Key Laboratory of 3D Information Acquisition and Application of Ministry
Key Laboratory of 3D Information Acquisition and Application of Ministry
Zhao S.,Capital Normal University |
Zhao S.,Beijing Laboratory of Water Resources Security |
Zhao S.,Key Laboratory of 3D Information Acquisition and Application of Ministry |
Zhao S.,Beijing Municipal Key Laboratory of Resources Environment and GIS |
And 5 more authors.
Acta Geographica Sinica | Year: 2015
Based on previous studies, the climate drought index can be used to assess the evolution trend of ecological environment under various arid climatic conditions. It is necessary for us to further explore the relationship between vegetation coverage (index) and climate drought conditions. Therefore, in this study, based on MODIS-NDVI products and meteorological observation data, the Palmer Drought Severity Index (PDSI) and vegetation coverage in North China were first calculated. Then the interannual variation of PDSI and vegetation coverage over 2001-2013 was analyzed by using a Theil-Sen slope estimator. Finally in an ecoregion perspective the correlation between them was discussed. The experimental results demonstrated that PDSI index and vegetation coverage value varied over different ecoregions. During the period 2001-2013, vegetation coverage increased in southern and northern mountains in North China, while it showed a decreasing trend in Beijing-Tianjin- Tangshan City Circle area and suburban agricultural zone. During the 13 years, the climate of the northeastern part of North China became more humid, while in the southern part of North China, it tended to be dry. According to the correlation analysis results, 73.37% of North China had a positive correlation between the vegetation coverage and climate drought index. A negative correlation was observed mainly in urban and periurban areas of Beijing, Tianjin, Hebei Province and Henan Province. In most parts of North China, drought conditions in summer and autumn had more influence on vegetation coverage. ©, 2015, Science Press. All right reserved.
Li H.,Capital Normal University |
Li H.,Key Laboratory of 3D Information Acquisition and Application of Ministry |
Li H.,Base of the State Laboratory of Urban Environmental Processes and Digital Modeling |
Gong Z.,Capital Normal University |
And 8 more authors.
Acta Geographica Sinica | Year: 2012
The reservoir wetland of Beijing, constitutes one of the important eco-systems in Beijing. The driving factors index system of Beijing reservoir wetland landscape evolution in the study area was built in the two aspects of the natural environment and socio-economy Natural driving factors include precipitation, temperature, entry water and groundwater depth; social economic driving factors include the resident population, urbanization rate and per capita GDP. Using TM images from 1984 to 2010 to extract reservoir wetland's spatial distribution information of Beijing, we analyzed the area of reservoir wetland change laws in nearly 30 years. The driving mechanism of reservoir wetland evolution in the study area was explored by the Logistic regression model in different periods. The results indicated that in different phases, the driving factors and their influence on reservoir wetland evolution had certain differences. During 1984-1998, the leading driving factors were annual average precipitation and entry water index with the contribution rate of Logistic regression being 5.78 and 3.50, respectively, which was mainly affected by natural environmental factors; from 1998 to 2004, the impact of human activities intensified and man-made reservoir wetland reduced, and the main driving factors were the number of residents, groundwater depth and urbanization rate with the contribution rate of Logistic regression 9.41, 9.18, and 7.77, respectively. During 2004-2010, reservoir wetland evolution was impacted by both natural and socio-economic factors, and the dominant driving factors were urbanization rate and precipitation with the contribution rate of 6.62 and 4.22, respectively.
Zhang M.,Capital Normal University |
Zhang M.,Key Laboratory of 3D Information Acquisition and Application of Ministry |
Zhang M.,Key Laboratory of Resources Environment and CIS of Beijing Municipal |
Gong Z.N.,Capital Normal University |
And 8 more authors.
