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Hu S.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education | Hu D.,Key Laboratory of Resources Environment and GIS of Beijing Municipal | Zhao W.,Capital Normal University
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2010

Vegetation is an important part of urban ecosystem; therefore timely access to vegetation coverage information is of great significance for monitoring urban ecological environment. Linear spectral mixture model (LSMM) was carried out for urban vegetation coverage extraction using medium-resolution Landsat TM remote sensing data. Meanwhile, the fuzzy c-means (FCM) method was chosen to extract vegetation coverage by improving the training sample selection method to obtain the end-member sample based on minimum noise transform (MNF), pixel purity index analysis (PPI), and N-dimensional visualization analysis. Finally, high-resolution SPOT5 remote sensing data extracted in two ways were used to carry out the accuracy test for vegetation coverage. The results showed that the correlation coefficients between the inspection data and LSMM-based and improved FCM-based data were 0. 8252 and 0. 9381, respectively. It indicated that the improved FCM-based method with higher accuracy can better eliminate the nonlinear effect of other elements. Source

Xiong Q.L.,Environment and Geographic Information System Key Laboratory of Beijing | Zhao W.J.,Environment and Geographic Information System Key Laboratory of Beijing | Gong Z.N.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education | Zhao W.H.,Beijing Municipal Environmental Monitoring Center
Advanced Materials Research | Year: 2013

Inhalable particles (PM10) and fine particles (PM2.5) have become the primary air pollutants in Beijing, seriously affecting visibility of the city, quality of the urban environment and the health of residents. To reflect the spatial and temporal variability condition of inhalable particles systematically in Beijing city in recent years, particulate matter of 0.3, 0.5,1.0, 3.0 and 5.0μm in heated period during 2007~2011 and non-heated period during 2007~2012 were measured in the field, statistical analysis about them was conducted. And spatial analytical method was used to study their distribution pattern. The results show that: (1) Differences of particle number concentration between heated period and non-heated period,were mainly reflected in PM0.3 and PM1.0. The mean concentration of PM0.3 (9.5E+07/ m3)in heated period was 2 times more of that (4.3E+07 /m3) in non-heated period. By contrast, the mean concentration of PM1.0 (5.6E+06/m3) in non-heated period was 27% more than that(4.4E+06/m3) in heated period; while concentration of other size was not very different. (2) The highest air pollution concentrations of particulate during non-heated period are in Fengtai District and Chaoyang District, which are respectively in the south and east of Beijing, followed by the city center. While the pollution in Shijingshan Dstrict in the west and Haidian District in the north was relatively lighter. (3) In heated period, the air particulate pollution of Beijing city was mainly concentrated in the east and southeast of Chaoyang District, as well as the city center and its surrounding area. © (2013) Trans Tech Publications, Switzerland. Source

Gao M.-L.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education | Gao M.-L.,Key Laboratory of Resources Environment and GIS of Beijing Municipal | Gao M.-L.,Capital Normal University | Zhao W.-J.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education | And 12 more authors.
Remote Sensing | Year: 2014

The availability of ZY-3 satellite data provides additional potential for surveying, mapping, and quantitative studies. Topographic correction, which eliminates the terrain effect caused by the topographic relief, is one of the fundamental steps in data preprocessing for quantitative analysis of vegetation. In this paper, we rectified ZY-3 satellite data using five commonly used topographic correction models and investigate their impact on the regression estimation of shrub forest leaf biomass obtained from sample plots in the study area. All the corrections were assessed by means of: (1) visual inspection (2) reduction of the standard deviation (SD) at different terrain slopes (3) correlation analysis of different correction results. Best results were obtained from the Minnaert+SCS correction, based on the non-Lambertian reflection assumption. Additional analysis showed that the coefficient correlation of the biomass fitting result was improved after the Minnaert+SCS correction, as well as the fitting precision. The R2 has increased by 0.113 to reach 0.869, while the SD (standard deviation) of the biomass dropped by 21.2%. Therefore, based on the facts, we conclude that in the region with large topographic relief, the topographical correction is essential to the estimation of the biomass. © 2014 by the authors; licensee MDPI, Basel, Switzerland. Source

Fan L.,Capital Normal University | Fan L.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education | Fan L.,Key Laboratory of Resources Environment and GIS of Beijing Municipal | Zhao W.-J.,Capital Normal University | And 9 more authors.
Jilin Daxue Xuebao (Diqiu Kexue Ban)/Journal of Jilin University (Earth Science Edition) | Year: 2012

Spectral feature is the physical basis of rock identification. In order to remove the rock spectral noise, the spectra including common 15 rock samples belonging to 10 rock types are pretreated by averaging, resampling, smoothing, and fitting the value of water vapor absorption band. The continuum removing methods are used to obtain absorption-band parameters of spectra. Among the rock samples, the mica slate's absorption feature is the most obvious. The normalized data studied by using R-mode principle factor method shows that the first principal factor axis represents the major absorption spectra of cations, anions and water vapor, and the second represents a small number of cation band. The characteristic spectral bands of the rock are 385-525 nm, 735-1365 nm, 1435-1785 nm, 1890-1952 nm and 1995-2310 nm. The physical meanings of these bands are also identified. The rock spectra are classified into four types by two-dimensional image analysis. From first type to last type, the spectra prove the gradually shallow absorption depth, the decreasing area, the gradually narrowing width and the increasing number of absorption peaks. Iron and pelitization alteration phenomenon are obvious. The classification results verified by cluster analysis are of better correspondence. A physical basis for rock classification and identification are provided by remote sensing technology. It is of significance to abstract effectively hyper spectral data and classify hyper spectra images. Source

Zhang M.,Capital Normal University | Zhang M.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education | Zhang M.,Key Laboratory of Resources Environment and GIS of Beijing Municipality | Gong Z.-N.,Capital Normal University | And 5 more authors.
Chinese Journal of Ecology | Year: 2016

Wetland is an ecosystem formed by the interaction of land and water; whose size is highly susceptible to climate change and human activities. In this report; we sampled Baiyangdian wetland; the largest natural lake wetland in the North China; by extracting and analyzing wetland information from the eleven remote sensing images during 1984-2013. Thirteen parameters derived from the climate; economic; population and agricultural aspects were evaluated by principal component analysis and the major driving forces affecting the wetland size were determined. The results revealed that the wetland size increased first and then decreased; followed by a slow and gradual increase with an overall descendent trend. The total area of Baiyangdian wetland was on average 25008 hm2 during 1984-1997 and 21573 hm2 during 1998-2013. Social and economic development, agricultural development and precipitation reduction were major driving factors, and social and economic developments were the most significant contributing factor. To curb the decreasing trend of the wetland size, we should effectively control the use of upstream water, improve water use efficiency, and essentially reduce the pressure of human activities on the wetland, thus naturally increasing water input in the wetland. © 2016, editorial Board of Chinese Journal of Ecology. All rights Reserved. Source

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