共查询到19条相似文献，搜索用时 796 毫秒
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遥感及其技术应用和卫星技术的发展为资源环境调查提供了丰富的信息,在经济活动中发挥着巨大作用。本文根据美国陆地资源卫星TM影像特点,分析了若尔盖县草原沙4ETM影像色调特征,同时根据草原沙化在遥感影像上的特征,建立图像解译标志,获取若尔盖县草原沙化分布和面积情况。为进一步开展四川省草原沙化调查提供技术支持,为宏观决策者实施草原沙化治理提供科学依据。 相似文献
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呼伦贝尔草原资源面积变化分析 总被引：3，自引：0，他引：3
采用先进的遥感（Remote Sensing，RS）、地理信息系统（Geographic Information System，GIS）和全球定位系统（Global Position System，GPS）手段，结合地面常规调查，依据地面样地样方资料，建立了TM、ETM影像解译标志，并与80年代1：50万草原类型图进行叠加分析，准确的获得呼伦贝尔市草原资源面积现状及变化数据，更新了80年代草原本底数据。结果表明：由于开垦及过度利用等原因，草原面积较80年代减少了134．73万hm^2，草原退化、沙化、盐渍化增加了188．51万hm^2。 相似文献
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目前对科尔沁沙化草原的治理已刻不容缓。采用围封+补播的方法治理沙化草原,已初见成效。应用3S技术,采用地面监测与遥感监测相结合的方法,对草原资源与生态环境的动态进行周期性观测与评价,为保护草原生态和加强草原建设提供科学依据。 相似文献
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野外调查是草原调查工作的基础,2013年以来,甘肃省开展了草原资源调查,采用了遥感、GIS及GPS技术与地面调查相结合的方法。本文对地面调查方法和技术流程做了阐述,对实际操作中出现的技术难点作了分析,为今后草原管理工作提供技术指导。 相似文献
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草地资源遥感调查方法的研究 总被引：1，自引：1，他引：0
七十年代以来,遥感技术发展十分迅速,它广泛地应用于地质、地理、土壤、森林、草地等多种学科。草地资源遥感调查就是利用遥感技术调查草地的数量、质量和分布,它更新了常规调查的方法和手段,缩短了调查周期,改变了草地资源图件的制图工艺和流程,提高了总体调查的准确性。新一代陆地资源卫星遥感影像的应用,明显提高了地类的可判性和判读精度,增加了各类草地面积数据的可靠性,特别是经过 TM 波段比较值处理和 TM 缨帽变换等处理后的影像,质量较高,其解译精度完全符合大面积草地资源调查的精度要求。 相似文献
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内蒙古草原荒漠化遥感监测分析 总被引：3，自引：0，他引：3
利用1988年以来的遥感资料,计算了不同时期的NDVI,同时基于遥感影像和光谱特征直接提取了土地退化指标,分析了内蒙古自治区植被覆盖宏观变化和荒漠化的情况.结果表明:历史上水草丰美的锡林郭勒、呼伦贝尔草原的植被指数呈下降趋势,尤其是呼伦贝尔沙地植被指数下降幅度明显;近年来一些大的沙尘源地如浑善达克沙地、毛乌素沙地的植被呈持续好转状态;对内蒙古生态环境的保护任重而道远,在加紧治理一些风沙源地的同时,要加强对草原的保护与管理,在稳定生态的同时逐步提高农牧民的生产生活水平. 相似文献
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In order to promote the application of hyperspectral remote sensing in the quantification of grassland areas’ physiological and biochemical parameters, based on the spectral characteristics of ground measurements, the dry AGB and multisensor satellite remote sensing data, including such methods as correlation analysis, scaling up, and regression analysis, were used to establish a multiscale remote sensing inversion model for the alpine grassland biomass. The feasibility and effectiveness of the model were verified by the remote sensing estimation of a time-space sequence biomass of a plateau grassland in northern Tibet. The results showed that, in the ground spectral characteristic parameters of the grassland’s biomass, the original wave bands of 550, 680, 860, and 900 nm, as well as their combination form, had a good correlation with biomass. Also, the remote sensing biomass estimation model established on the basis of the two spectral characteristics (VI2 and Normalized Difference Vegetation Index [NDVI]) had a high inversion accuracy and was easy to realize, with a fitting R2 of 0.869 and an F test value of 92.6. The biomass remote sensing estimate after scale transformation had a standard deviation of 53.9 kg/ha from the fitting model established by MODIS NDVI, and the estimation accuracy was 89%. Therefore, it displayed the ability to realize the estimation of large-scale and long-time sequence remote sensing biomass. The verification of the model’s accuracy, comparison of the existing research results of predecessors, and analysis of the regional development background demonstrated the effectiveness and feasibility of this method. 相似文献
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Dawei Xu Baorui Chen Beibei Shen Xu Wang Yuchun Yan Lijun Xu Xiaoping Xin 《Strength and Conditioning Journal》2019,72(2):318-326
