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Gao M.,Key Laboratory of 3D Information Acquisition and Application | Gao M.,Key Laboratory of Resources Environment | Gao M.,Capital Normal University | Gong H.,Key Laboratory of 3D Information Acquisition and Application | And 11 more authors.
GIScience and Remote Sensing | Year: 2016

The uneven distribution of solar radiation due to topographic relief can significantly change the correlation between reflectance and other features such as biomass in rugged terrain regions. In this article, we use the transfer theory to improve the Minnaert approach. After comparing topographic correction methods for Landsat 8 Operational Land Imager (OLI) and EO-1 Advanced Land Imager (ALI) imagery acquired from the mountainous region in Beijing, China, we used visual inspection, statistical analysis, and correlation analysis to evaluate the algorithms and performance of the proposed Minnaert-E approach. The results indicate that corrections based on non-Lambertian methods have better performance than those based on the Lambertian assumption. The correction performances can be ranked as the Minnaert-E, followed by the Minnaert and the SCS+C corrections, and, finally, the C-HuangWei correction, which performed the worst. We found that the Minnaert-E approach can effectively weaken the influence of terrain relief on pixels and restore the true reflectance of the pixels in the relief area. Further analysis indicates that the Minnaert-E has a better effect on image processing where the slope gradient is restricted to less than 10° or between 30° and 43°. © 2015 Taylor and Francis.


Gong Z.,Capital Normal University | Gong Z.,Key Laboratory of 3D Information Acquisition | Gong Z.,Key Laboratory of Resources Environment | Gong Z.,Base of the State Laboratory of Urban Environmental Processes and Digital Modeling | And 14 more authors.
International Journal of Applied Earth Observation and Geoinformation | Year: 2015

Vegetation abundance is a significant indicator for measuring the coverage of plant community. It is alsoa fundamental data for the evaluation of a reservoir riparian zone eco-environment. In this study, a sub-pixel Markov model was introduced and applied to simulate dynamics of vegetation abundance in theGuanting Reservoir Riparian zone based on seven Landsat Thematic Mapper/Enhanced Thematic MapperPlus/Operational Land Imager data acquired between 2001 and 2013. Our study extended Markov model'sapplication from a traditional regional scale to a sub-pixel scale. Firstly, Linear Spectral Mixture Analysis(LSMA) was used to obtain fractional images with a five-endmember model consisting of terrestrialplants, aquatic plants, high albedo, low albedo, and bare soil. Then, a sub-pixel transitive probabilitymatrix was calculated. Based on the matrix, we simulated statuses of vegetation abundance in 2010and 2013, which were compared with the results created by LSMA. Validations showed that there wereonly slight differences between the LSMA derived results and the simulated terrestrial plants fractionalimages for both 2010 and 2013, while obvious differences existed for aquatic plants fractional images, which might be attributed to a dramatically diversity of water level and water discharge between 2001and 2013. Moreover, the sub-pixel Markov model could lead to an RMSE (Root Mean Square Error) of0.105 and an R2 of 0.808 for terrestrial plants, and an RMSE of 0.044 and an R2 of 0.784 for aquatic plantsin 2010. For the simulated results with the 2013 image, an RMSE of 0.126 and an R2 of 0.768 could beachieved for terrestrial plants, and an RMSE of 0.086 and an R2 of 0.779 could be yielded for aquatic plants. These results suggested that the sub-pixel Markov model could yield a reasonable result in a short period. Additionally, an analysis of dynamics of vegetation abundance from 2001 to 2020 indicated that thereexisted an increasing trend for the average fractional value of terrestrial plants and a decreasing trendfor aquatic plants. © 2014 Elsevier B.V.


Hu Z.,Capital Normal University | Hu Z.,Key Laboratory of Resources Environment | Hu Z.,Laboratory of 3D Information Acquisition and Application | Wang Z.,Tianjin Institute of Urban Construction | And 4 more authors.
Journal of Natural Disasters | Year: 2013

In this study, a road flooding information extraction model based on high resolution satellite remote sensing imagery was researched. A road flooding information extraction system was developed through the realization of inter-programming among different software environments by combining remote sensing and geographic information system technologies. First, road information extraction rules were built by analyzing spectral, geometrical and textural characteristics of fused image, which can be generated from original high resolution multi-spectral satellite remote sensing imagery. The rules were utilized to make an object-oriented road information extraction model. Second, with the knowledge of pure water s very low reflecting rate in near and mid-infrared electromagnetic wave band, and considering the complexity caused by different environmental background, an adaptive water information extraction model was built. On above bases, a component-based communication and data sharing mechanism between the application environment of remote sensing and geographic information system was established. An interactive user interface that supports model running was then developed. It can provide a spatial overlap function, extract malfunctioned road from original roads, and apply to systems with specific requirements of road flooding information extraction for correlative works.


