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Kim P. Bryceson 《国际地球制图》2013,28(4):21-37
A retrospective investigation was undertaken of the area around Broken Hill in the Western region of New South Wales, where Australian plague locust (Chortoicetes terminifera) nymphal band control took place during September ‐ November (spring) of 1987. Processed Landsat‐5 multispectralscanner data for March 1987 (autumn) were used to locate the likely spring/summer locust infestation areas using habitat type, condition and soil type as the delineating parameters. The results show that a vegetation index (indicating the degree of vegetation greeness in an area) is useful for predicting where locusts are most likely to aggregate, a classification of vegetation types is needed for determining likely breeding sites, and that there is an additional relationship between soils/geology and the location of locust infestations. These results are discussed in relation to the future operational use of the techniques in the Australian Plague Locust Commission. 相似文献
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蝗虫防治工作的关键在于及时准确地获取蝗情信息。本文在总结目前蝗虫防治辅助信息获取过程中及时性与共享率方面不足的基础上,综合考虑蝗情查询的实际需求提出将蝗虫防治工作与WebGIS技术结合,以Geoserver 2.11发布地理信息网络服务,结合数据库管理软件SQL Server 2005、空间数据引擎ArcSDE 9.3、网络服务器IISA 6.0、NI_Map地图服务应用程序接口设计开发蝗虫防治辅助信息查询系统,综合利用Web技术的跨平台与互操作特性以及GIS技术对空间数据的组织管理功能为蝗虫防治提供良好的数据管理与信息支持平台,增强蝗虫防治辅助信息获取的及时性、应用范围以及共享率。系统采用BS＋CS混合模式,实现了全国范围内蝗情采集数据的信息化管理,大比例尺地图参照下的蝗虫防治辅助信息可视化查询,以及不同类型空间数据的快速更新。 相似文献
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基于地面高光谱数据的东亚飞蝗危害程度监测 总被引：5，自引：0，他引：5
20世纪80年代以来东亚飞蝗在中国再度猖獗,及时、准确地监测东亚飞蝗的危害程度,对于东亚飞蝗的有效防治有重要意义。本研究以河北省黄骅市为研究区,利用地面高光谱数据,分析和比较了正常生长芦苇和受蝗虫危害芦苇的冠层反射光谱和高光谱特征参数的差异,并建立了高光谱特征参数与芦苇叶面积指数（LAI）的关系模型。结果表明,其中的虫害光谱指数（DSI）最适用于反映研究区芦苇受蝗虫危害的程度。在此基础上,利用DSI对研究区蝗虫的危害程度进行了划分,即：DSI〉62.856未受危害;41.254≤DSI≤59.496轻度危害;DSI〈41.254严重危害。 相似文献
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For three agricultural crop types, winter wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), and canola (Brassica napus L.), we estimated biophysical parameters including fresh and dry biomass, leaf area index (LAI), and vegetation water content, for which we found the equivalent water thickness (EWT), fuel moisture content per fresh weight (FMCFW), and fuel moisture content per dry weight (FMCDW). We performed these estimations using data from the newly launched Landsat 8 Operational Land Imager (OLI) sensor, as well as its predecessor the Landsat 7 Enhanced Thematic Mapper Plus (ETM+). Progress in the design of the new sensor (i.e., Landsat 8), including narrower near-infrared (NIR) wavebands, higher signal-to-noise ratio (SNR), and greater radiometric resolution highlights the necessity to investigate the biophysical parameters of agricultural crops, especially compared to data from its predecessor. This study aims to evaluate vegetation indices (VIs) derived from the Landsat 8 OLI and the Landsat 7 ETM+. Both the Landsat 8 OLI and Landsat 7 ETM+ VIs agreed well with in-situ data measurements. However, the Landsat 8 OLI-derived VIs were generally more consistent with in situ data than the Landsat 7 ETM+ VIs. We also note that the Landsat 8 OLI is better able to capture the small variability of the VIs because of its higher SNR and wider radiometric range; in addition, the saturation phenomenon occurred earlier for the Landsat 7 ETM+ than for the Landsat 8 OLI. This indicates that the new sensor is better able to estimate the biophysical parameters of crops. 相似文献
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Landsat系列卫星光学遥感器辐射定标方法综述 总被引：1，自引：0，他引：1
