基于FLAASH模型的Landsat ETM＋卫星影像大气校正

主要介绍FLAASH大气校正原理及算法,并运用FLAASH大气校正模型对美国旧金山地区ETM＋卫星影像进行大气校正,再对校正前后的影像进行地物光谱曲线分析和NDVI分析评价。研究表明,ETM＋卫星影像经FLAASH大气校正后,较好地消除了大气影响。     

基于资源一号卫星QUICK和FLAASH大气较正植被信息的表相

为了获取更为准确的地面植被信息,分别通过采用ENVI的两种大气校正方法对国产资源一号卫星遥感数据进行处理,比对两种不同方法处理后的同一地物的波谱及影像。首选FLAASH大气较正是定量获取局部或全局的较为真实的植被信息的精准方法。     

卫星遥感图像解译方法

卫星遥感图像解译方法谭宽祥（林业部中南院长沙市４１００１４）卫星遥感图像是遵循地物——电磁波——影像的信息传递过程，而卫星遥感图像的解译则是遵循影像——电磁波——地物信息的还原过程。图像解译必须在对电磁波谱有了深刻了解的基础上，并充分了解专业要求，从...     

SPOT全色波段影像的几何校正

林业遥感往往需要将不同来源的ＳＰＯＴ影像与ＴＭ影像融合在一起，不同影像的像元就必须能精确地配准，而ＳＰＯＴ全色波段的几何精校正尤为困难，影像上清楚的地物点，地形图上不清楚；表现在地形图上清楚的地物点，影像上不清楚。这使得影像校正很困难。另外，云南复杂的地形也使ＳＰＯＴ影像的各个位置有不同程度的变形。在菜阳河保护区影像校正中，先在影像上选择好控制点，然后用ＧＰＳ采点确定控制点的地理坐标；并用高程式模     

SPOT全色波段影像的几何校正

林业遥感往往需要将不同来源的SPOT影像与TM影像融合在一起,不同影像的像元就必须能精确地配准,而SPOT全色波段的几何精校正尤为困难,影像上清楚的地物点,地形图上不清楚;表现在地形图上清楚的地物点,影像上不清楚.这使得影像校正很困难.另外,云南复杂的地形也使SPOT影像的各个位置有不同程度的变形.在菜阳河保护区影像校正中,先在影像上选择好控制点,然后用GPS采点确定控制点的地理坐标;并用高程式模型校正由地形变化引起的扭曲.     

影像校正中GCP选取的探讨

由于SPORT5卫星影像的原始数据存在着一定的几何变形,因而在应用中,首先要进行SPORT5影像的正射校正。该文从山西省森林资源“二类”调查工作实际出发,围绕正射校正中地面控制点(Ground Control Point简称GCP)选取这个环节,从模式、个数、要求、方法以及误差的调整等几个方面来探讨如何通过GCP的选取来提高SPORT5卫星影像的校正精度。     

云阴影区机载高光谱影像森林树种分类

[目的]使用窄波段植被指数、纹理信息等特征对影像进行分类,探究植被指数和纹理信息对于云阴影下树种分类的潜力。[方法]使用经过大气校正后的高光谱影像进行窄波段植被指数的计算、纹理分析以及主成分分析,并对计算的结果进行波段组合。用于计算纹理信息的波段通过最佳指示因子进行选择,选取的波段数为31(0.67 nm),51(0.86 nm),55(0.89 nm) 3个波段。结合高分辨率的航空相片进行训练样本的选择,采用Support Vector Machine(SVM)方法对经过大气校正后的反射率影像和重组后的特征影像分别进行分类,使用样地实测的树种信息对分类结果进行验证,使用总体精度和Kappa系数作为分类精度的评价指标。[结果]相对于直接使用反射率影像进行分类,使用窄波段植被指数以及纹理信息可以显著地提高云阴影下地物的分类精度,其分类精度和Kappa系数分别为90.4%和0.88,比直接使用反射率影像的分类精度和Kappa系数分别提高了18%和0.2。[结论]使用重新组合后的影像进行树种分类比直接使用反射率影像进行分类,其分类精度更高,说明窄波段植被指数与纹理特征可以提高云阴影区树种分类的精度。使用波段重组后的影像对云阴影下地物分类,其对于单个地物的分类精度也有明显的提高。     

在ERDAS IMAGINE中建立邯郸市TM影像土地类型解译标志

为了准确地了解邯郸市的土地利用类型,掌握土地资源的发展动态,在ERDAS IMAGINE软件支持下,将Landsat5号卫星所得的TM4、3、2波段数据组合输出成为标准假彩色影像,对其进行几何校正、重采样、图像裁剪与镶嵌等操作,依据遥感图像特征、地物相关关系、区域特点和全国土地利用分类系统,对处理后所得的邯郸市TM影像...     

