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101.
102.
Crop Residue Discrimination Using Ground-Based Hyperspectral Data   总被引:1,自引:0,他引:1  
Crop residue has become an increasingly important factor in agriculture management. It assists in the reduction of soil erosion and is an important source of soil organic carbon (soil carbon sequestration). In recent past, remote sensing, especially narrowband, data have been explored for crop residue assessment. In this context, a study was carried out to identify different narrow-bands and evaluate the performance of SWIR region based spectral indices for crop residue discrimination. Ground based hyperspectral data collected for wheat crop residue was analyzed using Stepwise Discriminant Analysis (SDA) technique to select significant bands for discrimination. Out of the seven best bands selected to discriminate between matured crop, straw heap, combine-harvested field with stubbles and soil, four bands were from SWIR (1980, 2030, 2200, 2440 nm) region. Six spectral indices were computed, namely CAI, LCA, SINDRI, NDSVI, NDI5 and hSINDRI for crop residue discrimination. LCA and CAI showed to be best (F?>?115) in discriminating above classes, while LCA and SINDRI were best (F?>?100) among all indices in discriminating crop residue under different harvesting methods. Comparison of different spectral resolution (from 1 nm to 150 nm) showed that for crop residue discrimination a resolution of 100 nm at 2100–2300 m region would be sufficient to discriminate crop residue from other co-existing classes.  相似文献   
103.
Abstract

This study investigates urban climatologic modification associated with development and changing land use in the relatively arid urban environment of Phoenix, Arizona. An analysis of surface temperatures, as portrayed on Landsat thermal remotely sensed data, were compared to current land use patterns in regions of the rapidly expanding urban landscape. A second focus of this study involved investigation of the surface temperatures of this environment, as extracted from the radiometric data of the Landsat thermal band, to provide insights into the complexities of the relationship to the near‐surface atmospheric temperature, a parameter used extensively in climate change analyses and in models for energy and water demand in this desert region. The near surface air temperature is usually measured approximately two meters above the ground surface. In general, spatial temperature patterns of the metropolitan region were strongly correlated with the presence of open water or biomass which provide an evapotranspirative heat sink.  相似文献   
104.
Sub-daily alias and draconitic errors in the IGS orbits   总被引:6,自引:2,他引:4  
Harmonic signals with a fundamental period near the GPS draconitic year (351.2 days) and overtones up to at least the sixth multiple have been observed in the power spectra of nearly all products of the International GNSS Service (IGS), including station position time series, apparent geocenter motions, orbit jumps between successive days, and midnight discontinuities in earth orientation parameter (EOP) rates. Two main mechanisms have been suggested for the harmonics: mismodeling of orbit dynamics and aliasing of near-sidereal local station multipath effects. Others have studied the propagation of local multipath errors into draconitic position variations, but orbit-related processes have been less examined. We elaborate our earlier analysis of GPS day-boundary orbit discontinuities where we observed some draconitic features as well as prominent spectral bands near 29-, 14-, 9-, and 7-day periods. Finer structures within the sub-seasonal bands fall close to the expected alias frequencies for 24-h sampling of sub-daily EOP tide lines but do not coincide precisely. While once-per-revolution empirical orbit parameters should strongly absorb any sub-daily EOP tide errors due to near-resonance of their respective periods, the observed differences require explanation. This has been done by simulating EOP tidal errors and checking their impact on a long series of estimated daily GPS orbits and EOPs. Indeed, simulated tidal aliases are found to be very similar to the observed IGS orbital features in the sub-seasonal bands. Moreover and unexpectedly, some low draconitic harmonics were also produced, potentially a source for the widespread errors in most IGS products. The results from this study are further evidence for the need of an improved sub-daily EOP tide model.  相似文献   
105.