Landsat系列卫星自1972发射以来,已经连续提供了40多年的中等分辨率多光谱遥感数据,广泛应用于农业、水资源管理、灾害响应等领域。目前,很多研究人员开始考虑利用这些数据开展中分辨率尺度的长时间序列地表定量信息监测,更加精细地反映局地甚至全球气候变化。开展这些研究的前提在于对数据进行辐射定标,并通过不同卫星的交叉辐射传递保证数据辐射精度的一致性。从Landsat 1到Landsat 8,随着遥感器性能和数据获取能力的提升,辐射定标方法不断更新,涉及发射前实验室定标、内定标灯方法、全孔径太阳定标器方法、交叉定标方法、场地定标方法等。本文在对Landsat系列卫星的遥感器性能进行分类、归纳、对比的基础上,系统梳理了Landsat系列卫星遥感器辐射定标方法发展过程以及不同定标方法的优缺点,特别是对定标精度的影响。Landsat系列卫星辐射定标的发展过程为遥感数据高精度定量化应用提供了非常重要的基础,未来辐射定标方法不但要随着新型遥感器研制而更新,更要注重多源遥感数据的交叉验证以及全过程辐射定标方法的完善与应用,保障遥感数据辐射定标精度的一致性。 相似文献
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Landsat系列卫星对地观测40年回顾及LDCM前瞻 总被引：7，自引：0，他引：7
Landsat系列卫星数据凭借其长期连续、全球覆盖、适中的时间空间分辨率和科学的数据存档与分发策略等优势,逐渐成为地表特征和地球系统科学研究中最有效的遥感数据之一,并广泛应用于生态环境、农林地矿、能源资源、教育科研和政府管理等领域。而第8代陆地卫星--陆地卫星数据连续任务卫星(LDCM)于2013年2月发射升空,该卫星携带了运行性陆地成像仪(OLI)和热红外传感器(TIRS)两种传感器。与Landsat 7/ETM+相比,OLI/TIRS在波段设置、辐射分辨性能和扫描方式上都得到很大改进,其中OLI共包括9个波段,新增海岸带(coastal)监测和卷云(cirrus)识别波段,TIRS则设置了两个热红外波段。如果LDCM能够成功升空运行,它将继续承担起长期连续对地观测的使命。 相似文献
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基于东亚飞蝗生育周期的遥感蝗灾监测新模式 总被引：6，自引：1，他引：6
当前 ,国际遥感蝗灾监测的技术路线一般是爆发蝗灾后受损面积、程度的监测与评价 ,研究灾害的有效预警与预测方法 ,对防灾减灾更具有现实意义。通过连续 2 0 0 1、2 0 0 2年连续实地对渤海湾夏蝗孵化期、生长期和成虫期等 7个阶段的野外观测 ,对蝗虫生境物理和生物依赖条件样方统计、光谱测试和遥感机理实验 ,提出了“飞蝗生育周期遥感三段监测”的论点 ,根据这个论点将遥感监测设计为 3个阶段 :(1 )孵化期水热条件遥感反演 ;(2 )生长期食量猛增遥感监测芦苇叶面积指数和植被盖度变化 ;(3)成虫期寻找新食源对芦苇盖度 (温度 )和地表水条件 ,进而对聚集条件和迁移方向的分析指导灭蝗。有效发挥了遥感连续动态观测的技术特点 ,为建立环渤海湾东亚飞蝗遥感监测体系提供了基本技术路线 ,介绍的思路与方法也可以对森林病虫害等大规模突发病虫灾害起到借鉴作用 相似文献
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Mapping crop types is of great importance for assessing agricultural production, land-use patterns, and the environmental effects of agriculture. Indeed, both radiometric and spatial resolution of Landsat’s sensors images are optimized for cropland monitoring. However, accurate mapping of crop types requires frequent cloud-free images during the growing season, which are often not available, and this raises the question of whether Landsat data can be combined with data from other satellites. Here, our goal is to evaluate to what degree fusing Landsat with MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) data can improve crop-type classification. Choosing either one or two images from all cloud-free Landsat observations available for the Arlington Agricultural Research Station area in Wisconsin from 2010 to 2014, we generated 87 combinations of images, and used each combination as input into the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm to predict Landsat-like images at the nominal dates of each 8-day MODIS NBAR product. Both the original Landsat and STARFM-predicted images were then classified with a support vector machine (SVM), and we compared the classification errors of three scenarios: 1) classifying the one or two original Landsat images of each combination only, 2) classifying the one or two original Landsat images plus all STARFM-predicted images, and 3) classifying the one or two original Landsat images together with STARFM-predicted images for key dates. Our results indicated that using two Landsat images as the input of STARFM did not significantly improve the STARFM predictions compared to using only one, and predictions using Landsat images between July and August as input were most accurate. Including all STARFM-predicted images together with the Landsat images significantly increased average classification error by 4% points (from 21% to 25%) compared to using only Landsat images. However, incorporating only STARFM-predicted images for key dates decreased average classification error by 2% points (from 21% to 19%) compared to using only Landsat images. In particular, if only a single Landsat image was available, adding STARFM predictions for key dates significantly decreased the average classification error by 4 percentage points from 30% to 26% (p < 0.05). We conclude that adding STARFM-predicted images can be effective for improving crop-type classification when only limited Landsat observations are available, but carefully selecting images from a full set of STARFM predictions is crucial. We developed an approach to identify the optimal subsets of all STARFM predictions, which gives an alternative method of feature selection for future research. 相似文献