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.


Xing L.,Capital Normal University | Xing L.,Key Laboratory of Resources Environment | Hu D.,Capital Normal University | Hu D.,Key Laboratory of Resources Environment | And 2 more authors.
Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 | Year: 2011

Typhoon is one of the worst natural disasters in the world. Sustainable development of the social and economic of our country is restricted by the effect of Typhoon. High-intensity rainfall brought by Typhoon is an important factor in the formation of disaster. There are two factors, the hazard of the Typhoon disaster control factors and the vulnerability of the regions Typhoon disaster happened, to evaluate Typhoon disaster comprehensive hazard. The Typhoon disaster hazard evaluation and early warning system is developed using the Development Kit ArcEngine based on COM-GIS and integrating real-time rainfall data from the satellite. Collection and storage of the data of Typhoon, searching and visualization of the path of Typhoon, storage of the location of real-time Typhoon point, early Warning of real-time Typhoon point, forecast of the next Typhoon point, early warning of the path of Typhoon and Typhoon disaster hazard Evaluation functions and so on are realized. It provides scientific basis for the evaluation and forecast of disasters and command decision-making of Typhoon disaster control. © 2011 IEEE.


Li X.,Capital Normal University | Li X.,Key Laboratory of Resources Environment | Hu D.,Capital Normal University | Hu D.,Key Laboratory of Resources Environment | And 4 more authors.
Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 | Year: 2011

Regional precipitation-induced landslide is one of the major geologic hazards in our country, which features large areas of damage, simultaneity, sudden breakout and serious consequences. Especially in Sichuan province where has happened earthquake, tectonic changed, secondary disasters happened very frequently. It is essential to carry out the research into the forecast and early warning of precipitation-induced landslide at the beginning of the national campaign launched for the geologic hazard weather forecast and early warning. Sichuan province was chose as study area, remote sensing image and actual statistics was basic material, combined the rainfall data, analysis the relationship of spatial and temporal distribution of landslide and rainfall comprehensively, the sensitivity of shallow landslide in Sichuan and the critical value of rainfall that induced landslides was determined. And simulate prediction was made, the time was July 17, 2009. The whole method was practical and feasible, scientific basis could be provided for prevention and mitigation. © 2011 IEEE.


Liao T.,Capital Normal University | Liao T.,Key Laboratory of Resources Environment | Hu D.,Capital Normal University | Hu D.,Key Laboratory of Resources Environment | And 4 more authors.
Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 | Year: 2011

Selecting Sichuan Province as the study area, setting rainfall-induced shallow landslide hazard for the research objectives, choosing slope, fault zone, rivers, lithology, soil type and vegetation as the main evaluation factors of the environmental vulnerability assessment. Based on the landslides disaster database since 5.12 Earthquake in Sichuan Province, the weights of the evaluation factors are determined. Producing 2008-2010 environmental vulnerability assessment maps in Sichuan Province Using Analytic Hierarchy Process with the GIS software, and the Spatial resolution of which is 250 meters. The risk of the environmental vulnerability assessment maps are divided into five levels: Slight(I), mild(II), moderate(III), high(IV) and the highest (V) risk areas. From this study, we conclude that vulnerability is with temporal and spatial distribution, and it can be quantified effectively using AHP model. © 2011 IEEE.


Qin M.,Capital Normal University | Qin M.,Key Laboratory of Resources Environment | Zhong R.,Capital Normal University | Zhong R.,Key Laboratory of Resources Environment | And 2 more authors.
Proceedings - 2011 19th International Conference on Geoinformatics, Geoinformatics 2011 | Year: 2011

Soil moisture is an important factor for agricultural production and drought monitoring, and soil moisture retrieval for Tibetan plateau has an important practical significance for global climate change and flood monitoring. In this paper, the radiative transfer progress is built to measure the exchange from the soil surface to vegetation. In order to retrieval the soil moisture, the vegetation optical depth is calculated by microwave polarization difference index (MPDI), and brightness temperature data is obtained by AMSRE L3 data; at the same time, some surface soil parameters such as surface roughness and soil dielectric are estimated by establishing soil dielectric constant model. So the soil moisture result would be calculated by using microwave radiation transfer equation and the soil dielectric constant model. Finally the distribution of the soil moisture on Tibetan Plateau is obtained. © 2011 IEEE.

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