Zircon occurs in voids and cracks in phosphatic coprolites enclosed in siderite concretions in Mississippian shales near Edinburgh, Scotland. The zircon formed during hydrothermal alteration of early-diagenetic concretions and occurs as spherical aggregates of prismatic crystals, sometimes radiating. Vitrinite reflectance measurements indicate temperatures of ~270°C for the zircon-bearing concretions and the host shales. Molecular parameter values based on dibenzothiophene and phenanthrene distribution and occurrence of di- and tetra-hydro-products of polycyclic aromatic compounds suggest that the rocks experienced relatively high-temperature aqueous conditions related to hydrothermal fluids, perhaps associated with neighboring mafic intrusions. The zircon was dissolved from the concretions, transported in fluids, and reprecipitated in voids. This is the first record of the precipitation of authigenic zircon in sedimentary rock as a new phase, not as outgrowths.  相似文献   
106.
Hyperspectral remote sensing, because of its large number of narrow bands, has shown possibility of discriminating the crops. Current study was carried out to select the optimum bands for discrimination among pulses, cole crops and ornamental plants using the ground-based Hyperspectral data in Patha village, Lalitpur district, Uttar Pradesh state and Kolkata, West Bengal state. The field observations of reflectance were taken using a 512-channel spectroradiometer with a range of 325–1075 nm. The stepwise discriminant analysis was carried out and separability measures, such as Wilks’ lambda and F-Value were used as criteria for identifying the narrow bands. The analysis showed that, the best four bands for pulse crop discrimination lie mostly in NIR and early MIR regions i.e. 750, 800, 940 and 960 nm. Within cole crops discrimination is primarily determined by the green, red and NIR bands of 550, 690, 740, 770 and 980 nm. The separability study showed the bands 420,470,480,570,730,740, 940, 950, 970, 1030 nm are useful for discriminating flowers.  相似文献   
107.
Hyperspectral data are generally noisier compared to broadband multispectral data because their narrow bandwidth can only capture very little energy that may be overcome by the self-generated noise inside the sensors. It is desirable to smoothen the reflectance spectra. This study was carried out to see the effect of smoothing algorithms - Fast-Fourier Transform (FFT) and Savitzky–Golay (SG) methods on the statistical properties of the vegetation spectra at varying filter sizes. The data used in the study is the reflectance spectra data obtained from Hyperion sensor over an agriculturally dominated area in Modipuram (Uttar Pradesh). The reflectance spectra were extracted for wheat crop at different growth stages. Filter sizes were varied between 3 and 15 with the increment of 2. Paired t-test was carried out between the original and the smoothed data for all the filter sizes in order to see the extent of distortion with changing filter sizes. The study showed that in FFT, beyond filter size 11, the number of locations within the spectra where the smooth spectra were statistically different from its original counterpart increased to 14 and reaches 21 at the filter size 15. However, in SG method, number of statistically different locations were more than those found in the FFT, but the number of locations did not changing drastically. The number of statistically disturbed locations in SG method varied between 16 and 19. The optimum filter size for smoothing the vegetation spectra was found to be 11 in FFT and 9 in SG method.  相似文献   
108.
Cropping system study is not only useful to understand the overall sustainability of agricultural system, but also it helps in generating many important parameters which are useful in climate change impact assessment. Considering its importance, Space Applications Centre, took up a project for mapping and characterizing major cropping systems of Indo-Gangetic Plains of India. The study area included the five states of Indo-Gangetic Plains (IGP) of India, i.e. Punjab, Haryana, Uttar Pradesh, Bihar and West Bengal. There were two aspects of the study. The first aspect included state and district level cropping system mapping using multi-date remote sensing (IRS-AWiFS and Radarsat ScanSAR) data. The second part was to characterize the cropping system using moderate spatial resolution multi-date remote sensing data (SPOT VGT NDVI) and ground survey. The remote sensing data was used to compute three cropping system performance indices (Multiple Cropping Index, Area Diversity Index and Cultivated Land Utilization Index). Ground survey was conducted using questionnaires filled up by 1,000 farmers selected from 103 villages based on the cropping systems map. Apart from ground survey, soil and water sampling and quality analysis were carried out to understand the effect of different cropping systems and their management practices. The results showed that, rice-wheat was the major cropping system of the IGP, followed by Rice-Fallow-Fallow and Maize-Wheat. Other major cropping systems of IGP included Sugarcane based, Pearl millet-Wheat, Rice-Fallow-Rice, Cotton-Wheat. The ground survey could identify 77 cropping systems, out of which 38 are rice-based systems. Out of these 77 cropping systems, there were 5 single crop systems, occupying 6.5% coverage (of all cropping system area), 56 double crop systems with 72.7% coverage, and 16 triple crop systems with 20.8% coverage. The cropping system performance analysis showed that the crop diversity was found to be highest in Haryana, while the cropping intensity was highest in Punjab state.  相似文献   
109.