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《地理信息系统科学与遥感》2013,50(4):460-479
Yellowstone National Park (YNP) is legally mandated to monitor geothermal features for their future preservation, and remote sensing is a component of the current monitoring plan. Landsat imagery was explored as a tool for mapping terrestrial emittance and geothermal heat flux for this purpose. Several methods were compared to estimate terrestrial emittance and geothermal heat flux (GHF) using images from 2007 (Landsat Thematic Mapper) and 2002 (Landsat Thematic Mapper Plus). Accurate estimations were reasonable when compared to previously established values and known patterns but were likely limited due to inherent properties of Landsat data, the effects of solar radiation, and variation among geothermal areas. Landsat data can be valuable for calculation of GHF in YNP. The method suggested in this paper is not highly parameterized. Landsat data provide the means to calculate GHF for all of YNP and have the potential to enable scientists to identify locations for in-depth study. 相似文献
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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
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This study contributes to the quality assessment of atmospherically corrected Landsat surface reflectance data that are routinely generated by the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS). This dataset, named Landsat Surface Reflectance Climate Data Record (Landsat CDR), is available at global scale and offers unprecedented opportunities to land monitoring and management services that require atmospherically corrected Earth observation (EO) data. Our assessment is based on the comparison of the Landsat CDR data against a set of Landsat and DEIMOS-1 images processed to a high degree of accuracy using an industry-standard atmospheric correction algorithm (ATCOR-2). The software package has been used for many years and its correction procedures can be considered consolidated and well-established. The dataset of Landsat and DEIMOS-1 images was acquired over a semi-arid agricultural area located in Lower Austria and was independently corrected by using a manual fine-tuning of ATCOR-2 parameters to reach the highest possible accuracy. Results show a very good correspondence of the surface reflectance in each of the six reflective spectral channels as well as for the NDVI (Normalized Difference Vegetation Index). An additional comparison against a NDVI time series from MODIS revealed also a good correspondence. Coefficients of determination (R2) between the two multi-year and multi-seasonal Landsat/DEIMOS datasets range between 0.91 (blue band) and 0.98 (nIR, SWIR-1 and SWIR-2). The results obtained for our semi-arid test site in Austria confirm previous findings and suggest that automatic atmospheric procedures, such as the one implemented by LEDAPS are accurate enough to be used in land monitoring services that require consistent multi-temporal surface reflectance data. 相似文献
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An image dataset from the Landsat OLI spaceborne sensor is compared with the Landsat TM in order to evaluate the excellence of the new imagery in urban landcover classification. Widely known pixel-based and object-based image analysis methods have been implemented in this work like Maximum Likelihood, Support Vector Machine, k-Nearest Neighbor, Feature Analyst and Sub-pixel. Classification results from Landsat OLI provide more accurate results comparing to the Landsat TM. Object-based classifications produced a more uniform result, but suffer from the absorption of small rare classes into large homogenous areas, as a consequence of the segmentation, merging and the spatial parameters in the spatial resolution (30 m) of Landsat images. Based exclusively on the overall accuracy reports, the SVM pixel-based classification from Landsat 8 proved to be the most accurate for the purpose of mapping urban land cover, using medium spatial resolution imagery. 相似文献
