Gong Z.-N.,Capital Normal University |
Gong Z.-N.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education |
Gong Z.-N.,Key Laboratory of Resources Environment and GIS of Beijing Municipal |
Gong Z.-N.,Base of the State Laboratory of Urban Environmental Processes and Digital Modeling |
And 12 more authors.
Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves | Year: 2014
Quantitative estimation of emerged plant water content with multi-spectral remote sensing technique is of great significance for emerged plant physiological status and growth trend monitoring. The hyperspectral reflectance of canopy of wetland typical emerged plant (reed and cattail) was measured by Field-Spec 3 wild high-spectrum radiometer. The leaf water content and leaf area index (LAI) of corresponding samples were also measured. First of all, the ground spectral data (reed and cattail) were resampled to simulate the spectral of WorldView-2 imagery, then the simple ratio vegetation index (SR) and normalized difference vegetation index (NDVI) were constructed with arbitrary two band combination from the simulated WorldView-2 spectra, respectively. The correlation between canopy water content (CWC) and vegetation index were analyzed. The estimation models were obtained by using regression and correlation analysis for different emerged plant community. In addition, the research result of ground data was applied to WorldView-2 high resolution multispectral imagery covering the study area, and the CWC of emerged plant community was estimation in spatial scale. The results show that the SR and NDVI constructed by the simulated WorldView-2 spectra had a good overall correlation with CWC. The SR(8, 3)reedwas selected as the optimal vegetation index to estimate the CWCreed, the best models are evaluated and validated as y=0.005x+0.003. The NDVI(8, 3)cattailwas selected as the optimal vegetation index to estimate the CWCcattail, the best models were evaluated and validated as y=2.461x2-0.313x+0.032. According to two K-fold cross validation examination, these estimation models have the satisfactory prediction accuracy. The prediction accuracy of CWCreedwas 87.42% and the prediction accuracy of CWCcattailwas 82.12%. Furthermore, based on the research result of ground data, we made use of WorldView-2 high resolution multispectral imagery to map the CWC of different emerged plant community. According to the examination of measured data, the estimation RMSE of CWCreedand CWCcattailfrom imagery were 0.0048 and 0.0052, respectively. The estimation accuracy were 83.56% and 80.31%, respectively. It was demonstrated that using WorldView-2 high resolution multispectral imagery to estimate the CWC of wetland emerged plant community has a high feasibility. ©, 2014, Science Press. All right reserved.
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.
Gao M.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education |
Gong Z.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education |
Zhao W.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education |
Gao Y.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education |
Hu D.,Key Laboratory of Resources Environment
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2014
Biomass is an important indicator of ecosystem productivity, and it has a crucial influence on the formation and development of ecosystem structure. Shrubs are of the crucial component of the ecological system, and they are of great consequence to the ecological environment. In addition, shrubs are precious biological resources in arid and semi-arid region in the mountainous area, and shrubs are considerable associated tree species in the flat terrain area of urban at the same time. Actually, shrubs can grow well under drought and cold, no matter soil is luxuriant or not, dry or wet, that makes them play a major role in water and soil conservation, as well as ecological protection and restoration. Shrubs biomass is an important manifestation of the ecosystem productivity, and it has an enormous impact on the formation and development of the ecological system structure. Also, quantitative estimation of canopy biophysical variables, especially the biomass, is very crucial in different studies such as meteorology, agriculture and ecology. Meanwhile, remote sensing is an important data source to estimate the variables in large areas, and satellite based indices have been used in many researches to estimate biomass, leaf area index, and canopy cover. Today spectral signatures have been popular used in the remote sensing of vegetation variables. However, in areas of sparse vegetation covered, reflection of soil and rock can often greatly affect sensors'response to the ground vegetation canopy reflection, especially in mountainous areas, that makes separation of vegetation signals difficult. In this paper the authors tried to extract 10 different vegetation indices, respectively based on the HJ satellite data, high accuracy DEM data from ZY-III satellite data to estimate Vitex negundo canopy biomass in the study area in Beijing Jundu Mountain area, combined with field sampling data. A least-squares regression fitting model is presented to express quantitative relationship between vegetation indices and Vitex negundo canopy biomass in the study area in Beijing Jundu Mountain area. The authors obtained a good fitting model through the contrast analysis of the different models. Then using the optimal result model to estimate the Vitex negundo canopy biomass and map the Vitex negundo canopy biomass distributions in the study area. The results show that the multiple linear regression model created in this paper has better retrieval accuracy and predictive capability, with a very significant correlation coefficient of 0.856, and standard error 58.5 g/ m2, prediction standard error 98.1 g/ m2, and the coefficient of determination was 0.865. However, biomass regression model is subject to the limitation of the season and environmental conditions. In the different seasons, with different geographical conditions, the results are different from one another. With different sample combinations, the proposed model results changed not much, which showed that in a certain time and geographical conditions, method proposed in this paper had a stable of repeatability. Remote sensing and estimation of Vitex negundo canopy biomass in Beijing mountainous area, provide new ideas to the use of remote sensing technology in shrub community biomass monitoring, and have special meaning in the research into the evolution of ecological environment, as well as energy cycling.