There is an urgent necessity to monitor changes in the natural surface features of earth. Compared to broadband multispectral data, hyperspectral data provides a better option with high spectral resolution. Classification of vegetation with the use of hyperspectral remote sensing generates a classical problem of high dimensional inputs. Complexity gets compounded as we move from airborne hyperspectral to Spaceborne technology. It is unclear how different classification algorithms will perform on a complex scene of tropical forests collected by spaceborne hyperspectral sensor. The present study was carried out to evaluate the performance of three different classifiers (Artificial Neural Network, Spectral Angle Mapper, Support Vector Machine) over highly diverse tropical forest vegetation utilizing hyperspectral (EO-1) data. Appropriate band selection was done by Stepwise Discriminant Analysis. The Stepwise Discriminant Analysis resulted in identifying 22 best bands to discriminate the eight identified tropical vegetation classes. Maximum numbers of bands came from SWIR region. ANN classifier gave highest OAA values of 81% with the help of 22 selected bands from SDA. The image classified with the help SVM showed OAA of 71%, whereas the SAM showed the lowest OAA of 66%. All the three classifiers were also tested to check their efficiency in classifying spectra coming from 165 processed bands. SVM showed highest OAA of 80%. Classified subset images coming from ANN (from 22 bands) and SVM (from 165 bands) are quite similar in showing the distribution of eight vegetation classes. Both the images appeared close to the actual distribution of vegetation seen in the study area. OAA levels obtained in this study by ANN and SVM classifiers identify the suitability of these classifiers for tropical vegetation discrimination.  相似文献   
110.
Quality assessment of GPS reprocessed terrestrial reference frame   总被引:5,自引:1,他引:4  
The International GNSS Service (IGS) contributes to the construction of the International Terrestrial Reference Frame (ITRF) by submitting time series of station positions and Earth Rotation Parameters (ERP). For the first time, its submission to the ITRF2008 construction is based on a combination of entirely reprocessed GPS solutions delivered by 11 Analysis Centers (ACs). We analyze the IGS submission and four of the individual AC contributions in terms of the GNSS frame origin and scale, station position repeatability and time series seasonal variations. We show here that the GPS Terrestrial Reference Frame (TRF) origin is consistent with Satellite laser Ranging (SLR) at the centimeter level with a drift lower than 1 mm/year. Although the scale drift compared to Very Long baseline Interferometry (VLBI) and SLR mean scale is smaller than 0.4 mm/year, we think that it would be premature to use that information in the ITRF scale definition due to its strong dependence on the GPS satellite and ground antenna phase center variations. The new position time series also show a better repeatability compared to past IGS combined products and their annual variations are shown to be more consistent with loading models. The comparison of GPS station positions and velocities to those of VLBI via local ties in co-located sites demonstrates that the IGS reprocessed solution submitted to the ITRF2008 is more reliable and precise than any of the past submissions. However, we show that some of the remaining inconsistencies between GPS and VLBI positioning may be caused by uncalibrated GNSS radomes.  相似文献   
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