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Zhenbo Liu Xuezheng Shi Eric Warner Yunjian Ge Dongsheng Yu Shaoxiang Ni Hongjie Wang 《International Journal of Applied Earth Observation and Geoinformation》2008
Locust plagues have been the source of some of the most severe natural disasters in human history. Soil moisture content is among the most important of the numerous factors influencing plague onset and severity. This paper describes a study initiated in three pilot locust plague monitoring regions, i.e., Huangzao, Yangguanzhuang, and Tengnan in Huanghua county, Hebei province, China, to examine the impact of soil moisture status on oriental migratory locust [Locusta migratoria manilensis (L.) Meyen] plague breakout as related to the life cycle, oviposition in autumn, survival in winter, and incubation in summer. Thirty-nine temperature vegetation dryness index (TVDI) data sets, which represent soil moisture content, were extracted from MODIS remote sensing images for two representative time periods: a severe locust plague breakout year (2001–2002) and a slight plague year (2003–2004). TVDI values demonstrated distinctive soil moisture status differences between the 2 years concerned. Soil moisture conditions in the severe plague year were shown to be lower than those in slight plague year. In all three pilot regions, average TVDI value in the severe plague year was 0.07 higher than that in slight plague year, and monthly TVDI values in locust oviposition period (September and October) and incubation period (March, April and May) were higher than their corresponding monthly figures in slight plague year. No remarkable TVDI differences were found in other months during the locust life cycle between the 2 years. TVDI values for September and October (2001), March, April and May (2002) were 0.11, 0.08, 0.16, 0.11 and 0.16 higher than their corresponding monthly figures in 2003–2004 period, respectively. 相似文献
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A new method was developed in this study for producing a clear-sky Landsat composite for cropland from cloud-contaminated Landsat images acquired in a short time period. It used Thiel–Sen regression to normalize all Landsat scenes to a MODIS image to make all Landsat images radiometrically consistent and comparable. Pixel selection criteria combining the modified maximum vegetation index and the modified minimum visible reflectance selection methods were designed to enhance the pixel selection of land/water over cloud/shadow in the image compositing. The advantages of the method include (1) avoiding complicated atmospheric corrections but with reliable surface reflectance results, (2) being insensitive to errors induced by image co-registration uncertainties between Landsat and MODIS images, (3) avoiding the lack of samples for the regression analysis using the full Landsat scenes (rather than overlay regions), and (4) enhancing cloud/shadow detection. The composite image has MODIS-like surface reflectance, thus making MODIS algorithms applicable for retrieving biophysical parameters. The method was automatically implemented on a set of 13 cloud-contaminated (>39%) Landsat-7 (Scan-Line Corrector-Off) and Landsat-8 scenes acquired during peak growing season in a crop region of Manitoba, Canada. The result was a 95.8% cloud-free image. The method can also substantially increase the usage of cloud-contaminated Landsat data. 相似文献
