Chunfang Kong

Suitability evaluation of urban construction land based on geo-environmental factors of Hangzhou, China

Suitability evaluation of urban construction land based on geo-environmental factors is the process of determining the fitness of a given tract of land for construction. This process involves a consideration of the geomorphology, geology, engineering geology, geological hazards, and other geological factors and is the basis of urban construction land planning and management. With the support of Geographic Information Systems (GIS), grid analysis, and geo-spatial analysis techniques, four factor groups comprising nine separate subfactors of geo-environmental attributes were selected to be used in the evaluation of the suitability level for construction land in Hangzhou. This was based on K-means clustering and back-propagation (BP) neural network methods due to their advantages in fast computing, unique adaptive capacity, and self-organization. Simultaneously, the evaluation results based on K-means clustering and BP neural network were compared and analyzed, and the accuracy evaluation was set. The results showed that the geo-environmental suitability evaluation results of construction land based on K-means clustering and BP neural network were similar in terms of the distribution and scale of construction land suitability level. At the same time, the results of the two evaluation methods were consistent with the variability in suitability level, engineering geology, and hydrogeology of Hangzhou. The results also showed that the real advantage of the methods proposed in this paper lies in their capacity to streamline the mapping process and to ensure that the results are consistent throughout. The suitability level of the urban construction land based on the geo-environment in Hangzhou was divided into four construction sites: land for building super high-rise and high-rise buildings, land for building multistorey buildings, land for low-rise buildings, and nonbuilding land. The results of the suitability evaluation for each category will provide a scientific basis for decision-making in urban development in Hangzhou.

Changes of urban wetlands in Wuhan, China, from 1987 to 2005

Urban wetlands play a significant role in the sustainable development of the urban eco-environment. However, accelerated urbanization has caused rapid changes in urban wetland landscape patterns, which may seriously affect their functions. Based on land-use maps, TM images, and field data from the Wuhan wetlands, the spatiotemporal evolution and wetland landscape pattern were quantitatively analyzed, with reference to landscape ecology indices of diversity, fragmentation, dominance, shape, and dimension. The results showed that: (1) the natural wetland area decreased: lake wetlands and marsh wetlands decreased by 18.71% and 50.3% from 1987 to 2005, respectively; (2) artificial wetland area increased by 47.75% in Wuhan over the same period; (3) the lake wetland area of Wuhan declined due to the conversion of large lakes to smaller ones; (4) the value of the diversity index (H), evenness index (E), and fragmentation index (F) decreased, while the value of the dominance index (D) increased from 1987 to 2005; (5) the landscape shape index (LSI) and fractal dimension (FD) of the river wetlands, lake wetlands, bottomland wetlands, and marsh wetlands decreased, while the LSI and FD of the reservoir and pond wetlands increased from 1987 to 2005; and (6) natural, societal, and economic, as well as human, activities are major factors for the structural changes in the Wuhan wetland landscape, as revealed by canonical correlation analysis. Results suggest that the ecological environment of urban wetlands should be protected to maximize the services of urban wetland ecosystems in Wuhan, China.Urban wetlands play a significant role in the sustainable development of the urban eco-environment. However, accelerated urbanization has caused rapid changes in urban wetland landscape patterns, which may seriously affect their functions. Based on land-use maps, TM images, and field data from the Wuhan wetlands, the spatiotemporal evolution and wetland landscape pattern were quantitatively analyzed, with reference to landscape ecology indices of diversity, fragmentation, dominance, shape, and dimension. The results showed that: (1) the natural wetland area decreased: lake wetlands and marsh wetlands decreased by 18.71% and 50.3% from 1987 to 2005, respectively; (2) artificial wetland area increased by 47.75% in Wuhan over the same period; (3) the lake wetland area of Wuhan declined due to the conversion of large lakes to smaller ones; (4) the value of the diversity index (H), evenness index (E), and fragmentation index (F) decreased, while the value of the dominance index (D) increased from 1987 to 2005;...

