Evaluating the impact of red-edge band from Rapideye image for classifying insect defoliation levels     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

The prospect of regular assessments of insect defoliation using remote sensing technologies has increased in recent years through advances in the understanding of the spectral reflectance properties of vegetation. The aim of the present study was to evaluate the ability of the red edge channel of Rapideye imagery to discriminate different levels of insect defoliation in an African savanna by comparing the results of obtained from two classifiers. Random Forest and Support vector machine classification algorithms were applied using different sets of spectral analysis involving the red edge band. Results show that the integration of information from red edge increases classification accuracy of insect defoliation levels in all analysis performed in the study. For instance, when all the 5 bands of Rapideye imagery were used for classification, the overall accuracies increases about 19% and 21% for SVM and RF, respectively, as opposed to when the red edge channel was excluded. We also found out that the normalized difference red-edge index yielded a better accuracy result than normalized difference vegetation index. We conclude that the red-edge channel of relatively affordable and readily available high-resolution multispectral satellite data such as Rapideye has the potential to considerably improve insect defoliation classification especially in sub-Saharan Africa where data availability is limited.  相似文献   

Hyperspectral imagery for disaggregation of land surface temperature with selected regression algorithms over different land use land cover scenes     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

Land surface temperature (LST), a key parameter in understanding thermal behavior of various terrestrial processes, changes rapidly and hence mapping and modeling its spatio-temporal evolution requires measurements at frequent intervals and finer resolutions. We designed a series of experiments for disaggregation of LST (DLST) derived from the Landsat ETM + thermal band using narrowband reflectance information derived from the EO1-Hyperion hyperspectral sensor and selected regression algorithms over three geographic locations with different climate and land use land cover (LULC) characteristics. The regression algorithms applied to this end were: partial least square regression (PLS), gradient boosting machine (GBM) and support vector machine (SVM). To understand the scale dependence of regression algorithms for predicting LST, we developed individual models (local models) at four spatial resolutions (480 m, 240 m, 120 m and 60 m) and tested the differences between these using RMSE derived from cross-validated samples. The sharpening capabilities of the models were assessed by predicting LST at finer resolutions using models developed at coarser spatial resolution. The results were also compared with LST produced by DisTrad sharpening model. It was found that scale dependence of the models is a function of the study area characteristics and regression algorithms. Considering the sharpening experiments, both GBM and SVM performed better than PLS which produced noisy LST at finer spatial resolutions. Based on the results, it can be concluded that GBM and SVM are more suitable algorithms for operational implementation of this application. These algorithms outperformed DisTrad model for heterogeneous landscapes with high variation in soil moisture content and photosynthetic activities. The variable importance measure derived from PLS and GBM provided insights about the characteristics of the relevant bands. The results indicate that wavelengths centered around 457, 671, 1488 and 2013–2083 nm are the most important in predicting LST. Nevertheless, further research is needed to improve the performance of regression algorithms when there is a large variability in LST and to examine the utility of narrowband vegetation indices to predict the LST. The benefits of this research may extend to applications such as monitoring urban heat island effect, volcanic activity and wildfire, estimating evapotranspiration and assessing drought severity.  相似文献   

Monitoring urbanization dynamics in India using DMSP/OLS night time lights and SPOT-VGT data     

《International Journal of Applied Earth Observation and Geoinformation》2013

India is a rapidly urbanizing country and has experienced profound changes in the spatial structure of urban areas. This study endeavours to illuminate the process of urbanization in India using Defence Meteorological Satellites Program – Operational Linescan System (DMSP-OLS) night time lights (NTLs) and SPOT vegetation (VGT) dataset for the period 1998–2008. Satellite imagery of NTLs provides an efficient way to map urban areas at global and national scales. DMSP/OLS dataset however lacks continuity and comparability; hence the dataset was first intercalibrated using second order polynomial regression equation. The intercalibrated dataset along with SPOT-VGT dataset for the year 1998 and 2008 were subjected to a support vector machine (SVM) method to extract urban areas. SVM is semi-automated technique that overcomes the problems associated with the thresholding methods for NTLs data and hence enables for regional and national scale assessment of urbanization. The extracted urban areas were validated with Google Earth images and global urban extent maps. Spatial metrics were calculated and analyzed state-wise to understand the dynamism of urban areas in India. Significant changes in urban proportion were observed in Tamil Nadu, Punjab and Kerala while other states also showed a high degree of changes in area wise urban proportion.  相似文献   

Impact of feature selection on the accuracy and spatial uncertainty of per-field crop classification using Support Vector Machines     

《ISPRS Journal of Photogrammetry and Remote Sensing》2013

Crop mapping is one major component of agricultural resource monitoring using remote sensing. Yield or water demand modeling requires that both, the total surface that is cultivated and the accurate distribution of crops, respectively is known. Map quality is crucial and influences the model outputs. Although the use of multi-spectral time series data in crop mapping has been acknowledged, the potentially high dimensionality of the input data remains an issue. In this study Support Vector Machines (SVM) are used for crop classification in irrigated landscapes at the object-level. Input to the classifications is 71 multi-seasonal spectral and geostatistical features computed from RapidEye time series. The random forest (RF) feature importance score was used to select a subset of features that achieved optimal accuracies. The relationship between the hard result accuracy and the soft output from the SVM is investigated by employing two measures of uncertainty, the maximum a posteriori probability and the alpha quadratic entropy. Specifically the effect of feature selection on map uncertainty is investigated by looking at the soft outputs of the SVM, in addition to classical accuracy metrics. Overall the SVMs applied to the reduced feature subspaces that were composed of the most informative multi-seasonal features led to a clear increase in classification accuracy up to 4.3%, and to a significant decline in thematic uncertainty. SVM was shown to be affected by feature space size and could benefit from RF-based feature selection. Uncertainty measures from SVM are an informative source of information on the spatial distribution of error in the crop maps.  相似文献   