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.
Gong Z.,Capital Normal University |
Gong Z.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education |
Gong Z.,Key Laboratory of Resources Environment and GIS of Beijing Municipal |
Gong Z.,Base of the State Laboratory of Urban Environmental Processes and Digital Modelling |
And 8 more authors.
International Journal of Remote Sensing | Year: 2014
Vegetation abundance is a critical indicator for measuring the status of vegetation. It is also important for evaluating the eco-environment of wetland. In this article, linear spectral mixture analysis (LSMA) and fuzzy c-means (FCM) classification methods were applied to estimate vegetation abundance in Wild Duck Lake Wetland, one of the typical freshwater wetlands in North China, based on Landsat Thematic Mapper (TM) data acquired on 27 June 2011. Due to its effectiveness in characterizing vegetation activity and greenness, the normalized difference vegetation index (NDVI) was incorporated into the six reflective bands of the Landsat TM image to provide enough dimensionality to support the use of the a five-endmember LSMA model, which includes terrestrial plants, aquatic plants, high albedo, low albedo, and bare soil. Then, a fully constrained LSMA algorithm was performed to obtain vegetation abundance in our study area. An FCM classification algorithm was also used to generate vegetation abundance. Finally, both results were modified using the extracted water area of Wild Duck Lake Wetland, which was obtained with the combination of NDVI and normalized difference water index. The root mean square error (RMSE) and the coefficient of determination (R2) were calculated to assess the accuracy of vegetation abundance by using a WorldView-2 multispectral image. Validation showed that although there were slight differences between the vegetation abundance images, they shared similar spatial patterns of vegetation distribution: high vegetation abundance values in agricultural areas and riparian areas, moderate in grassland areas, and low in residential areas. The FCM classification generated an R2 of 0.791, while the LSMA yielded a result with an R2 of 0.672. Additionally, the RMSE also indicated that the FCM classification can obtain a much better result than LSMA: the former's RMSE is 0.091 and the latter is 0.172. The result suggests that the FCM classification based on the nonlinear assumption can handle mixed pixels more effectively than LSMA. © 2013 Taylor & Francis.
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.
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.
Cui Y.,Capital Normal University |
Cui Y.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education |
Zhu L.,Capital Normal University |
Zhu L.,Key Laboratory of 3D Information Acquisition and Application of Ministry of Education |
And 2 more authors.
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2013
Object-oriented technique is a new method providing more accurate mapping product with higher detail. In this paper, TM images of 2010 were selected as the data sources. Based on object-oriented method, six categories information of west Liaohe river basin were extracted, including cultivated land, forest land, grassland (xero-mesophytes and hygro- mesophytes), water and unutilized land. Comparing and analyzing the spectral and spatial information among the categories, appropriate threshold were set in membership function. Meanwhile, the field spectral characteristics analysis was utilized to help in determining the appropriate grassland classification rules. Then combining classification tree, the automatic classification was accomplished and the general accuracy was 82. 13%. Moreover, we discussed the characteristic of vegetation distribution in study area. Using spatial analysis of GIS to statistic different vegetation area, different vegetation area in different counties and relationship between vegetation and first class river, the results showed: (1) forest land and grassland were predominant vegetation in study area, which area accounted for 38. 9% and 23. 3% respectively. (2) Forest land, cultivated land and hygro-mesopgytes were mainly distributed in counties which located in middle and lower reaches of the river. Influenced by human impact, cultivated land and forest land concentrated distribution in Horqin Left Middle Banner and Horqin Left Back Banner. (3) Forest land and hygro-mesophytes were mainly distributed in 10 km buffer zone of the first class river, cultivated land concentrated distribution in 5km buffer zone of the first class river.
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.
PubMed | Key Laboratory of 3D Information Acquisition and Application of Ministry of Education
Type: Journal Article | Journal: Guang pu xue yu guang pu fen xi = Guang pu | Year: 2012
Typical submerged plants, floating plants, emerged plants, hygrophyte plants, and mesophyte plants were chosen, and derivative method and continuum removal method were used to analyze the spectral characteristics and changing trend of plants along water environment gradient. Emerged plants and hygrophyte plants have the highest reflectance value; floating plants have lower value, while submerged plants take the lowest reflectance value due to the effect of water surface. Derivative method could emphasize the changed trends of original spectral curve, thus more characteristic bands could take on. Spectral curves reached the fastest increasing points around 520 and 710 nm, which could be considered as characteristics bands to distinguish submerged plants and others. Emerged plants and hygrophyte plants have the peak green value. According to water environment gradient from high to low, the red edges of submerged plants, floating plants and emerged plants increase, while hygrophyte plants and mesophyte plants have lower red edge value. Original spectral curves were translated to absorption curves by continuum removal, the absorption depth changes from low to high as follows: submerged plants < floating plants < merged plants < hygrophyte plants, while that is lower for mesophyte plants compared to hygrophyte plants. Absorption area increased along water environment gradient from high to low except mesophyte plants.