Jiang Weiguo

The effects of land use and landscape position on labile organic carbon and carbon management index in red soil hilly region, southern China

Labile organic carbon (LOC) and carbon management index (CMI), which are sensitive factors to the changes of environment, can improve evaluating the effect of land management practices changes on soil quality. The objective of this study was to investigate the effects of land use types and landscape positions on soil quality as a function of LOC and CMI. A field study in a small watershed in the red soil hilly region of southern China was conducted, and soil samples were collected from four typical lands (pine forest (PF) on slope land, barren hill (BH) on slope land, citrus orchard (CO) on terrace land and Cinnarnornum Camphora (CC) on terrace land) at a sampling depth of 20 cm. Soil nutrients, soil organic carbon (SOC), LOC and CMI were measured. Results showed that the LOC and CMI correlated to not only soil carbon but also soil nutrients, and the values of LOC and CMI in different land use types followed the order CC > PF > CO > BH at the upper-slope, while CO > CC > BH > PF at mid-slope and down-slope. With respect to slope positions, the values of LOC and CMI in all the lands were followed the order: upper-slope > down-slope > mid-slope. As whole, the mean values of LOC and CMI in different lands followed the order CC > CO > PF > BH. High CMI and LOC content were found in the terrace lands with broadleaf vegetations. These results indicated that the terracing and appropriate vegetations can increase the carbon input and lability and decrease soil erosion. However, the carbon pools and CMI in these lands were significantly lower than that in reference site. This suggested that it may require a long time for the soil to return to a high-quality. Consequently, it is an efficient way to adopt the measures of terracing and appropriate vegetations planting in improving the content of LOC and CMI and controlling water and soil loss in fragile ecosystems.

Combining Spectral with Texture Features into Object- oriented Classification in Mountainous Terrain Using Advanced Land Observing Satellite Image

Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS (Advanced Land Observing Satellite) in mountainous terrain. Mountainous terrain mapping using ALOS image faces numerous challenges. These include spectral confusion with other land cover features, topographic effects on spectral signatures (such as shadow). At first, topographic radiometric correction was carried out to remove the illumination effects of topography. In addition to spectral features, texture features were used to assist classification in this paper. And texture features extracted based on GLCM (Gray Level Co-occurrence Matrix) were not only used for segmentation, but also used for building rules. The performance of the method was evaluated and compared with Maximum Likelihood Classification (MLC). Results showed that the object-oriented method integrating spectral and texture features has achieved overall accuracy of 85.73% with a kappa coefficient of 0.824, which is 13.48% and 0.145 respectively higher than that got by MLC method. It indicated that texture features can significantly improve overall accuracy, kappa coefficient, and the classification precision of existing spectrum confusion features. Object-oriented method Integrating spectral and texture features is suitable for land use extraction of ALOS image in mountainous terrain.

Changes and spatial patterns of eco-environment in the farming-pastoral region of northern China

This paper firstly selects 10 kinds of indexes to reflect eco-environment background condition and builds the multi-subject spatial database by using ground meteorological data, remote sensing data and DEM. It then discusses in detail the methods about evaluating eco-environment background condition and analyzing eco-environment change. The eco-environment background conditions of 1989 and 1999 are synthetically appraised. Finally, the paper analyzes the spatial distribution, quantitative change, the trend of change, the areas of change and the dynamic spatial pattern of eco-environment. The results are as follows: (1) The eco-environment background condition becomes worse from southeast to northwest in the farming-pastoral region of northern China. (2) The eco-environment background condition deteriorates from 1989 to 1999. (3) In the adjacent areas of Shanxi-Shaanxi-Inner Mongolia-Gansu-Ningxia, Horqin Sandy Land and its peripheries, and eastern Qinghai province, eco-environmental deterioration is very serious.

