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1.
Prasad S Thenkabail Eden A Enclona Mark S Ashton Christopher Legg 《Remote sensing of environment》2004,90(1):23-43
The goal of this research was to compare narrowband hyperspectral Hyperion data with broadband hyperspatial IKONOS data and advanced multispectral Advanced Land Imager (ALI) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data through modeling and classifying complex rainforest vegetation. For this purpose, Hyperion, ALI, IKONOS, and ETM+ data were acquired for southern Cameroon, a region considered to be a representative area for tropical moist evergreen and semi-deciduous forests. Field data, collected in near-real time to coincide with satellite sensor overpass, were used to (1) quantify and model the biomass of tree, shrub, and weed species; and (2) characterize forest land use/land cover (LULC) classes.The study established that even the most advanced broadband sensors (i.e., ETM+, IKONOS, and ALI) had serious limitations in modeling biomass and in classifying forest LULC classes. The broadband models explained only 13-60% of the variability in biomass across primary forests, secondary forests, and fallows. The overall accuracies were between 42% and 51% for classifying nine complex rainforest LULC classes using the broadband data of these sensors. Within individual vegetation types (e.g., primary or secondary forest), the overall accuracies increased slightly, but followed a similar trend. Among the broadband sensors, ALI sensor performed better than the IKONOS and ETM+ sensors.When compared to the three broadband sensors, Hyperion narrowband data produced (1) models that explained 36-83% more of the variability in rainforest biomass, and (2) LULC classifications with 45-52% higher overall accuracies. Twenty-three Hyperion narrowbands that were most sensitive in modeling forest biomass and in classifying forest LULC classes were identified and discussed. 相似文献
2.
Wayne S. Walker Josef M. Kellndorfer Michael Hoppus 《Remote sensing of environment》2007,109(4):482-499
Exploiting synergies afforded by a host of recently available national-scale data sets derived from interferometric synthetic aperture radar (InSAR) and passive optical remote sensing, this paper describes the development of a novel empirical approach for the provision of regional- to continental-scale estimates of vegetation canopy height. Supported by data from the 2000 Shuttle Radar Topography Mission (SRTM), the National Elevation Dataset (NED), the LANDFIRE project, and the National Land Cover Database (NLCD) 2001, this paper describes a data fusion and modeling strategy for developing the first-ever high-resolution map of canopy height for the conterminous U.S. The approach was tested as part of a prototype study spanning some 62,000 km2 in central Utah (NLCD mapping zone 16). A mapping strategy based on object-oriented image analysis and tree-based regression techniques is employed. Empirical model development is driven by a database of height metrics obtained from an extensive field plot network administered by the USDA Forest Service-Forest Inventory and Analysis (FIA) program. Based on data from 508 FIA field plots, an average absolute height error of 2.1 m (r = 0.88) was achieved for the prototype mapping zone. 相似文献
3.
Mait Lang Tiit Nilson Andres Kuusk Andres Kiviste Maris Hordo 《Remote sensing of environment》2007,110(4):445-457
Several published foliage mass and crown radius regression models were tested on the preparation of the input for the reflectance model of Kuusk and Nilson [Kuusk, A. and Nilson, T. (2000), A directional multispectral forest reflectance model. Remote Sensing of Environment, 72(2):244–252.] for 246 forest growth sample plots in Estonia. In each test, foliage mass and crown radius for trees in the sample plots were predicted with a particular pair of allometric regression models. The forest reflectance model was then run using the estimated foliage mass and crown radius values. Reflectance factors were simulated and compared with the reflectance values obtained from three atmospherically corrected Landsat 7 Enhanced Thematic Mapper (ETM+) scenes. The statistics of linear regression between the simulated and measured reflectance factors were used to assess the performance of foliage and crown radius models. The hypothesis was that the best allometric regression models should provide the best fit in reflectance. The strongest correlation between the simulated and measured reflectance factors was found in the short-wave infrared band (ETM + 5) for all the images. The highest R2 = 0.71 was observed in Picea abies dominated stands. No excellent combination of foliage mass and crown radius functions was found, but the ranking based on determination coefficients showed that some linear crown radius models are not applicable to our data. Processing of raster images, reflectance measurement for small sample plots, usage of tree-species-specific fixed parameters (specific leaf area, etc.), and the ignored influence of phenology introduced additional variation into the relationships between simulated and measured reflectance factors. Further studies are needed, but these preliminary results demonstrate that the proposed method could serve as an effective way of testing the performance of foliage mass and canopy cover regressions. 相似文献
4.
为研究漓江流域近15年植被覆盖度变化情况,以1991、2000、2006年3个时相的TM/ETM+影像为基础,采用基于归一化植被指数(NDVI)的像元二分模型对漓江流域植被覆盖度进行估算,分析了植被覆盖度时空变化特征;结合研究区地质数据,进一步分析地质条件对植被覆盖度的影响。结果表明:①受气候和人类活动的影响,1991—2000年漓江流域植被覆盖度有所增加,表现为高和较高植被覆盖区面积增加,中度、较低和低植被覆盖区面积减少;2000—2006年漓江流域植被覆盖度略有降低,表现为高植被覆盖区面积减少,较高和中度植被覆盖区增加,较低和低植被覆盖区面积减少;②由于地质条件的影响,非岩溶区的平均植被覆盖度高于岩溶区,两者的变化趋势与流域整体变化基本一致;③从空间分布上看,1991—2006年漓江流域植被覆盖度的变化较显著。 相似文献
5.
Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data 总被引:2,自引:0,他引:2
Wilfrid Schroeder Elaine Prins Louis Giglio Ivan Csiszar Christopher Schmidt Jeffrey Morisette Douglas Morton 《Remote sensing of environment》2008,112(5):2711-2726
In this study we implemented a comprehensive analysis to validate the MODIS and GOES satellite active fire detection products (MOD14 and WFABBA, respectively) and characterize their major sources of omission and commission errors which have important implications for a large community of fire data users. Our analyses were primarily based on the use of 30 m resolution ASTER and ETM+ imagery as our validation data. We found that at the 50% true positive detection probability mark, WFABBA requires four times more active fire area than is necessary for MOD14 to achieve the same probability of detection, despite the 16× factor separating the nominal spatial resolutions of the two products. Approximately 75% and 95% of all fires sampled were omitted by the MOD14 and WFABBA instantaneous products, respectively; whereas an omission error of 38% was obtained for WFABBA when considering the 30-minute interval of the GOES data. Commission errors for MOD14 and WFABBA were found to be similar and highly dependent on the vegetation conditions of the areas imaged, with the larger commission errors (approximately 35%) estimated over regions of active deforestation. Nonetheless, the vast majority (> 80%) of the commission errors were indeed associated with recent burning activity where scars could be visually confirmed in the higher resolution data. Differences in thermal dynamics of vegetated and non-vegetated areas were found to produce a reduction of approximately 50% in the commission errors estimated towards the hours of maximum fire activity (i.e., early-afternoon hours) which coincided with the MODIS/Aqua overpass. Lastly, we demonstrate the potential use of temporal metrics applied to the mid-infrared bands of MODIS and GOES data to reduce the commission errors found with the validation analyses. 相似文献
6.
Li Luo 《Remote sensing of environment》2010,114(6):1220-3019
With the constant proliferation of computational power, our ability to develop hybrid classifiers has improved. Hybrid classifiers integrate results from multiple algorithms and often improve classification accuracy. In this paper, a hybrid classification framework was used to evaluate two research hypotheses: i) can manipulated results from prior classifiers (“intermediate inputs” (IIs)) improve classification accuracy in subsequent classification steps. and ii) is there an optimal dataset proportion for creation and usage of intermediate inputs. These additional intermediate inputs were based on spatial and texture statistics calculated on a partially classified image. The implementation of intermediate inputs on an impervious surface classification task using a 2001 Landsat ETM+ image from central New York was demonstrated. The results suggested that there was an average accuracy improvement of 3.6% (maximum 6.6%) by using intermediate inputs. These improvements were proved statistically significant by a Z-test and tended to increase as classification difficulty increased. The experiments in this paper also showed that there was an optimal point that balanced the number of pixels and pixel classification accuracy from prior steps used to produce intermediate inputs. Additionally, some traditional problems such as separation of impervious surfaces and soil were successfully tackled through intermediate inputs. The concept of the intermediate inputs may easily apply to other sensors and/or ground features. 相似文献
7.
ETM+和ASTER数据在遥感信息提取中的对比研究 总被引:3,自引:0,他引:3
遥感蚀变信息提取是找矿的一个重要技术手段。本文选择位于秘鲁南部阿雷基帕(AREQUIPA)省境内的萨卡纳(CERCANA)和伊卡(ICA)省境内的Moarcona铁矿区作为本文的两个研究区,从分析地物光谱出发,利用ETM+和ASTER卫星影像数据,通过主成份分析法和比值分析法分别对两个研究区进行泥化蚀变信息提取和铁染蚀变信息提取,并对两者的提取结果进行对比分析。最后结果表明,相较于ETM+数据,ASTER数据在矿化蚀变信息的提取方面具有更大的优势。 相似文献
8.
9.
This article described the way to extract information of copper and lead anomaly in high vegetation coverage area through a case study from the Datuanbao copper ore deposit and its environs,Jiangcheng,Yunnan Province.Principal component analysis,false color composite,stretch Histogram and supervise classification etc were analyzed in the remote sensing images using ENVI4.6 software.It is suggested that the linear structure,which is delineated by convolution filter and morphological analysis method,is characterized by statistical self-similarity and fractal geometry.It is found that the high value of fractal dimension is roughly coincident with the copper and lead anomaly of vegetation by the comparison between contour maps of plant geochemical anomaly and fractal dimensions,which is calculated by box-counting.As a matter of fact,80 percent of copper and lead deposits or occurrences are located in areas of high value of fractal dimension and vegetation anomaly.By the comprehensive analysis of stratigraphy,igneous rocks,copper and lead mineralizations,fractal dimension of linear structures and vegetation anomaly from remote sensing,nine exploration targets with three levels of probabilities are figured out. 相似文献
10.
John C. Price 《Remote sensing of environment》2003,86(4):491-499
Nearly simultaneous reflectance data sets from the Landsat 7 Enhanced Thematic Mapper Plus (ETM+), at 30-m resolution, and the Terra satellite instrument MODIS, at 500-m resolution, are compared for their ability to map fractional coverage of surface types over large areas. Lower spatial resolution MODIS classification results are generally comparable those of ETM+, with discrepancies for some regions with mixed surface types. Analysis of laboratory and field spectra suggests an ambiguity, the “brightness ambiguity”, which can prevent accurate area estimation of pixels having two or more surface types. This ambiguity, plus general mathematical inversion issues, can account for the discrepancy. Thus, occasional high-resolution measurements, as from Landsat 7, are necessary to refine estimations of large area surface types from MODIS and similar lower spatial resolution instruments. 相似文献