最新刊期
卷 22 ， 期 2 ， 2018
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摘要：A high-accuracy satellite platform is required to obtain remote-sensing images that meet the requirements of high image quality and high resolution for payload imaging. In practical engineering applications, the thermal deformation error caused by the thermal environment of star sensors is always neglected. Therefore, relative thermal deformation between star sensors will negatively affect altitude determination by dual sensors. Thus, the thermal deformation error must be identified and corrected. In this study, the thermal deformation model is established on the basis of satellite remote-sensing data and then corrected. The parameters of the thermal deformation model established using the Fourier series reflect the real results of on-orbit thermal deformation, and the magnitudes of sinusoidal and cosine functions in the Fourier series are determined. Then, the estimated parameters are used to compensate for the output of star sensors. Comparing the altitude error of star sensors before and after correction revealed that measurement precision improved by 40% after correction. Results showed that the proposed method for thermal deformation correction can improve the measurement precision of star sensors and reduce the influence of slow-frequency error on the precisions of altitude determination. The proposed method has potential engineering applications for obtaining high-quality images.关键词：remote sensing satellite;dual star sensors;thermal deformation;on-orbit correction;measurement precision- 491
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发布时间：2021-06-07 -
摘要：A Directional Polarization Camera (DPC) is a multi-angle multi-spectral wide-field polarization remote sensor that performs polarization measurement. Matching the divergence angle of the calibration light source with the corresponding field angle of the DPC pixel is important in achieving high-precision laboratory polarimetric calibration. A model of matching the divergence angle of the calibration light source with the corresponding field angle of the DPC pixel is established by comparing the state difference between on-orbit detection and laboratorial polarization calibration. This comparison is performed according to DPC on-orbit optical system imaging theory using the differential operation method. The divergence angle of the calibration light source should be larger than 0.14° to fulfill the polarization calibration requirement according to the analysis result of the model. The 499 nm polarization channel is taken as an example, and spectrum-tunable integrating spheres are used instead of the 0.125° divergence angle of quasi-parallel light as polarization calibration light source to test the validity of the model and the analysis result. Using spectrum-tunable integrating spheres instead of quasi-parallel light decreases the average deviations between the measurement DOLP of DPC and theoretical reference from 1.26×10–2 to 4.4×10–3. We validate the model of matching the divergence angle of the calibration light source with the corresponding field angle. The method that uses spectrum-tunable integrating spheres instead of quasi-parallel light satisfies the high-precision laboratory polarimetric calibration requirements of DPC for scientific applications.关键词：polarization remote sensor;polarization calibration;polarization calibration light source;divergence angle;precision verification- 545
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发布时间：2021-06-07 -
摘要：The photometric stability of lunar targets is high. The lunar irradiance reflected from the sun can be considered a benchmark for radiance calibration in the visible and near-infrared spectra. Meanwhile, lunar calibration is a new method of calibrating and validating satellite-based instruments. Therefore, a method that uses a lunar target as a stable radiation calibration target and the lunar irradiance model is introduced to carry out the radiation response tracking method of the FY-2 static meteorological satellite. Data from the FY-2E scanning radiometer from January 2010 to October 2014, which contain the moon target by orbit forecast, are collected. After a series of processes, including the extraction of lunar images, calculation of the lunar illumination model and satellite observation lunar irradiance, and correction of distance of sat–moon–sun, the response change of the visible band of the FY-2E scanning radiometer is obtained. Finally, the result is compared with that of the deep convective cloud radiometric calibration method. The main conclusions are as follows. (1) The total degradation of radiometric response is 9.2% with an annual decay rate of 1.96% by the lunar method. The uncertainty and the 95% confidence interval are 2.66% and ± 0.79%, respectively. The results are similar to that of the DCC method, and this affinity shows the validity of the lunar method. (2) The low quantization level (6 bit) and stray light of the FY-2 visible channel can affect the results. (3) In addition to the attenuation trend, the FY-2E radiation response shows the characteristics of seasonal cycle. The lunar radiometric calibration tracking method can effectively monitor sensor response attenuation and be used as radiometric benchmark for visible band calibration in the entire life of the sensor for the improvement of the accuracy of radiometric calibration.关键词：moon target;lunar irradiance model;FY-2;visible band;radiometric response change- 680
