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1.
The leaf area index (LAI) of plant canopies is an important structural parameter that controls energy, water, and gas exchanges of plant ecosystems. Remote sensing techniques may offer an alternative for measuring and mapping forest LAI at a landscape scale. Given the characteristics of high spatial/spectral resolution of the WorldView-2 (WV2) sensor, it is of significance that the textural information extracted from WV2 multispectral (MS) bands will be first time used in estimating and mapping forest LAI. In this study, LAI mapping accuracies would be compared from (a) spatial resolutions between 2-m WV2 MS data and 30-m Landsat TM imagery, (b) the nature of variables between spectrum-based features and texture-based features, and (c) sensors between TM and WV2. Therefore spectral/textural features (SFs) were first selected and tested; then a canonical correlation analysis was performed with different data sets of SFs and LAI measurement; and finally linear regression models were used to predict and map forest LAI with canonical variables calculated from image data. The experimental results demonstrate that for estimating and mapping forest LAI, (i) using high resolution data (WV2) is better than using relatively low resolution data (TM); (ii) extracted from the same WV2 data, texture-based features have higher capability than that of spectrum-based features; (iii) a combination of spectrum-based features with texture-based features could lead to even higher accuracy of mapping forest LAI than their either one separately; and (iv) WV2 sensor outperforms TM sensor significantly. However, we need to address the possible overfitting phenomenon that might be brought in by using more input variables to develop models. In addition, the experimental results also indicate that the red-edge band in WV2 was the worst on estimating LAI among WV2 MS bands and the WV2 MS bands in the visible range had a much higher correlation with ground measured LAI than that red-edge and NIR bands did.  相似文献   

2.
本文讨论了以热带森林植被为主体的再生资源的面积动态变化监测。研究中包括两个部分。首先,我们利用多时相遥感图像对大面积的西双版纳州进行地类判读,系统地分析了森林植被的动态变化。其次,利用Landsat MSS和TM数据对自然保护区的动态变化进行了包含无监督分类和归一化差值植被指数分析的数字图像处理,变化分类也相当符合实际。总的实验结果表明,这种监测方法是很有效的,可在再生资源监测中特别是在森林植被监测中加以推广应用。  相似文献   

3.
Feature reduction in a remote sensing dataset is often desirable to decrease the processing time required to perform a classification and improve overall classification accuracy. This paper introduces a feature reduction method based on the singular value decomposition (SVD). This SVD-based feature reduction method reduces the storage and processing requirements of the SVD by utilizing a training dataset. This feature reduction technique was applied to training data from two multitemporal datasets of Landsat TM/ETM+ imagery acquired over a forested area in Virginia, USA and Rondônia, Brazil. Subsequent parallel iterative guided spectral class rejection (pIGSCR) forest/non-forest classifications were performed to determine the quality of the feature reduction. The classifications of the Virginia data were five times faster using SVD-based feature reduction without affecting the classification accuracy. Feature reduction using the SVD was also compared to feature reduction using principal components analysis (PCA). The highest average accuracies for the Virginia dataset (88.34%) and for the Rondônia dataset (93.31%) were achieved using the SVD. The results presented here indicate that SVD-based feature reduction can produce statistically significantly better classifications than PCA.  相似文献   

