Yaowen Xie

RUSLE model based quantitative evaluation on the soil erosion of Wen County of Gansu Province, China

With steep slopes, high mountains, concentrated rainfalls and frequent rainstorms, the agricultural production and economic development of the Wen County, the southernmost county, also heavily damaged by 5.12 Earthquake, of Gansu Province in northwest China, are gravely constrained by serious soil erosion. To make effective soil and water conservation measures, quantitative evaluation of soil erosion situation is urgently needed. Traditional qualitative evaluation methods and techniques of soil erosion are unable to meet the rapid and quantitative need. Using GIS (Geographic Information System), RS (Remote Sensing) and combining with RUSLE (the Revised Universal Soil Loss Equation) model, which being widely used in many regions, this study aims to quantitatively and objectively survey the soil erosion situation of Wen County in 2008. The results of the study will provide reference for soil and water conservation and ecological construction in this area. The TM images acquired in June 25, 2008 were selected as the remote sensed data, and thus 30m×30m resolution was defined as the basic evaluating cell correspondingly. After a series of processing and calculation, the land use and NDVI (Normalized Difference Vegetation Index) data are obtained. Based on the daily rainfall, vector soil data, DEM, along with the land use and NDVI data, the RUSLE factors are calculated including rain erosivity (R), soil erodibility (K), cover and management factor(C), slope length (LS) and supporting practice factor (P). Then, using RUSLE model, the soil erosion modulus is calculated and the grades of soil erosion, namely slight, light, moderate, intensive, extreme intensive, and severe, are determined. The conclusions are as follows: 1. The total soil erosion of Wen County is serious and the area of slight, light, moderate, intensive, extreme intensive and severe are respectively 512.86km2, 1100.15km2, 881.52km2, 605.05km2, 661.74km2 and 1016.13km2, taking up 10.74%, 23.03%, 18.45%, 12.67%, 13.85% and 21.27% of the total area correspondingly. The soil erosion area is 4264.59km2, taking up 89% of total statistical area and all kinds of erosion types show a relative balanced distribution in amounts, although light erosion, moderate erosion and severe erosion have a greater-than 15% proportion respectively. 2. The distribution of erosion land has great regularity: Slight erosion and light erosion mainly distribute in the top area of mountain ridges with good vegetation cover, or plain land besides rivers with low slopes. Moderate and strong erosion distribute in the middle of hillsides. The very strong and severe erosion are concentrated in the hillsides near river ways, or very steep part of mountains. 3. The erosion grades are closely correlated with the land use and population. The area covered by forest or high densities grass has light erosion grades, while the high populated farmland and low vegetation coverage land win the very high erosion grades.

Lanzhou urban growth prediction based on Cellular Automata

Lanzhou City, the capital city of Gansu Province and located in the geometric center of Chinas land territory, is a typical narrow zonal valley city in the west of China with the Yellow River going through it. It is also an industrial city with many large petroleum and chemical industries. Lanzhou is one of the important traffic hubs and freight transfer stations in northwestern China. The development of Lanzhou City is severely restricted by surrounding mountains so facing a series of problems such as environment pollution, traffic jam, unreasonable land use and sustainability. So, it is necessary to make urban expansion prediction to provide references for the urban planning department of this city. SLEUTH is kind of Model applies self-adaption Cellular Automata to model the urban expansion and land use, and it has been successfully used in predicting the growth of many metropolises all over the world. Taking remote sensing image such as MSS, TM, ETM and CCD as the main data sources and along with the maps of urban planning, topographic and socio-economic statistical, the spatial and attribute database of the study area was built firstly. Then the SLEUTH model was applied to rebuild the sprawl process and predicting the urban expansion in the future. The results show the Urban Area Index had a linearly increasing trend from 2007 to 2025 and the pixel number will increase from 145718 to 178560. Urban Edges Index will grow nonlinearly and the pixel number will increase from 6250.31 to 178560. Urban Cluster Index will increase rapidly from 236.21 to 394.07 by 2013, and then it will stabilize. The Mean Urban Cluster Index will gradually reduce to a stable status by 2013. The analyses indicate that the remaining land in Lanzhou for urban expansion is quite limited; urban expansion is mostly influenced by road and traffic situation; slope is a major limitation for urban expansion. In the future, for the development of Lanzhou, it need to strengthen and accelerate the construction of central city area, move administrative organizations out of the centre area, strengthen the modernization of urban traffic, support the development of minor towns around the city so they can share part of responsibilities of metropolitan Lanzhou City.

