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1.
水平和垂直尺度乔、灌、草覆盖度遥感提取研究进展 总被引：10，自引：0，他引：10
植被覆盖及其变化是区域生态系统环境变化的重要指示,而植被覆盖度是植物群落覆盖地表状况的一个综合量化指标,是生态模型、碳循环、水循环模型等的重要特征参量。传统的植被覆盖度是指一定尺度下所有植被(乔、灌、草)覆盖的综合反映值,当考虑植被垂直方向的异质性,垂直尺度的乔、灌、草覆盖度提取为定量化准确衡量生态环境、全球气候变化等领域提供更具有生态意义的植被参量。目前,遥感大面积估算水平尺度乔、灌、草覆盖度已有比较成熟和可靠的算法,主要方法有：植被指数法、回归分析法、分类决策树法、神经网络法、像元分解模型法、物理模型反演法等,其估算精度基本能达到应用要求。植被垂直方向的异质性给垂直尺度乔、灌、草覆盖度遥感提取带来较大挑战,垂直尺度上的乔、灌、草覆盖度遥感提取的研究在欧美等国已经有了一定规模的开展,在国内则处于起步阶段。遥感提取垂直尺度乔、灌、草覆盖度的主要手段有：激光雷达（LIDAR）、多角度遥感以及两层结构冠层反射模型反演。综述了水平尺度和垂直尺度上乔、灌、草覆盖度遥感提取的最新进展,比较和分析主要的遥感提取方法、模型和现存的一些问题,并对未来的研究发展趋势进行了展望。 相似文献
2.
As wheat represents the main staple food and strategic crop in Egypt and worldwide and since remote sensing satellite imagery is the tool to obtain synoptic, multi-temporal, dynamic, and time-efficient information about any target on the Earth, the main objective of the current study is to use remote sensing satellite imagery to generate remotely sensed empirical preharvest wheat yield prediction models. The main input parameters of these models are spectral data either in the form of spectral reflectance data released from Satellite Pour l’Observation de la Terre (SPOT) 4 satellite imagery or in the form of spectral vegetation indices. The other input factor is leaf area index (LAI) that was measured by LAI Plant Canopy Analyzer. The four spectral bands of SPOT4 imagery are green, red, near-infrared, and middle infrared; the five vegetation indices that are forms of ratios between red and near-infrared bands are normalized difference vegetation index, ratio vegetation index, soil-adjusted vegetation index, difference vegetation index, and infrared percentage vegetation index. Another vegetation index is green vegetation index that is calculated through a ratio between green band and near-infrared band. Each of the above-mentioned factors was used as an input factor against wheat yield to generate wheat yield prediction models. All generated models are site-specific limited to the area and the environment and could be applicable under similar conditions in Egypt. The study was carried out in Sakha experimental station by using the dataset from two wheat season 2007/2008 and 2009/2010. The total wheat area was 1.3 ha cultivated by Sakha 93 cultivar. Modeling and validation process were carried out for each season independently. Modeled yield was tested against reported yield through two common statistical tests; the standard error of estimate between modeled yield and reported yield, and the correlation coefficient for a direct regression analysis between modeled and reported yield with each generated model. Generally, as shown from the correlation coefficient of the generated models, green and middle infrared bands did not show good accuracy to predict wheat yield, while the other spectral bands (red and near-infrared) bands showed high accuracy and sufficiency to predict yield. This was proven through the correlation coefficient of the generated models and through the generated models with the wheat crops for the two seasons. Accordingly, the green vegetation index that is generally calculated from green and near-infrared bands showed relatively lower accuracy than the rest of the vegetation index models that are calculated from red and near-infrared bands. LAI showed high accuracy to predict yield as shown from the statistical analysis. The models are applicable after 90 days from sowing stage and applicable in similar regions with the same conditions. 相似文献
3.
