POINT PATTERN MATCHING ALGORITHM BASED ON POINT PAIR TOPOLOGICAL CHARACTERISTICS AND SPECTRAL MATCHING

Most of the Point Pattern Matching (PPM) algorithm performs poorly when the noise of the point's position and outliers exist. This paper presents a novel and robust PPM algorithm which combined Point Pair Topological Characteristics (PPTC) and Spectral Matching (SM) together to solve the afore mentioned issues. In which PPTC, a new shape descriptor, is firstly proposed. A new comparability measurement based on PPTC is defined as the matching probability. Finally, the correct matching results are achieved by the spectral matching method. The synthetic data experiments show its robustness by comparing with the other state-of-art algorithms and the real world data experiments show its effectiveness.

Fast identification of mural pigments at Mogao Grottoes using a LIBS-based spectral matching algorithm

To quickly identify the mineral pigments in the Dunhuang murals,a spectral matching algorithm(SMA)based on four methods was combined with laser-induced breakdown spectroscopy(LIBS)for the first time.The optimal range of LIBS spectrum for mineral pigments was determined using the similarity value between two different types of samples of the same pigment.A mineral pigment LIBS database was established by comparing the spectral similarities of tablets and simulated samples,and this database was successfully used to identify unknown pigments on tablet,simulated,and real mural debris samples.The results show that the SMA method coupled with the LIBS technique has great potential for identifying mineral pigments.

Shape correspondence for cel animation based on a shape association graph and spectral matching

We present an effective spectral matching method based on a shape association graph for finding region correspondences between two cel animation keyframes.We formulate the correspondence problem as an adapted quadratic assignment problem,which comprehensively considers both the intrinsic geometric and topology of regions to find the globally optimal correspondence.To simultaneously represent the geometric and topological similarities between regions,we propose a shape association graph(SAG),whose node attributes indicate the geometric distance between regions,and whose edge attributes indicate the topological distance between combined region pairs.We convert topological distance to geometric distance between geometric objects with topological features of the pairs,and introduce Kendall shape space to calculate the intrinsic geometric distance.By utilizing the spectral properties of the affinity matrix induced by the SAG,our approach can efficiently extract globally optimal region correspondences,even if shapes have inconsistent topology and severe deformation.It is also robust to shapes undergoing similarity transformations,and compatible with parallel computing techniques.

Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000–2015) data

Mapping croplands,including fallow areas,are an important measure to determine the quantity of food that is produced,where they are produced,and when they are produced(e.g.seasonality).Furthermore,croplands are known as water guzzlers by consuming anywhere between 70%and 90%of all human water use globally.Given these facts and the increase in global population to nearly 10 billion by the year 2050,the need for routine,rapid,and automated cropland mapping year-after-year and/or season-after-season is of great importance.The overarching goal of this study was to generate standard and routine cropland products,year-after-year,over very large areas through the use of two novel methods:(a)quantitative spectral matching techniques(QSMTs)applied at continental level and(b)rule-based Automated Cropland Classification Algorithm(ACCA)with the ability to hind-cast,now-cast,and future-cast.Australia was chosen for the study given its extensive croplands,rich history of agriculture,and yet nonexistent routine yearly generated cropland products using multi-temporal remote sensing.This research produced three distinct cropland products using Moderate Resolution Imaging Spectroradiometer(MODIS)250-m normalized difference vegetation index 16-day composite time-series data for 16 years:2000 through 2015.The products consisted of:(1)cropland extent/areas versus cropland fallow areas,(2)irrigated versus rainfed croplands,and(3)cropping intensities:single,double,and continuous cropping.An accurate reference cropland product(RCP)for the year 2014(RCP2014)produced using QSMT was used as a knowledge base to train and develop the ACCA algorithm that was then applied to the MODIS time-series data for the years 2000–2015.A comparison between the ACCA-derived cropland products(ACPs)for the year 2014(ACP2014)versus RCP2014 provided an overall agreement of 89.4%(kappa=0.814)with six classes:(a)producer’s accuracies varying between 72%and 90%and(b)user’s accuracies varying between 79%and 90%.ACPs for the individual years 2000–2013 and 2015(ACP2000–ACP2013,ACP2015)showed very strong similarities with several other studies.The extent and vigor of the Australian croplands versus cropland fallows were accurately captured by the ACCA algorithm for the years 2000–2015,thus highlighting the value of the study in food security analysis.

A Novel Fuzzy Inference System-Based Endmember Extraction in Hyperspectral Images

Spectral unmixing helps to identify different components present in the spectral mixtures which occur in the uppermost layer of the area owing to the low spatial resolution of hyperspectral images.Most spectral unmixing methods are globally based and do not consider the spectral variability among its endmembers that occur due to illumination,atmospheric,and environmental conditions.Here,endmember bundle extraction plays a major role in overcoming the above-mentioned limitations leading to more accurate abundance fractions.Accordingly,a two-stage approach is proposed to extract endmembers through endmember bundles in hyperspectral images.The divide and conquer method is applied as the first step in subset images with only the non-redundant bands to extract endmembers using the Vertex Component Analysis(VCA)and N-FINDR algorithms.A fuzzy rule-based inference system utilizing spectral matching parameters is proposed in the second step to categorize endmembers.The endmember with the minimum error is chosen as the final endmember in each specific category.The proposed method is simple and automatically considers endmember variability in hyperspectral images.The efficiency of the proposed method is evaluated using two real hyperspectral datasets.The average spectral angle and abundance angle are used to analyze the performance measures.