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发布时间：2021-06-07 -
摘要：Land surface albedo is an important surface parameter applied in surface energy balance. GF-4, which is the first geostationary orbit satellite that combines high spatial and temporal resolution in China, has great potential in obtaining regional albedo in the country. The present geostationary orbit satellites are relatively low in spatial resolution, and the observation ranges of most cannot cover all land areas because their orbitals are deviated from China. Multi-frequency observation cannot be easily realized in the country. Therefore, to address the problemsof short time and low spatial resolution of albedo products in China and obtain the albedo images of geostationary orbit satellite data, an albedo inversion method based on kernel-driven bidirectional reflectance distribution (BRDF), taking GF-4 stationary satellite data as data source, is constructed. Earth surface classification is integrated to provide an initial value to kernel factorsto explore the feasibility of semi-empirical kernel-driven BRDF model applied on GF-4 satellite data. Compared with the least squares fitting method, the Powell iterative optimization algorithm has better convergence effect and is thus used to optimize the result of the model. Then, the land surface narrowband albedos of each band can be gained through angle integration using the BRDF model. Therefore, narrowbandalbedo is converted into broadband for the GF-4 satellite data for the first time by using the Santa Barbara DISORT model and combining the spectral library with the spectral response function of the GF-4 satellite. Albedo inversion in visible (0.4—0.7 μm) and shortwave bands (0.3—3 μm) are acquired. Finally, a cross-validation experiment using Landsat8 reflectivity and MODIS albedo productsis conducted. The albedo comparison results retrieved by Landsat8 and GF-4 data shows that the accuracy of albedo in the visible band retrieved by GF-4 data is 85.6%, and that in the shortwave band retrieved by GF-4 is 93.4%. The albedo comparison results retrieved by MODIS and GF-4 data shows that the accuracy of albedo in the visible band retrieved by GF-4 data is 87.7%, and that in shortwave band retrieved by GF-4 data is 85.9%. The experiment indicates that albedo retrieved by GF-4 data has high accuracy, and GF-4 satellite albedo products have considerable potential applications. The algebraic inversion method that uses GF-4 satellite data successfully obtains high-resolution albedo imagesfrom a geosynchronous orbit satellite. If this method is further verified, then it can be used for the mass production of albedo products and address the problemsof short time and low spatial resolution. However, relevant verification work should be conducted due to the current lack of ground test data.关键词：GF-4 satellite;high frequency observation;land surface Albedo;BRDF;geostationary orbit- 541
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发布时间：2021-06-07
Chinese-Built Satellite
- 摘要：Gross primary productivity (GPP) is an important parameter in describing terrestrial ecosystem productivity. This review surveys the existing remote sensing GPP estimation algorithms including vegetation index based and light use efficiency based models and their accuracies, and summarizes two 1 km spatial resolution GPP product accuracy under eight different vegetation types. MOD17, which is the most commonly used GPP product, provides global-scale spatio-temporal continuous data. A strong correlation exists between global-scale MODIS/GPP and in-situ measurement (R2=0.59) with medium estimation accuracy (RMSE=2.86 gC/m2/day). Estimation accuracy is high in deciduous broadleaved and evergreen coniferous forests but low in evergreen broadleaved forests and savanna. Finally, we analyze the uncertainties in GPP estimation and verification with the remote sensing method and suggest possible approaches to improve the accuracy of GPP estimation and its development tendency.关键词：gross primary productivity;terrestrial ecosystem model;remote sensing GPP algorithm;MODIS/GPP product;BESS/GPP product;terrestrial carbon cycle;global change
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发布时间：2021-06-07
Review
- 摘要：The offshore wind energy industry has surged in recent years as a main source of clear energy. Meanwhile, remote sensing can retrieve sea surface wind data and provide valuable information to locate suitable offshore wind power plants. Published studies mostly focus on the retrieval of average wind speed and average wind power density. However, wind directional distribution is also required in locating potential offshore wind power plants. Therefore, a method is proposed to retrieve the directional distribution of wind energy from satellite scatterometer observations. According to Chinese national standard (GB/T 18710-2002), wind directional frequency and directional distribution of wind energy density are used to delineate the directional distribution of wind energy. In addition, certain circular statistical parameters of wind energy, circular mean, and circular standard deviation are selected to depict the characteristic of wind energy. Wind speed and directional data in