The spatial distribution of different grassland types is important for effectively analyzing spatial patterns, obtaining key vegetation parameters using remote sensing (e.g., biomass, leaf area index, net primary production), and using and protecting grasslands. Existing classifications of grasslands by remote sensing are mostly divided according to the fractional vegetation cover or biomass, but classifications according to grassland types are scarce. In this study, we focused on the classification of different grassland types using remote sensing based on object-based image analysis (OBIA) with multitemporal images in combination with a 30-m digital elevation model (DEM) and the normalized difference vegetation index (NDVI). The grasslands were located in Hulunber, Inner Mongolia, and an autonomous region of China. The support vector machine (SVM) and random forest (RF) machine learning classifiers were selected for the classification. The results revealed the following: 1) It is feasible to generally extract different grassland types on the basis of OBIA with multisource data; the overall classification accuracy and Kappa value exceeded 90% and 0.9, respectively, using the SVM and RF machine learning classifiers, and the classification accuracy of the different grassland types ranged from 61.64% to 98.71%; 2) Multitemporal images and auxiliary data (DEM and NDVI) improved the separability of different grassland types. The information in the growing season was conducive for distinguishing temperate meadow steppe from temperate steppe and was favorable for extracting lowland meadow and swamp in the nongrowing season. The DEM and NDVI also effectively reduced the number of image segmentation objects and improved the segmentation effects; 3) Spectral and textural features were more important than geometric features in this study. A few main variables played a major role in the classification, while a large number of variables had either no significant effect or a negative effect on the classification results when the optimal feature subset was determined. This study provides a scientific basis and reference for the classification of various grassland types by remote sensing, including the data selection, image segmentation, feature selection, classifier selection, and parameter settings. 相似文献
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MODIS遥感影像的几何精校正--以阿勒泰地区为例 总被引：2，自引：1，他引：1
遥感资料的准备和处理是遥感技术在实际应用中的核心工作,几何精校正是利用地面控制点(GCP)对遥感影像进行的几何校正。研究在对阿勒泰地区草地监测时用ERDAS IMAGINE软件对MODIS资料进行几何精校正,主要对相关模型参数设置、控制点输入和几何精校正作了探讨。结果表明:影响几何精校正的因素,主要表现在GCP的数量、分布和定位精度及校正方法和重采样方法。 相似文献
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在遥感和地理信息系统技术支持下,我国草地类型学研究有新的进展。本研究在伊犁地区草地群落高度、盖度、地上生物量、地下生物量、草地表层土壤容重、土壤全碳、土壤有机碳、土壤全氮、土壤全磷等空间分布数据的基础上,通过对不同草地类型不同指标的特征值分析,研究确定各草地类型不同指标的阀值范围,采用决策树分类法,实现新疆伊犁地区草地类型自动判别。研究结果表明,利用伊犁地区不同草地类型在群落高度、盖度、地上生物量、地下生物量、草地表层土壤容重、土壤全碳、土壤有机碳、土壤全氮、土壤全磷9个指标的特征值作为草地类型划分的依据,可以简单直观地反映各类草地的空间分布面积和分布范围,与20世纪80年代草地调查数据比较,分布趋势一致,结果可靠。同时,本研究为伊犁地区草地资源利用管理提供基础,为伊犁地区草地资源监测和信息管理平台建设提供依据,对于指导新疆伊犁地区草地畜牧业生产具有现实意义。 相似文献
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基于GPS影像的几何精纠正在农牧业动态监测中的应用——以庆阳地区为例 总被引：1，自引：1，他引：0
随着遥感技术的不断发展和日趋成熟,利用各种遥感影像监测大面积的草原年度性、季节性变化,已经成为各地进行草原动态监测及农牧业生产监测的主要手段.而遥感影像的几何性能与几何精度是影像解译的重要基础,它直接影响解译的精度,因此影像的几何纠正是影像处理的重要内容.为了进一步提高精度,就IRS-P6卫星影像为例,在ERDAS IMAGINE 8.7平台上,采用GPS控制点(矢量图)作为地理参照,并对其的优劣性进行了分析.通过遥感分类结果与实地调查结果数据的分析,证明了用GPS点作为地理参照具有更大的精度,从而可提高影像解译的准确度.该方法为我国西北部农牧业的遥感动态监测事业的飞速发展,提供了更大的可行性. 相似文献