The application of threshold methods for image segmentation in oasis vegetation extraction

In this study, three threshold algorithms for image segmentation were used to quickly and reliably determine the threshold of oasis vegetation of Jinta in the arid inland river of Northwest China. And then the extraction results were contrasted. This is a beneficial exploration of automatically extracting the boundary of the oasis. During the experiment, firstly, we obtained the greenness images after tasseled cap transformation of Landsat TM remote sensing images, and then we segmented them with thresholds that were obtained from the three methods: one is Otsu method, which is on basis of global binary image algorithm. In this method, we calculated the between-class variance and within-class variance values of the whole images and took the gray values of the images as the optimal thresholds when the between-class variance reached maximum value. Another is iterative method based on the idea of approximation. The average of the mean gray value of the background and foreground is considered as the threshold. The third is edge detection based method on basis of local binary image algorithm. In this method, we firstly detected and tracked the image edges of the greenness images, and then computed the segmentation threshold by weighting the average pixels values of image edges. These algorithms and processes were carried out by programming in MATLAB. The results show that, the thresholds determined by Otsu and iterative method are a little higher, which results in loss of information within the oasis, while the edge-based detection threshold segmentation on basis of Robert operator is more suitable for the whole image, for it takes into account the internal regularity of the oasis. But on the whole, the outer boundary of oasis vegetation can extracted at full and the threshold can be determined automatically by these three methods, allowing it to be further applied in the extraction of remote sensing information.

Dynamic analysis of landscape changes in the Heihe River Basin using remote sensing and GIS

Landscape spatial pattern is one of the main study fields in landscape ecology, as well in land use and land cover change studies. The formation and variation of landscape pattern are considered as the composite reactions of the area ecological environment quality, which come from mufti-factors interaction of nature and man-made. Heihe River Basin is the second largest endorheic drainage in the northwest of China; it is the typical arid inland river basin with desertscape. This paper is aimed to intensively study the drive mechanism of landscape pattern changes, and then provides a reference for the environmental protection and construction of Heihe region. Based on remote sensing and geographic information system, interpreting the 2000 and 2009s Landsat TM data, the landscape patterns were divided into six categories: arable land, forest, grass, aquatorium, residential area and unused land, then using the spatial pattern analysis software Fragstats to calculate the landscape pattern indices chose from class and landscape level. At last, these indices from two periods were analyzed by quantitative indicators. The results showed that: the area ratio of unused land and grassland exceeds 73% and 15% respectively; the desert landscape to which they were subject is the main landscape of Heihe River Basin, after the unused land and grassland are arable land, forest land, aquatorium and residential area. Unused lands absolute advantage of area ratio and largest patch index determined the landscape ground substance of Heihe River Basin. Landscape pattern of Heihe River Basin showed different changes from 2000 to 2009, the area of arable land, forest land, aquatorium and residential area increased 9.8%, 4.4%, 34.8% and 4.7% respectively; on the other hand, the area of grassland and unused land declined 3.5%, 0.6% respectively. The fragmentation of arable land, forest land, grassland and unused land decreased, residential area and aquatoriums increased. The whole landscape of Heihe River Basin was strongly influenced by human activities, so the Shannons diversity index (SHDI) rose from 0.8601 to 0.9568, Shannons evenness index (SHEI) rose from 0.48 to 0.534, aggregation indices (AI) in these two years were both greater than 98, division (DIVISION) reduced from 0.5415 to 0.4832, perimeter-area fractal dimension (PAFRAC) reduced from 1.4007 to 1.3479. Each patch type became equalized, and the total heterogeneity lowered. The dominance of unused land reduced slightly, the differences between each classs area ratios decreased, and these classes distributed more evenly. The exclusiveness of classes is powerful. The number of large patches decreased which turned into smaller patches. The self-similarity of patches became more intensive; its shape became more regular and tends to be simple. Component of ground substance reduced and its control function over landscape pattern diminished.