以新疆喀纳斯自然保护区为研究区, 评价了HJ-CCD影像数据估算植被叶面积指数(LAI)的能力及其对大气订正方法的敏感性.分别利用6S和FLAASH两种大气订正模型对HJ1B-CCD2影像进行大气订正, 比较了大气订正前后不同植被(针叶林、阔叶林、针阔混交林和草地)反射率及5种植被指数(NDVI、SR、SAVI、MSR、ARVI)的变化, 进而建立了4种植被类型LAI的遥感估算模型, 分析了LAI的空间分布格局.结果表明: 大气订正后可见光波段的反射率降低, 6S模型订正后近红外波段的反射率上升, 而FLAASH模型订正后近红外波段的反射率下降.大气订正后NDVI、SR、SAVI(除针叶林)和MSR上升, 6S模型订正后所有植被类型的ARVI下降, FLAASH模型订正后针叶林和阔叶林的ARVI上升, 而针阔混交林和草地的ARVI下降.大气订正提高了植被指数与LAI之间的相关性, 对于针叶林、阔叶林、针阔混交林而言, 利用6S模型订正后的反射率建立的模型优于FLAASH模型订正后的反射率建立的模型, 而草地却相反.经过大气订正, HJ-CCD影像数据可应用于研究区植被LAI的估算.研究区LAI的高值集中在湖泊和河流附近, 低值分布在海拔较高处.山地森林草原带、亚高山森林带、高山灌丛草甸带、高山冻原、高山冰川带植被LAI的平均值分别为2.6、3.9、2.5、1.7和1.0. 相似文献
4.
两种用于作物冠层叶绿素含量提取的改进光谱指数 总被引：1，自引：0，他引：1
在深入探讨目前广泛使用的提取叶绿素含量的植被指数的光谱响应机制基础上,利用PROSPECT+SAIL模型模拟的作物冠层反射率样本数据对比分析了这些植被指数对叶绿素含量变化的敏感性差异,包括PSSRa、PSSRb、PSNDa、PSNDb、NPCI、PRI、MCARI和TVI等.结果表明,上述植被指数或对土壤背景变化敏感,或受高值LAI影响趋于饱和,对作物叶绿素含量反演效果均不理想.提出了4种基于TVI和MCARI的改进植被指数MTVI1、MTVI2、MCARI1和MCARI2,揭示了它们对土壤背景和LAI不敏感,对叶绿素含量变化更为敏感的光谱机制,并根据实验数据对其进行验证.实验表明,改进的植被指数MTVI2和MCARI2是作物冠层叶绿素含量较好的预测器,可据此建立作物冠层叶绿素含量反演模型. 相似文献
5.
The relationship between drought activity and vegetation cover in Northwest China from 1982 to 2013 总被引：1，自引：0，他引：1
Yelin Jiang Ranghui Wang Qing Peng Xiaoquan Wu Husen Ning Cheng Li 《Natural Hazards》2018,92(1):145-163
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. 相似文献
6.
Guilin Liu 《Arabian Journal of Geosciences》2016,9(9):541
Irrigation is critical for oasis agriculture in Alar irrigated region, Northwestern China. The reference evapotranspiration (ET0) estimation using a modified Penman-Monteith method recommended by FAO is a baseline for rational irrigation scheduling. Thus, crop coefficients (Kc) were estimated using a ratio between reference and observed evapotranspiration. Then, we analyzed the relationship between temporal crop coefficients (Kc) and synchronized normalized difference vegetation index (NDVI) derived from multi-temporal remotely sensed images. The results showed that reference evapotranspiration increased from spring to summer hereafter decreased gradually to winter with the peak of ET0 ranging from 8 to 9 mm/day. A closely linear relation between NDVI and Kc of cotton was finally acquired with a coefficient of determination of 0.94. An acceptable accuracy of this model by comparing observed and simulated evapotranspiration illustrated the credibility of this model. This paper provides a scientific approach to estimate regional crop coefficient and evapotranspiration. 相似文献
7.
8.
基于植被指数和土地表面温度的干旱监测模型 总被引：79，自引：4，他引：79
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。 相似文献
9.