WorldView-2遥感影像在广西第五次沙化监测中的应用

World View-2遥感影像因具有多光谱波段和0.46 m空间分辨率,反映地物信息丰富、影像清晰等特点被各行业广泛使用。广西前期沙化监测采用的遥感影像均是空间分辨率为米级的影像,但监测工作效率与结果均不是很理想。文章对World View-2卫星遥感图像处理、遥感图像目视解译标志库建立、遥感图像判读及判读结果检验等方面进行阐述与分析。结果认为,采用该遥感影像进行沙化监测具有精度高、工作效率高的特点,可推广应用。     

用卫星影像密度值估测森林蓄积量

<正> 卫星照片是一种多波段影像。同普通照片一样,也是以底片上的密度差异记录被拍照物的光反射特性,显示被拍物体几何形状的。与普通照片不同的是,它对同一物体以多个(本研究用卫片是4个) 波段的方式进行记录,得到多张底片,每张底片只记录一个特定波段的地物反射特性,因而同一物体在各张底片上密度分布是不同的。正是由于这一点,卫星影像给我们提供了区分各种地物的可能性。本研究是通过卫片的影像密度值来估测森     

应用环境星监测北部湾地区采伐和造林动态的研究

采用2008和2009年末环境星CCD数据,对广西北部湾地区的森林采伐和造林动态进行了监测。结果表明:1)环境星CCD图像有较好的内部几何一致性,几何配准之后,2期图像之间可以达到0.5个像元以内的配准精度,适合进行动态监测;2)采用NDVI差值法,监测的采伐和造林情况与目视判读结果有很高的一致性,可以达到较高的监测精度;3)监测结果显示,监测期内广西北部湾地区桉树林的面积正在扩张,2009年末相对2008年末桉树面积增加为13.4%,其中一半以上为采伐针叶林后种植的桉树。     

TM影像的计算机屏幕解译和荒漠化监测

以覆盖科尔沁沙地１３个旗县的６景ＴＭ影像为例,简介了以计算机屏幕解释这种技术路线作卫星影像分类图的过程,论述了卫星遥感技术监测荒漠化土地变化和作出环境发展趋势评估的潜力。指出对待盐渍化和沙化这两个问题,对不同区域应各有侧重,最后介绍了联合国粮农组织（ＦＡＯ）的土地分类原则,用土地单元,土地利用类型及附加特性注记地类的方法。     

Assessing seasonal vegetation change in coastal wetlands with airborne remote sensing: an outline methodology

Airborne remote sensing offers high-density, spatially-averaged synoptic samples of radiation reflected from a surface which can be used to infer ecological processes and community composition. Unfortunately, the cost of the overheads in terms of time and resources, and scheduling constraints when deriving quantitative information have limited its use in operational monitoring programs. When the changes in reflected radiation related to the phenomenon under investigation are large, only minimal low-cost processing is required to identify ecosystem modification if high frequency multi-temporal imagery can be combined with expert knowledge. This methodology is likely to be of particular value in coastal environments where access for conventional measurements is restricted and changes in sensitive tidal wetlands may provide an early indicator of changing natural processes and/or human impact. Regularly acquired airborne remotely sensed imagery has been used in a reconnaissance study to identify and map seasonal vegetation patterns on intertidal surfaces in back barrier environments on the North Norfolk coast, England, U.K. The development of an operational system for coastal zone management is discussed.     

无人机遥感在我国森林资源监测中的应用动态

文章分析了无人机遥感技术在森林资源监测中的应用特点,总结了获取无人机遥感影像的技术流程.从利用无人机遥感影像获取林木几何参数、提取森林生物量信息、监测森林病虫害和森林消防4个方面阐述了无人机遥感技术在我国森林资源监测中的应用动态.在讨论无人机遥感技术在林业应用中具备成本低、效率高等优势的基础上,对无人机遥感技术在我国森林资源监测中的应用前景作了展望.     

基于GF-2号影像的森林优势树种分类

利用遥感数据开展森林资源优势树种的分类对森林资源的监测、森林可持续经营及生物多样性研究具有重要意义。研究针对复杂地形区域的破碎化森林,采用高分二号(GF-2)的多光谱影像作为基础数据进行森林优势树种的精细分类。本文以地形复杂、森林破碎化的湖北省竹山县九华山林场为研究对象,采用面向对象分类方法对树种进行精细分类,比较支持向量法、最近邻法(KNN)和随机森林(RF)三种不同分类算法的分类效果。在尺度阈值为30、合并阈值为95时分割的基础上,利用SVM、KNN和RF分类结果和分类精度差异较大。分类精度最高的是SVM分类方法,总体精度为68.52%,Kappa系数为0.62;其次为随机森林分类法,总体精度为60.29%,Kappa系数为0.54;KNN分类方法精度最低,总体精度为59.41%,Kappa系数为0.53。GF-2号数据能满足树种分类基本需求,在复杂地形和景观破碎化地区用支持向量机进行树种的分类精度更高,但仍存在一定的局限性。     