certain timespans are used as input in the proposed method. These wind data can be obtained from satellite observations or reanalysis datasets. Then, 0.1°×0.1° global maps of wind energy directional distribution parameters are retrieved by the proposed method from 2007—2016 advanced scatterometer (ASCAT) wind products. These retrieval results are accordant with antecedent research and scientific facts. To test and verify these retrieved results, they are compared with parameters calculated from 20 NDBC buoys. First, the ASCAT wind products and buoy data are screened for quality control. Then, all buoy-measured winds are converted to 10 m height to match the ASCAT wind retrievals. Subsequently, a time and spatial matchup dataset of ASCAT and buoy data are built, and the differences between them are calculated. A non-parametric hypothesis test is also implied to assess the accuracy of circular error statistics. A total of 80% of the test dataset pairs passed all hypothesis tests and satisfied all assessment criteria (total difference <10%). Meanwhile, 100% of the dataset pairs satisfied the criteria and passed the test in which only wind direction parameters were considered. Furthermore, 90% of the dataset pairs passed the test for wind energy circular statistical parameters. In addition, 80% of the dataset pairs satisfied the total difference criteria of directional distribution wind energy. One model was constructed to describe the relation between the retrieval accuracy of wind directional distributions and record number using the law of large numbers and a basic understanding of the remote sensing process. The function that expresses the relation between record number and retrieval accuracy was obtained, and the minimal record number required to obtain reliable retrieval results was calculated with the aforementioned function by numerical stimulation and curve fitting. Moreover, the impact of the time characteristic of remote sensing data (fixed local time) was considered in the analysis. Models were built to describe the retrieval error of the remote sensing process and the actual offshore wind directional distributions on the basis of normal distribution and circular statistics. These models enabled us to understand the effect of the retrieval error of remote sensing quantitatively and qualitatively. Thus, the deconvolution algorithm was designed to eliminate this effect. Conclusion: (1) The proposed parameter systems can be retrieved by remote sensing data to depict the directional characteristics of wind energy thoroughly. (2) Two methods, namely, the total difference and the Kuiper test, were effectively used to test and verify the difference among the directional distributions. The Kuiper test results showed that the total difference identical criterion of the two directional distributions was built. (3) The validation demonstrated the effectivity and accuracy of the new method and the data product produced by this model. (4) At least 800 records were required for the reliable retrieval of DDED, and the number for DF was 350. (5) The error in the retrieval of wind direction from remote sensing data influenced not only the final retrieval accuracy of the directional distribution of wind energy but also the distribution itself. The more dispersed the distribution, the less the effect of the retrieval error of wind direction on the accuracy of directional distribution retrieval.关键词：offshore wind energy;wind directional distribution;ASCAT;wind direction frequency;wind power density;sea surface wind vector;direction statistics
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发布时间：2021-06-07 - 摘要：The low spatial resolution of hyperspectral images always leads to the “mixed pixel” problem, where multiple objects exist in one pixel. The unmixing of mixed pixels is vital to the quantitative application of hyperspectral remote sensing. Non-negative matrix factorization (NMF) is a hot spot in hyperspectral unmixing research because of its non-negative constraints and capability to process high-dimensional data. However, NMF-based unmixing algorithms are ineffective because of universality, local minima, and other restrictions; additional specific features of hyperspectral images should be explored. Hyperspectral remote sensing images have significant correlation features, such as spatial and spectral correlation. The present study aims to improve the unmixing effect by adopting correlation features of hyperspectral remote sensing images. An NMF-based hyperspectral unmixing algorithm with spatial and spectral correlation analyses, named NMF hyperspectral unmixing algorithm based on spatial and spectral correlation (NMFSSC), is proposed to address the universality and local minima problems of NMF. The proposed method adopts the correlation features of hyperspectral data in the unmixing process as the spatial correlation constraint of building adjacent pixels. The Markov Random Field (MRF) model and spectral correlation (piecewise smoothness) are used as constraints in building adjacent bands with complexity mapping technique. In this algorithm, the spatial correlation constraint of adjacent pixels is processed as the parallel and alternate step of the standard NMF object function. The spectral correlation of the adjacent bands is built as a new inner constraint of the standard function. During each iteration