海洋渔业GIS中温度水平梯度计算的误差分析和新算法研究

Error Analysis and a New Algorithm to Calculate Horizontal Temperature Gradient in Marine Fishery GIS

在海洋渔业GIS应用中,用现有GIS直接计算渔区温度水平梯度时,由实际距离问题引起的相对误差达26％、绝对误差达0.124℃／10km,同时还存在渔区格网不规则问题和渔区格点值问题。本文提出了基于SST等值线计算渔区温度水平梯度一种新的GIS算法。该算法的结果优于用ArcGISTIN计算的结果,并可用于计算盐度、叶绿素等其它海洋要素的水平梯度。

Because the statistical unit of catch production is fishing grid whose size is 30'×30'or 10'×10' in marine fishery, the horizontal temperature gradient of fishing grid need to be calculated in order to analyze fishing ground environment by scientists. But there are the questions of real distance, irregular grid (after fishing grid is projected to Mercator projection) , value of grid points ( not cell value) if current commercial GIS software is used to calculated temperature gradients of fishing grid. For example, the max relative error of temperature gradient of fishing grid reaches 26. 48% , and the max absolute error of horizontal temperature gradient of fishing grid is 0. 124℃/10km, which is caused by the question of real distance and calculated from SST isolines on January 1-4,2001 in Northwest Pacific Ocean. A new algorithm to calculate horizontal temperature gradient of fishing grid from SST isoline is presented in this paper. The basic principle of this new algorithm is as follow: Interpolating temperature of fishing grid points in geographical coordinate system in order to build regular grid and index lines which angle is 45 degrees. The multi-section algorithm is used to interpolate temperature of fishing grid points, and exceptional temperature values are dealt with single point change surface interpolation containing orientation. The coordinate of fishing grid points with interpolating temperature is projected using Mercator projection, and the regular fishing grid becomes irregular fishing grid. The eight direction horizontal temperature gradients are computed with temperature values of nine points on each fishing grid, and the length of any two points, which is an important parameter, uses geodetic distance of elliptic earth. The methods of validating results are as follows: (1) The interpolating temperature of grid points is validated with two methods. One is manual estimation with temperature values of fishing grid points overlaying original SST isoline. Another is to compare SST isoline by overlaying original SST isoline on SST isoline generated with interpolating temperature of grid points. The same methods are used to validate the interpolating temperature of grid points by ArcGIS TIN. The result by algorithm of this paper is better than results by ArcGIS TIN. ( 2 ) The horizontal temperature gradient of fishing grid is validated by manual estimation with horizontal temperature gradient values of fishing grid overlaying original SST isoline. The same methods are used to validate results by ArcGIS GRID the interpolating temperature of grid points by ArcGIS. The result by algorithm of this paper is better than the results by ArcGIS.