Identifying effective vegetation biophysical and spectral parameters for investigating light to moderate grazing effects on grasslands improves management practices on grasslands. Using mixed grasslands as a case study, this paper compares responses of vegetation biophysical properties and spectral parameters derived from satellite images to grazing intensity, and identifies the suitable biophysical and spectral parameters to detect grazing effects in these areas. Biophysical properties including cover, canopy height and Leaf area index (LAI) were measured in three sites with different grazing managements and one benchmark site in 2008 and 2009 in Grasslands PlaceTypeNational Park and surrounding provincial pastures, Canada. Thirteen vegetation spectral indices, calculated by statistically combining different spectral information, were evaluated. The results indicate that canopy height and the ratio of photosynthetically active vegetation cover to non-photosynthetically active vegetation cover (PV/NPV) showed significant differences between ungrazed and grazed sites. All spectral vegetation indices except the canopy index (CI) show significant differences between grazing treatments. Red-Near infrared (Red-NIR) based vegetation indices, such as Modified Triangular Vegetation Index 1 (MTVI1), Soil-adjusted Vegetation Index (SAVI), are significantly correlated to the PV/NPV. Green/Mid-infrared (Green/MIR) related vegetation indices, i.e. Plant Senescence Reflectance Index (PRSI) and Normalized Canopy Index (NCI), show significant correlation with canopy height. Models based on a linear combination of MTVI1 and SAVI were developed for PV/NPV and PRSI and NCI for canopy height. Models that simulated PV/NPV and canopy height show significant correlations with grazing intensity, suggesting the feasibility of remote sensing to quantify light to moderate grazing effects in mixed grasslands. 相似文献
10.
Remotely sensed thermal infrared (TIR) data have been widely used to retrieve land surface temperature (LST). LST is an important parameter in the studies of urban thermal environment and dynamics. In the study, an attempt has been made using LANDSAT 8 thermal imagery to compute LST and the associated land cover parameters viz; land surface emissivity (LSE), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI) and normalized difference water index (NDWI). Landsat 8 TIRS band 10 & 11 (thermal bands) during 21 Oct. 2016, 22 Nov.2016, 24 Dec. 2016 and 09 Jan. 2017 were processed for LST analysis. However, band 5 & band 4 of the imagery was processed for NDVI, band 6 & band 5 for NDBI and band 2 & band 5 for NDWI analysis. LST has been derived from both the bands 10 &11 and validated by in-situ observations on the date and time of satellite overpass from the study area. Band 10 derived LST have shown much temperature difference while comparing with the in-situ observations. However, LST derived from band 11 found similar & close to the in-situ measurements. Relationship between band 11 results and in-situ observed measurements were developed, which has showing a strong correlation with (r2 = 0.991). Land surface emissivity were also evaluated which shows variation in different land cover surfaces like vegetation, settlement, forest cover and water body. The study has proven that land surface temperature derived from satellite band 11 is the actual surface temperature of the study area. 相似文献
11.
Integration of vegetation processes in rain–runoff (RR) models significantly affects runoff response by influencing evapotranspiration in mesoscale catchments. However, it is impossible to interpret the impacts of vegetation processes on runoff simulations in macroscale catchments using results from mesoscale catchments. Few studies involved vegetation process impacts on hydrological simulations by integrating daily vegetation information into conceptual RR models of macroscale catchments. In this study, we integrated the remotely sensed leaf area index (LAI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) into a daily Distributed Time-Variant Gain Model (DTVGM). Then, this study assessed the performances of two DTVGM versions, with and without vegetation processes, in the Wei River catchment, China. The results showed that: (1) Integration of MODIS-LAI into the DTVGM model improved the calibration and runoff simulation results of the initial DTVGM model. (2) Inclusion of vegetation processes in the DTVGM changed the simulated proportions of water balance components in the hydrological model and made the simulation of water balance components more accurate. (3) The fact that inclusion of vegetation processes could improve the hydrological simulation performance of the daily conceptual RR model in the macroscale catchment was consistent with studies in mesoscale catchment. 相似文献
12.
基于计算机模拟的植物返青期遥感监测方法比较研究 总被引：10，自引：0，他引：10
植物返青期变化与气象和气候因素密切相关,已成为研究全球变化对陆地生态系统影响和反馈机理的一个重要参数。利用遥感手段及时准确地监测区域及全球尺度植物返青期变化,是当前地学、生态学研究的一个前沿课题。但是目前国内外对植物返青期遥感监测方法缺乏有效比较,还没有形成统一认识。因此,在综述植物返青期传统测量方法和遥感监测方法最新研究进展的基础上,利用计算机模拟手段,对目前常用的4种遥感监测方法（滑动平均方法、NDVI比率阈值方法、最大变化斜率方法及Logistic函数拟合方法）进行了比较研究。模拟结果表明：4种方法的返青期计算值最大相差20天,突出反映了它们在构建原理方面的差别,即滑动平均方法将NDVI突增点对应的时期作为植物返青期;NDVI比率阈值方法将最大上升斜率点对应的时期作为植物返青期;最大变化斜率方法将NDVI数据斜率角变化最大的点对应的时期作为植物返青期;Logistic函数拟合方法则将拟合曲线上曲率变化最大的点对应的时期作为植物返青期;同时,4种方法所得返青期均满足一个共同的特点,即返青期之后NDVI曲线应保持最大持续增长。该研究也表明计算机模拟技术在帮助认识和理解植物返青期遥感监测方法中的巨大潜力。 相似文献
13.