of the unmixing procedure, the distribution error of endmembers can be revised by the MRF-based spatial correlation constraint. The local minima problem can be revised by the complexity mapping constraint, thus potentially improving overall unmixing precision. Actual hyperspectral data with high and low spatial correlation are adopted in the experiments. Three algorithms, namely, Minimum Volume Constrained Nonnegative Matrix Factorization (MVCNMF), Piecewise Smoothness NMF with Sparseness Constraints (PSNMFSC), and NMF with Alternating Projected Subgradients (APSNMF), are used with NMFSSC in the experiments. Results indicate that the proposed NMFSSC algorithm can improve unmixing precision, especially when dealing with high-spatial-correlation test data. The unmixing precision of NMFSSC is lower on the low-spatial-correlation data than on the high-spatial-correlation set, but the method still shows certain advantages over the three reference algorithms. Therefore, NMFSSC has a wide-ranging application scope. In summary, the proposed algorithm can increase the unmixing accuracy of most actual hyperspectral remote sensing data, especially those with high spatial correlation. The local minima and universality problems of the standard NMF can be significantly addressed by adopting the MRF model and complexity mapping technique. However, the precision of the proposed algorithm can deteriorate as the correlation feature of hyperspectral data becomes increasingly vague. If the spatial and spectral correlations of the data are low, then the precision of the algorithm can be reduced. The next step is to widen the application scope of the unmixing algorithm and stabilize its performance.关键词：Nonnegative Matrix Factorization(NMF);pixel un-mixing;spatial correlation;spectral correlation;Markov Random Field(MRF);complexity mapping
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发布时间：2021-06-07 -
摘要：The size and amount of remote sensing images constantly increase with the improving resolution of remote sensing images. Meanwhile, the development of remote sensing applications also requires high image registration performance. Therefore, an automatic fast feature-level image registration method for high-resolution remote sensing images is proposed. The method includes five steps. First, the reference image and the image to be registered are processed by Haar wavelet transform to obtain the low-frequency approximate images to match. Then, the original images are registered according to the matching result of the approximate images, thereby potentially effectively reducing calculation and improving registration speed. Second, edges in the optical image are extracted by the Canny operator, and edges in the SAR image are extracted by the Ratio Of Averages (ROA) operator. Then, the edge line features are transformed into point features. The use of edge point features can achieve positioning accuracy and acquire stable features. Third, in the feature matching session, the main and auxiliary directions of the point features are considered such that each point feature has multiple directions to enhance the robustness of image registration. Then, the initial matching points are determined by the ratio of the minimum angle to the second minimum angle, which is less than a threshold. Fourth, in the matching point pair filtering session, the random sample consensus is enhanced to improve registration accuracy by adding the constraint condition. The high-quality matching point pairs are selected to fit the model parameters. Finally, in the affine session, the block thought is used to uniformly select matching point pairs to be evenly distributed in the image to avoid the local optimal problem on the registration and further improve image registration accuracy. To verify the efficiency of the method, experiments are conducted under the following conditions: the same sensor optical image registration and sensor SAR image registration, image registration among different bands, image registration with different resolutions, and image registration of different satellite sensors with large size. High resolution WorldView-2, Pleiades, and TerraSAR images are used to perform the experiments. The proposed method is compared with the typical SIFT and SURF algorithms. Four quantitative evaluation indexes, namely, Matching Ratio (MR), Matching Efficiency (ME), Root Mean Square Error (RMSE), and time consumed are used for the registration result evaluation. Experimental results show that the proposed method effectively achieves high registration accuracy under the different conditions. An automatic fast feature-level image registration method for high-resolution remote sensing images is proposed. Multiple datasets of registration experimental results for high-resolution remote sensing images indicate that the proposed method can be rapidly implemented and has high accuracy and strong robustness.关键词：remote sensing registration;high resolution remote sensing image automatic registration;image matching;feature matching;feature extraction- 573