4.
The contribution of forest degradation to changes in forest carbon stocks remains poorly quantified and constitutes a main source of uncertainty in the forest carbon budget. Charcoal production is a major source of forest degradation in sub-Saharan Africa. We used multitemporal Sentinel-2 imagery to monitor and quantify forest degradation extent in the main supplying area of a major urban center of southern Africa over a 4-year period. We implemented an indirect approach combining Sentinel-2 imagery to map kiln and field measurements to estimate AGB removals and carbon losses from charcoal production. This work generated 10 m resolution maps of forest degradation extent from charcoal production in the study area at quarterly intervals from 2016–2019. These maps reveal an intense and rapid forest degradation process and expose the spatial and temporal patterns of forest degradation from charcoal production with high detail. The total area under charcoal production over the study period reached 26,647 ha (SD = 320.8) and the forest degradation front advanced 10.5 km in a 4-year period, with an average of 19.4 ha of woodlands degraded daily. By the end of 2019, charcoal production disturbed most mopane stands in the study area and woodland fragmentation increased in 70.4 % of the mopane woodlands. We estimated that charcoal production was responsible for 2,568,761 Mg (SD = 42,130) of aboveground biomass extracted from the forest and 1,284,381 Mg (SD = 21,075) of carbon loss. The magnitude of these figures underlines the relevance of charcoal production as a main cause of forest cover change and remarks the existing uncertainties in the quantification of forest degradation processes. These results illustrate the potential of multitemporal medium resolution imagery to quantify forest degradation in sub-Saharan Africa and improve REDD + Monitoring, Reporting, and Verification systems in compliance with international reporting commitments.  相似文献   

5.
针对以光谱特征差异为依据,提取森林湿地信息精度低的问题,该文采用兼容多源数据的分类回归树(CART)提取方法,并以大沾河国家森林湿地进行实证研究。基于Landsat8遥感数据、Radarsat-2极化雷达数据和地形辅助数据,采用SPM软件分别构建3种特征变量组合的CART决策树模型,并获取分类规则,最后根据规则对研究区的森林湿地信息进行提取。结果表明:3种特征变量组合中,兼容光谱、纹理、雷达与地形辅助数据的CART决策树的森林湿地信息提取精度最高,用户精度和制图精度分别达到了88.46%和82.14%。研究结果体现了雷达数据与地形辅助数据有助于提取森林湿地信息。  相似文献   

6.
Biodiversity mapping in extensive tropical forest areas poses a major challenge for the interpretation of Landsat images, because floristically clearly distinct forest types may show little difference in reflectance. In such cases, the effects of the bidirectional reflection distribution function (BRDF) can be sufficiently strong to cause erroneous image interpretation and classification. Since the opening of the Landsat archive in 2008, several BRDF normalization methods for Landsat have been developed. The simplest of these consist of an empirical view angle normalization, whereas more complex approaches apply the semi-empirical Ross–Li BRDF model and the MODIS MCD43-series of products to normalize directional Landsat reflectance to standard view and solar angles. Here we quantify the effect of surface anisotropy on Landsat TM/ETM+ images over old-growth Amazonian forests, and evaluate five angular normalization approaches. Even for the narrow swath of the Landsat sensors, we observed directional effects in all spectral bands. Those normalization methods that are based on removing the surface reflectance gradient as observed in each image were adequate to normalize TM/ETM+ imagery to nadir viewing, but were less suitable for multitemporal analysis when the solar vector varied strongly among images. Approaches based on the MODIS BRDF model parameters successfully reduced directional effects in the visible bands, but removed only half of the systematic errors in the infrared bands. The best results were obtained when the semi-empirical BRDF model was calibrated using pairs of Landsat observation. This method produces a single set of BRDF parameters, which can then be used to operationally normalize Landsat TM/ETM+ imagery over Amazonian forests to nadir viewing and a standard solar configuration.  相似文献   

7.
Satellite imagery analysis has played a key role in environmental monitoring and modeling over the past few decades. Remotely sensed multitemporal, multisensor data are often required in Earth observation applications. A common problem associated with the use of multisource image data is the gray value differences caused by non-surface factors such as different illumination, atmospheric or sensor conditions. Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi-sensor, multi-date studies. This paper presents methodology for correction of Landsat TM images in Radon domain. We propose radiometric correction using Radon Transform based regression method. The transform domain method statistically determines correction values based on contrast between spectral properties of various homogeneous areas. TM band 1 is the band most affected by atmospheric scattering whereas TM band 5 is less affected by atmospheric scattering effect. Hence TM Band 5 is taken as the reference image. Results are assessed statistically and compared with results of popular spatial domain Regression Line Method. The application of the methods for vegetation analyses is also shown in this paper. Test results show that the method gives improved results in removal of atmospheric influence.  相似文献   