Classification and Extraction of Urban Land-Use Information from High-Resolution Image Based on Object Multi-features

ABSTRACT Urban land provides a suitable location for various economic activities which affect the development of surrounding areas. With rapid industrialization and urbanization, the contradictions in land-use become more noticeable. Urban administrators and decision-makers seek modern methods and technology to provide information support for urban growth. Recently, with the fast development of high-resolution sensor technology, more relevant data can be obtained, which is an advantage in studying the sustainable development of urban land-use. However, these data are only information sources and are a mixture of “information” and “noise”. Processing, analysis and information extraction from remote sensing data is necessary to provide useful information. This paper extracts urban land-use information from a high-resolution image by using the multi-feature information of the image objects, and adopts an object-oriented image analysis approach and multi-scale image segmentation technology. A classification and extraction model is set up based on the multi-features of the image objects, in order to contribute to information for reasonable planning and effective management. This new image analysis approach offers a satisfactory solution for extracting information quickly and efficiently.

Dynamic changes in Tangxunhu wetland over a period of rapid development (1953–2005) in Wuhan, China

Tangxunhu wetland is one of China’s largest freshwater lakes and plays a significant role in the sustainable development of the city of Wuhan. Based on terrain maps, TM images, and statistical data from 1953 to 2005, the spatial characters and changing features of Tangxunhu wetland were quantitatively assessed by calculating the landscape metrics of shape index (SI), fractal dimension (D), and stability index (S). The results showed that Tangxunhu wetland had meandrous development over the past 53 years, withSI, D, and S decreasing from 1953 to 1967, increasing from 1967 to 2000, and then decreasing again from 2000 to 2005.SI, D, andS were lowest in 1967, indicating maximuminstability, but highest in 2000, indicating maximum stability. These changes in Tangxunhu wetland were associated with various natural, social, and economic factors.

GEO-Environmental Suitability Evaluation of Land for Urban Construction Based on A Back-Propagation Neural Network and GIS: A Case Study of Hangzhou

Evaluating the geo-environmental suitability of land for urban construction is an important step in the analysis of urban land use potential. Using geo-environmental factors and the land use status of Hangzhou, China, a back-propagation (BP) neural network model for the evaluation of the geo-environmental suitability of land for urban construction was established with a geographic information system (GIS) and techniques of grid, geospatial, and BP neural network analysis. Four factor groups, comprising nine separate subfactors of geo-environmental features, were selected for the model: geomorphic type, slope, site soil type, stratum steadiness, Holocene saturated soft soil depth, groundwater abundance, groundwater salinization, geologic hazard type, and geologic hazard degree. With the support of the model, the geo-environmental suitability of Hangzhou land for urban construction was divided into four suitability zones: zone I, suitable for super high-rise and high-rise buildings; zone II, suitable for multi-story buildings; zone III, suitable for low-rise buildings; and zone IV, not suitable for buildings. The results showed that a BP neural network can capture the complex non-linear relationships between the evaluation factors and the suitability level, and these results will support scientific decision-making for urban-construction land planning, management, and rational land use in Hangzhou.

Using methane dynamic model to estimate methane emission from natural wetlands in China

Natural wetlands are the largest land-based natural sources for methane (CH4) emissions. Chinas natural wetland area accounts for about 4% of the area of the natural wetlands worldwide. Based on the data of global lakes and wetlands, in this study we conducted modeling work of CH4 emissions from natural wetlands in China by using terrestrial ecosystem model (TEM) of the 1995–2005. The results show that Chinas terrestrial natural wetland based CH4 emission is 7.48Tg/a, which is mainly distributed in the Qinghai-Tibet Plateau and in northwest region of China accounting for 68% of the emissions nationwide. Lake wetlands, marsh/floodplains and seasonal wetland are the major three types of wetlands are the major sources of CH4 emissions in China, accounting for 65% of total emissions. Monthly simulations of CH4 emissions from 1995–2005 show that regional maximum on CH4 emissions are closely related to soil temperatures and in the period of June, July and August, of which the emission maximum is in July. These simulation based estimates will be of great importance to Chinas climate change and greenhouse gas control study.