Characterizing rangeland vegetation using Landsat and 1-mm VLSA data in central Wyoming (USA)

As an alternative to ground-cover data collection by conventional and expensive sampling techniques, we compared measurements obtained from very large scale aerial (VLSA) imagery for calibrating moderate resolution Landsat data. Using a grid-based sampling scheme, 162 VLSA images were acquired at 100 m above ground level. The percent vegetation cover in each photo was derived using SamplePoint (a manual inventory method) and VegMeasure (a reflectance based, automated method). Approximately two-thirds of the VLSA images were used for calibrating Landsat data while the remainder was used for validation. Regression models with Landsat bands accounted for 55% of the VegMeasure-based measurements of vegetation, whereas models that included both Landsat bands and elevation data accounted for 67%. The relationship between the Landsat bands and the percent vegetation cover measured by SamplePoint was lower (R ² = 20%), highlighting the differences between the inventory and reflectance based protocols. Results from the model validation indicated that the model’s predictive power was lower when the vegetation cover was either <20% or >55%. Additional work is needed in these ecosystems to improve the calibration techniques for sites with low and high vegetation cover; however, these results demonstrate the VLSA imagery could be used for calibrating Landsat data and deriving rangeland vegetation cover. By adopting such methodologies the US Federal land management agencies can increase the efficiency of the monitoring programs in Wyoming and in other western states of the US. Mention of trade names is for information only and does not imply endorsement by USDA over comparable products or services.     

Forecasting tree mortality using change metrics derived from MODIS satellite data

Insect-induced tree mortality can cause substantial timber and carbon losses in many regions of the world. There is a critical need to forecast tree mortality to guide forest management decisions. Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery provides inexpensive and frequent coverage over large areas, facilitating forest health monitoring. This study examined time series of MODIS satellite images to forecast tree mortality for a Pinus radiata plantation in southern New South Wales, Australia. Dead tree density derived from ADS40 aerial imagery was used to evaluate the performance of change metrics derived from time series of MODIS-based vegetation indices. Continuous subset selection by LASSO regression and model assessment using a variant of the bootstrap were used to select the best performing change metrics out of a large amount of predictor variables to account for over-fitting. The results suggest that 250 m 16-daily MODIS images are effective for forecasting tree mortality. Seasonal change metrics derived from the Normalized Difference Vegetation Index (NDVI) outperformed the Enhanced Vegetation Index (EVI) and the Normalized Difference Infrared Index (NDII). Temporal analysis illustrated that optimal forecasting power was obtained using change metrics based on three years of satellite data for this population. The forecast could be used to optimise the scheduling of detailed forest health surveys and silvicultural operations which currently are planned based on stratified, annual assessments. This coarse-scale, spatio-temporal analysis represents a potentially cost-effective early warning approach to forecasting tree mortality in pine plantations by identifying compartments that require more detailed investigation.     

Influence of using texture information in remote sensed data on the accuracy of forest type classification at different levels of spatial resolution

We evaluated the influence of texture information from remote sensed data on the accuracy of forest type classification at different spatial resolutions. We used 4-m spatial resolution imagery to create five different sets of imagery with lower spatial resolutions down to 30 m. We classified forest type using spectral information alone, texture information alone, and spectral and texture information combined at each spatial resolution, and compared the classification accuracy at each resolution. The classification and regression tree method was used for classification. The accuracy of all three tests decreased slightly with lower spatial resolution. The accuracy with the combined data was generally higher than with either the spectral or texture information alone. At most resolutions, the lowest accuracy was with texture information alone. However, there was no clear difference in accuracy between the combined data and spectral data alone at 25- and 30-m spatial resolution. These results indicate that adding texture information to spatial information improves the accuracy of forest type classification from very high resolution (4-m spatial resolution) to medium resolution imagery (20-m spatial resolution), but this accuracy improvement does not appear to hold for relatively coarse resolution imagery (25- to 30-m spatial resolution).     

面向对象技术在城市绿地信息提取中的应用

以乌鲁木齐市为例,采用高分辨率卫星QuickBird数据为主要信息源,应用面向对象的多尺度分割技术,对城市绿地信息的提取方法进行了研究。利用专题层分割影像,结合成员隶属度函数,实现城市绿地信息的自动提取。研究表明使用该方法提取信息速度快、准确率高、成本低,可以实现城市绿地信息的快速而准确的提取。     

快鸟数据在退耕还林中应用方法的研究

利用高分辨率快鸟数据对退耕地进行监测,依据规划图,在GIS系统中,进行逐个图班的退耕地块检查,获取退耕地块的面积,地块类型,未造林面积等数据。识别退耕地的新造幼龄林,用NDVI的植被增强方法对退耕地进行增强,以提高幼龄林的识别率。最后用基于ISODATA判定规则的非监督分类方法对退耕地进行分类,得到试验区各地类的面积及所占百分比。分类结果表明,地垄的边界,树冠,树坑等地物信息均能提取出来。