Spectral vegetation indices (VIs) are a well-known and widely used method for crop state estimation. The ability to monitor crop state by such indices is an important tool for agricultural management. Even though differences in imagery and point-based spectroscopy are obvious, their impact on crop state estimation by VIs is not well-studied. The aim of this study was to assess the performance level of the selected VIs calculated from spaceborne multispectral imagery and point-based field spectroscopy in application to crop state estimation. For this purpose, irrigated chickpea field was monitored by RapidEye satellite mission and additional measurements by field spectrometer were obtained. Estimated VIs average and coefficient of variation from each observation were compared with physical crop measurements: leaf water content, LAI and chlorophyll level. The results indicate that indices calculated from spaceborne spectral images regardless of the claimed response commonly react on phenology of the irrigated chickpea. This feature makes spaceborne spectral imagery an appropriate data source for monitoring crop development, crop water needs and yield prediction. VIs calculated from field spectrometer were sensitive for estimating pigment concentration and photosynthesis rate. Yet, a hypersensitivity of field spectral measures might lead to a very high variability (up to 69%) of the calculated values. Consequently, the high spatial variability of field spectral measurements depreciates the estimation agricultural field state by average mean only. Nevertheless, the spatial variability might have certain behavior trend, e.g., a significant increase in the active growth or stress and can be an independent feature for field state assessment. 相似文献
14.
MushtakTalibJabbar 《中国地质大学学报(英文版)》2002,13(1):58-66,94
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. 相似文献
15.
农作物遥感估产研究进展 总被引：2，自引：0，他引：2
粮食作物的丰欠对国民经济影响很大,因而通过卫星遥感手段及时获得农作物的产量与面积信息,具有重要的政治意义和经济价值。本文总结了近十几年来国内外学者在遥感单产模式和作物面积信息提取方面的研究成果,提出了它们各自存在的优缺点及今后的发展方向。 相似文献
16.
基于地表温度与植被指数特征空间反演地表参数的研究进展 总被引：6，自引：2，他引：4
遥感反演的地表温度(Ts)和植被指数(VI)构成的特征空间结合模型分析可以对显热通量、潜热通量及土壤含水量等地表参数进行估算.这种方法比较实用,且不过多地依赖地面观测数据.随着研究的深入,许多学者在Ts/VI特征空间基础上提出了更加丰富的空间变量.基于此,以不同空间变量为标准,分类介绍在Ts/VI特征空间的基础上对地表能量通量及土壤水分等参数的反演.其中包括在Ts/NDVI特征空间基础上提出温度植被干旱指数和条件植被温度指数来监测干旱;利用Ts/albedo特征空间反演蒸发比;用DSTV/VI特征空间反演蒸散量;用地气温差/植被指数特征空间反演蒸散量等.并介绍了Ts/VI特征空间与微波遥感结合反演地表含水量等相关研究的进展情况,最后提出未来研究的发展方向. 相似文献
17.
Biomass can indicate plant growth status, so it is an important index for plant growth monitoring. This paper focused on the
methodology of estimating the winter wheat biomass based on hyperspectral field data, including the LANDSAT TM and EOS MODIS
images. In order to develop the method of retrieving the wheat biomass from remote sensed data, routine field measurements
were initiated during periods when the LANDSAT satellite passed over the study region. In the course of the experiment, five
LANDSAT TM images were acquired respectively at early erecting stage, jointing stage, earring stage, flowering stage and grain-filling
stage of the winter wheat, and the wheat biomass was measured at each stage. Based on the TM and MODIS images, spectral indices
such as NDVI, RDVI, EVI, MSAVI, SIPI and NDWI were calculated. At the same time, the hyperspectral field data was used to
compute the normalized difference in spectral indices, red-edge parameters, spectral absorption, and reflection feature parameters.