Urban construction land suitability evaluation based on the BP neural network: A case study on Hangzhou

Urban construction land suitability evaluation is an important reference on urban construction land planning and use potential analysis. With the support of the GIS and Back-propagation (BP) neural network, the suitability of the Hangzhou urban construction land was divided into four levels: a construction land suitability zone I suitable for super high-rise and high-rise buildings, a construction land suitability zone II suitable for multi-story buildings, a construction land suitability zone III suitable for low-rising buildings, and construction land suitability zone IV not suitable for buildings. The results showed that the BP neural network can commendably capture the complex non-linear relationship between the evaluation factors and the suitability level. The research results will support the scientific decision-making for Hangzhou urban construction land planning and management and rational utility.

Dynamic evolution study of wetland landscape pattern in urban Wuhan based on TM images

Based on analysis of the terrain maps, remote sensing images, statistic data of wetland of Wuhan urban from 1985 to 2005, and with the technology of Remote Sensing (abbr. RS) and Geographic Information System (abbr. GIS), the wetland landscape spatial database and attribute database of Wuhan urban are set up using ARCGIS software of the year of 1985, 1995 and 2005. At the same time, according to fractal geometry and landscape ecological methodology and the theories, we can quantitatively analyze the form characters, evolution rules, and change factors of the wetland landscape pattern of Wuhan urban by calculating its diversity index, dominance index, equality index, fragmentation index, isolation index and fractal dimension, and so on. As a result, the wetlands form characters and evolution process of Wuhan urban are compared and analyzed; its time-spatial evolution character during the past 20 years is demonstrated. In the end, some advice will be given that human beings should adjust land-use structure in lake districts, reasonably develop, recover and reconstruct positive eco-environment, and promote its sustainable development in Wuhan urban according to its ecological environment characteristics.

Wetland landscape pattern evolvement character and its driving mechanism based on TM images of Hubei Province

Wetland, as an ecosystem with special functions, is the transitional areas between water and land in the earth, which has the richest biology diversity in nature, and is one of the most important surviving environments of human beings. Based on analysis of the terrain maps, remote sensing images, statistic data of wetland of Hubei province from 1985 to 2005, and with the technology of Remote Sensing (abbr. RS) and Geographic Information System (abbr. GIS), the wetland landscape spatial database and attribute database of Hubei province are set up using ARCGIS software of the year of 1985, 1995 and 2005.At the same time, according to fractal geometry and landscape ecological methodology and the theories, we can quantitatively analyze the form characters, evolution rules, and change factors of the wetland landscape pattern of Hubei provinces by calculating its diversity index, dominance index, equality index, fragmentation index, isolation index and fractal dimension, and so on. As a result, the wetlands form characters and evolution process of Hubei province are compared and analyzed; its time-spatial evolution character and mechanism during the past 20 years are demonstrated. And various natural and social factors, human activities, and driving forces which exert a significant impact on the evolution of Hubei province wetland are anatomized here. In the end, some advice will be given that human beings should adjust land-use structure in lake districts, reasonably develop, recover and reconstruct positive ecoenvironment, and promote its sustainable development in Hubei province according to its ecological environment characteristics.

Extraction of the fault information in recognizing and partitioning the spatial structure of basin group in the south of north of China

The fault is one of main studying objects in remote sensing of geology. It reflects the causation and basic characters of diastrophism. For the complexity and uncertainty characteristic of remote sensing information, this paper discusses how to fuse the information of remote sensing and geosciences based on traditional statistics and intelligence technique puts forward the theory of remote sensing image comprehending agent and builds the model of automatic extracting. Then, based on the theory and model, this paper analyzes the spectrum of fault, and completes the extraction, quantitive statistic analysis and spatial analysis for fault on remote sensing image to reveal the distribution rules and spatial structures to provide the sustainment for understanding the geological structure and tectonic of whole area.