不同样本分布的SVDD单目标土地覆盖分类方法研究     

帅冠元  张锦水  朱爽  潘耀忠 《遥感学报》2013,17(6):1627-1345

  相似文献   

基于虚拟日变台进行地磁矢量数据日变通化方法   总被引：3，自引：1，他引：2       下载免费PDF全文

顾春雷  张毅  徐如刚  袁洁浩  王雷  朱志春 《地球物理学报》2013,56(3):834-841

流动地震地磁矢量观测是一种获取地震前兆异常的方法,试验研究和观测实例表明,地震孕育引起的地磁场异常变化量级较小,因此在观测、数据处理过程中都要尽可能消除误差提高精度.本文主要从地磁矢量数据日变通化精度方面开展讨论,首先使用反距离加权插值法由泰安、武汉、崇明、杭州4个地磁台观测资料计算出蒙城地磁台相应的虚拟地磁数据,其磁偏角、水平分量、垂直分量三个要素与真实观测值的相关系数分别高达0.9987、0.9946和0.9806,验证了反距离加权插值方法对地磁观测数据空间插值的有效性.其次,选择东部和西部测区分别使用反距离加权插值方法建立各地磁矢量测点位置的虚拟日变台并用其进行通化,实例计算结果表明,该方法可有效提高日变通化精度,对于地磁台站稀疏地区更具实际应用价值.  相似文献   

Prediction of Anopheles minimus habitat in India—a tool for malaria management     

Aruna Srivastava Corresponding author  B. N. Nagpal  Rekha Saxena  Vas Dev  S. K. Subbarao 《International journal of geographical information science》2013,27(1):91-98

This paper reports research to predict the distribution of An. minimus, a malaria vector in forest fringe areas using GIS to support precision surveys for malaria control. Because An. minimus is a forest‐associated species, generalized thematic maps (1:6?000?000) of forest cover, soil type, altitude, rainfall and temperature were used. Digitization, overlaying, integration and analysis of thematic maps were done using Arc/Info 8.1 NT and Arc/View 3.2 (GIS, ESRI) software. GIS delineated favourable areas for An. minimus where the species is likely to be found, and precision surveys can be conducted. Precision field surveys in selected locations of favourable/non‐favourable areas were carried out. The species could be found in all locations designated as a favourable area and was absent in non‐favourable areas. In two districts, one where the species is reported to have disappeared in the early 1950s and the other where it was not reported in earlier surveys, GIS helped in precision surveys, and An. minimus was found. The technique can quickly cover vast and inaccessible areas and is easy to duplicate in other parts of the world to assist cost‐effective control of malaria. It can also delineate areas favourable for any species of flora and fauna to help precision surveys.  相似文献   

Assessment of sliver polygons in geographical vector data     

M. Delafontaine  G. Nolf  N. van de Weghe  M. Antrop  Ph. de Maeyer 《International journal of geographical information science》2013,27(6):719-735

As positional error is a major issue in the assessment of spatial data quality, its propagation has been studied widely in map overlaying. However, few studies deal with a manifest consequence of positional error in map overlaying, namely sliver polygons. Sliver polygons are generally treated as awkward by-products that need to be removed quickly. Nevertheless, as they represent spurious areas, their nature and properties carry useful information, for example, for land use/cover assessment. Therefore, next to sliver removal, there is a need for intelligent detection and eventually further analysis of sliver polygons. This article proposes a general, semi-automated method for the assessment of slivers in vector polygon layers. A case study in Flanders (Belgium) illustrates a possible application in area estimation evaluation of land use allocation classes.  相似文献   

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王梅  江在森  侯贺晟 《大地测量与地球动力学》2010,30(2):19-24

GPSλ?????в???????????????????б??????????????????仯?????????????????????????????????????, ???????????????????????????????????????????м?????п??幹??????????????з????????????????????????????????????????????GPS????е????仯???????????????????????????????Ч????????????????е???????????????????????  相似文献   

最小二乘支持向量回归滤波系统性能分析   总被引：2，自引：2，他引：0       下载免费PDF全文

邓小英  杨顶辉  刘涛  李月  杨宝俊 《地球物理学报》2010,53(8):2004-2011

支持向量机(Support Vector Machine: SVM)一直作为机器学习方法在统计学习理论基础上被研究和发展,本文从信号与系统的角度出发,证明了平移不变核最小二乘支持向量机(Least Squares SVM: LS-SVM)是一个线性时不变系统.以Ricker子波核为例,探讨了不同参数对最小二乘支持向量回归(Least Squares Support Vector Regression: LS-SVR)滤波器频率响应特性的影响,这些参数的不同选择相应地控制着滤波器通带上升沿的陡峭性、通带的中心频率、通带带宽以及信号能量的衰减,即滤波器长度越长通带的上升沿越陡,核参数值越大通带的中心频率越高,且通带带宽越宽,正则化参数值越小,通带带宽越窄(但通带中心频率基本保持恒定),有效信号幅度衰减越严重.合成地震记录的仿真实验结果表明,Ricker子波核LS-SVR滤波器在处理地震勘探信号的应用中,滤波性能优于径向基函数(Radial Basic Function: RBF)核LS-SVR滤波器以及小波变换滤波和Wiener滤波方法.  相似文献