A second-order upwinding finite difference scheme for the steady Navier-Stokes equations in primitive variables in a driven cavity with a multigrid solver

This study combines the sampling technique, geographic information system and remote sensing technique to conduct a sampling survey on forest cover area of Jinggangshan National Nature Reserve in China on the basis of TM remote sensing image. The spatial simple random sampling, spatial stratified sampling and sandwich sampling model are respectively utilized to establish the sampling design. For the spatial simple random sampling model, the spatial autocorrelation analysis method is adopted to determine the spatial autocorrelation coefficient through calculating Moran's I index, while in the spatial stratified sampling and sandwich sampling model, the yearly maximum NDVI (Normalized Difference Vegetation Index) is utilized to conduct the spatial stratification. Through comparison of the sampling accuracy of three sampling models, a higher precision and more reasonable sampling method and sampling model is provided for remote sensing monitoring of forest cover area. The study results show that: sandwich sampling model is featured as the highest sampling accuracy, followed by the spatial stratified sampling and simple random sampling. Under the requirement of same precision, sandwich spatial sampling model can reduce quantity of the sampling points, and create all kinds of report units according to demands of different spatial area, so it is featured as the better suitability.

IBIS (Integrated Biosphere Simulator) model is an ecosystem process model, which represents the research direction of a global carbon cycle simulation. Based on the existing research achievements, the regional ecological carbon sink potential is simulated from point to surface with a long time serie of meteorological data (1954-2010), data on different ecosystem vegetation types, soil texture data, terrain data and remote sensing data. The results are listed as follows: there is no significant variation of potential carbon sink of Shenzhen vegetation over the past 30 years, carbon sequestration caapcity ranges within 43.52-55.82×104Mg C/a, and the potential carbon sink intensity value within 0-624 C/m2/a. Precipitation is a main factor which influnces the ecosystem carbon sink intensity in Shenzhen City. The carbon sink intensity of ecosystem is increased with more annual precipitation.

The carbon emission caused by land use change is a human carbon source only second to fossil fuel combustion, the urbanization process in China is extremely intensified, which carbon emissions effect caused by land use change becomes a key factor to influence China's target of carbon emission reduction. Taken Shenzhen city as a typical case, this study utilizes unit root and co-integration test method to research existence of carbon emissions EKC (Environmental Kuznets Curve) in Shenzhen on the basis of the carbon emissions EKC theory and land-use carbon emissions data of 1979-2010 years, in combination with the existing research foundation. The result proves that, the carbon emission EKC per capita exists in Shenzhen, and the inflection point time of carbon emissions per capita is also calculated for Shenzhen city, which provides new research ideas and scientific guidance for urban carbon emission reduction in China.

This paper is to propose a method of ecological carbon sink regionalization in the view of GHG (greenhouse gas) emission reduction, which could provide scientific theory basis for development and utilization of urban land resources, ecological environment construction, biodiversity conservation, the industry layout and formulation of the regional sustainable development strategy. Based on the existing researches foundation, this study takes Shenzhen as a typical case to put forward a method for carbon sink regionalization of urban land use with further quantitative evaluation of ecosystem carbon storage (density), carbon sources/sinks function and carbon sink potential of Shenzhen city. The results show that: Shenzhen ecological carbon sink is regionalized into six categories 55 regions, including 15 intensive carbon sink regions, 17 medium carbon sink regions, 10 weak carbon sink regions, 4 carbon neutral regions, 5 medium carbon source regions and 4 intensive carbon source regions.