基于GIS与GPS的农户土壤养分空间变异及精准施肥研究
|
摘要
精准农业是21世纪世界各国农业的发展方向,不仅提高了作物的产量还减少了肥料的投入,提高了肥料的利用率,减少了环境污染,使施肥地块的经济、环境和生态效益明显改善,其中变量施肥是精准农业体系中的一个重要方面,本文在利用GIS和GPS研究土壤养分空间变异的基础上,利用以农户作为精准施肥的单元,探讨在中国农村进行精准施肥的途径。利用ARCGIS进行土壤养分空间变异研究,采取克里格插值算法,生成了图形平滑、结果准确的土壤养分空间变异分布图,为精准施肥提供了可靠的数据基础,使变量施肥的基础数据具有可靠性,同时利用农业专家系统配方推荐施肥技术在中国南方土壤上进行大比例尺以农户地块为施肥单元的推荐施肥研究,根据需要开发推荐施肥信息查询系统采用面向对象技术,充分利用组件式地理信息系统的强大GIS功能,为精准施肥查询和使用提供支持,研究结果表明:
1.土壤五个特性中pH、有机质、全氮符合正态分布,趋势参数宜选取零阶,速效磷、速效钾符合对数正态分布,趋势参数宜选取二阶。
2.土壤空间变异度大小,速效磷>速效钾>全氮>有机质>pH,主要与土壤母质性质和施肥习惯有关,pH的空间变异最小主要是由土壤母质造成的、有机质和全氮的变化是因为肥,造成其土壤变异较小,钾在土壤中流动性比较大变异相对较小,而磷在土壤流动性较小主要是由于其在土壤中的含量常随施肥点位置不同而有较大的差异。
3.土壤五个特性最适合的模型均为球面模型,其基底值C0与基台值C0+C的比例,速效磷及速效钾的基底值C0与基台值C0+C比例<25%,说明二者具有强烈的空间相关性,其空间变异主要是由土壤母质、地形、气候等非人为因素(空间自相关部分)引起的,全氮和有机质的基底值C0与基台值C0+C比例在25%~75%之间,表明二者具有中等相关性,其空间变异是由内在因子(土壤母质等)和外在因子(人类活动)共同作用的结果,pH的基底值C0与基台值C0+C比例比例>75%,说明其空间变异主要是由人类活动引起的,pH空间变异方向和当地的公路方向非常一致,主要的原因是修路使用石灰的影响,石灰的粉尘沿着公路向两旁扩散,造成土壤pH与公路越近越高,离公路越远越低,当距离达到一定程度,修路造成的影响就不复存在。五个土壤特性的变程大小,pH>全氮>有机质>速效钾>速效磷,变程最小的速效磷其变程为71.732m仍大于50m采样间隔,说明采样间距符合要求。
4.有机质和全氮的相关系数达到了0.814在一尾下达到了极显著,说明有机质和全氮之间具有高度的正相关关系,即全氮含量的高低和有机质的高低有很大的关系,水提pH与有机质、全氮、速效磷在一尾下都达到了极显著,说明水提pH分别与有机质、全氮、速效磷之间具有高度的正相关关系,即有机质、全氮、速效磷含量的高低和水提pH的高低有很大的关系,海拔和速效钾之间相关系数在一尾下达到了显著,说明海拔和速效钾之间也具有高度的正相关关系。
5.克里格差值法土壤全氮、速效磷、速效钾含量克里格差值分析:表明本研究区内全氮含量在变化范围在0.84‰-1.933‰之间,绝大多数地区土壤全氮含量在1.06‰以上,其空间变异相对较缓,只有在研究区的东北有一些地区变异较大。土壤速效磷值变化范围在1.0mg/kg-62.0 mg/kg之间,其空间变异非常复杂,其中按照国家标准12MG/KG的含量本研究区域东部仍有一些地区缺磷土壤需要补磷,而西南部一些地区,土壤速效磷含量较高达到了43MG/KG以上,可以少施或不施磷肥。土壤速效钾值范围在39.0mg/kg-135.0 mg/kg之间,其空间变异非常复杂,其中按照国家标准80MG/KG的含量该研究区域绝大部分地区缺钾,主要和当地少施钾肥的施肥习惯有关,土壤需要补钾。
6.采用可视化编程语言Visual Basic和控件式MAPGIS开发技术,以开发出了一个界面友好,使用方便的农户施肥推荐配方查询系统,为精准施肥查询和使用提供支持。
本文提出的精准施肥方案,采用农户为单元的施肥推荐既可以避免土壤养分空间变异造成的推荐施肥偏差,又可考虑中国农村分散经营的实际的状况,从而使土壤养分管理更加精细化,即考虑了土壤的空间连续性、土壤空间变异性,而且采用的配方施肥系统是经过多年肥料试验得出的土壤校正系数,并以此为依据得出的精准施肥推荐,不仅技术先进可靠,而且经济可行,对于我国以农户为单位的农田施肥应用具有一定的指导意义。
Precision Agriculture is the main trend of global agriculture envelopments in 21st century,which can increase the use factor of the fertilizer、reduce the environment pollution; which can also improve the benefits of the economy、the environment and the zoology of fertilization plot. Variable rate fertilization is one important aspect of the Precision Agriculture system . The research discussed the approach of Precision Fertilization in the country of the china, which was based on GIS and GPS and used the peasant plot as the unit. The research is based on the advanced succeed experience of variable rate fertilization ,which was used the best GIS software–ARCGIS and the research method -ordinary Kriging interpolation method recognized that is a recognized and the best method to research the soil nutrient space variation. The Ordinary Kriging interpolation method can create the soil nutrient space variation map. The figure is smooth and the result is exact. The soil nutrient space variation map offers a credible data and makes the base data of variable rate fertilization no doubt. At the same time the data was used to research the recommendation prescription by the unit of peasant land, which was based on the recommendation fertilization technology of Agriculture Expert System at a large scale on south china country. Recommendation fertilization information query system was developed by Visual Basic 6.0 and COM-Mapgis6.5SDK in this paper. Which was developed by the face-object-technique programme language and the ComGIS that mean the groupware geography information system, for supporting the query and use of recommendation fertilization? There are some important conclusions educed from this paper:
Firstly, pH、organic matter and total nitrogen accord with normal school and the trend parameter accord with no-rank in those five soil characteristics .The available p and the available k accord with the logarithm normal school and the trend parameter accord with two-ranks .
Secondly, The sequence from max to min of the space aberrance variation is that Available pH、the available k、total nitrogen、organic matter、pH, which are related mainly with the soil fountainhead and the soil fertilization habit. The reason of pH is brought by the the soil fountainhead and the soil fertilization habit. The variation of total nitrogen and organic matter, which are related mainly with the the soil fountainhead and the soil fertilization habit. The little variation of the kalium is because that the kalium fluxion is great. The little variation of the phosphor is strong related the fertilization habit.
Thirdly, the fit model of those soil characters is the spherical. The proportion between the nugget and the sill of the available p and the available k is less than 25 percent, which means both soil characters have strong space relativity for the inhuman factors such as the soil fountainhead、the terrain、climate. The proportion between the nugget and the sill of total nitrogen and organic matter between 25 percent and 75 percent, which means both soil characters have middling space relativity caused by soil fountainhead and human activity. The proportion between the nugget and the sill of pH exceeded 75 percent which means both soil characters space relativity caused mainly by human activity. The pH space variation direction is accorded with the road because the calcareousness powder pervasion which was used to build the road. The more near the road, the more high the pH. The sequence from max to min of the range is that pH、organic matter、total nitrogen、available k,、available p ,even the range of available p is more than the sampling interval which means it is up to the mustard
Fourth, the mutuality correlation modulus between organic matter and total nitrogen reached the best salience, which means the total nitrogen had a high correlation with organic matter. The pH had a high correlation with the organic matter、and the available p. The available k had a high correlation with the altitude.
Fifth, the Kriging Interpolation result indicates that the changing extension of total nitrogen between 0.84‰-1.933‰, most areas reached 1.06‰.The space variation of the total nitrogen is slow, but the east-north of research area is obvious. The changing extension of available p between 1.0mg/kg-62.0 mg/kg, the space variation of the p is complexity .The east of research area lacks the available p and need p fertilizer, but the west-south does not need it. The changing extension of available k between 39.0mg/kg-135.0 mg/kg and the space variation of the k is complexity. The mostly research area lacks the available k. It had a high correlation with the local fertilization habit. The soil needs the k fertilizer.
Sixth, A farmer recommendation fertilization query system was developed by query Visual Basic and COM-MAPGIS, which would support the query and the use of precision Agriculture.
