Determination of the factors governing soil erodibility using hyperspectral visible and near-infrared reflectance spectroscopy

Soil erodibility, which is difficult to estimate and upscaling, was determined in this study using multiple spectral models of soil properties (soil organic matter (SOM), water-stable aggregates (WSA) > 0.25 mm, the geometric mean radius (D_g)). Herein, the soil erodibility indicators were calculated, and soil properties were quantitatively analyzed based on laboratory simulation experiments involving two selected contrasting soils. In addition, continuous wavelet transformation was applied to the reflectance spectra (350–2500 nm) of 65 soil samples from the study area. To build the relationship, the soil properties that control erodibility were identified prior to the spectral analysis. In this study, the SOM, D_g and WSA >0.25 mm were selected to represent the most significant soil properties controlling erodibility and describe the erodibility indicator based on a logarithmic regression model as a function of SOM or WSA > 0.25 mm. Five, six and three wavelet features were observed to calibrate the estimated soil properties model, and the best performance was obtained with a combination feature regression model for SOM (R² = 0.86, p < 0.01), D_g (R² = 0.79, p < 0.01) and WSA >0.25 mm (R² = 0.61, p < 0.01), respectively. One part of the wavelet features captured amplitude variations in the broad shape of the reflectance spectra, and another part captured variations in the shape and depth of the soil dry substances. The wavelet features for the validated dataset used to predict the SOM, WSA >0.25 mm and D_g were not significantly different compared with the calibrated dataset. The synthesized spectral models of soil properties, and the formation of a new equation for soil erodibility transformed from the spectral models of soil properties are presented in this study. These results show that a spectral analytical approach can be applied to complex datasets and provide new insights into emerging dynamic variation with erodibility estimation.     

Re-parameterization of a quasi-analytical algorithm for colored dissolved organic matter dominant inland waters

Quasi-Analytical Algorithms (QAAs) are based on radiative transfer equations and have been used to derive inherent optical properties (IOPs) from the above surface remote sensing reflectance (R_rs) in aquatic systems in which phytoplankton is the dominant optically active constituents (OACs). However, Colored Dissolved Organic Matter (CDOM) and Non Algal Particles (NAP) can also be dominant OACs in water bodies and till now a QAA has not been parametrized for these aquatic systems. In this study, we compared the performance of three widely used QAAs in two CDOM dominated aquatic systems which were unsuccessful in retrieving the spectral shape of IOPS and produced minimum errors of 350% for the total absorption coefficient (a), 39% for colored dissolved matter absorption coefficient (a_CDM) and 7566.33% for phytoplankton absorption coefficient (a_phy). We re-parameterized a QAA for CDOM dominated (hereafter QAA_CDOM) waters which was able to not only achieve the spectral shape of the OACs absorption coefficients but also brought the error magnitude to a reasonable level. The average errors found for the 400–750 nm range were 30.71 and 14.51 for a, 14.89 and 8.95 for a_CDM and 25.90 and 29.76 for a_phy in Funil and Itumbiara Reservoirs, Brazil respectively. Although QAA_CDOM showed significant promise for retrieving IOPs in CDOM dominated waters, results indicated further tuning is needed in the estimation of a(λ) and a_phy(λ). Successful retrieval of the absorption coefficients by QAA_CDOM would be very useful in monitoring the spatio-temporal variability of IOPS in CDOM dominated waters.     

Detection of coffee berry necrosis by digital image processing of landsat 8 oli satellite imagery

Coffee berry necrosis is a fungal disease that, at a high level, significantly affects coffee productivity. With the advent of surface mapping satellites, it was possible to obtain information about the spectral signature of the crop on a time scale pertinent to the monitoring and detection of plant phenological changes. The objective of this paper was to define the best machine learning algorithm that is able to classify the incidence CBN as a function of Landsat 8 OLI images in different atmospheric correction methods. Landsat 8 OLI images were acquired at the dates closest to sampling anthracnose field data at three times corresponding to grain filling period and were submitted to atmospheric corrections by DOS, ATCOR, and 6SV methods. The images classified by the algorithms of machine learning, Random Forest, Multilayer Perceptron and Naive Bayes were tested 30 times in random sampling. Given the overall accuracy of each test, the algorithms were evaluated using the Friedman and Nemenyi tests to identify the statistical difference in the treatments. The obtained results indicated that the overall accuracy and the balanced accuracy index were on an average around 0.55 and 0.45, respectively, for the Naive Bayes and Multilayer Perceptron algorithms in the ATCOR atmospheric correction. According to the Friedman and Nemenyi tests, both algorithms were defined as the best classifiers. These results demonstrate that Landsat 8 OLI images were able to identify an incidence of the coffee berry necrosis by means of machine learning techniques, a fact that cannot be observed by the Pearson correlation.     

