[Spatial and temporal distributions of rainfall erosivity in the Yanhe River Basin].

Rainfall erosivity (R) is a measure of effects of the rainfall factor on the potential capacity for soil water erosion. The characteristic of spatial and temporal of R value is the basis for soil erosion prediction. The spatial and temporal distributions of rainfall erosivity were analyzed using daily rainfall data collected between 1980 and 2003 from 22 rainfall stations located across the Yanhe River Basin. The results showed that the seasonal distribution of R values formed a single peak, concentrated between May and September and accounted for 91.61% of the total annual R value. The changes in annual average rainfall erosivity followed a similar trend to those for the annual average rainfall and erosive rainfall. The average annual R value was 1580.58 MJ x mm x (hm2 x h x a)(-1), the maximum annual rainfall erosivity (1981) was 2417.70 MJ x mm x (hm2 x h x a)(-1) and the minimum (1999) was 585.29 MJ x mm x (hm2 x h x a)(-1). The variation coefficient of annual rainfall erosivity was the medium with a value of 0.32. The annual rainfall erosivity was the greatest at the Shaofangbian station with a value of 2190.33 MJ x mm x (hm2 x h x a)(-1), while the least erosivity was found at the Liandaowan and Yangshan station with values of 1151.37 MJ x mm (hm2 x h x a)(-1) and 1146.87 MJ x mm x (hm2 x h x a)(-1), respectively. The annual average R values had a similar trend of spatial distribution with annual average erosive rainfall. The annual changes in R values increased at the rainfall stations of north, while those were found to decrease at other stations of Yanhe River Basin. Overall, the annual rainfall erosivity tended to decrease in the Yanhe River Basin with the trend coefficient value of -0.004.

[Land use/land cover change and their ecological effect in small watershed on gully region of the Loess Plateau].

Based on land use data of 1994 and 2004 in Wangdonggou watershed, through developing dynamic model of LUCC and indices of regional ecological environment, this paper quantified the characteristics of LUCC and its ecological effect. The results showed that from 1994 to 2004, farmland decreased while grassland and orchard increased greatly, forest and nonproductive land changed little. The speed of individual land use changes was in the order of grassland > orchard > nonproductive land > farmland > forest land. As to the spatial change, a total of 11 major land use change types were identified, among which the change from farmland to others and form others to forest were the most important land use change. The gravitational center of farmland and orchard moved to the northwest tableland, while those of forest land and grassland moved to the southeast gully land. From 1994 to 2004, owing to LUCC, the ecological environment was improved, but the type of land use and their change took effect differently with both improving and decreasing effect. The decrease of farmland affected ecological environment negatively, while the increase of forest and grassland and orchard improved the ecological environment and its ecosystem service values. Those improving the ecological environment were from other types of land use to forest and orchard, while those worsening the ecological environment were from forest to others and from farmland to nonproductive land.

Landscape dynamitic change in Mu Us Desert derived from Landsat TM data.

Landscape ecology emphasizes large areas and ecological effects of the spatial patterning of ecosystem. Recent developments in landscape ecology have emphasized the important relationship between spatial patterns and many ecological processes. Quantitative methods in landscape ecology link spatial patterns and ecological processes at broad spatial and temporal scales. In turn the increased attention on temporal change of ecosystem has highlighted the need for quantitative methods that can analyze patterns. This research applies quantitative methods--change detection to assess the ecosystem temporal change in the arid and semiarid area. Remote sensing offers the temporal change of ecosystem on landscape characteristics.