CAJ | 학술논문

不同时相土地利用/覆被数据间的空间配准误差，是产生土地利用/覆被伪变化图斑的一个主要原因。本文从土地利用/覆被原始图斑与其相邻的变化图斑间的空间关系角度，提出了由同一原始图斑产生的土地利用/覆被伪变化图斑的面积对称理论，设计和实现了针对因空间配准误差而导致的土地利用/覆被伪变化图斑自动化检测模型，并以内蒙古自治区通辽市奈曼旗1980年和2000年两期土地利用/覆被图对该模型进行了实验模拟。结果表明：当两期数据的空间配准误差不超过原始影像1个像元时，总体检测精度达到90%以上；误差不超过5个像元时，总体检测精度达到80%以上；误差不超过原始影像10个像元时，总体检测精度达到70％以上。同时，由于运行时唯一需设定的面积对称系数阈值可设为0.2-0.4（默认设为0.3），该检测模型可适用于由空间配准误差引起的伪变化图斑的自动检查，可满足由于空间配准误差所引起土地利用/覆被伪变化图斑剔除的需求。
불동시상토지이용/복피수거간적공간배준오차，시산생토지이용/복피위변화도반적일개주요원인。본문종토지이용/복피원시도반여기상린적변화도반간적공간관계각도，제출료유동일원시도반산생적토지이용/복피위변화도반적면적대칭이론，설계화실현료침대인공간배준오차이도치적토지이용/복피위변화도반자동화검측모형，병이내몽고자치구통료시내만기1980년화2000년량기토지이용/복피도대해모형진행료실험모의。결과표명：당량기수거적공간배준오차불초과원시영상1개상원시，총체검측정도체도90%이상；오차불초과5개상원시，총체검측정도체도80%이상；오차불초과원시영상10개상원시，총체검측정도체도70％이상。동시，유우운행시유일수설정적면적대칭계수역치가설위0.2-0.4（묵인설위0.3），해검측모형가괄용우유공간배준오차인기적위변화도반적자동검사，가만족유우공간배준오차소인기토지이용/복피위변화도반척제적수구。
Co-registration error between two land use maps based on different dates can cause a considerable overestimation of the land use/cover change. Even a small amount of misregistration markedly reduces the accu-racy of land cover change estimates. Without relevant information about misregistration, existing methods can-not work effectively to detect and eliminate the false changes caused by misregistration. In this paper, we pro-pose a methodology (Symmetric Theory) from the viewpoint of the relationship between original land use poly-gon and the changed polygons to detect the false change caused by misregistration. Symmetric Theory presents that the area of‘changing from’and‘changing to’polygons overlaid from the original polygon is symmetric in some degree, if true change polygons are eliminated from the changing polygons. Based on this theory, an auto-mated detecting model is designed and developed. A case study was conducted using this method based on two land cover maps from 1980 and 2000, and their simulated misregistration maps for Naiman County, Tongliao City, Inner Mongolia, China (a total area of 8137.6 km2). This study shows that this method can effectively discriminate the spurious land cover changes from true land cover changes with false change detection accuracy ranging from 75.0%to 87.4%, true change detection accuracy ranging from 71.2%to 93.8%, and overall detection accuracy rang-ing from 73.3%to 92.7%. However, with the image shifts from half to ten pixels (15m to 300m), the ability of de-tecting false changes decreases with the increase of image misregistration. And when using this method, the SI threshold should be set as 0.2-0.4. If no relevant knowledge is mentioned, 0.3 is the best choice.