Use of high spectral resolution remote sensing to determine leaf palatability of eucalypt trees for folivorous marsupials

In this study we assess the feasibility of remotely measuring canopy biochemistry, and thus the potential for conducting large-scale mapping of habitat quality. A number of studies have found nutrient composition of eucalypt foliage to be a major determinant of the distribution of folivorous marsupials. More recently it has been demonstrated that a specific group of secondary plant chemicals, the diformylphloroglucinols (DFPs), are the most important feeding deterrents, and are thus vital determinants of habitat quality. We report on the use of laboratory spectroscopy to attempt to identify one such DFP, sideroxylonal-A, in the foliage of Eucalyptus melliodora, one of the few eucalypt species browsed by folivorous marsupials. Reflectance spectra were obtained for freeze-dried, ground leaves using near infrared spectroscopy (NIRS) and for both oven-dried and fresh whole leaves using a laboratory-based (FieldSpec) spectroradiometer. Modified partial least squares (MPLS) regression was used to develop calibration equations for sideroxylonal-A concentration based on the reflectance spectra transformed as both the first and second difference of absorbance (Log 1/R). The predictive ability of the calibration equations was assessed using the standard error of calibration statistic (SECV). Coefficients of determination (r²) were highest for the ground leaf spectra (0.98), followed by the fresh leaf and dry leaf spectra (0.94 and 0.87, respectively). When applied to independent validation sub-sets, sideroxylonal-A was most accurately predicted from the ground leaf spectra (r² = 0.94), followed by the dry leaf and fresh leaf spectra (0.72 and 0.53, respectively). Two spectral regions, centred on 674 nm and 1394 nm, were found to be highly correlated with sideroxylonal-A concentration for each of the three spectral data sets studied. Results from this study suggest that calibration equations derived from modified partial least squares regression may be used to predict sideroxylonal-A concentration, and hence leaf palatability, of Eucalyptus melliodora trees, thereby indicating that the remote estimation of habitat quality of eucalypt forests for marsupial folivores is feasible.     

FR－Ⅰ和FR－Ⅱ型射电源的关系—谱特征

本文比较了两类射电源ＦＲ－Ⅰ和ＦＲ－Ⅱ型的射电－光学—Ｘ－ｒａｙ的谱特征。ＦＲ－Ⅰ射电源的射电－光学谱比ＦＲ－Ⅱ射电源平得多（△αｒｏ≈０．１９）；但对于光学－Ｘ－ｒａｙ和射电－Ｘ－ｒａｙ谱，ＦＲ－Ⅰ却比ＦＲ－Ⅱ陡得多（△αｏｘ≈０．４０；△αｒｘ≈０．１０）。初步结果表明，ＦＲ－Ⅱ（Ｇ）可能是ＦＲ－Ⅱ（Ｑ）向ＦＲ－Ⅰ过渡的中间状态。     

Hyperspectral feature analysis of chlorophyll a and suspended solids using field measurements from Taihu Lake,eastern China

Abstract

We report results of three field campaigns conducted at 39 stations. At each station, we measured reflectance spectra in situ and collected water samples for measuring chlorophyll a (CHL) and suspended solids (SS) concentrations in the laboratory. To identify the indicative bands and develop suitable estimation models for CHL (C _CHL) and SS (C _SS) concentrations in Taihu Lake, a spectral-feature method and a derivative method were applied. The following conclusions were drawn: (a) the critical C _CHL and C _SS probably causing their spectral variation are, respectively: 0, 10, 50 and 75 μg L^?1, and 0, 10, 50 and 100 mg L^?1; (b) the derivative method is better than the spectral-feature method for estimating C _CHL and C _SS; (c) the optimal variable for CHL is a reflectance second-order derivative at 501 nm or a reflectance first-order derivative at 698 nm; the optimal variable for SS can change when its concentration is low and the range is narrow; otherwise, the optimal variable is a reflectance first-order derivative at 878 nm; and (d) the CHL and SS have an effect on one another's retrieval. The C _CHL estimation accuracy would benefit from narrowing the C _SS range. With C _CHL increasing and its range broadening, the corresponding C _SS estimation accuracy decreases gradually.     