In conclusion, this paper bring forward the way of precision fertilization which not only considers the continuity and the variability of soil space but also adopts the recommendation fertilization system that bases on the soil nutrient Correlation coefficient by many years fertilizer experimentation . This method is not only advanced in technology but also doable in economy. It will have some direction meanings for application of precision agriculture technique in china as unit of peasant land.
1.土壤五个特性中pH、有机质、全氮符合正态分布,趋势参数宜选取零阶,速效磷、速效钾符合对数正态分布,趋势参数宜选取二阶。
2.土壤空间变异度大小,速效磷>速效钾>全氮>有机质>pH,主要与土壤母质性质和施肥习惯有关,pH的空间变异最小主要是由土壤母质造成的、有机质和全氮的变化是因为肥,造成其土壤变异较小,钾在土壤中流动性比较大变异相对较小,而磷在土壤流动性较小主要是由于其在土壤中的含量常随施肥点位置不同而有较大的差异。
3.土壤五个特性最适合的模型均为球面模型,其基底值C0与基台值C0+C的比例,速效磷及速效钾的基底值C0与基台值C0+C比例<25%,说明二者具有强烈的空间相关性,其空间变异主要是由土壤母质、地形、气候等非人为因素(空间自相关部分)引起的,全氮和有机质的基底值C0与基台值C0+C比例在25%~75%之间,表明二者具有中等相关性,其空间变异是由内在因子(土壤母质等)和外在因子(人类活动)共同作用的结果,pH的基底值C0与基台值C0+C比例比例>75%,说明其空间变异主要是由人类活动引起的,pH空间变异方向和当地的公路方向非常一致,主要的原因是修路使用石灰的影响,石灰的粉尘沿着公路向两旁扩散,造成土壤pH与公路越近越高,离公路越远越低,当距离达到一定程度,修路造成的影响就不复存在。五个土壤特性的变程大小,pH>全氮>有机质>速效钾>速效磷,变程最小的速效磷其变程为71.732m仍大于50m采样间隔,说明采样间距符合要求。
4.有机质和全氮的相关系数达到了0.814在一尾下达到了极显著,说明有机质和全氮之间具有高度的正相关关系,即全氮含量的高低和有机质的高低有很大的关系,水提pH与有机质、全氮、速效磷在一尾下都达到了极显著,说明水提pH分别与有机质、全氮、速效磷之间具有高度的正相关关系,即有机质、全氮、速效磷含量的高低和水提pH的高低有很大的关系,海拔和速效钾之间相关系数在一尾下达到了显著,说明海拔和速效钾之间也具有高度的正相关关系。
5.克里格差值法土壤全氮、速效磷、速效钾含量克里格差值分析:表明本研究区内全氮含量在变化范围在0.84‰-1.933‰之间,绝大多数地区土壤全氮含量在1.06‰以上,其空间变异相对较缓,只有在研究区的东北有一些地区变异较大。土壤速效磷值变化范围在1.0mg/kg-62.0 mg/kg之间,其空间变异非常复杂,其中按照国家标准12MG/KG的含量本研究区域东部仍有一些地区缺磷土壤需要补磷,而西南部一些地区,土壤速效磷含量较高达到了43MG/KG以上,可以少施或不施磷肥。土壤速效钾值范围在39.0mg/kg-135.0 mg/kg之间,其空间变异非常复杂,其中按照国家标准80MG/KG的含量该研究区域绝大部分地区缺钾,主要和当地少施钾肥的施肥习惯有关,土壤需要补钾。
6.采用可视化编程语言Visual Basic和控件式MAPGIS开发技术,以开发出了一个界面友好,使用方便的农户施肥推荐配方查询系统,为精准施肥查询和使用提供支持。
本文提出的精准施肥方案,采用农户为单元的施肥推荐既可以避免土壤养分空间变异造成的推荐施肥偏差,又可考虑中国农村分散经营的实际的状况,从而使土壤养分管理更加精细化,即考虑了土壤的空间连续性、土壤空间变异性,而且采用的配方施肥系统是经过多年肥料试验得出的土壤校正系数,并以此为依据得出的精准施肥推荐,不仅技术先进可靠,而且经济可行,对于我国以农户为单位的农田施肥应用具有一定的指导意义。
Precision Agriculture is the main trend of global agriculture envelopments in 21st century,which can increase the use factor of the fertilizer、reduce the environment pollution; which can also improve the benefits of the economy、the environment and the zoology of fertilization plot. Variable rate fertilization is one important aspect of the Precision Agriculture system . The research discussed the approach of Precision Fertilization in the country of the china, which was based on GIS and GPS and used the peasant plot as the unit. The research is based on the advanced succeed experience of variable rate fertilization ,which was used the best GIS software–ARCGIS and the research method -ordinary Kriging interpolation method recognized that is a recognized and the best method to research the soil nutrient space variation. The Ordinary Kriging interpolation method can create the soil nutrient space variation map. The figure is smooth and the result is exact. The soil nutrient space variation map offers a credible data and makes the base data of variable rate fertilization no doubt. At the same time the data was used to research the recommendation prescription by the unit of peasant land, which was based on the recommendation fertilization technology of Agriculture Expert System at a large scale on south china country. Recommendation fertilization information query system was developed by Visual Basic 6.0 and COM-Mapgis6.5SDK in this paper. Which was developed by the face-object-technique programme language and the ComGIS that mean the groupware geography information system, for supporting the query and use of recommendation fertilization? There are some important conclusions educed from this paper:
Firstly, pH、organic matter and total nitrogen accord with normal school and the trend parameter accord with no-rank in those five soil characteristics .The available p and the available k accord with the logarithm normal school and the trend parameter accord with two-ranks .
