, and 0.2 for 0–5 cm, 0–10 cm, and 10–20 cm thicknesses, respectively. Although climate change probably contributes to the formation of drought by decreasing precipitation (50 mm decrease in Chinese section) and increasing temperature (0.5°C increase in North Korean section), human activities such as surges in daily water consumption appear as the main threats that leading to droughts in this wetland.     

利用遥感和GIS监测旱情的方法研究

主要以山东，河南两省为例，探讨了利用ＮＯＡＡ／ＡＶＨＲＲ图像资料监测大面积表的几种研究方法，并对每种方法的优缺点进行了评估。结果表明，几种方法结合使用并借助地理信息系统，进行大面积的旱情监测是可行的，另外还进行了利用机载雷达图像监测河北省土壤水分的方法尝试研究，分析表明微波遥感监测土壤水分具有广阔的应用前景，可以利用星载ＳＡＲ图像资料作进一步的分析研究，从而获取微波监测土壤水分的最佳波段和最佳极化     

基于CCI土壤水分产品的干旱指数精度评价及其对东北地区粮食产量的影响

土壤水分是监测作物旱情的基本因子,以欧空局1978~2014年微波遥感土壤水分产品、中国经济与社会发展统计数据库以及气象数据为基础,结合土壤水分亏缺指数（Soil Water Deficit Index, SWDI）分析东北地区的干旱程度与玉米亩产的关系。结果表明：①东北三省干旱程度空间上呈现自东北向西南逐渐加重的空间分布模式;②基于CCI (Climate Change Initiative)土壤水分产品计算的SWDI干旱指数与降雨量和气温有良好的相关关系,可用于评估干旱发生的严重程度;③玉米生长季关键需水期——7月的SWDI与玉米产量的相关性最好,二者在黑龙江、吉林和辽宁省的R2分别为0.43、0.78和0.38,非常适合用于评估干旱对玉米单产的影响。该结论对于研究大范围土壤水分含量对农作物产量的影响以及相关农业决策具有重要指导意义。     

Precision Evaluation of Drought Index based on CCI Soil Moisture Products and Its Effect on Grain Yield in Northeast China

Soil moisture is the basic factor for monitoring crop drought. Based on the microwave remote sensing soil moisture products of ESA from 1978 to 2014, the statistical database of China's economic and social development and meteorological data, combined with the Soil Moisture Deficit Index (SWDI), the relationship between the degree of drought in Northeast China and corn yield was analyzed. The results show that: (1) the drought level of the three provinces is increasing from northeast to southwest; (2) the SWDI drought index calculated based on CCI (Climate Change Initiative) soil moisture products has a good correlation with rainfall and temperature, which can be used to evaluate the severity of drought; (3) the correlation between SWDI and maize yield is the best in the key water demand period (July), and R2 of Heilongjiang, Jilin and Liaoning provinces are 0.43, 0.78 and 0.38 respectively, which is very suitable for quantifying the effect of drought on maize yield. This conclusion has important guiding significance for the study of the influence of soil moisture content on crop yield and the relevant agricultural decision-making.     

“衡邵干旱走廊”土壤墒情自动监测系统研究

旱灾是湖南省各类自然灾害中最主要的自然灾害之一,基于湖南省抗旱体系不完善,旱情信息来源少、监测技术手段落后等问题,确定以湖南省常年旱情较为严重的"衡邵干旱走廊"为典型研究区域,对土壤墒情自动监测系统进行研究。在研究过程中,采用现代数据采集技术,成功解决土壤墒情信息的自动采集、传输、存储和处理等关键技术问题。在土壤水分传感器性能综合比选、墒情站设计和实施方面积累宝贵经验,为今后抗旱减灾工作提供技术指导。