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2016
Wetlands, unique ecosystems formed by the interaction of land and water, are susceptible to climate change and human activity. Landscape developmental processes are an important subject in the fields of geography and ecology. Landscape pattern index is an indicator of landscape structure, composition, and spatial configuration. In this paper, we discuss changes in landscape patterns in Baiyangdian wetland during 1984-2014, and the driving forces behind these changes, based on Landsat Thematic Mapper (TM) and GF-1 remote sensing images. A landscape classification system was formulated, and landscape pattern indices were selected at the landscape and class levels to reflect patterns in structural composition and spatial configuration and to analyze the evolution of the landscape. Our results showed that the area of emergent and submerged plants had decreased, and farmland and residential areas increased rapidly. Open water showed an “increasing-decreasing-increasing” tendency, while forest and bare land area did not change significantly in the study period. The wetland area (emergent plants + submerged plants + open water) decreased from 1984 to 2014, with an average area of 25008 hm2 before 1998 and 21573 hm2 after 1998. Emergent plants were the main cover type in Baiyangdian, covering 37%-61% of the total study area, followed by farmland, submerged plants, and open water. Interconversion among emergent plants, submerged plants, and open water occurred with changes in the hydrologic regime. Over the past three decades, farmland has had the largest average patch area, followed by emergent plants. Emergent plants had the highest patch area index and dimension index, indicating that this was a dominant cover type in the study area. In addition, the cohesion indices of farmland and emergent plants were highest and showed a smoothing trend, while residential areas, forestland, and bare land showed a discrete distribution, high degree of fragmentation, and inferior connectivity. Shannon’s diversity indices showed a decreasing trend in Baiyangdian from 1989 to 2004, during which the landscape pattern tended to be unstable, and cohesion indices and wetland connectivity increased. Shannon’s diversity indices, cohesion indices, and landscape heterogeneity increased between 1984 and 1989 and between 2004 and 2014. Population and economic development are major factors affecting changes in landscape patterns in Baiyangdian. © 2016, Ecological Society of China. All rights reserved.
Zhang Y.,Key Laboratory of 3D Information Acquisition and Application of Ministry |
Gong Z.,Key Laboratory of 3D Information Acquisition and Application of Ministry |
Gong H.,Key Laboratory of 3D Information Acquisition and Application of Ministry |
Zhao W.,Key Laboratory of 3D Information Acquisition and Application of Ministry
Journal of Geographical Sciences | Year: 2011
The landscape pattern of Beijing wetlands has undergone a significant change as a result of natural and artificial elements. Supported by remote sensing and GIS technology, using multi-temporal TM images from 1984 to 2008 in Beijing, this paper analyzed the dynamic characteristics of wetlands landscape pattern through selected typical indices including patch area, patch average area, fractal dimension index, diversity, dominance, contagion indices and the spatial centroids of each wetlands type were calculated. Finally, the paper explored the evolution mode and driving factors of wetland landscape pattern. The results were obtained as follows: the total wetland area increased during the period 1984-1996, then decline from 1996 to 2004. The wetland area in 1994 accounted for only 47. 37% of that in 2004. The proportion of artificial wetland area was larger than that of natural wetland. The proportion of reservoir wetland was 33. 50% to 53. 73% and had the maximum average area. pond and paddy field wetland type with the least average area accounted for 16. 46% to 45. 09% of the total wetland area. The driving forces of the natural river wetland were mainly natural elements; its fractal dimension index was greater than the others. The Shannon diversity index of wetland landscape increased from 1. 11 in 1992 to 1. 34 in 2004, indicating that the difference between proportions of each wetland type decreased and areas of each wetland type were evenly distributed. The contagion index went down from 65. 59 to 58. 41, indicating that the connectivity degraded. Miyun Reservoir had the largest area and its area change had a great impact on the location of the centroid. Wetland resources degenerated gradually from the joint effects of natural and artificial factors. During the period 2006-2008, the precipitation increased and the drought condition was relieved. The government implemented series of positive policies to save water resources, and the wetland area increased. © 2011 Science China Press and Springer-Verlag Berlin Heidelberg.