Feixue Li

Classification mapping and species identification of salt marshes based on a short-time interval NDVI time-series from HJ-1 optical imagery

Abstract Salt marshes are seen as the most dynamic and valuable ecosystems in coastal zones, and in these areas, it is crucial to obtain accurate remote sensing information on the spatial distributions of species over time. However, discriminating various types of salt marsh is rather difficult because of their strong spectral similarities. Previous salt marsh mapping studies have focused mainly on high spatial and spectral (i.e., hyperspectral) resolution images combined with auxiliary information; however, the results are often limited to small regions. With a high temporal and moderate spatial resolution, the Chinese HuanJing-1 (HJ-1) satellite optical imagery can be used not only to monitor phenological changes of salt marsh vegetation over short-time intervals, but also to obtain coverage of large areas. Here, we apply HJ-1 satellite imagery to the middle coast of Jiangsu in east China to monitor changes in saltmarsh vegetation cover. First, we constructed a monthly NDVI time-series to classify various types of salt marsh and then we tested the possibility of using compressed time-series continuously, to broaden the applicability of this particular approach. Our principal findings are as follows: (1) the overall accuracy of salt marsh mapping based on the monthly NDVI time-series was 90.3%, which was ∼16.0% higher than the single-phase classification strategy; (2) a compressed time-series, including NDVI from six key months (April, June–September, and November), demonstrated very little reduction (2.3%) in overall accuracy but led to obvious improvements in unstable regions; and (3) a simple rule for Spartina alterniflora identification was established using a scene solely from November, which may provide an effective way for regularly monitoring its distribution.

Using Construction Expansion Regulation Zones to Manage Urban Growth in Hefei City, China

AbstractThe management of urban land development, as well as the conservation and optimization of agricultural land and urban green space, is crucial for sustainable urban development. China has experienced rapid urbanization and industrialization since 1978, which brought unintended negative social and environmental consequences. Hefei, the capital of Anhui Province in eastern China, is identified by the Economist Intelligence Unit as one of the top 20 emerging cities in China. Its urbanized area grew from 29  km2 to 268  km2, an 824% increase, between 1980 and 2005. This paper reviews Hefei’s urban growth management since 1987. It then analyzes in detail the construction expansion regulation zone, an innovative measure proposed by the Ministry of Land and Resources China (MLRC). The regulation zone includes four types of zones: a permitted expansion construction zone, a conditionally permitted expansion construction zone, a restricted expansion construction zone, and a prohibited expansion construction ...

Topographic Mapping of Offshore Sandbank Tidal Flats Using the Waterline Detection Method: A Case Study on the Dongsha Sandbank of Jiangsu Radial Tidal Sand Ridges, China

The waterline detection method (WDM) based on satellite images is one of the most effective methods for constructing digital elevation models (DEMs) for tidal flats. The general practicability of the WDM has been demonstrated in previous studies for small areas. This article attempts to generate a DEM over a large offshore sandbank with a tidal flat area of more than 620 km2 by integrating the conventional WDM with a hydraulic model and multitemporal satellite images. For illustration purposes, a case study was conducted at the Dongsha sandbank, one of the largest sandbanks among the radial tidal sand ridges of Jiangsu Province, China. In this study, 34 multitemporal satellite images acquired at different tidal phases in 2006 were analyzed to detect the waterlines. The water level at each satellite overpass moment was simulated by a south Yellow Sea hydraulic model, and discrete waterline points were combined with the corresponding water levels to produce a topographic map. Compared with the DEM produced during the same period by the airborne light detection and ranging (LiDAR) data, the DEM derived from WDM effectively contains the average height error within 47 cm, which is satisfactory. All of these findings may be useful for researchers and local authorities, as the findings could be used as a reference for sandbank evolution research or to support environmental management, coast protection, and storm forecasting.

Toward a Method of Constructing Tidal Flat Digital Elevation Models with MODIS and Medium-Resolution Satellite Images

ABSTRACT Liu, Y.; Li, M.; Mao, L.; Cheng, L., and Li, F., 2013. Toward a method of constructing tidal flat digital elevation models with MODIS and medium-resolution satellite images. The terrain of tidal flats often varies remarkably over space and time, but few existing methods are capable of producing fine–spatiotemporal resolution digital elevation models (DEMs) for tidal flats. This research aims to fill the knowledge gap and propose a 6-step method to construct tidal flat DEMs by incorporating both moderate-resolution imaging spectroradiometer and medium-resolution satellite images. The six steps include: waterline extraction, water level simulation, height assignment, median filtering, waterline point fusion, and interpolation to DEMs. A case study was conducted at the Dongsha sandbank—one of the largest sandbanks among the radial tidal sand ridges of Jiangsu Province, China. The resultant DEMs were compared with the light detection and ranging–based DEMs for vertical accuracy assessment. The results show that the proposed method successfully shortens the temporal resolution of DEMs to 3 months, while retaining high spatial resolution and vertical accuracy. An additional analysis of seasonal sediment change for tidal flats based on the proposed method shows that the sediment deposition in the Dongsha sandbank apparently has a semiannual cycle—the tidal flats are deposited in winter and eroded in summer. All of these findings are valuable references for researchers and local authorities to conduct research on the evolution of tidal flats and to boost environmental management, coastal protection, and economic exploitation.

Thematic maps for county-level land use planning in Contemporary China

Land use thematic maps are essential for the implementation of land use planning. China launched the third round of its land use planning in 2003, and the making of land use thematic maps series is one of the innovations for the new planning. The objective of this paper is to provide information about generating county-level land use thematic maps. The study area, Dachang Hui Autonomous County (178 km2), is located in Northern China and shares a boundary with Beijing. Methods for generating thematic land use maps are presented. These thematic maps include an existing land use map, zoning map for proposed land use, prime farmland protection map, zoning map for construction land expansion, planned land consolidation map, and planned major land use projects map. The scale for these maps is 1:50,000. All these maps are useful for researchers and local government, allowing them to be used as a reference for the study of land use mapping and support land resource management and planning.

