Land Cover Change In China Research Articles

Land-cover change analysis of China using global-scale Pathfinder AVHRR Landcover (PAL) data, 1982–92

This paper reviews the application of NOAA/NASA Pathfinder AVHRR Land (PAL) dataset (8 km) to detect land-cover change in China between 1982 and 1992. Changes in productivity, as indicated by a normalized difference vegetation index (NDVI), not changes in land-cover classifications are analysed. The research uses the change detection techniques of simple differencing, or univariate differencing, and standardised principal component analysis. Both techniques produce similar results which indicate that forest regions are decreasing in productivity while agricultural regions are increasing. The majority of pixels indicating changes are ones showing an increase in productivity and are clustered primarily in agricultural regions, especially the North China Plain, along with grasslands. The paper demonstrates the potential of using global-scale PAL data to monitor land-cover change in areas where official governmental data are either suspect or hard to acquire. China is an important area in which to analyse lan...

Land-cover change analysis of China using global-scale Pathfinder AVHRR Landcover (PAL) data, 1982?92

This paper reviews the application of NOAA/NASA Pathfinder AVHRR Land (PAL) dataset (8 km) to detect land-cover change in China between 1982 and 1992. Changes in productivity, as indicated by a normalized difference vegetation index (NDVI), not changes in land-cover classifications are analysed. The research uses the change detection techniques of simple differencing, or univariate differencing, and standardised principal component analysis. Both techniques produce similar results which indicate that forest regions are decreasing in productivity while agricultural regions are increasing. The majority of pixels indicating changes are ones showing an increase in productivity and are clustered primarily in agricultural regions, especially the North China Plain, along with grasslands. The paper demonstrates the potential of using global-scale PAL data to monitor land-cover change in areas where official governmental data are either suspect or hard to acquire. China is an important area in which to analyse landcover change because little is known about recent changes and the region has a strong potential impact on global environmental change.

Seasonal patterns of spatial differentiation of landcover change in China

Using the 1° × 1° NOAA AVHRR NDVI data set in China, an index on the spatial different gradient of landcover is created. Then based on the index and supported by the geographical information system, it is revealed through principal component and factor analyses methods that there exist four types of seasonal patterns of spatial differentiation of landcover change in China, i. e. November to next March type, June to September type, May or October type and April type.

Wheat yield functions for analysis of land-use change in China

CERES-Wheat, a dynamic process crop growth model, is specified and validated for eight sites in the major wheat-growing regions of China. Crop model results are then used to test the Mitscherlich-Baule and the quadratic functional forms for yield response to nitrogen fertilizer, irrigation water, temperature, and precipitation. The resulting functions are designed to be used in a linked biophysical-economic model of land-use and land-cover change in China. While both functions predict yield responses adequately, the Mitscherlich-Baule function is preferable to the quadratic function because its parameters are biologically and physically realistic. Variables explaining a significant proportion of simulated yield variance are nitrogen, irrigation water, and precipitation; temperature was a less significant component of yield variation within the range of observed year-to-year variability at the study sites. Crop model simulations with a generic soil with median characteristics of the eight sites compared to simulations with site-specific soils showed that agricultural soils in China have similar and, in general, low-to-moderate water-holding capacities and organic matter contents. The validated crop model is useful for simulating the range of conditions under which wheat is grown in China, and provides the means to estimate production functions when experimental field data are not available.