国土资源遥感
國土資源遙感
국토자원요감
REMOTE SENSING FOR LAND & RESOURCES
2014年
3期
160-165
,共6页
刘萌%杨武年%邵怀勇%孙小飞
劉萌%楊武年%邵懷勇%孫小飛
류맹%양무년%소부용%손소비
遥感%GIS%土地利用/覆被变化( LUCC)%转移矩阵%马尔科夫预测
遙感%GIS%土地利用/覆被變化( LUCC)%轉移矩陣%馬爾科伕預測
요감%GIS%토지이용/복피변화( LUCC)%전이구진%마이과부예측
remote sensing%GIS%land use/cover change (LUCC)%transfer matrix%Markov forecast
四川广元市青川县是国家生态试点县和退耕还林实施县,查明该区土地利用/覆被现状及其时空动态变化信息,为政府有关部门规划决策提供科学依据具有重要意义。应用RS和GIS技术,基于2000年、2005年和2010年3个时相的陆地卫星TM图像,通过图像处理和信息提取,获得了该区3期土地利用/覆被数据。在此基础上,分析了青川县近10 a土地利用/覆被动态变化过程,查明了引起动态变化的主要驱动力因素,最后,对该区2015年和2020年土地利用/覆被的面积比例进行了预测。研究结果表明:青川县2000-2005年间,耕地、水域和未利用地面积减少,林地、草地和建设用地面积增加;2005-2010年间,耕地和草地面积减少,林地、水域、建设用地和未利用地面积增加;两段时期耕地面积持续减少,但减幅减小,林地面积持续增加,增幅减小,建设用地持续增加且增幅增大,水域和未利用地先减后增,草地先增后减。究其原因,认为政策、经济发展和人口增长及自然灾害等因素是研究区土地利用变化的主要影响因子。经过预测,在相关政策不变且没有自然灾害发生的情况下,2015年林地面积占全县总面积的比例将由2010年的58.57%增长为59.01%,到2020年将继续增长为59.44%,耕地面积比例到2020年将减少至29.13%,建设用地面积比例继续增加至0.22%。
四川廣元市青川縣是國傢生態試點縣和退耕還林實施縣,查明該區土地利用/覆被現狀及其時空動態變化信息,為政府有關部門規劃決策提供科學依據具有重要意義。應用RS和GIS技術,基于2000年、2005年和2010年3箇時相的陸地衛星TM圖像,通過圖像處理和信息提取,穫得瞭該區3期土地利用/覆被數據。在此基礎上,分析瞭青川縣近10 a土地利用/覆被動態變化過程,查明瞭引起動態變化的主要驅動力因素,最後,對該區2015年和2020年土地利用/覆被的麵積比例進行瞭預測。研究結果錶明:青川縣2000-2005年間,耕地、水域和未利用地麵積減少,林地、草地和建設用地麵積增加;2005-2010年間,耕地和草地麵積減少,林地、水域、建設用地和未利用地麵積增加;兩段時期耕地麵積持續減少,但減幅減小,林地麵積持續增加,增幅減小,建設用地持續增加且增幅增大,水域和未利用地先減後增,草地先增後減。究其原因,認為政策、經濟髮展和人口增長及自然災害等因素是研究區土地利用變化的主要影響因子。經過預測,在相關政策不變且沒有自然災害髮生的情況下,2015年林地麵積佔全縣總麵積的比例將由2010年的58.57%增長為59.01%,到2020年將繼續增長為59.44%,耕地麵積比例到2020年將減少至29.13%,建設用地麵積比例繼續增加至0.22%。
사천엄원시청천현시국가생태시점현화퇴경환림실시현,사명해구토지이용/복피현상급기시공동태변화신식,위정부유관부문규화결책제공과학의거구유중요의의。응용RS화GIS기술,기우2000년、2005년화2010년3개시상적륙지위성TM도상,통과도상처리화신식제취,획득료해구3기토지이용/복피수거。재차기출상,분석료청천현근10 a토지이용/복피동태변화과정,사명료인기동태변화적주요구동력인소,최후,대해구2015년화2020년토지이용/복피적면적비례진행료예측。연구결과표명:청천현2000-2005년간,경지、수역화미이용지면적감소,임지、초지화건설용지면적증가;2005-2010년간,경지화초지면적감소,임지、수역、건설용지화미이용지면적증가;량단시기경지면적지속감소,단감폭감소,임지면적지속증가,증폭감소,건설용지지속증가차증폭증대,수역화미이용지선감후증,초지선증후감。구기원인,인위정책、경제발전화인구증장급자연재해등인소시연구구토지이용변화적주요영향인자。경과예측,재상관정책불변차몰유자연재해발생적정황하,2015년임지면적점전현총면적적비례장유2010년적58.57%증장위59.01%,도2020년장계속증장위59.44%,경지면적비례도2020년장감소지29.13%,건설용지면적비례계속증가지0.22%。
Qingchuan County of Guangyuan City in Sichuan Province is a national ecological pilot county and implementation country of returning farmland to forest. The understanding of the current situation and spatial -temporal dynamic change of land use/cover is of great significance in providing the scientific basis for relevant government departments. In this paper, with the application of RS and GIS technology, on the basis of TM images in 2000, 2005 and 2010, and through image processing and information extracting, the authors acquired land use/cover maps in different years and established the database. On such a basis, the land use/cover dynamic change process in Qingchuan in the past 10 years was analyzed, and the driving force that caused the change was identified. At last, land use/cover area ratio of the study area in 2015 and 2020 were predicted. According to the results obtained, between 2000 and 2005, the area of arable land, water and unused land decreased, while the area of woodland, grassland and construction land increased;between 2015 and 2020, the area of arable land and grassland decreased, while the area of woodland, water, construction land and unused land increased. During the ten years, the area of arable land continually decreased with the scale reduced, the area of woodland continually increased with the scale reduced, the area of construction land increased continually with the scale increased, the area of water and unused land decreased and then increased, and the area of grassland increased and then decreased. An analyses reveals that policy, economic development, population growth, and natural disasters seem to be the principal impact factors of land use changes in the study area. It is inferred that, under the conditions that relevant policy is unchanged and no natural disasters occur, the proportion of woodland area will increase from 58. 57% in 2010 to 59 . 01% in 2015 , and increase to 59 . 44% in 2020 . The proportion of arable area will decrease to 29 . 13% and the proportion of construction land will continually increase to 0 . 22% by 2020 .