共查询到18条相似文献，搜索用时 109 毫秒
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改进的表观热惯量法反演土壤含水量 总被引：4，自引：0，他引：4
提出一种改进的表观热惯量计算模型,以中科院栾城农业生态系统试验站为基地,通过实测的模型参数,利用提出的表观热惯量模型计算不同植被覆盖下、不同实验区土壤含水量的热惯量值,并与土壤含水量进行相关性分析,以找到热惯量方法可以用来反演土壤含水量的适用条件(归一化植被指数NDVI的阈值).实验结果表明,该模型监测土壤含水量是可行的,在植被覆盖度较低的情况下(NDVI≤O.35)具有较高的精度,在植被覆盖度较高(NDVI＞0.35)时,热惯量模型失效,因此用热惯量方法反演土壤含水量植被覆盖时将NDVI阈值的最大值设为0.35.将该方法应用到MODIS数据中,以河北省栾城县、赵县、藁城市3市县为研究区,分别反演该区土壤含水量,反演结果与实际情况相符合.实地取点人工监测土壤含水量为25.1％,栾城站模型计算结果为22.4％,匹配性较好,该方法在遥感数据中得到了很好的应用. 相似文献
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为了更好地研究内蒙古额济纳盆地的土壤水分时空分布及动态变化,基于MODIS数据,利用热惯量模型,计算了表观热惯量,并与实测数据进行回归分析建模,反演了内蒙古额济纳盆地的土壤水分。结果表明,利用MODIS数据产品,反演参量获取简单,可降低反演土壤含水量的复杂性,有利于大、中尺度的实际应用;砂土对应的表观热惯量均值较大,粘土次之,壤土最小;相比粘土,壤土和砂土的表观热惯量值比较大且分散;绿洲区表观热惯量值比戈壁和沙漠区大;热惯量模型在20 cm左右深度土壤水分反演效果最好,可有效反演干旱区土壤水分。 相似文献
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热惯量法在监测土壤表层水分变化中的研究 总被引：95，自引：2，他引：95
利用遥感方法监测一定层水深土壤水分变化，关键是建立卫星数据与地表水热变化关系，该文地遥感定量反演土壤水热变化的数值模拟系统及热惯量在其边界，初始条件确定中所起的作用进行的简述，并介绍了热惯量法求解表层水分含量的发展概况，为进一步提高定量化监测方法的地必琢计算精度，该文发展了地表能量平均方程的一种新的化简方法，经过这样的处理，可从遥感图象数据直接得到真实热惯量值，进而得到土壤水分含量分布，通过野外实 相似文献
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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
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土壤水分的遥感监测方法 总被引：4，自引：0，他引：4
本文讨论了用雷达图像散射系数法、NOAA-AVHRR数字图像热惯量法和作物缺水指数法监测土壤水分的结果,并将这些方法与常规气象方法、绿度指数法和温差法监测土壤水分的效果进行了比较和评价。结果表明,微波遥感监测土壤水分有广阔的应用前景,但必须深入开展基础研究。在我国目前情况下,采用NOAA-AVHRR数字图像及有关气象数据计算热惯量、作物蒸散和缺水指数,从而估算土壤水分的方法是一种比较切实可行的方法。 相似文献
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《国土资源遥感》2021,(2)
为进一步研究风云三号(FY-3B)土壤水分降尺度获取高分辨率土壤水分的方法,使其更适用于农业、水文、生态等区域尺度的应用要求,以MODIS为数据源,青藏高原那曲地区为研究区,利用表观热惯量模型(apparent thermal inertia,ATI)与温度植被指数(temperature vegetation index,TVI)模型在不同植被覆盖度下适用的特点,构建综合ATI与TVI的土壤水分反演模型;结合低分辨率FY-3B土壤水分产品,利用土壤水分降尺度方法,获取高分辨率下土壤水分反演模型系数,并得到高分辨率土壤水分。通过与地面观测数据对比,降尺度后土壤水分与实测数据的R~2在0.4以上,RMSE在0.055～0.103 cm~3/cm~3之间,表明降尺度后的土壤水分能够较好地反映区域土壤水分的空间分布与变化。 相似文献
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旱情遥感监测研究进展与应用案例分析 总被引：3，自引：2，他引：1
在大范围、长时序的旱情监测中,遥感技术以其快速、经济和大空间范围获取的特点,弥补了基于台站气象数据旱情监测的不足,为防旱和抗旱决策提供了实时、动态、宏观的辅助决策数据。本文对已有旱情遥感监测方法进行分析和整理,将其总结为基于土壤热惯量、基于土壤波谱特征、基于蒸散模型和基于植被指数的旱情监测方法,并对各类方法从监测原理、适用范围和应用进展等方面进行了阐述。在此基础之上,详细介绍一种结合了全球植被水分指数和短波角度归一化指数的优势建立的旱情遥感监测模型和方法。以2010年春季西南地区旱情为应用案例,从监测模型方法、数据处理流程和应用分析等方面,介绍一种基于植被水分指数的旱情监测方法,并对其监测结果进行统计分析与评价。 相似文献
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《国土资源遥感》2017,(2)
以辽西北为研究区域,选取典型干旱年2009年作物(春玉米)主要生长季,采用表观热惯量(apparent thermal inertia,ATI)、距平植被指数(anomalies of vegetation index,AVI)和植被供水指数(vegetation supply water index,VSWI)3种基于不同理论的遥感干旱指数方法对土壤水分进行反演,分析其监测效果。结果表明,3种指数分别在一定程度上反映出了辽西北地区2009年的旱情趋势,但得到的反演结果并不一致;ATI在中高植被覆盖率下的监测效果高于预期结果,比较符合历史气象资料;AVI可以有效反映当年作物主要生长季各时期相对的受旱状况;VSWI夸大了植被的影响作用,存在严重的滞后性。 相似文献
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地表土壤水分含量的时空分布信息是十分重要的,常常作为水文模型、气候模型、生态模型的输入参数,同时,也是干旱预报、农作物估产等工作的重要指标。被动微波遥感是监测土壤含水量最有效的手段之一。相比红外与可见光,它具有波长长,穿透能力强的优势。相比主动微波雷达,被动微波辐射计具有监测面积大、周期短,受粗糙度影响小,对土壤水分更为敏感,算法更为成熟的优势。目前,已研究出许多反演土壤水分的方法.本课题的主要内容是借助AMSR-E土壤水分影像数据、MODIS归一化植被指数(NDVI)影像数据和MODIS分类影像数据,利用ENVI软件进行遥感图像数据处理,运用统计分析方法建立NDVI与土壤水分的经验模型,研究中国西部地区稀疏植被覆盖区土壤水分的反演。 相似文献
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基于混合像元的方法,利用ERS风散射计(WSC)数据估算植被覆盖率和同时期NDVI有较高的相关性(0.78),计算出的垂直入射菲涅耳反射系数的空间分布状况也比较合理。 相似文献
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Ankita Jain 《国际地球制图》2017,32(9):1017-1033
Estimation of vegetation covered soil moisture with satellite images is still a challenging task. Several models are available for soil moisture retrieval in which water cloud model (WCM) is most common. But, it requires an estimation of accurate vegetation parameterization. Thus, there is a need to develop such an approach for soil moisture retrieval which minimize these limitations. Therefore, this paper deals with the soil moisture retrieval using fully polarimetric SAR data by fusing the information from different bands. Various polarimetric indices and observables were critically analysed, and found that the index; SPAN (total scattered power) gives better information of vegetation cover as compared to other indices/observables. Based on this, WCM model has been modified using SPAN as parameter and soil moisture content were retrieved. 相似文献
