南京林业大学学报（自然科学版）
南京林業大學學報（自然科學版）
남경임업대학학보（자연과학판）
JOURNAL OF NANJING FORESTRY UNIVERSITY(NATURAL SCIENCE EDITION)
2014年
1期
77-82
,共6页
干扰指数%Landsat TM/ETM+%干扰模式%驱动力分析%城市森林%南京
榦擾指數%Landsat TM/ETM+%榦擾模式%驅動力分析%城市森林%南京
간우지수%Landsat TM/ETM+%간우모식%구동력분석%성시삼림%남경
forest disturbance index%Landsat TM/ETM+%disturbance patterns%driving forces analysis%urban forests%Nanjing
以南京紫金山、幕府山和老山为研究对象，利用1992、1995、1998、2001、2003、2005、2007和2011年8期的Landsat TM /ETM＋数据进行缨帽变换，通过对变换后的各分量进行归一化操作进而建立森林干扰指数模型，然后进行3个区域森林干扰指数分级操作，最后借助森林资源二类调查数据以及Google Earth影像的目视解译结果，对发展的森林干扰指数分析方法进行了验证。验证结果表明：基于Landsat TM/ETM＋数据而发展的森林干扰分析方法是有效且可靠的。南京3个区域的森林干扰在1992-2001年间变化不明显，2001-2005年干扰上升明显，2005年之后下降趋势明显。空间上，幕府山森林受干扰最强，老山林场次之，紫金山最小。每个区域干扰强度的分布也各有特点，但相同的是区域周边的干扰指数明显大于中心地区。驱动南京城市森林干扰时空变化的因素主要包括人口增长、经济开发活动及景区游览等。
以南京紫金山、幕府山和老山為研究對象，利用1992、1995、1998、2001、2003、2005、2007和2011年8期的Landsat TM /ETM＋數據進行纓帽變換，通過對變換後的各分量進行歸一化操作進而建立森林榦擾指數模型，然後進行3箇區域森林榦擾指數分級操作，最後藉助森林資源二類調查數據以及Google Earth影像的目視解譯結果，對髮展的森林榦擾指數分析方法進行瞭驗證。驗證結果錶明：基于Landsat TM/ETM＋數據而髮展的森林榦擾分析方法是有效且可靠的。南京3箇區域的森林榦擾在1992-2001年間變化不明顯，2001-2005年榦擾上升明顯，2005年之後下降趨勢明顯。空間上，幕府山森林受榦擾最彊，老山林場次之，紫金山最小。每箇區域榦擾彊度的分佈也各有特點，但相同的是區域週邊的榦擾指數明顯大于中心地區。驅動南京城市森林榦擾時空變化的因素主要包括人口增長、經濟開髮活動及景區遊覽等。
이남경자금산、막부산화로산위연구대상，이용1992、1995、1998、2001、2003、2005、2007화2011년8기적Landsat TM /ETM＋수거진행영모변환，통과대변환후적각분량진행귀일화조작진이건립삼림간우지수모형，연후진행3개구역삼림간우지수분급조작，최후차조삼림자원이류조사수거이급Google Earth영상적목시해역결과，대발전적삼림간우지수분석방법진행료험증。험증결과표명：기우Landsat TM/ETM＋수거이발전적삼림간우분석방법시유효차가고적。남경3개구역적삼림간우재1992-2001년간변화불명현，2001-2005년간우상승명현，2005년지후하강추세명현。공간상，막부산삼림수간우최강，로산림장차지，자금산최소。매개구역간우강도적분포야각유특점，단상동적시구역주변적간우지수명현대우중심지구。구동남경성시삼림간우시공변화적인소주요포괄인구증장、경제개발활동급경구유람등。
Taking the three areas of Zijin, Mufu and Laoshan Mountains located in Nanjing as the case study, using the Landsat TM/ETM+ observations dated in 1992, 1995, 1998, 2001, 2003, 2005, 2007 and 2011, indices including brightness, greenness and wetness derived from the tasseled cap transform were obtained first, followed by the establish-ment of the forest disturbance index via a normalization approach. Ultimately, grading the forest disturbance severity was made and the forest disturbance analyses were in part validated by using the forest resources inventories coupled with the high spatial resolution Google Earth imagery. Results showed that the forest disturbance analysis methods developed from Landsat TM/ETM+ imagery in the current work were effective and reliable after an intensive validation. Forest disturb-ance intensity remained almost unchanged during the period 1992 to 2001, giving way to an increase in forest disturbance severity over the time period 2001 to 2005, connecting to a declining trend after 2005. Additionally, the average disturb-ance values of the three regions differed from each other, Mufu Mountains with the strongest forest disturbance and Zijin Mountains the lowest, which adequately reflects the differences in forest management purposes and approaches. Distribu-tion of forest disturbance severity of the regions also had their own characteristics, but the patterns that higher disturb-ance severities were observed along the boundaries of the three regions, with lower disturbance levels located in the cen-tral portions of the regions, were same. Ultimately, the driving forces responsible for the differences in observed forest disturbances were identified as demographic expansion, mining events, forest logging and forest insects and disease and forest eco-tourism.