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作为驱动地表与大气之间能量交换的关键物理量,地表温度在众多领域中都发挥着重要作用,包括气候变化、环境监测、蒸散发估算以及地热异常勘探等。Landsat热红外数据因其时间连续性和高空间分辨率等特点被广泛应用于地表温度反演中。本文详细地介绍了Landsat热红外传感器及其可用的数据与产品的现状,梳理了2001年—2020年20年间基于Landsat热红外数据的地表温度遥感反演与应用的相关文献发表及互引情况,系统地综述了基于Landsat热红外数据的地表温度反演算法,包括基于辐射传输方程的算法、单窗算法、普适性单通道算法、实用单通道算法和分裂窗算法等。在此基础上,进一步介绍了每种算法的参数化方案,包括地表比辐射率和大气参数的估算方法。最后针对Landsat热红外数据地表温度遥感反演提出了未来可能的发展趋势与研究方向。 相似文献
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Arindam Guha Priyom Roy Swati Singh K. Vinod Kumar 《Journal of the Indian Society of Remote Sensing》2018,46(4):501-514
In this study, visible near infrared, shortwave infrared spectral bands of Landsat 8 satellite sensor, two polarisation channel of L band ALOS-PALASAR sensor, SRTM-DEM derived digital elevation data were processed to delineate different geomorphic components of alluvial fans of Tista-Mahanada fan complex. We found image composite of independent components, principal components of Landsat 8 bands were effective in delineating proximal and distal fan segments. Fused images of Landsat 8 and ALOS data were used for enhancing incised distributaries and paleochannels. Field data on depositional sequence of fans, were used to substantiate the image based delineation. Topographic breaks along selected longitudinal profiles (identified with the changes in land use and drainage pattern) of digital elevation data were conjugately analysed using Landsat false colour composites. GPR survey along selected transect highlights the vertical dislocation in the recently deposited sequences of alluvial fan regime indicative of post depositional disturbances. 相似文献
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With the longest archive of satellite remote sensing images, the Landsat series of satellites have demonstrated their great potential in aquatic environmental studies. However, although various atmospheric correction (AC) methods have been developed for Landsat observations in water color applications, a comprehensive assessment of their accuracies across different AC methods and instruments has yet to be performed. Using in situ spectral data collected by Aerosol Robotic Network-Ocean Color (AERONET-OC) sites, the performances of five types of AC methods over three different Landsat missions (i.e., Landsat 5/7/8) were evaluated. The Landsat 8 Operational Land Imager (OLI) showed more accurate AC retrievals than the other two instruments, and the results for its green and red bands appeared more reliable than those for the other wavelengths (uncertainty levels of ∼30 %). The iterative NIR algorithm with 2-bands (NIR-SWIR2) model selection embedded in SeaDAS showed the best performances for OLI in two blue bands. Moreover, larger residual errors were found for most Landsat 5/7 bands regardless of the AC methods and spectral bands employed with an uncertainty of >50 %. Interestingly, a simple aerosol subtraction method over the Rayleigh-corrected reflectance (Rrc) outperformed the exponential extrapolation (EXP) algorithms, especially for Landsat 5/7. Neither the image-based AC algorithm nor the surface reflectance (SR) products provided by the United States Geological Survey (USGS) showed acceptable performances over coastal environments. The uncertainties in the various Landsat reflectance products over water surfaces could be associated with a relatively poor signal-to-noise ratio (SNR) in addition to radiometric calibration uncertainties, imperfect aerosol removal methods. Future research is required to collect in situ data across a wider range of water optical properties (particularly more turbid inland waters) to examine the corresponding applicability of Landsat-series observations. 相似文献
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田永军 《测绘与空间地理信息》2002,25(2):30-31
概述了卫星遥感影像及其特点 ,并对东北地区在利用卫星遥感影像进行地表分类时所出现的若干问题进行了探讨 ,这对我国的土地利用工作有一定的参考价值 相似文献