农业工程学报
農業工程學報
농업공정학보
2014年
24期
288-297
,共10页
余述琼%张蚌蚌%相慧%孔祥斌
餘述瓊%張蚌蚌%相慧%孔祥斌
여술경%장방방%상혜%공상빈
土地利用%监测%等别%耕地质量%样点%布控方法%因素组合%滇黔高原山地区
土地利用%鑑測%等彆%耕地質量%樣點%佈控方法%因素組閤%滇黔高原山地區
토지이용%감측%등별%경지질량%양점%포공방법%인소조합%전검고원산지구
land use%monitoring%grading%arable land quality%sample point%layout method%factors combination%Dianqian plateau mountain area
科学确定耕地质量等级监测样点布控方法,形成中国耕地质量动态监测布控体系,是掌握耕地质量动态、支撑国家粮食安全的重要技术依据。该文基于标准样地设置,以滇黔高原山地区为例,提出以耕地质量等别为控制,熟制—土壤类型—海拔—土地利用系数—土地经济系数因素组合确定监测样点的方法,即因素组合法;其步骤为:根据因素组合类型初步确定监测点数量;依据面积比例修正各等别监测点数量;基于GIS确定和选取监测点空间位置和来源,形成监测样点;构建模型对监测点代表性进行检验。结果表明,滇黔高原山地区确定144个监测样点,其中7个来源于国家级标准样地,44个来源于省级标准样地,93个来源于耕地分等单元图斑;采用因素组合法形成滇黔高原山地区监测样点,能够实现国家尺度上二级区内对耕地质量变化的动态监测,监测样点满足统计学要求和面积代表性。基于因素组合的耕地质量监测样点布控方法,可以为建立覆盖全国的耕地质量监测体系提供借鉴,为中国耕地数量、质量并重的宏观管理提供技术支撑。
科學確定耕地質量等級鑑測樣點佈控方法,形成中國耕地質量動態鑑測佈控體繫,是掌握耕地質量動態、支撐國傢糧食安全的重要技術依據。該文基于標準樣地設置,以滇黔高原山地區為例,提齣以耕地質量等彆為控製,熟製—土壤類型—海拔—土地利用繫數—土地經濟繫數因素組閤確定鑑測樣點的方法,即因素組閤法;其步驟為:根據因素組閤類型初步確定鑑測點數量;依據麵積比例脩正各等彆鑑測點數量;基于GIS確定和選取鑑測點空間位置和來源,形成鑑測樣點;構建模型對鑑測點代錶性進行檢驗。結果錶明,滇黔高原山地區確定144箇鑑測樣點,其中7箇來源于國傢級標準樣地,44箇來源于省級標準樣地,93箇來源于耕地分等單元圖斑;採用因素組閤法形成滇黔高原山地區鑑測樣點,能夠實現國傢呎度上二級區內對耕地質量變化的動態鑑測,鑑測樣點滿足統計學要求和麵積代錶性。基于因素組閤的耕地質量鑑測樣點佈控方法,可以為建立覆蓋全國的耕地質量鑑測體繫提供藉鑒,為中國耕地數量、質量併重的宏觀管理提供技術支撐。
과학학정경지질량등급감측양점포공방법,형성중국경지질량동태감측포공체계,시장악경지질량동태、지탱국가양식안전적중요기술의거。해문기우표준양지설치,이전검고원산지구위례,제출이경지질량등별위공제,숙제—토양류형—해발—토지이용계수—토지경제계수인소조합학정감측양점적방법,즉인소조합법;기보취위:근거인소조합류형초보학정감측점수량;의거면적비례수정각등별감측점수량;기우GIS학정화선취감측점공간위치화래원,형성감측양점;구건모형대감측점대표성진행검험。결과표명,전검고원산지구학정144개감측양점,기중7개래원우국가급표준양지,44개래원우성급표준양지,93개래원우경지분등단원도반;채용인소조합법형성전검고원산지구감측양점,능구실현국가척도상이급구내대경지질량변화적동태감측,감측양점만족통계학요구화면적대표성。기우인소조합적경지질량감측양점포공방법,가이위건립복개전국적경지질량감측체계제공차감,위중국경지수량、질량병중적굉관관리제공기술지탱。
With the stability of arable land’s quantity, monitoring land quality has become a high priority research for understanding the effects of the dynamic change of arable land on food security in China, as well as the layout method on monitoring arable land quality change. However, there are integrated factors such as climate, terrain, soil, access to irrigation, rural road, trade-off between input and output, which affect arable land quality change over time and space. We propose a new monitoring framework titled factors’ combination, which includes such factors affecting arable land quality as natural conditions (e.g., climate, soil, geomorphology), the utilization of level (e.g., farmland infrastructure, land management, land use coefficient), income level (e.g., land use structure and mode, the input and output of arable land, land economic coefficient), and reference cropping system to form a monitoring reference arable land unit. We illustrate this new method using the Dianqian plateau mountain area as a case study. Spatial overlay analysis of main factors and geostatistics method using GIS were employed to test this method. Specific steps of factors’ combination method are as follows: 1) we preliminarily determine the number of monitoring reference samples according to the type of factors’ combination; 2) on the basis of the proportion of arable land area at each grade accounting for the total area, we then revise the number of monitoring samples and supplement monitoring samples for those gradations which have relatively few monitoring samples;3) based on GIS analysis results, if the same factors’ combination distributes in the different space positions of second zone and meets the requirements of monitoring sample, multiple figure spots of the factors’ combination will be kept at the same time, and eventually figure spot of the grading unit will be determined;4) given overlay the map spot of grading unit and the national standard sample and the provincial standard sample respectively, we take the national standard sample or provincial standard sample as the monitoring sample for those overlaying parts;then convert the remaining figure spots of grading into a point as the monitoring sample, and determine the final number of monitoring samples, spatial location and its source;5) we build up model on representative index of area of monitoring sample and adopt the geo-statistical method to carry on the representative test for monitoring sample to optimize the monitoring sample. The results show that 144 monitoring reference sample units include 7 from the national standard sample, 44 from provincial standard sample and 93 from arable land grading unit, and they were selected as a whole for monitoring arable land quality in Dianqian plateau mountain area using our new method of factors’ combination. The distribution of the selected monitoring reference land units not only provide samples to monitor the arable land quality change in the second zone of national scale, but also meet the requirements of statistical science and representative of area. Layout method for monitoring sample point of arable land quality level using factors’ combination, can provide reference for building up the whole country’s dynamic monitoring systems, and offer technical support to achieve comprehensive management of quantity and quality of arable land at national level in China.