Then the correlation coefficients between the wheat biomass and spectral parameters of the experiment sites were computed.
According to the correlation coefficients, the optimal spectral parameters for estimating the wheat biomass were determined.
The bestfitting method was employed to build the relationship models between the wheat biomass and the optimal spectral parameters.
Finally, the models were used to estimate the wheat biomass based on the TM and MODIS data. The maximum RMSE of estimated
biomass was 66.403 g/m2. 相似文献
18.
Image classification is one of the crucial techniques in detecting the crops from remotely sensed data. Crop identification and discrimination provide an important basis for many agricultural applications with various purposes, such as cropping pattern analysis, acreage estimation, and yield estimation. Accurate and faster estimation of crop area is very essential for projecting yearly agriculture production for deciding agriculture policies. Remote sensing is a technique that allows mapping of large areas in a fast and economical way. In many applications of remote sensing, a user is often interested in identifying the specific crop only while other classes may be of no interest. Indian Remote Sensing Satellite (IRS-P6) LISS IV sensor image of spatial resolution 5.8 m has been used to identify the sugarcane crop for the Chhapar village of Muzaffarnagar District, India. Classification of satellite data is one of the primary steps for information extraction for crop land identification. In recent years, decision tree approach to image analysis has been developed for the assessment and improvement of traditional statistically based image classification. In this study, ISODATA, MLC, and vegetation indices based decision tree approaches are used for classifying LISS IV imagery. The 11 vegetation index images have been generated for decision tree classification. All the three methods are compared and it is found that the best performance is given by the decision tree method. Vegetation indices based decision tree method for sugarcane classification, the user’s accuracy, producer’s accuracy, overall accuracy, and kappa coefficient were found 88.17, 86.59, and 87.93% and 0.86 respectively. 相似文献
19.
Spatial distributions of vegetation cover are closely related to topographical characters like slope, steepness, soil types, elevations, etc. In seismo-tectonic regions fault lines or tectonic lineaments are the most prominent surface signatures that can be reflected by vegetation distribution as tectonic displacement causes the change of topographical parameters. In the present study a part of northern Baromura hill (between 23º 42′ N to 23º49 N latitudes and 91º30 E to 91º36 E longitudes), which is considered as an active seismo-tectonic region of Tripura as well as northeast India, was selected for assessing the relationship between spatial variation of plant cover and topography. Geologically, Baromura hill is a north–south extended fold belt and formed by late Tertiary to Quaternary depositions. Evidences show that tectonic events played very important role in landform evolution of this area during the geological past. In this research an extensive fieldwork was conducted in the study area to understand the geomorphic and vegetation signatures and their environmental relationships. Various spectral resolutions of Landsat ETM+ were used for digital analysis. To analyse the vegetation character of this area digital operation was done within the spectral range 0.63–1.75 μm. Band 4 and band 3 were used for NDVI operation. Band 5 or mid-wave infrared band was classified in unsupervised mode to understand the range of plant water in the study area. Overlay operation with those operated images shows the spatial distribution pattern of vegetation cover indicates the landform condition. Three clear tectonic lineaments (faults) were detected from the digital study in on the northern part Baromura hill. Structural conditions of those fault lines were verified by geo-electrical survey during fieldwork. GPS tool was used for fixing the ground control points. Resistivity characters of the study area assessed from VES profile strongly supports that vegetation cover analysis from remotely sensed data within 0.63–1.75 μm spectral ranges can be a very useful tool for detecting surface tectonic signatures of the landform. 相似文献
20.
遥感提取植物生理参数LAI/FPAR的研究进展与应用 总被引：19，自引：2，他引：17
植物生理参数LAI/FPAR是2个重要的陆地特征参量。利用遥感光谱模型并结合地面验证是提取区域尺度的LAI/FPAR最有效的途径。提取LAI/FPAR的模型主要有光谱指数模型和辐射传输模型两类,经过精确的辐射标定和大气纠正的遥感数据可以得到较高精度的LAI/FPAR数据。影响LAI/FPAR精度的因素很多,其中主要因素是像元的异质性、植被类型和物候期等。LAI/FPAR与作物产量有更直接的关系,也是大量作物生长模型的基础,利用这些参数可以实现真实的作物产量预测,特别是开展全球尺度的单产预测。 相似文献