Research Of Spatial Interpolation Algorithm And Its Application In Air Quality Monitoring

Air quality monitoring has become one important aspect of China's environmental protection. The air quality monitoring system based on Remote Sensing (RS) monitors and assesses regional environment via remotely sensed data obtained by environmental satellite and other satellite, assisted by other data like surface environmental survey data, geographic information data and meteorological data. Applying the known proximity spatial data to estimate and predict unknown spatial data is an effective way of tackling the incompleteness in obtaining spatial data, which is known as spatial interpolation. While there are many kinds of spatial interpolation algorithm, restudy, modification and application of spatial interpolation combined with a particular case is necessary. Through studying spatial interpolation algorithm, especially the Inverse Distance Weighted (IDW) and Ordinary Kriging (OK), this paper revises IDW, and designs the air quality monitoring system based on RS, and applies the improved IDW to the system.The main contents and contribution of the thesis:(1) It studies the frequently-used spatial interpolation algorithm, with the interpolation principle and realization of inverse distance weighted algorithm (IDW) and Ordinary Kriging (OK) in particular. IDW is based upon the principle of similarity in distance proximity, and hence, the shorter the distance of the known points, the larger the influence they have on interpolation points. OK is grounded on the theory of variogram and structural analysis, and therefore, dereferencing is on the basis of optimal unbiased predication of regional variables in a limited area.(2) On the grounds of comparing the advantages and defects of IDW and OK, the paper points out solving the weighting coefficient of IDW by substituting variogram which reflects spatial structural changes of regional variables and views distance as independent variables for the power of distance and searching for evaluating points through directional system to avoid large deviation of interpolation results caused by uneven distribution of evaluating points. It not only proposes the revised algorithm of IDW applying variogram and directional system, but realizes and cross-validates this algorithm.(3) Based on RS and other spatial information technology, in accordance with technical standards and specifications about Remote monitoring of ambient air changes, Combined of air quality monitoring management and technical applications in Henan, the thesis describes the design of air quality monitoring system of systematical architecture and functions, divides in four main parts, which does include air quality remote sensing applications, based information sharing platform, database and models, Completes the remote sensing monitoring, assessment and air pollution visualization tasks, and applies the revised IDW algorithm to the system.