8.
于莉楠  宁晓刚  王浩  刘纪平 《测绘学报》2019,48(8):1004-1013
复杂城区边界通常存在建筑物大小差异较大、周边林区高低起伏、散点建筑成片出现的情况,对城区边界提取算法造成严重干扰。针对这一问题,本文提出一种基于拓扑插值和光谱特征的高分辨率遥感影像复杂城区边界提取方法。一方面,通过对大型建筑特征点进行拓扑插值,避免由于大型建筑特征点稀疏造成的城区边界缺失;另一方面,利用植被光谱特征来滤除城区周边高低起伏的林区和散点建筑带来的冗余特征点,从而有效抑制城区误提取。通过试验和对比分析表明,本文方法在提取复杂城区边界方面,具有较好的稳健性和较高的精度。  相似文献   

9.
Remotely sensed multitemporal, multisensor data are often required in Earth observation applications. A common problem associated with the use of multisource image data is the grey value differences caused by non-surface factors such as different illumination, atmospheric, or sensor conditions. Image normalization is required to reduce the radiometric influences caused by non-surface factors and to ensure that the grey value differences between temporal images reflect actual changes on the surface of the Earth. This paper proposes new approaches to radiometric correction of multitemporal satellite imagery using wavelet analysis and Fourier transform. The results obtained are compared with commonly used NO-change regression (NC) normalization and Histogram Matching spatial domain methods. Both visual inspection and statistical accuracy assessment show that proposed transform domain approaches are valid.  相似文献   

10.
This study is aimed at demonstrating the feasibility of the large scale LAI inversion algorithms using red and near infrared reflectance obtained from high resolution satellite imagery. Radiances in digital counts were obtained in 10 m resolution acquired on cloud free day of August 23, 2007, by the SPOT 5 high resolution geometric (HRG) instrument on mostly temperate hardwood forest located in the Great Lakes – St. Lawrence forest in Southern Quebec. Normalized difference vegetation index (NDVI), scaled difference vegetation index (SDVI) and modified soil-adjusted vegetation index (MSAVI) were applied to calculate gap fractions. LAI was inverted from the gap fraction using the common Beer–Lambert's law of light extinction under forest canopy. The robustness of the algorithm was evaluated using the ground-based LAI measurements and by applying the methods for the independently simulated reflectance data using PROSPECT + SAIL coupled radiative transfer models. Furthermore, the high resolution LAI was compared with MODIS LAI product. The effects of atmospheric corrections and scales were investigated for all of the LAI retrieval methods. NDVI was found to be not suitable index for large scale LAI inversion due to the sensitivity to scale and atmospheric effects. SDVI was virtually scale and atmospheric correction invariant. MSAVI was also scale invariant. Considering all sensitivity analysis, MSAVI performed best followed by SDVI for robust LAI inversion from high resolution imagery.  相似文献   

11.
基于影像的Landsat TM/ETM+数据正规化技术   总被引:7,自引:0,他引:7  
阐述了基于影像的LandsatTM/ETM^+的数据正规化技术及其发展。该技术通过将Landsat影像的亮度值转换成传感器处的辐射值和反射率采对影像进行辐射校正。实例表明,使用正规化技术处理后的影像可以明显削弱日照和大气的影响,去除它们产生的噪声;其所书的传感器处的反射率与地面实测反射率的RMS值非常小。  相似文献   

