测绘与空间地理信息
測繪與空間地理信息
측회여공간지리신식
GEOMATICS & SPATIAL INFORMATION TECHNOLOGY
2015年
7期
30-33
,共4页
张熙%鹿琳琳%王萍%隋悦%周春艳
張熙%鹿琳琳%王萍%隋悅%週春豔
장희%록림림%왕평%수열%주춘염
资源一号02 C%面向对象%森林分类%多尺度分割%最优尺度
資源一號02 C%麵嚮對象%森林分類%多呎度分割%最優呎度
자원일호02 C%면향대상%삼림분류%다척도분할%최우척도
ZY1 -02 C%object -based%forest classification%multi -scale segmentation%optimal scale
资源一号02 C卫星是我国自主研发的高分辨率卫星。利用面向对象的信息提取技术,开展基于资源一号02C高分辨率数据的林区植被分类,具体分为三个步骤:1)对影像进行多尺度分割,获取最优尺度;2)根据各类地物特点及相互间关系,建立地物类型层次;3)结合光谱、纹理、形状多种对象特征,进行地物分类。以广西猫儿山自然保护区为例,根据区内地物特点,将地物分为针叶林、阔叶林、竹林、灌丛、耕地、非植被、阴影等7种类型,经检验表明该方法总体分类精度达到82.24%,kappa系数为0.77,优于面向对象的最邻近法和基于像元的最大似然分类。
資源一號02 C衛星是我國自主研髮的高分辨率衛星。利用麵嚮對象的信息提取技術,開展基于資源一號02C高分辨率數據的林區植被分類,具體分為三箇步驟:1)對影像進行多呎度分割,穫取最優呎度;2)根據各類地物特點及相互間關繫,建立地物類型層次;3)結閤光譜、紋理、形狀多種對象特徵,進行地物分類。以廣西貓兒山自然保護區為例,根據區內地物特點,將地物分為針葉林、闊葉林、竹林、灌叢、耕地、非植被、陰影等7種類型,經檢驗錶明該方法總體分類精度達到82.24%,kappa繫數為0.77,優于麵嚮對象的最鄰近法和基于像元的最大似然分類。
자원일호02 C위성시아국자주연발적고분변솔위성。이용면향대상적신식제취기술,개전기우자원일호02C고분변솔수거적림구식피분류,구체분위삼개보취:1)대영상진행다척도분할,획취최우척도;2)근거각류지물특점급상호간관계,건입지물류형층차;3)결합광보、문리、형상다충대상특정,진행지물분류。이엄서묘인산자연보호구위례,근거구내지물특점,장지물분위침협림、활협림、죽림、관총、경지、비식피、음영등7충류형,경검험표명해방법총체분류정도체도82.24%,kappa계수위0.77,우우면향대상적최린근법화기우상원적최대사연분류。
ZY1-02C high resolution satellite is research and developed by our country .In this paper, we do research on forest classi-fication use object-based information extraction technology with ZY 1-02C high resolution image .Firstly, implement multi -scale segmentation and obtain the optimal scale;secondly , developing hierarchical structure considering the object features and relationship of each other;then, extract land cover informationwith the help of a variety of object characteristics like spectrum , texture, shape and so on.Our study area is Guangxi Mao′er Mountain Nature Reserve , classify the study area into seven land cover types include conifer-ous forest, broad-leaved forest, bamboo, shrub, farmland, non-vegetation area and shade , the overall accuracy is 82.51%, kappa coefficient is 0.79, higher than the object -based Nearest Neighbor classification and pixel -based Maximum Likelihood classifica-tion.