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Intercomparison of two trapezoid-based soil moisture downscaling methods using three scaling factors
This paper compared two soil moisture downscaling methods using three scaling factors. Level 3 soil moisture product of advanced microwave scanning radiometer for EOS (AMSR-E) is downscaled from 25 to 1?km. The downscaled results are compared with the soil moisture observations from polarimetric scanning radiometer (PSR) microwave radiometer and field sampling. The results show that (1) the scaling factor of normalized soil thermal inertia (NSTIs) and vegetation temperature condition index (VTCI) are better than soil evaporative efficiency in reflecting soil moisture; (2) for method 1, NSTIS is the best in the downscaling of soil moisture. For method 2, VTCI is the best; (3) no significant differences of the correlation coefficients (R2) and the biases were found between the two methods for the same scaling factors. However, method 2 shows a better potential than method 1 in the time-series applications of the downscaling of soil moisture; (4) compared with the relationship between the area-averaged soil moisture of AMSR-E and that of PSR, R2 of the 6 sets of the downscaled soil moisture almost do not decrease, which suggests the validity of the downscaling of soil moisture with the two downscaling methods using the three scaling factors. 相似文献
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Influence of surface and vegetation characteristics on C-band radar measurements for soil moisture content 总被引：1，自引：0，他引：1
Shakil Ahmad Romshoo Masahiro Koike Sadayukihir Onaka Taikan Oki Katumi Musiake 《Journal of the Indian Society of Remote Sensing》2002,30(4):229-244
Soil moisture estimation using microwave remote sensing faces challenges of the segregation of influences mainly from roughness and vegetation. Under static surface conditions, it was found that Radarsat C-band SAR shows reasonably good correlation and sensitivity with changing soil moisture. Dynamic surface and vegetation conditions are supposed to result in a substantial reduction in radar sensitivity to soil moisture. A C-band scatterometer system (5.2 GHz) with a multi-polarization and multi-angular configuration was used 12 times to sense the soil moisture over a tall vegetated grass field. A score of vegetation and soil parameters were recorded on every occasion of the experiment. Three radar backscattering models Viz., Integral Equation Model (IEM), an empirical model and a volume scattering model, have been used to predict the backscattering phenomena. The volume scattering model, using the Distorted Born Approximation, is found to predict the backscattering phenomena reasonably well. But the surface scattering models are expectedly found to be inadequate for the purpose. The temporal variation of soil moisture does show good empirical relationship with the observed radar backscattering. But as the vegetation biomass increases, the radar shows higher sensitivity to the vegetation parameters compared to surface characteristics. A sensitivity analysis of the volume scattering model for all the parameters also reveals that the radar is more sensitive to plant parameters under high biomass conditions, particularly vegetation water content, but the sensitivity to surface characteristics, particularly to soil moisture, is also appreciable. 相似文献
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A. Brosinsky A. Lausch D. Doktor C. Salbach I. Merbach S. Gwillym-Margianto M. Pause 《Journal of the Indian Society of Remote Sensing》2014,42(2):311-324