12.
本文讨论了IHS彩色变换和主成分变换在苏州市TM多波段图像信息提取研究中的应用效果。研究表明,地物在多波段数据的彩色合成图像上具有较为稳定、特征的色调信息。利用苏州市水体、植被、城镇三大类地物的色调特征对TM_3(红)、TM_4(绿)、TM_5(蓝)彩色合成图像的色调成分H作了伪彩色密度分割,准确地反映了它们的分布状况。在主成分图像的IHS反变换彩色合成图像上,主成分的信息内容得到了定量、形象直观的反映,苏州市新旧城区的光谱差异、该市现状以及现代城市规划特点得到了清晰的显现。水稻、菜地、山地之间的光谱差异也得到明显的增强。主成分变换和彩色变换相结合,为多波段数据信息提取提供了一种新的方法。  相似文献   

13.
结合树龄信息的遥感森林生态系统生物量制图   总被引:10,自引:0,他引:10  
森林生态系统是陆地生态系统中的重要组成部分,其中的地上生物量(AGB,Aboveground Biomass)在全球气候变化和碳循环研究中起着重要的作用。本文利用ETM^+遥感影像,首先建立了实测叶面积指数(LAI,Leaf Area Index)与实测生物量数据的回归关系,基于遥感叶面积指数图像得到初步地上生物量空间分布图;同时在短波植被指数(SWVI,Short Wave Vegetation Index)与实测树龄之间建立了回归关系,在此基础上得到了树龄空间分布图。然后通过将植被指数(VI,Vegetation Index),LAI,树龄等变量针对不同的树种类型进行逐步回归,得到了较好的回归模型,并结合土地利用/土地覆盖估算了贵州省黎平县的地上生物量,绘制了其空间分布图。统计结果显示:总体森林生态系统的AGB与LAI和RSR(Reduced Simple Ratio)之间有一定的相关关系(R^2=0.895);杉木林的AGB与LAI和归一化植被指数(NDVI,Normalized Difference Vegetation Index)之间有较强的相关性(R^2=0.93);针叶树种的LAI与年龄是AGB较好的估算因子(R^2=0.937);阔叶林的AGB与年龄有一定的相关性(R^2=0.792);混交林的AGB与LAI和SR(Simple Ratio)有较强的相关性(R^2=0.931)。结果表明,将树龄和土地覆盖/土地利用类型的信息加入到地上生物量估算模型的建立中,是一种改善利用多光谱遥感估算精度的较好的方法。结合土地覆盖/土地利用类型的高分辨率的树龄空间分布图,可为森林生态系统的可持续发展和管理提供科学的论据。  相似文献   

14.
Computer simulation models have seldom been applied for estimating the structural and biophysical variables of forest canopy. In this study, an approach for the estimation of leaf area index (LAI) using the information contained in hyperspectral, multi-angle images and the inversion of a computer simulation model are explored. For this purpose, L-systems combined with forest growth model ZELIG were applied to render 3-D forest architectural scenarios. The Radiosity-graphics combined model (RGM) was used to estimate forest LAI from the Compact High-Resolution Imaging Spectrometer/Project for On-Board Autonomy (CHRIS/PROBA) data. LAI inversion was performed using the look-up table (LUT) method. The estimated LAI was evaluated against in situ LAI measurement and compared against the LAI predictions from CHRIS data obtained using the Li-Strahler geometric-optical canopy reflectance model (GOMS). The results indicated that the method used in this study can be efficient strategy to estimate LAI by RGM model inversion.  相似文献   

15.
Image Analysis for GIS Data Acquisition   总被引:2,自引:0,他引:2  
The automatic interpretation of aerial and satellite imagery by means of image analysis is currently one of the major research tasks in photogrammetry and related disciplines. The primary goal is the automatic extraction of visible, spatial topographic objects from imagery. The extracted objects represent one possible form of input for creating geographic databases. In this paper, different aspects of image analysis are discussed and a framework is provided for scene interpretation, which is based on the integration of image analysis and a GIS data model. Two examples concerned with the combined extraction of roads and trees, and with the multitemporal interpretation and monitoring of moorland, are given to illustrate the research.  相似文献   