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发布时间：2021-06-07 - 摘要：Features extracted from a single scale cannot effectively express differences among land objects and recognize object boundaries.Thus, hyperspectral image classification suffers from low classification accuracy and the “pepper-and-salt” phenomenon. In this context, we propose a set of multi-scale spatial features that is based on guided filtering to improve the performance of image classification in quantitative accuracy and visual interpretation. The structure-transferring property of the guided filtering is investigated to appropriately represent land objects with different sizes. The proposed feature extraction and classification algorithm consists of three steps. First, Principal Component Analysis (PCA) is used to reduce the dimensionality of hyperspectral images and remove noise. Second, the first several principal components that have the most amount of information are guided by the first principal component to obtain filtered features. Multi-scale features are extracted by guided filtering with increasing radii, which can represent structures of different land cover types. Finally, the feature set is fed into classifiers for image classification. We operated experiments on one synthetic and three hyperspectral datasets, namely, Pavia University, Pavia Center, and Salinas. Multiple multi-scale features, including multi-scale features based on guided filtering, multi-scale morphological, and multi-scale texture features, were extracted. Three advanced classifiers, namely, Support Vector Machine(SVM), Random Forest(RF), and K-Nearest Neighbor(KNN), were considered for comparison. The results of the experiments conducted on the synthetic data set showed that the proposed feature extraction method could better smooth the inner pixels of land objects while preserving object boundaries compared with multi-scale morphological features. Compared with the combination of multi-scale morphological features and SVM, the combination of multi-scale guided filtering features and SVM achieved a 6.5% increment in overall accuracy on the Pavia University dataset. The highest classification accuracies for the Pavia Centre and Salinas images were 98.51% and 98.39%, respectively.These resultswere achieved by the proposed multi-scale guided filtering method. A single scale cannot effectively represent the spatial information of land objects. Thus, multi-scale features are extracted using guided filtering. These features can preserve the spatial structures transferred from the guidance image and smooth the details of the input image due to the structure-transferring property of guided filtering. Land objects with various scales can also be effectively described by these multi-scale filtering features by setting different filtering window sizes. The quantitative results and visual inspection showthat multi-scale filtering features can effectively describe the structures of land objects in comparison with morphological and texture features and thus result in high classification accuracy and better visual quality. The proposed feature is suitable for analyzing land scenes with complicated structures, such as urban areas.关键词：hyperspectral image;guided filter;multi-scale feature;classification;spatial information
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发布时间：2021-06-07
Technology and Methodology
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摘要：The type and content of minerals can constrain the specifically geological environment where they form. Therefore, studying the identification and abundance retrieval of minerals on Martian surface is essential in understanding the geological structure and historical evolution of Mars. Eberswalde Crater, a hotspot of Mars exploration, possesses a complex hydrological system. However, the large-scale mineral retrieval in this region has rarely been studied. Hence, we used hyperspectral technology to quantitatively retrieve the mineral abundances in the delta region of Eberswalde. Furthermore, we analyzed the geological environment that possibly existed at that time on the basis of the distribution and content of minerals. This study adopted a sparse unmixing algorithm to quantitatively retrieve mineral abundances by using Targeted Reduced Data Records (TRDR), which are obtained by Compact Reconnaissance Imaging Spectrometer for Mars (CRISM), together with the CRISM spectral library. However, the high mutual coherence of spectral libraries limits the performance of sparse unmixing because the equation to be solved is ill conditioned and time consuming. Therefore, we used the hyperspectral signal identification by minimum error (Hysime) algorithm to analyze the signal subspace of CRISM data. All the mineral spectra of the spectral library were projected onto the subspace. The spectrum with small projection error was then retained as the endmember, which truly contributed to the observed mixtures. Finally, a collaborative sparse unmixing algorithm was applied to CRISM to retrieve the mineral abundances of the delta region in Eberswalde. The abundance maps show five types of primary minerals (pyroxene, olivine, plagioclase, siderite, diaspore) and one type of alteration minerals (tremolite). Pyroxene is mainly distributed in front of the alluvial fan. Olivine is distributed (east-west) in the central area. Plagioclase is mainly distributed in the western delta region and a small crater edge in the northeastern corner. Siderite, with relatively less content, is mainly distributed along the edge of the alluvial fan. Diaspore is mainly distributed along the river valley, and the relatively enriched