Generation of artificial earthquakes for matching target response unsmooth spectrum via wavelet package transform

The seismic records of target response spectrum used in the time-history analysis should be allowed to meet the norms. However, the previous fitting methods of target spectrum are mostly for the situations that the target spectrum is a smooth curve. In many cases, it needs to match unsmooth target spectrum for single determined response spectrum. An adjustment of time history via wavelet packet transform was presented, which is able to fit unsmooth target spectrum. It was found that there is a certain bias between the band center frequency of the component of seismic record after wavelet packet decomposition and the peak frequency of response spectra of wavelet packet components. For this reason, five strategies were presented to select iteration points, and the effects of the five strategies were compared with two calculation examples. It was turned out that the peak frequency of the response spectrum of wavelet packet component can lead to good fitting effect when it is selected as the iteration point. In the iteration process, it shows great promise in fitting non-smooth target spectrum and has a trend of converge.

Spectral Match Optimization Based on Grey Relational Analysis

A spectral match optimization based on grey incidence matrix was put forward to evaluate camouflage painting design.A synthetic degree of incidence (SDI) was defined to comprehensively reflect the spectrum similarity based on theory of grey incidence analysis.A grey optimization model for camouflage painting sheme was constructed on the basis of SDI and grey incidence matrix.Its weight values were determined according to area percentages of all components in the camouflage scene,and a quantitative ordering for various schemes could be obtained according to the evaluation coefficients.Experiment results show that the method mentioned in this paper can provide a quantitative basis for the camouflage decision-making,and it can also be used in other camouflage scheme selection.

On selection and scaling of ground motions for analysis of seismically isolated structures

A broader consensus on the number of ground motions to be used and the method of scaling to be adopted for nonlinear response history analysis （RHA） of structures is yet to be reached. Therefore, in this study, the effects of selection and scaling of ground motions on the response of seismically isolated structures, which are routinely designed using nonlinear RHA, are investigated. For this purpose, isolation systems with a range of properties subjected to bidirectional excitation are considered. Benchmark response of the isolation systems is established using large sets of unscaled ground motions systematically categorized into pulse-like, non-pulse-like, and mixed set of motions. Different subsets of seven to 14 ground motions are selected from these large sets using （a） random selection and （b） selection based on the best match of the shape of the response spectrum of ground motions to the target spectrum. Consequences of weighted scaling （also commonly referred to as amplitude scaling or linear scaling） as well as spectral matching are investigated. The ground motion selection and scaling procedures are evaluated from the viewpoint of their accuracy, efficiency, and consistency in predicting the benchmark response. It is confirmed that seven time histories are sufficient for a reliable prediction of isolation system displacement demands, for all ground motion subsets, selection and scaling procedures, and isolation systems considered. If ground motions are selected based on their best match to the shape of the target response spectrum （which should be preferred over randomly selected motions）, weighted scaling should be used if pulse-like motions are considered, either of weighted scaling or spectral matching can be used if non-pulse-like motions are considered, and an average of responses from weighted-scaled and spectrum-matched ground motions should be used for a mixed set of motions. On the other hand, the importance of randomly selected motions in representing inherent variability of response is recognized and it is found that weighted scaling is more appropriate for such motions.

Site specific probabilistic seismic hazard analysis at Dubai Creek on the west coast of UAE

A probabilistic seismic hazard analysis （PSHA） was conducted to establish the hazard spectra for a site located at Dubai Creek on the west coast of the United Arab Emirates （UAE）. The PSHA considered all the seismogenic sources that affect the site, including plate boundaries such as the Makran subduction zone, the Zagros fold-thrust region and the transition fault system between them; and local crustal faults in UAE. PSHA indicated that local faults dominate the hazard. The peak ground acceleration （PGA） for the 475-year return period spectrum is 0.17 g and 0.33 g for the 2,475-year return period spectrum. The hazard spectra are then employed to establish rock ground motions using the spectral matching technique.

A discrete model for response estimation of soil-structure systems with embedded foundations

The need for simplified physical models representing frequency dependent soil impedances has been the motivation behind many researches throughout history. Generally, such models are generated to capture impedance functions in a wide range of excitation frequencies, which leads to relatively complex models. That is while there is just a limited range of frequencies that really influence the response of the structure. Here, a new methodology based on the response-matching concept is proposed, which can lead to the development of simpler discrete models. The idea is then used to upgrade an existing simple model of surface foundations to the case of embedded foundations. The applicability of the model in both frequency domain and time domain analyses of soil-structure systems with embedded foundations is discussed. Moreover, the accuracy of the results is compared with another existing discrete model for embedded foundations.