16.
While validation of the MODIS fPAR product is well behind that of the LAI product, it is recently receiving more attention. In this study, MODIS fPAR and Landsat-5 TM-derived fPAR (TM fPAR) were calculated and quantitatively compared using imagery from 2005 to 2008 for the semiarid rangelands of Idaho, USA. fPAR change maps were calculated between active growth and late-summer senescence periods. Accuracy of the MODIS fPAR and TM fPAR were determined indirectly by incorporating field-based measurements of above-ground forage biomass and percent ground cover from a variety of sites (n = 442).  相似文献   

17.
The Regione del Veneto (Italy) is cooperating with the University of California, Santa Barbara and other researchers in Italy and the U.S.A. to develop a system of econometric crop production modeling. Five crops are to be included in this project: small grains (wheat and barley), corn, sugar beets, soybeans, orchards and vineyards. A critical part of the crop yield modeling process is the identification of crops using multispectral satellite data. This paper explores two strategies to improve crop classification accuracies: (1) use of ancillary data stored in digital format and (2) use of multitemporal data. Ancillary information stored on digital files were used in this research to remove (mask) non‐agricultural areas from satellite image data. Comparison between the classification of masked and unmasked images showed that improvement ranged from 3% to 26% depending on crop type. The multidate classification was performed by compiling an image of transformed spectral bands and three TM‐5 bands. The transformed bands were TM band 4 over TM band 3. Based on the work conducted in this study it is clear that crop type determination from satellite imagery is possible for small field agricultural areas such as those found in Italy.  相似文献   

18.
TM 图像的信息量分析及特征信息提取的研究   总被引:1,自引:0,他引:1  
图像信息量分析是图像处理的基础,为此,本文研究了三个不同植被覆盖类型区,即多林区(森林覆盖在40%以上)、一般林地分布的丘陵区(森林覆盖10-30%)和农田为主的丘陵与平原区的图像信息量。分析同一地区冬夏两季的图像信息特征后得知,红外波段的信息量高于可见光波段,其中信息量最大的是TM5波段,最小的是TM2波段。同时对不同情况下波段间的相关性、均值和标准差等统计特征值也进行了分析。据此就图像增强、信息特征提取方法,如主成分分析、缨帽变换(KT变换)、比值等方法以及波段组合等进行了系统研究,并就其实用条件进行了探讨和评价。  相似文献   

19.
The objective of this study was to investigate the relationship between crown closure and tree density in mixed forest stands using Landsat Thematic Mapper (TM) reflectance values (TM 1- TM 5 and TM 7) and six vegetation indices (SR, DVI, SAVI, NDVI, TVI and NLI). In this study, multiple regression analysis was used to estimate the relationships between the crown closure and tree density (number of tree stems per hectare) using reflectance values and vegetation indices (VIs). The results demonstrated that the model that used SR and DVI had the best performances in terms of crown closure (R2?=?0.674) and the model that used the DVI and SAVI had the best performances in terms of tree density (R2?=?0.702). The regression model that used TM 1, TM 3 together with TM 4 showed the performances of the crown closure (R2?=?0.610) and the regression model that used TM 1 showed the performances of the tree density (0.613). Results obtained from this research show that vegetation indices (VIs) were a better predictor of crown closure and tree density than other TM bands.  相似文献   

20.
基于神经网络方法的芦苇叶面积指数遥感反演   总被引:2,自引:0,他引:2  
提出了一种从TM图像上获取芦苇冠层叶面积指数的方法:首先对芦苇的生长背景进行分类;然后,对不同的背景光谱利用冠层反射率(FCR)模型计算得到查找表;最后,利用实测数据和查找表中的数据作为参数进行BP神经网络模型训练,从而得到芦苇冠层LAI。结果表明,人工神经网络方法有很强的非线性拟合能力,能够消除背景对反演结果的影响,有效提高LAI反演的精度。  相似文献   

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