diaspore in the northeastern corner was probably caused by the transportation of liquid water in the past. Tremolite is distributed in the northeastern corner of the delta region. We identified a similar trend in both curves by comparing mineral spectra obtained from images with correspondent spectra in the spectral library. The result of the unmixing was consistent with the mineral distribution in the spectral index map, as shown by the comparison of the abundance maps of the three main minerals, namely, plagioclase, pyroxene, and olivine, and the correspondent spectral index map, thereby showing the effectiveness of the inversion results in this study. A collaborative sparse unmixing algorithm was used to quantitatively retrieve the mineral abundances of the delta region in Eberswalde. Six types of minerals were found, namely, pyroxene, olivine, plagioclase, siderite, diaspore, and tremolite. From the perspective of mineralogy, the instability of pyroxene and olivine indicated that the area where they are distributed is close to provenance and the original provenance is ultrabasic rock (e.g., peridotite) and basic rock (e.g., gabbro), respectively. The existence of tremolite and siderite indicated metasomatism between the rich water and the carbon dioxide fluid in this area. The minerals in the area of the alluvial fan were distributed outside the alluvial fan by fluid transportation. The presence of tremolite in the northeastern corner of delta region reflected the existence of contact metamorphism before the alluvial fan.关键词：Mars;eberswalde crater;minerals;collaborative sparse unmixing;abundance retrival- 590
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发布时间：2021-06-07 -
摘要：The evolution process of the generation, development, and extinction of valley networks on Mars and its analog on Earth should be understood by conducting a comparative study from the viewpoint of comparative planetology, which may be ultimately meaningful for exploring the ancient life relics on Mars. The valley networks of Evros Vallis on Mars and Kaidu River in the Tarim Basin in Xinjiang are extracted from the Mars Orbiter Laser Altimeter (MOLA) and ASTER Global Digital Elevation Map (ASTER GDEM) data. Then, the morphometric and hydrological parameters, namely, the mean length of tributaries at all levels, mean sinuosity at all levels, drainage density, channel density, river gradient, and stream fractal dimension of the entire valley networks, are calculated and compared. Both valley networks are quasi-dendritic valley systems, and the quantitative calculation results show the following. (1) The mean length of tributaries at all levels of Evros Vallis is 1.4 to 2.5 times longer than that of Kaidu River, which indicates that the scale of Evros Vallis is generally larger. (2) The average of the mean sinuosity of tributaries at all levels of Evros Vallis is 1.19, which indicates straightness; that of Kaidu River is sinuous and larger, with an average value of 1.35. (3) The stream fractal dimensions of Evros Vallis and Kaidu River are 1.63 and 1.70, respectively, which demonstrates that the geomorphic development stage of both drainage basins is at the end of topographic infancy and the beginning of maturity. However, the drainage and channel densities of the former are much smaller than those of the latter, indicating that the overall development stage of the former is less than that of the latter. (4) The longitudinal profile of Evros Vallis shows a concave-down trend with a relative gentle channel. Its river gradient is 1.63‰, and the river gradient of Kaidu River is 3.74‰. Its longitudinal profile can be divided into two as follows: the source section is concave-down, with a gentle channel and river gradient of 2.54‰, and the estuary section is concave-up, with a steep channel and river gradient of 5.18‰. The morphometric and hydrologic parameters of Evros Vallis on Mars are similar to those of natural rivers on Earth. In addition, fluvial landforms are found in the main stream channel, desiccation mud crack polygons, and rampart craters of Evros Vallis, showing that water and/or ice once existed when Evros Vallis was dry, as observed on the downstream channel. These features strongly suggest that this drainage area was formed by a long time of runoff erosion. However, the water source and duration still require further studies by combining the research outcomes in regional and global paleogeography and paleoclimate.关键词：Martian surface;Evros Vallis;Kaidu river;morphometric characteristics;hydrological characteristics;quantitative comparison- 525
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发布时间：2021-06-07 -
