The Use of Remote Sensing and GIS in the Sustainable Management of Tropical Coastal Ecosystems

The sustainable use and management of important tropical coastal ecosystems (mangrove forests, seagrass beds and coral reefs) cannot be done without understanding the direct and indirect impacts of man. The ecosystem's resilience and recovery capacity following such impacts must be determined. The efficacy of mitigation measures must also be considered. Remote sensing and geographic information systems (GIS) are excellent tools to use in such studies. This paper reviews the state of the art and application of these tools in tropical coastal zones, and illustrates their relevance in sustainable development. It highlights a selected number of remote sensing case-studies on land cover patterns, population structure and dynamics, and stand characteristics from South-East Asia, Africa and South-America, with a particular emphasis on mangroves. It further shows how remote sensing technology and other scientific tools can be integrated in long-term studies, both retrospective and predictive, in order to anticipate degradation and to take mitigating measures at an early stage. The paper also highlights the guidelines for sustainable management that can result from remote sensing and GIS studies, and identifies existent gaps and research priorities.There is a need for more comprehensive approaches that deal with new remote sensing technologies and analysis in a GIS-environment, and that integrate findings collected over longer periods with the aim of prediction. It is also imperative to collect and integrate data from different disciplines. These are essential in the spirit of sustainable development and management, particularly in developing countries, which are often more vulnerable to environmental degradation.     

Spatial sampling and the environment: some issues and directions

In this paper we summarize research issues for spatial environmental sampling stemming from a NISS/USEPA workshop held on 21-22 September 1994 at Chapel Hill, NC.     

Semi-parametric statistical approaches for space-time process prediction

The problem of estimation and prediction of a spatial-temporal stochastic process, observed at regular times and irregularly in space, is considered. A mixed formulation involving a non- parametric component, accounting for a deterministic trend and the effect of exogenous variables, and a parametric component representing the purely spatio-temporal random variation is proposed. Correspondingly, a two-step procedure, first addressing the estimation of the non- parametric component, and then the estimation of the parametric component is developed from the residual series obtained, with spatial-temporal prediction being performed in terms of suitable spatial interpolation of the temporal variation structure. The proposed model formula-tion, together with the estimation and prediction procedure, are applied using a Gaussian ARMA structure for temporal modelling to space-time forecasting from real data of air pollution concentration levels in the region surrounding a power station in northwest Spain.     

基于GIS的安徽省土壤空间分布的分形特征研究

分维数和稳定性指数是土壤空间分布的重要指数。通过建立安徽省土壤的空间数据库,运用分形理论,获得安徽省土壤类型周长与面积的关系,进而计算出各类土属在空间上的分维数和稳定性指数大小,得出如下结论:①安徽省土壤图斑的周长与面积之间存在双对数函数关系,相关性系数大部分在0.9以上,证明了安徽省土壤空间分形的客观存在。②安徽省各类土壤空间分维数大小在1.1375—1.9948之间,平均值为1.6138,最大的是泥质岩砾质土,最小的是脱青湖泥田。分维数在空间分布上存在差异,总的趋势是从西北向东南逐渐变大。③各种土属的稳定性指数在1.0252—0.0124之间,平均值约为0.2324,最大的是湿潮土,最小的是砂礓黄土。     

城郊农业区小流域土地利用结构对氮素输出的影响

以位于湖南省长沙市城郊农业区的金脱河流域为研究区域,通过解译2009年的Spot-5卫星遥感图获取了小流域的土地利用图;结合流域的DEM图,利用ArcGIS 9.3的水文、空间分析模块将流域划分为若干个子流域,分析各子流域的土地利用结构.从2009年12月～2010年11月在各子流域出口处采取水样,分析其TN、NH4+-N、NO3--N输出浓度、输出量的时空变化特征以及与土地利用结构、施肥等因素之间的关系.结果表明,流域径流氮素污染严重,其TN、NH4+-N输出浓度呈明显的季节变化特征,为冬季>春季>夏、秋季,而NO3--N的输出浓度的季节差异较小.流域内的土地利用结构对NO3--N的输出浓度起着重要的控制作用,林地、水面表现为源作用,水田、旱地、居民地为汇作用;不同的时间尺度上土地利用结构对其影响不同,年度尺度上对NO3--N输出影响最大的为旱地,春夏季为林地,秋冬季为旱地.TN、NH4+-N的输出浓度与土地利用结构的相关性较差,各形态氮素的输出量与纯氮施用量、人口数、养猪量表现为极显著正相关.     

