Study on spatial pattern of land-use change in China during 1995-2000

It is more and more acknowledged that land-use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. Supported by the Landsat TM digital images, spatial patterns and temporal variation of land-use change during 1995 -2000 are studied in the paper. According to the land-use dynamic degree model, supported by the 1km GRID data of land-use change and the comprehensive characters of physical, economic and social features, a dynamic regionalization of land-use change is designed to disclose the spatial pattern of land-use change processes. Generally speaking, in the traditional agricultural zones, e.g., Huang-Huai-Hai Plains, Yangtze River Delta and Sichuan Basin, the built-up and residential areas occupy a great proportion of arable land, and in the interlock area of farming and pasturing of northern China and the oases agricultural zones, the reclamation I of arable land is conspicuously driven by changes of production conditions, economic benefits and climatic conditions. The implementation of "returning arable land into woodland or grassland" policies has won initial success in some areas, but it is too early to say that the trend of deforestation has been effectively reversed across China. In this paper, the division of dynamic regionalization of land-use change is designed, for the sake of revealing the temporal and spatial features of land-use change and laying the foundation for the study of regional scale land-use changes. Moreover, an integrated study, including studies of spatial pattern and temporal process of land-use change, is carried out in this paper, which is an interesting try on the comparative studies of spatial pattern on change process and the change process of spatial pattern of land-use change.

STUDY ON THE SPATIAL PATTERNS OF LAND-USE CHANGE AND ANALYSES OF DRIVING FORCES IN NORTHEASTERN CHINA DURING 1990-2000

Land-use change is an important aspect of global environment change. It is, in a sense, the direct result of human activities influencing our physical environment. Supported by the dynamic serving system of national resources, including both the environment database and GIS technology, this paper analyzed the land-use change in northeastern China in the past ten years (1990 - 2000). It divides northeastern China into five land-use zones based on the dynamic degree (DD) of land-use: woodland/grassland - arable land conversion zone, dry land - paddy field conversion zone, urban expansion zone, interlocked zone of farming and pasturing, and reclamation and abandoned zone. In the past ten years, land-use change of northeastern China can be generalized as follows: increase of cropland area was obvious, paddy field and dry land increased by 74. 9 and 276. 0 thousand ha respectively; urban area expanded rapidly, area of town and rural residence increased by 76. 8 thousand ha; area of forest and grassland decreased sharply with the amount of 1399. 0 and 1521. 3 thousand ha respectively; area of water body and unused land increased by 148. 4 and 513. 9 thousand ha respectively. Besides a comprehensive analysis of the spatial patterns of land use, this paper also discusses the driving forces in each land-use dynamic zones. The study shows that some key biophysical factors affect conspicuously the conversion of different land- use types. In this paper, the relationships between land- use conversion and DEM, accnmlated temperature(>= 10 degrees C) and precipitation were analysed and represented. We conclude that the land- use changes in northeast China resulted from the change of macro social and economic factors and local physical elements. Rapid population growth and management changes, in some sense, can explain the shaping of woodland/grassland - cropland conversion zone. The conversion from dry land to paddy field in the dry land - paddy field conversion zone, apart from the physical elements change promoting the expansion of paddy field, results from two reasons: one is that the implementation of market-economy in China has given farmers the right to decide what they plant and how they plant their crops, the other factor is originated partially from the change of dietary habit with the social and economic development. The conversion from paddy field to dry land is caused primarily by the shortfall of irrigation water, which in turn is caused by poor water allocation managed by local governments. The shaping of the reclamation and abandoned zone is partially due to the lack of environment protection consciousness among pioneer settlers. The reason for the conversion from grassland to cropland is the relatively higher profits of fanning than that of pasturing in the interlocked zone of farming and pasturing. In northeastern China, the rapid expansion of built-up areas results from two factors: the first is its small number of towns; the second comes from the huge potential for expansion of existing towns and cities. It is noticeable that urban expansion in the northeastern China is characterized by gentle topographic relief and low population density. Physiognomy, transportation and economy exert great influences on the urban expansion.

NDVI spatial pattern and its differentiation on the Mongolian Plateau

GIMMS NDVI database and geo-statistics were used to depict the spatial distribution and temporal stability of NDVI on the Mongolian Plateau. The results demonstrated that: (1) Regions of interest with high NDVI indices were distributed primarily in forested mountainous regions of the east and the north, areas with low NDVI indices were primarily distributed in the Gobi desert regions of the west and the southwest, and areas with moderate NDVI values were mainly distributed in a middle steppe strap from northwest to southeast. (2) The maximum NDVI values maintained for the past 22 years showed little variation. The average NDVI variance coefficient for the 22-year period was 15.2%. (3) NDVI distribution and vegetation cover showed spatial autocorrelations on a global scale. NDVI patterns from the vegetation cover also demonstrated anisotropy; a higher positive spatial correlation was indicated in a NW-SE direction, which suggested that vegetation cover in a NW-SE direction maintained increased integrity, and vegetation assemblage was mainly distributed in the same specific direction. (4) The NDVI spatial distribution was mainly controlled by structural factors, 88.7% of the total spatial variation was influenced by structural and 11.3% by random factors. And the global autocorrelation distance was 1178 km, and the average vegetation patch length (NW-SE) to width (NE-SW) ratio was approximately 2.4:1.0.

Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis

Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

Modelling raindrop impact and splash erosion processes within a spatial cell: a stochastic approach

A new approach is proposed to simulate splash erosion on local soil surfaces. Without the effect of wind and other raindrops, the impact of free-falling raindrops was considered as an independent event from the stochastic viewpoint. The erosivity of a single raindrop depending on its kinetic energy was computed by an empirical relationship in which the kinetic energy was expressed as a power function of the equivalent diameter of the raindrop. An empirical linear function combining the kinetic energy and soil shear strength was used to estimate the impacted amount of soil particles by a single raindrop. Considering an ideal local soil surface with size of I m x I m, the expected number of received free-failing raindrops with different diameters per unit time was described by the combination of the raindrop size distribution function and the terminal velocity of raindrops. The total splash amount was seen as the sum of the impact amount by all raindrops in the rainfall event. The total splash amount per unit time was subdivided into three different components, including net splash amount, single impact amount and re-detachment amount. The re-detachment amount was obtained by a spatial geometric probability derived using the Poisson function in which overlapped impacted areas were considered. The net splash amount was defined as the mass of soil particles collected outside the splash dish. It was estimated by another spatial geometric probability in which the average splashed distance related to the median grain size of soil and effects of other impacted soil particles and other free-falling raindrops were considered. Splash experiments in artificial rainfall were carried out to validate the availability and accuracy of the model. Our simulated results suggested that the net splash amount and re-detachment amount were small parts of the total splash amount. Their proportions were 0.15% and 2.6%, respectively. The comparison of simulated data with measured data showed that this model could be applied to simulate the soil-splash process successfully and needed information of the rainfall intensity and original soil properties including initial bulk intensity, water content, median grain size and some empirical constants related to the soil surface shear strength, the raindrop size distribution function and the average splashed distance. Copyright (c) 2007 John Wiley & Sons, Ltd.