The assessment and quantification of spatio-temporal soil characteristics and moisture patterns are important parameters in the monitoring and modeling of soil landscapes. Remote-sensing techniques can be applied to characterize and quantify soil moisture patterns, but only when dealing with bare soil. For soils with vegetation, it is only possible to quantify soil-moisture characteristics through indirect vegetation indicators, i.e. the “vitality” of plants. The “vitality” of vegetation is a sum of many indicators, whereby different stress factors can induce similar changes to the biochemical and physiological characteristics of plants. Analysis of the cause and effect of soil-moisture properties, patterns and stress factors can therefore only be carried out using an experimental approach that specifically separates the causes. The study describes an experimental approach and the results from using an imaging hyperspectral sensor AISA-EAGLE (400–970 nm) and a non-imaging spectral sensor ASD (400–2,500 nm) under controlled and comparable conditions in a laboratory to study the spectral response compared to biochemical and biophysical vegetation parameters (“vitality”) as a function of soil moisture characteristics over the entire blooming period of Ash trees. At the same time that measurements were taken from the hyperspectral sensors, the following vegetation variables were also recorded: leaf area index (LAI), chlorophyll meter value — SPAD-205, vegetation height, C/N content and leaf water content as indicators of the “vitality” and the state of the vegetation. The spectrum of each hyperspectral image was used to calculate a range of vegetation indices (VI’s) with relationships for soil moisture characteristics and stress factors. The relationship between vegetation indices and plant “vitality” indicators was analysed using a Generalized Additive Model (GAM). The results show that leaf water content is the most appropriate vegetation indicator for assessing the “vitality” of vegetation. With the Water Index (WI) it was possible to differentiate between the moisture treatments of the control, moisture drought stress and the moisture flooding treatment over the entire growing season of the plants (R 2?=?0.94). There is a correlation between the “vitality” vegetation parameters (LAI, C/N content and vegetation height) and the indicators NDVI, WI, PRI and Vog2. In our study with Ash trees the vegetation parameter chlorophyll was found not to be a suitable indicator for detecting the “vitality” of plants using the spectral indicators. There is a possibility that the sensitivity of the indicators selected was too low compared to changes in the chlorophyll content of Ash trees. Adding the co-variable ‘time’ strengthens the correlation, whereas incorporating time and moisture treatment only improves the model very slightly. This shows that changes to the biochemical and biophysical characteristics caused by phenology, overlay a differentiation of the moisture treatments. 相似文献
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遥感监测土壤湿度综述及其在新疆的应用展望 总被引：3，自引：1，他引：2
土壤湿度在全球水循环运动中扮演着非常重要的角色,是水文、气象和农业研究中的重要参数,国内外都极为重视对土壤湿度的研究。国外利用可见光、红外、热红外、微波遥感监测土壤水分已有三、四十年的历史,随着研究的深入和技术的发展,现已形成地面、航空、航天、多星的立体干旱遥感监测格局。国内遥感监测土壤湿度的方法主要有微波遥感、热红外遥感、距平植被指数法、植被供水指数、作物缺水指数等方法。本文通过对国内外已有的土壤湿度遥感监测方法的介绍和总结,对比分析了各种方法的原理、适用领域及其研究进展,并针对新疆的具体情况,认为借助Mod is影像进行新疆地区土壤湿度的监测是较为可行的一种方法。 相似文献
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利用GPS信噪比（signal-to-noise ratio,SNR）观测值监测土壤湿度的精度直接受多径干涉相位与土壤湿度间的关系模型影响。传统方法基于线性模型,通过增加样本数量、排除特例提高普适性,但未合理考虑坡度、植被及天气等因素。基于上述因素短期变化可忽略的假设,引入时间窗口,采用自相关分析确定窗口长度,利用窗口内样本动态线性回归构建预测和插值模型反演土壤湿度。实验结果表明,引入窗口后,预测、插值误差分别下降17.4%和54.6%,相关系数上升16.2%和32.9%。插值模型利用了待估时刻之后的观测量,精度更高;预测模型精度略低,但更适于实时应用。同时,残差极大值与土壤湿度的上升之间显著相关。预测残差较土壤湿度具有极大值更小、时刻略微提前的时域特征。 相似文献