利用谱聚类方法研究新丰江库区的震源机制解

为检验震源机制解谱聚类方法的实用性,选择新丰江库区为研究区域,利用FOCMEC方法反演了该区域2012年1月1日—2018年12月31日M_L2.0以上地震的震源机制解,并对其进行了谱聚类分析,最终获得该区域7种震源机制解类型;通过分析每种类型的震源机制解特征及其时空分布特征,探讨了震源机制解类型分布与区域构造的关系。结果表明:(1)新丰江库区地震破裂类型以正断型为主,兼有部分倾滑分量,其次为走滑型;(2)不同类型的震源机制解具有区域性的空间分布特征,主要受不同的构造背景影响,反映了新丰江库区地震活动和构造特征之间的关系;(3)不同类型震源机制解所描述的断裂分布反映了峡谷及大坝区库水渗透的构造条件,解释了区域地震频发的可能原因;(4)每种类型的震源机制解在研究时间范围内数量变化较为稳定。     

A study on feasibility of SI for identification of earthquake damages in Taiwan

Using the actual damage data of the strong earthquakes in Taiwan, the effectiveness of the earthquake risk indices, namely, peak ground acceleration (PGA) and spectral intensity (SI), is verified. PGA and Housner's [Housner GW. Spectrum intensity of strong-motion earthquakes. In: Proceedings of symposium on earthquakes and blast effects on structures. EERI, UCLA; 1952] definition of SI are directly compared. A three-parameter spectral intensity system with spectral intensities SI_a, SI_v, and SI_d in the acceleration, velocity, and displacement regions, respectively, is discussed. Here, the effectiveness of SI, SI_a, SI_v, and SI_d has been compared by using the available earthquake-damage data in Taiwan. Three period ranges, namely, 0.1–0.6, 0.6–1.6, and 1.6–3.0 s were used for structures of 1–6 stories, 7–20 stories, and 21 and more stories, respectively. The results indicate that the three-parameter system is a good risk index of the damage potential of earthquakes.     

小球藻和铜绿微囊藻的高浓度Chl-a高光谱定量模型

本研究将地物高光谱遥感技术应用于室内实验,从而得到小球藻和铜绿微囊藻的高光谱特征.通过多种半经验方法,如单波段、波段比值和微分法,建立了两藻种最优的Chl-a高光谱定量模型,并与室外情况进行了对比.结果表明:小球藻的最优定量模型为Chl-a=174.6 1138292(R703) 2.3(109[(R703)]2(p＜0.01),相应的方法适宜性为:一阶微分法＞单波段法＞波段比值法;铜绿微囊藻的最优定量模型为Chl-a=5299164(R757)1.9773(p＜0.01),相应的方法适宜性为:单波段法＞波段比值法＞一阶微分法;从高光谱特征来看,小球藻在540 nm和700 nm附近存在明显的特征波峰,其位置随Chl-a浓度增大而向长波方向偏离,铜绿微囊藻在530 nm、660 nm和700 nm附近存在3个较强的特征波峰,在610 nm和680 nm附近存在明显的波谷;与以往室外研究不同的是铜绿微囊藻的反射率在400-500 nm之间的R值并不低,是因为没有非藻类颗粒物的影响,总吸收明显降低.     

VICARIOUS RADIOMETRIC CALIBRATION OF SATELLITE FY-ID SENSORS AT VISIBLE AND NEAR INFRARED CHANNELS

For the problem of in-flight test site radiometric calibration for the FY-1D Meteorological Satellite onboard sensor's visible and near infrared channels,this paper described the calibration method,satellite-ground synchronous observation data acquired at China Dunhuang Calibration Test Site,parameter derivation and radiative transfer computation during the calibration,and the calibration result analysis.At FY-1D seven channels (with central wavelength at Channels 1:630 nm,2:865 nm;6:1610 nm;7:455 nm,8:505 nm;9:555 nm;10:932 nm),calibration coefficients obtained during the ground site calibration were compared with that respectively of prelaunch calibration.It is demonstrated that results of FY-1D onboard two sensors' (A and B) at channels 1,2,6 and 10 were close to pre-calibration,and the absolute difference of Gobi desert reflectance computed using test site and pre-launch calibration coefficients was no more than 2%. At other channels,large pre-launch calibration errors resulted in a poor consistency between the test site and pre-launch calibration.The errors can be corrected by the test site calibration results. Based on a rough estimation,the overall error of the calibration was about 6%. The paper also presented the in-flight vicarious calibration at the visible and near infrared channels of FY-1C sensor A which was launched in 1999 and has been put into operational mode since 2002.The results exhibit that FY-1C sensor's response has 23% attenuation at Channels 7 and 8,while only minor degradation at the other channels was found. During the mission,calibrations were also conducted at NOAA-17's Channels 1 and 2 (1:430-830 nm,2:500-1072 nm).A very good consistency has been achieved between the test site and pre-launched calibration results.