Temporal-Spatial Changes of the Oasis in the Heihe River Basin over the Past 25 Years

In China, the arid area occupies a quarter of the total area of the land. It mainly distributes in five provinces: Gansu, Ningxia, Qinghai, Xinjiang and Inner Mongolia. In the arid area, oasis is the special landscape on the background of deserts. It is not only the most centralized area of human activities but also the largest area where human disturbances happen at the regional scale. Oasis covers only 4%–5% of the area of the arid region, whereas they load over 90% of the population and 95% of the social wealth in this area (Li et al., 2007). Therefore, oasis plays very important roles in the economic and social development. In recent 60 years, the artificial oasis of this region kept expanding, as a result, living space of human beings became larger, and the overall productivity and capability were improved as well, which made great contribution to the development of regional economy. However, the ecological environment of the arid area is fragile due to the dry climate, scarce rainfall and short water resource. Consequently, over exploitation on oasis led to imbalanced and unreasonable reallocation of water resource, which further make the local water cycle process changed and finally results in salinization, desertification and wind erosion in other parts (Wang, 2009). If no effective measures are taken, stability of the oasis and sustainable development of the economy in arid area of China will face serious threats.

A study on the ecological services value of oasis ecosystem — Take the middle reaches of Heihe River, China as an example

Studying the services value of oasis ecosystems in arid middle reaches of the Heihe Oasis is significant for understanding the development and evolution, revealing the maintaining mechanism of oasis security, and promoting the resources and environment sustainable development of this area. Based on the data of landsat TM image in the middle of Heihe River Basin acquired in 2000 and 2006, land use and land cover data were obtained first and also the changes were analyzed. On this basis, the service value per unit area of each type ecosystem was calculated, and the economic value of food production per hectare was calculated by production and area of crops in 2000, 2006. According to the result of calculation of the ecological services value per unit area, ecosystem service value and dynamic changes were analyzed. In addition, the sensitivity index was used to test rationality of ecological value coefficients. The result showed that firstly the land use types of farmland, grassland, water area and unused land decreased from 2000 to 2006 with a change rate of 4.50%, 1.62%, 2.42%, 0.96%, respectively, whereas, types of forest land, construction land and sandy land increased with a change rate of 16.64%, 4.96%, 2.38%, respectively. Secondly, the total services value of oasis ecosystem was increasing from 249.31 billion RMB Yuan in 2000 to 280.43 billion RMB Yuan in 2006, there were 12.48% net increment of 31.12 billion RMB Yuan, this was mainly due to the increasing forest land area and grassland ecosystem had the higher ecological service value per unit area. Thirdly, the services value of farmland, forest land, grassland, water area and sandy land ecosystem keep increasing, the service value of forest land, grassland and water area ecosystem accounted for above 80% of the total value, and forest ecosystem gave the greatest contribution to the total ecosystem service value, reaching 19.49 billion RMB Yuan. Fourthly, the sensitivity analysis suggested that these estimates were relatively reasonable. The ecological value coefficients adopted were suitable for application in the study area. So, it is important to protect oasis ecological environment and improve the service function of oasis ecosystem.

Research on the land cover classification in Maqu County based on the TM image

In this study, 9 quantitative indices of remote sensing were established by using the spectrum information of Landsat TM image in 2006 and the topographical information of DEMs with the techniques of RS and GIS. Then, these indices were used to establish a discriminated function based on the stepwise discriminant analysis of spatial statistics in support of SPSS software. The wetland, grassland, river, bottomland, bare-rock and desert were extracted initially by this method. The results showed that classification precision of most ground objects was relatively high, except that wetland and grassland were mixed up to some extent. Then a template was used for further extraction. As grassland is the major land cover type in Maqu, this study also calculated the NDVI and on this basis estimated the vegetation coverage. The results showed that the moderate coverage grassland is the main land cover class in Maqu County which accounts for 83.44% of the total land area; Bare-rocks occupy 3.81%; Fields with rivers and wetlands are 1.95%, 9.98% respectively. Comparing with other studies, the result is more accurate by using a comprehensive method of stepwise discriminant analysis, “template-based” method and vegetation index when doing land cover classification, which has the certain promotion application value.

Design and implementation of GIS by ComGIS: A case study in National Earthen Site Geographic Information System

Geographic Information System, as the special technology of dealing with spatial data, it was significance to establish the Geographic Information System. The study developed and implemented a National Earthen Site Geographic Information System. It can provide some information of the existing earth sites, supply workers and experts some decision-making basis of research and protection. At the same time, the public can use it to retrieve some information to meet their needs of travel, study and even research work. The Earthen Site Database (ESDB) was setup firstly by using SQL Server software, which take SuperMap SDX+ as its spatial search engine and the format of SuperMap complex dataset as the storage format for vector data. Secondly, C/S framework was adopted so as to improve the flexibility of the system. Component GIS (ComGIS) technique was used to finish the secondary development of the system. Lastly, the NESGIS had realized by comGIS.