High-power and high optical conversion efficiency diode-end-pumped laser with multi-segmented Nd：YAG/Nd：YVO-4

A novel flat-flat resonator consisting of two crystals（Nd：YAG ＋ Nd：YVO4） is established for power scaling in a diode-end-pumped solid-state laser. We systematically compare laser characteristics between multi-segmented（Nd：YAG ＋ Nd：YVO4） and conventional composite（Nd：YAG ＋ Nd：YAG） crystals to demonstrate the feasibility of spectral line matching for output power scale-up in end-pumped lasers. A maximum continuous-wave output power of 79.2 W is reported at 1064 nm, with Mx2= 4.82, My2= 5.48, and a pumping power of 136 W in the multi-segmented crystals（Nd：YAG ＋ Nd：YVO4）. Compared to conventional composite crystals（Nd：YAG ＋ Nd：YAG）, the optical-optical conversion efficiency of multi-segmented crystals（Nd：YAG ＋ Nd：YVO4） from 808 nm to 1064 nm is enhanced from 30% to 58.8%,while the laser output sensitivity as affected by the diode-laser temperature is reduced from 55% to 9%.

Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data

The goal of this study was to map rainfed and irrigated rice-fallow cropland areas across South Asia,using MODIS 250 m time-series data and identify where the farming system may be intensified by the inclusion of a short-season crop during the fallow period.Rice-fallow cropland areas are those areas where rice is grown during the kharif growing season(June–October),followed by a fallow during the rabi season(November–February).These cropland areas are not suitable for growing rabi-season rice due to their high water needs,but are suitable for a short-season(≤3 months),low water-consuming grain legumes such as chickpea(Cicer arietinum L.),black gram,green gram,and lentils.Intensification(double-cropping)in this manner can improve smallholder farmer’s incomes and soil health via rich nitrogen-fixation legume crops as well as address food security challenges of ballooning populations without having to expand croplands.Several grain legumes,primarily chickpea,are increasingly grown across Asia as a source of income for smallholder farmers and at the same time providing rich and cheap source of protein that can improve the nutritional quality of diets in the region.The suitability of rainfed and irrigated rice-fallow croplands for grain legume cultivation across South Asia were defined by these identifiers:(a)rice crop is grown during the primary(kharif)crop growing season or during the north-west monsoon season(June–October);(b)same croplands are left fallow during the second(rabi)season or during the south-east monsoon season(November–February);and(c)ability to support low water-consuming,short-growing season(≤3 months)grain legumes(chickpea,black gram,green gram,and lentils)during rabi season.Existing irrigated or rainfed crops such as rice or wheat that were grown during kharif were not considered suitable for growing during the rabi season,because the moisture/water demand of these crops is too high.The study established cropland classes based on the every 16-day 250 m normalized difference vegetation index(NDVI)time series for one year(June 2010–May 2011)of Moderate Resolution Imaging Spectroradiometer(MODIS)data,using spectral matching techniques(SMTs),and extensive field knowledge.Map accuracy was evaluated based on independent ground survey data as well as compared with available sub-national level statistics.The producers’and users’accuracies of the cropland fallow classes were between 75%and 82%.The overall accuracy and the kappa coefficient estimated for rice classes were 82%and 0.79,respectively.The analysis estimated approximately 22.3 Mha of suitable rice-fallow areas in South Asia,with 88.3%in India,0.5%in Pakistan,1.1%in Sri Lanka,8.7%in Bangladesh,1.4%in Nepal,and 0.02%in Bhutan.Decision-makers can target these areas for sustainable intensification of short-duration grain legumes.

Development of a new index for automated mapping of ratoon rice areas using time-series normalized difference vegetation index imagery

Over recent decades, the global demand for food has continued to grow, owing to population growth and the loss of arable land. Rice ratooning offers new opportunities for increasing rice production and has received renewed interest because of the minimal additional labor input required for its adoption. Regular, regional-scale monitoring of the spatial patterns of both traditional and ratoon rice cropping systems provides essential information for agricultural resource management and food security studies. However, the similar phenological characteristics of traditional double rice and ratoon rice cropping systems make it challenging to accurately classify these cropping practices based on satellite observations alone. In this study, we first proposed an improved phenology-based rice cropping area detection algorithm using moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) imagery. A new index, ratoon rice index, was then developed to automatically delineate ratoon rice cropping areas with the aid of a base map of rice in Hubei Province, China. The accuracy assessment using ground truth data showed that our approach could map both traditional and ratoon rice cropping areas with high user accuracy (91.25% and 91.43%, respectively). The MODIS-retrieved rice cropping areas were validated using annual agricultural census data, and coefficient of determination (R2) values of 0.60 and 0.41 were recorded for traditional and ratoon rice cropping systems, respectively. The total area of ratoon rice was estimated to be 1 283.6 km2, 5.0% of the total rice cropping area, in Hubei Province in 2016. These demonstrated the feasibility of extracting the spatial patterns of both traditional and ratoon rice cropping systems solely from time-series NDVI and field survey data and strides made in facilitating the timely and routine monitoring of traditional and ratoon rice distribution at subnational level. Given sufficient historical satellite and phenology records, the proposed algorithm had the potential to enhance rice cropping area mapping efforts across a broad temporal scale (e.g., from the 1980s to the present).