Changes of Chinese Beginning Date of Vegetation Greenness Period Based on NOAA NDVI

Beginning date of greenness period of vegetation(BGP)is closely related to seasonal dynamics of the lower atmosphere and is therefore an important variable in influences and feed-back mechanisms of global climate variation to terrestrial ecosystem.Detecting BGP using remote-ly sensed data at regional or global scales has become an advanced topic in geography and ecolo-gy.Based on the processed NOAA/AVHRR NDVI data,the study is to use Logistic fitting model on cumulative frequency of NDVI to compute BGP of China by pixels from 1982 to 1999,count the annual average BGP of every vegetation type and bio-climate district,and analyze the inter-annual change trends,spatio-temporal dynamic change feature of BGP of various spatial types.The results indicate that:(1)BGP have an advance trend in most regions and obviously advance in North China Plain,northeast Guizhou,the middle and south Hunan,west Guangxi and typical grassland area of east Inner Mongolia.(2)The regions in which inter-annual fluctuation of BGP are over 10 days are mainly distributed in the area covered with agricultural vegetation types,the areas covered with evergreen vegetation types and the areas covered with steppe vegetation types.Thereinto,the fluctuation of BGP in Hetao plain,Guanzhong basin,east Henan,west Sichuan basin,Guangdong,Taiwan and so on,are over 15 days.(3)BGPs of the other vegetation types ex-cept temperate desert show an advance trends.(4)With the reduction of annual accumulative tem-perature and increase of drought indices,BGP of various bio-climate areas delay.An advance of BGP is found in South China,East China,Central China,North China,Inner Mongolia,Northeast China and Tibet,whereas a delay occurred in Shaanxi,Shanxi and Northwest China.(5)BGP of all vegetation types evidently delay in 1982,1983 or 1984,which may be associated with the strong EI-Nino effect in the 1982-1983 period.

Spatio-temporal features of vegetation restoration and variation after the Wenchuan earthquake with satellite images

Abstract The Wenchuan earthquake was a deadly earthquake that occurred on May 12, 2008, in Sichuan province of China. With the help of classic statistic methods, including arithmetic mean, standard deviation and linear trend estimation, vegetation restoration was recognized by analyzing spatio-temporal features of normalized difference vegetation index (NDVI) before and after this earthquake. Results indicate: (1) spatial distribution of NDVI mean values remains similar from 1998 to 2011. Higher values are mainly found in north, whereas lower values are mainly distributed over southeast, which is in good correlation with elevation and landform. Vegetation damage is at different levels in different seismic intensity (SI) regions: the higher SI is, the worse vegetation damage is. (2) Over the whole region, standard deviation is bigger after earthquake than before. Both absolute and relative changes in ecosystem stability increase with increasing SI. In different counties, variation of ecosystem stability is more obvious after earthquake, increase of standard deviation is approximately 6.5 times. Relatively, vegetation regionalization is the smallest analysis unit. Consequently, changes resulting from earthquake are unobvious. (3) Linear trend estimation coefficient increases from 0.0079 before the earthquake to 0.0359 after the earthquake in this whole region. This indicates that the plant ecosystem is rapidly restored between 2009 and 2011. The biggest linear trend is for the hill region, indicating good plant restoration and increase after earthquake. Fluctuation of linear trend estimation coefficient in different counties is more obvious after earthquake. Vegetation restoration after earthquake is most obvious in the regions that suffered the greatest SI (SI10 and SI11). In contrast, fluctuation in linear trend estimation coefficient of annual NDVI mean value for different classes of vegetation is more obvious before earthquake.

Application of refactoring and design pattern in land information system development

The unceasing change problem of land information systems can be resolved through the refactoring and design pattern. To promote the implementation of design pattern and refactoring methods in developing land information systems reusing software design, applying refactoring methods to the abstract factory and decorator design patterns in land information system development is discussed.

Land change process and its driving forces in the Farming-Pastoral Zone of Northern China

Based on the land use/cover change information derived from the 1km NOAA/AVHRR dataset in 1989, 1994 and 2000, the change of the land use structure and spatial pattern of the Farming-Pastoral Zone of Northern China were analyzed at first, then the effects of human activities on cultivated land process were explored by GIS and the driving forces of cultivated land change were investigated. The conclusions can be drawn as follows: (1) the constant increase of cultivated land and residential land and the decrease of the grassland and water body were the main characteristics of the land use/cover change in the Farming-Pastoral Zone of Northern China from 1989 to 2000, which show the effects of human activities on land dynamics. (2) The increase of landscape fragmentation index, diversity index and evenness index and the decrease of the dominance index show the effects of human activities grow gradually. (3) From 1989 to 2000, the barycenters of cultivated land and grassland had the trends to move from southwest to northeast with the topography. The barycenter of forestland move from northeast to southwest, and residential land from northwest to southeast. (4) By stepwise regression analysis, main driving forces of every geomorphologic district to cultivated land use change are identified. Keywordsthe Farming-Pastoral Zone of Northern China; land change process; landscape pattern; driving forces