摘要：The temporal and spatial variations in the Normalized Difference Vegetation Index (NDVI) were analyzed and the factors that affect the growth condition of different types of vegetation in Lake Taihu were identified using MODIS NDVI data gathered from 2000 to 2015. MOD13Q1 data were obtained with 16-day temporal resolution and 250 m spatial resolution. Projection transformation and irregular cutting were implemented according to the vector diagram of Lake Taihu. Then, abnormal values were eliminated by the band math module of ENVI 4.7 software (The range of NDVI is between –0.2 and 1). We analyzed the corresponding NDVI values and imported the results to MATLAB R2015b software according to the latitude and longitude that determine corresponding pixel points. The result indicated seasonal and inter-annual variations in the NDVI of aquatic vegetation in Lake Taihu. Annual minimum NDVI occurred in winter, and the maximum in August or September, reaching 0.35 with flourishing vegetation growth. The multi-year mean NDVI was 0.1, and the annual mean NDVI was the largest in 2007 at 0.14. The spatial distribution of NDVI and the different types of vegetation can be distinguished in Lake Taihu. The northwestern area of the lake (Zhushan Bay and Meiliang Bay) was covered by planktonic algae; the maximum value was larger than 0.2 in this area. The east area was mainly covered by submerged vegetation; the maximum value exceeded 0.6 in this region. In the different ecological areas of Lake Taihu, the responses of vegetation growth to meteorological factors differed. The seasonal NDVI variation of Lake Taihu was of single-peak type. The growth season of aquatic vegetation was from April to November. The inter-annual variability of spatial distribution of NDVI in the planktonic algae area could reflect the dynamics of cyanobacteria distribution. Submerged vegetation growth was positively correlated with mean air temperature. However, wind speed affected the growth of the planktonic algae.关键词：Lake Taihu;NDVI;temporal and spatial variation;meteorological factors- 822
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发布时间：2021-06-07 -
摘要：A trend analysis based on observations from GOME, SCIAMACHY, and OMI of the tropospheric NO2 column from 1996 to 2016 in North China Plain is presented. The columnar NO2 showed a rapid increase from 1996 to 2011, especially in Beijing, Tianjin, and Hebei. On the contrary, a significant decrease in tropospheric NO2 column was observed in North China Plain from 2012 to 2016 because of the effective control strategies from the twelfth Five-Year Plan. This study aims to investigate the spatial variations in tropospheric NO2 trend from 1996 to 2016 in North China Plain, from which the driving factors of economic development and polices were derived. First, the liner regression analysis method was used among tropospheric NO2 columns from GOME, SCIAMCHY, and OMI. Second, the spatial variations in NO2 trend in North China Plain were investigated using multivariate linear regression. Results showed that NO2 columns in North China Plain increased by 10.3% per year from 1996 to 2011, and then decreased by 8.77% per year from 2012 to 2016 because of the rapid economic development, environmental protection policy, and rainfall. From 1996 to 2011, high NO2 columns were mainly concentrated in Beijing, Tianjin, Tangshan, Baoding, Dezhou, Jinan, Nanjing, Changzhou, and Wuxi, with the value of NO2 columns being larger than 600×1013 molec·/cm2. Low NO2 columns were mainly concentrated in northern Hebei and southwestern Henan provinces, with the value of NO2 columns being less than 200×1013 molec·/cm2. The trend of NO2 columns had an acceptable agreement (0.54) with NO2 concentration in the space, indicating that the increase was mostly distributed in the region with high value. From 2012 to 2016, the high value of NO2 columns spread to southern Hebei, northern Henan, and western Shandong. Generally, the average NO2 column from 2012 to 2016 was considerably higher than that from 1996 to 2011. The trend of NO2 column decreased from 2012 to 2016 over North China Plain probably because of the effective control strategies implemented during the twelfth Five-Year Plan. In addition, tropospheric NO2 column showed a significant reduction during typical events in North China Plain, such as, Beijing Olympics, military parade, and Nanjing Youth Olympic Games. The tropospheric NO2 columns measured by GOME, SCIAMACHY, and OMI could be used to indicate the variations of NOx emissions. Results showed that the increase and decrease trends may be affected by rapid economic development, environmental protection policies, and rainfall.关键词：trend analysis;tropospheric NO2 columns;North China Plain;multi-source satellite remote sensing;long time period- 610
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发布时间：2021-06-07 -
摘要：The construction pace of the Middle-West urban agglomeration has greatly accelerated with the implementation of the “One Belt One Road” initiative and the new urbanization construction strategy. Adhering to the green concept of “intensive, energy saving, ecological development” and implementing a “people-oriented view” as core value have become the new trends. To understand the process of urban temporal-spatial growth pattern and driving forces, the urban spatial patterns at seven periods (1985, 1990, 1995, 2000, 2005, 2010, 2015) in Xi’an (the starting point of Silk Road) were extracted from multi-temporal Landsat satellite remote sensing data gathered in the past 30 years. Moreover, the quantitative and geometric characteristics of urban expansion were analyzed using the Urban Expansion Intensity Index (UEII), Urban Expansion Rate Index (UERI), and Compact Degree (CD). We analyzed the driving forces of urban expansion in Xi’an city from five aspects, such as population, Gross Domestic Product (GDP), macro policy (such as the integration of Xi’an and Xianyang), and traffic conditions. These measures were analyzed using social and economic statistical data in the same period. The results show the