Toward a sustainable utilization of land resources in China: problems, policies, and practices.

China’s economy is growing explosively with double-digit rates of growth. However, behind the scenes of this economic miracle, a dark underbelly exists. The potential impact of the unsustainable use of land resources is increasing. Each parcel of land has a stationary geographic location, while its utilization is optional. The re-adjustment and optimization of land use patterns ought to be encouraged. Spatial reconstruction refers to the combination of various land elements, which can promote the rational and efficient allocation of land resources through a four-layer action framework: the development of unused land, urban renewal, ecological reconstruction, and spatial displacement. The feasibility and validity of these methods are illustrated by practical cases in different provinces in China. We thus propose that pursuing sustainable development and building an ecological civilization will be necessary for China in future decades.

Review of the methods of delimitation for the spatial scope of urban agglomeration

The delimitation of urban agglomeration region is a critical issue in urban studies. But there are no standard methods so far for the delimitation. Starting with the concept of urban agglomeration, this paper reviews the methods of the delimitation of urban agglomeration region. We sum up two types of the methodology of the delimitation of urban agglomeration region. We compare and analyze a variety of promising and representative methods such as the key indicators distribution analysis, radiant ability of central city-based analysis, modeling analysis, multi-factor overlay analysis and spatial correlation analysis. Based on such, the common characteristics of the existing methods are abstracted and further developments are discussed. Finally we conclude that the analysis based on the functional zones, emphasizing the relations between the cities and the mode of combining qualitative analysis with quantitative analysis are the developing trends of the method. Facing to the more emergences of the polycentric urban agglomeration and the network urban agglomeration, the method combining spatial statistical analysis based on GIS with the analysis of the flow data among cities would be a better choice for the delimitation of urban agglomeration region.

Data decomposition method for parallel polygon rasterization considering load balancing

It is essential to adopt parallel computing technology to rapidly rasterize massive polygon data. In parallel rasterization, it is difficult to design an effective data decomposition method. Conventional methods ignore load balancing of polygon complexity in parallel rasterization and thus fail to achieve high parallel efficiency. In this paper, a novel data decomposition method based on polygon complexity (DMPC) is proposed. First, four factors that possibly affect the rasterization efficiency were investigated. Then, a metric represented by the boundary number and raster pixel number in the minimum bounding rectangle was developed to calculate the complexity of each polygon. Using this metric, polygons were rationally allocated according to the polygon complexity, and each process could achieve balanced loads of polygon complexity. To validate the efficiency of DMPC, it was used to parallelize different polygon rasterization algorithms and tested on different datasets. Experimental results showed that DMPC could effectively parallelize polygon rasterization algorithms. Furthermore, the implemented parallel algorithms with DMPC could achieve good speedup ratios of at least 15.69 and generally outperformed conventional decomposition methods in terms of parallel efficiency and load balancing. In addition, the results showed that DMPC exhibited consistently better performance for different spatial distributions of polygons. A novel data decomposition method based on polygon complexity (DMPC) is presented.DMPC can effectively parallelize different polygon rasterization algorithms.Large-scale vector polygon data can be favorably addressed with this method.DMPC can perform consistently well with different spatial distributions of polygons.

Study on disparity of regional economic development based on geoinformatic Tupu and GWR model: a case of growth of GDP per capita in China from 1999 to 2003

Regional disparity of economic development in China is always greatly concerned by investigators domestic and abroad, and sets of models have been used in the analysis. Spatial dependence, which is hidden in the data with spatial attributes, usually is not taken into account in classical statistics methods, such as ordinary linear regression(OLR) model. Along with the development of spatial statistics, more and more attentions are paid on spatial interactions between observations in the study of regional disparity. Geographically weighted regression (GWR) is a simple but effective model to recognize spatial variation and local difference, which considers the influence of the spatially non-stationarity of the variables. In this study, GWR model and Geo-Informatic Tupu were used to analyze the disparity of regional economic development in China, taking GDP per capita in 1999 and 2003 as a case, which is usually used to measure level of economic development. GDP per capita in the 338 cities in 1999 were selected to simulate GDP per capita in 2003 and to analysis non-stationarity of the growth of GDP per capita. Using Geo-Informatic Tupu, A series of maps were processed to display patterns of local parameter estimates, such as local r-squares, the residual sum of squares, local residual and so on, to gain a better understanding of the degree of spatial non-stationarity in a relationship over space. We tested for geographic heterogeneity in the parameters and compare them to estimates obtained from global regression approaches. The results suggested there was heterogeneity in the regression coefficients across broad regions of China, and a one-size fits all approach to describe growth processes appeared simplistic. The GWR model improved over the OLR model, and it was able to better explain the variation in the data and to simulate GDP per capita with smaller errors than the OLR models.

Real-time interactive object extraction system for high resolution remote sensing images based on parallel computing architecture

Random Walks has less interaction, better accuracy and higher computing independency. We introduce local intensity entropy to modify the weight function in Random Walks, in order to consider not only the intensity change of adjacent pixels, but also the statistical features of regions. Then we put forward a real-time interactive object extraction system for high resolution remote sensing images based on improved Random Walks method, and implement this system on generalpurpose GPU with nVidia CUDA platform. Experiment results show that the improved Random Walks we provide could accurately extract the boundaries of residential area, water area, plant area as well as road networks. The whole system is built on NVidia 8800GTX GPU using CUDA platform, and still achieves real-time performance when dealing with high resolution RS images larger than 100M pixels.