摘要
以黄土高原地貌复杂区的陕西省澄城县为研究区,通过野外采样调查和室内分析,获取大量耕地地力相关信息,并借助GIS技术和综合运用层次分析法、模糊数学法、综合指数法等对研究区耕地地力进行自动化、定量化和可视化评价。结果表明:澄城县耕地地力可分为5等,其中1等地占19.05%,2等地占22.75%,3等地占31.3%,4等地占16.97%,5等地占9.94%。1、2、3等地主要分布在地势较平坦、灌溉条件较好、肥力较高的黄土塬面上,而4、5等地主要分布于坡度较大、水土流失严重、土壤耕层较薄、肥力低的丘陵沟壑区,利用类型主要为旱地。在全县14个乡镇中,寺前镇、韦庄镇和城关镇耕地地力水平较高,而尧头镇耕地地力较差。
Through field investigation and laboratory analysis of samples to get a lot of information about farmland productivity of Chengcheng County of Shaanxi Province located in complex topography regions of Loess Plateau,the farmland productivity was evaluated automatically,quantitatively and visually with the integrated use of GIS,Analytical Hierarch Program（AHP）,Fuzzy Mathematical Theory（FMT） and Comprehensive Index Method.GIS was used to construct spatial database of the geographic elements and evaluation units,evaluation index system of the study area,then to process and analyze the spatial data.AHP was used to determine the weight of each index.FMT was used to determine the fuzzy memberships of the indicators′ different numerical values.CIM was used to determine the index of each evaluation units of farmland productivity.The results showed that the farmland productivity of Chengcheng County can be classified into 5 grades.The area of grade 1 accounted for 19.05%,grade 2 for 22.75%,grade 3 for 31.3 %,grade 4 for 16.97%,and grade 5 for 9.94% of the total area respectively.The first 3 grades of farmland mainly distributed in the loess plateau with flat terrain,better irrigation and higher fertility,but,grade 4 and 5 mainly distributed in the hilly regions with steep slope,serious soil erosion,thin topsoil,lower fertility and mostly dry land.In 14 towns of Chengcheng County,the farmland productivity of Siqian town,Weizhuang town and Chengguan town were higher and that in Yaotou town was lower.
出处
《地理与地理信息科学》
CSSCI
CSCD
北大核心
2011年第4期57-61,共5页
Geography and Geo-Information Science
基金
国家自然科学基金项目(30872073)
陕西省自然科学基金项目(SJ08D08)
关键词
GIS
黄土高原地貌复杂区
耕地地力
空间分布
GIS
complex topography regions of Loess Plateau
farmland productivity
spatial distribution