小流域土地利用结构对氮素输出的影响

以丹江口库区的胡家山小流域为研究区,以资源二号卫星影像图为底图,通过实地调查获取胡家山小流域土地利用图,利用ArcGIS的水文模拟、空间分析模块提取15个集水区,并分析其土地利用结构.根据2008年1～12月各个集水区的出口的总氮、硝态氮浓度的监测数据,定量地分析土地利用结构对氮素输出时空变化的影响.结果表明,胡家山小流域内旱地、居民地对氮素输出起显著源作用,与TN、NO-3-N的Pearson相关系数分别为0.869、0.856和0.826、0.867.林地、疏林地、草地等对氮素输出起汇作用,其中林地、草地汇作用显著,与TN、NO-3-N的Pearson相关系数分别为-0.820、-0.851和-0.602、-0.518.土地利用结构是氮素输出空间变化的关键因素,土地利用类型的空间分布使得汇土地利用类型旱地、居民地对小流域氮素输出影响最大;在不同时间尺度上,土地利用结构对氮素输出浓度影响有所不同.年度上,对氮素输出影响最大的是旱地,季节上,春、夏、秋、冬四季对氮素输出影响最大的分别是旱地、居民地、居民地、旱地;土地利用结构对氮素输出浓度的影响受到降雨、气温、人为等因素的作用.     

Technological innovation paths toward green industry in China

With the environmental carrying capacity reaching its limits and the decreasing margin benefits of traditional production factors, the green transformation and green development through technological innovations has been a major direction for the future development of Chinese industries. However, the characteristics and heterogeneities of various types of industries call for different approaches regarding technological innovations. How to choose the most effective mode of technological innovation according to the characteristics of a certain industry has been a key issue. This paper measures the green total factor productivity of 32 industrial trades using the Slacks Based Measure(SBM)-DDF method. The effects of three innovation modes in the green transformation of industrial industry, including the independent innovation(Ⅱ), the technology introduction(TI), and the government support(GS), are empirically analyzed based on industry heterogeneity. Results indicate that the green total factor productivities of different industries show significant differences if taking into account the energy input and the undesirable output of pollutant emissions. The green total factor productivities of traditional high input,high pollution, and high energy consumption industrial trades were significantly lower than those with obvious green features. The year of 2009 is a leap year for the industrial green transformation in China. For resource-intensive industries, the II and the GS are the important ways to achieve green transformation. For labor-intensive industries, the TI is the best path to achieve green transformation, while for technology-intensive industries, the II is the primary driving force for the promotion of green developments. In addition, the innovation-compensating effect of the current Chinese environmental regulations to the resource-intensive industries has been revealed. Improving the overall scale and the industrial concentration of the industries is also beneficial for the green transformation of the industries.     

A new approach to spatial source apportionment of haze pollution in large scale and its application in China

Long-lasting expansion of haze pollution in China has already presented a stern challenge to regional joint prevention and control. There is an urgent need to enlarge and reconstruct the coverage of joint prevention and control of air pollution in key area. Air quality models can identify and quantify the regional contribution of haze pollution and its key components with the help of numerical simulation, but it is difficult to be applied to larger spatial scale due to the complexity of model parameters. The time series analysis can recognize the existence of spatial interaction of haze pollution between cities, but it has not yet been used to further identify the spatial sources of haze pollution in large scale. Using econometric framework of time series analysis, this paper developed a new approach to perform spatial source apportionment. We applied this approach to calculate the contribution from spatial sources of haze pollution in China, using the monitoring data of particulate matter (PM_2.5) across 161 Chinese cities. This approach overcame the limitation of numerical simulation that the model complexity increases at excess with the expansion of sample range, and could effectively deal with severe large-scale haze episodes.     

北太平洋地区春季粉尘的空间分布特征——观测及模拟

通过对2001年4月的一次中亚强沙尘暴过程的观测事实分析和数值模拟,结果表明,源自中亚的强沙尘暴扬起的粉尘,通过西风急流远程传输到韩国、日本、北太平洋、北美大陆.北太平洋地区的沙尘沉积通量空间分布将主要取决于3个方面:沙尘沉积通量随传输距离的增加呈指数衰减;传输路径上粉尘有较高的沉降通量;沙尘过境时的降水空间格局将在很大程度上决定粉尘的沉降空间格局.     

Characterizing ionic species in PM2:5 and PM10 in four Pearl River Delta cities, South China

PM_(2.5)and PM_(10)samples were collected at four major cities in the Pearl River Delta(PRD),South China,during winter and summer in 2002.Six water-soluble ions,Na~ ,NH_4~ ,K~ ,Cl~-,NO_3~- and SO_4~(2-)were measured using ion chromatography.On average,ionic species accounted for 53.3% and 40.5% for PM_(2.5)and PM_(10),respectively in winter and 39.4% and 35.2%,respectively in summer. Secondary ions such as sulfate,nitrate and ammonium accounted for the major part of the total ionic species.Sulfate was the most abundant species followed by nitrate.Overall,a regional pollution tendency was shown that there were higher concentrations of sulfate, nitrate and ammonium in Guangzhou City than those in the other PRD cities.Significant seasonal variations were also observed with higher levels of species in winter but lower in summer.The Asian monsoon system was favorable for removal and diffusion of air pollutants in PRD in summer while highly loading of local industrial emissions tended to deteriorate the air quality as well.NO_3~-/SO_4~(2-) ratio indicated that mobile sources have considerably contribution to the urban aerosol,and stationary sources should not be neglected. Besides the primary emissions,complex atmospheric reactions under favorable weather conditions should be paid more attention for the control of primary emission in the PRD region.