following. (1) Urban coverage increased from 107.44 km2 to 724.19 km2, which shows an expansion of 6.74 times. The annual average expansion area in the past 30 years was approximately 20.56 km2. UEII and UERI displayed a growth tendency after initial declines, simultaneously reaching the summit from 2005 to 2010. (2) The urban spatial pattern mainly expanded to the east, north, and northwest districts from 1985 to 2000. However, the trend moved to the west, south, and southwest areas in the next 15 years. Meanwhile, CD showed a rapid decrease of 0.367 to 0.262 from 1985 to 2000 and then slowly declined by 0.07 since 2000. (3) The urban area presented two power relations with GDP and displayed a linear positive correlation with population. Finally, government policy, such as the integration of Xi’an and Xian Yang, can influence the urban macro structure, scale of expansion and development, road traffic, and infrastructure-supporting construction. As a Middle-West China megacity, Xi’an plays a leading role in the new urbanization construction strategy. However, urban development faces problems, such as rapid population growth, insufficient water resources, and fragile ecological environment. Therefore, we suggest that the government take the “green, ecological, low-carbon” sustainable development path, improve the planning of ecological function areas, accelerate the construction of ecological barriers, reasonably allocate water resources, and develop competitive industries.关键词：Xi'an city;urban expansion;spatial-temporal change;remote sensing monitoring;driving forces analysis- 602
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发布时间：2021-06-07 -
Water index formulation and its effectiveness research on the complicated surface water surroundings
摘要：Surface water includes irreplaceable and nonrenewable resources for terrestrial life. However, the rapid urbanization is causing diverse changes in size, amount, and quality of surface water. Accurately extracting surface water from remote sensing images is important for water environmental conservation and water resource management. This study aims to formulate a Multi-Band Water Index (MBWI) that consistently improves surface water extraction accuracy in the presence of various environmental noises. A new MBWI is designed to improve the accuracy of surface water extraction by increasing spectral separability between water and non-water surfaces. The method uses the average reflectance of the pure pixel of the seven land cover types, namely, surface water, forest, mountainous shadow, high-reflectance building, low-reflectance building, farmland, and bare soil, obtained from a Landsat 7 image of the Qinhuai River basin acquired on October 12, 2015. In general, the common threshold method is a popular approach to obtaining the results of surface water extraction from remote sensing imagery. However, determining the optimal threshold is an iterative, complicated, and challenging process. The K-means clustering method is applied to automatically extract surface water to avoid the artificial errors in determining the optimum threshold from the MBWI map. Surface water mapping outputs derived from water index methods that are based on K-means cluster are used to analyze the extraction accuracy of water indexes under complicated land cover types. To validate the availability of MBWI, twelve existing water indexes are collected from 1985 to 2016 as the comparable methods of surface water extraction. Furthermore, six test sites with various impact aspects for extracting surface water, e.g., mountainous shadows, high building shadows, and dark built-up areas that are usually sources of surface water extraction errors, are selected from three images (one Landsat 7 image and two Landsat 8 images) from Nanjing, Nanning, and Yantai. Compared with the existing water indexes, our proposed MBWI yields acceptable surface water mapping outputs. The assessment factors, namely, average overall accuracy (98.62%), Kappa coefficients (0.95), commission errors (3.46%), and omission errors (3.74%), are better than those of the existing surface water extraction methods. Results show that certain water indexes are weak in identifying surface water from land cover types. The Tasseled Cap Wetness (TCW) index is not effective in eliminating mountainous shadows. TCW and Automated Water Extraction Index with no shadow (AWEInsh) inaccurately identify white high-reflectance building noises with surface water. The accuracy of surface water extraction is usually constrained by land cover types that display similar reflectance to surface water. Therefore, low-reflectance non-water surfaces exist more or less in surface water mapping outputs. The maximum reflectance of surface water is presented in visible light bands, whereas that of the non-water surfaces is in infrared bands. Moreover, surface water reveals similarly decreasing trends from green to infrared bands. A new water index, named MBWI, is formulated according to the band difference of water and non-water surfaces. This difference has important practical significance for water resource studies and applications.关键词：Qinhuai River Basin;multi-band water index;K-means cluster;accuracy analysis- 639
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发布时间：2021-06-07
Remote Sensing Applications
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