Secondly, The sequence from max to min of the space aberrance variation is that Available pH、the available k、total nitrogen、organic matter、pH, which are related mainly with the soil fountainhead and the soil fertilization habit. The reason of pH is brought by the the soil fountainhead and the soil fertilization habit. The variation of total nitrogen and organic matter, which are related mainly with the the soil fountainhead and the soil fertilization habit. The little variation of the kalium is because that the kalium fluxion is great. The little variation of the phosphor is strong related the fertilization habit.
Thirdly, the fit model of those soil characters is the spherical. The proportion between the nugget and the sill of the available p and the available k is less than 25 percent, which means both soil characters have strong space relativity for the inhuman factors such as the soil fountainhead、the terrain、climate. The proportion between the nugget and the sill of total nitrogen and organic matter between 25 percent and 75 percent, which means both soil characters have middling space relativity caused by soil fountainhead and human activity. The proportion between the nugget and the sill of pH exceeded 75 percent which means both soil characters space relativity caused mainly by human activity. The pH space variation direction is accorded with the road because the calcareousness powder pervasion which was used to build the road. The more near the road, the more high the pH. The sequence from max to min of the range is that pH、organic matter、total nitrogen、available k,、available p ,even the range of available p is more than the sampling interval which means it is up to the mustard
Fourth, the mutuality correlation modulus between organic matter and total nitrogen reached the best salience, which means the total nitrogen had a high correlation with organic matter. The pH had a high correlation with the organic matter、and the available p. The available k had a high correlation with the altitude.
Fifth, the Kriging Interpolation result indicates that the changing extension of total nitrogen between 0.84‰-1.933‰, most areas reached 1.06‰.The space variation of the total nitrogen is slow, but the east-north of research area is obvious. The changing extension of available p between 1.0mg/kg-62.0 mg/kg, the space variation of the p is complexity .The east of research area lacks the available p and need p fertilizer, but the west-south does not need it. The changing extension of available k between 39.0mg/kg-135.0 mg/kg and the space variation of the k is complexity. The mostly research area lacks the available k. It had a high correlation with the local fertilization habit. The soil needs the k fertilizer.
Sixth, A farmer recommendation fertilization query system was developed by query Visual Basic and COM-MAPGIS, which would support the query and the use of precision Agriculture.
In conclusion, this paper bring forward the way of precision fertilization which not only considers the continuity and the variability of soil space but also adopts the recommendation fertilization system that bases on the soil nutrient Correlation coefficient by many years fertilizer experimentation . This method is not only advanced in technology but also doable in economy. It will have some direction meanings for application of precision agriculture technique in china as unit of peasant land.
引文
[1] Reetz HF. Site-specific nutrient management systems for the 1990s. Better crops with plant food,1994,4 (6):14-19.
[2] Blackmore B S, Wheeler P N. The role of precision farming in sustainable agriculture. Technology Innovation and Sustainable Agculture, 1994, 5(6): 13-17.
[3] Larscheid G, Blackmore B S, Moore M. Management Decision Based on Yield Maps. Technology Innovation and Sustainable Agriculture, 1997, 10(8): 58-63.
[4]卢彦舫.当前施肥中存在的问题及提高肥效的途径.农业工程学报,2001, 7(8):21-23.
[5]方樟法.从同一田块 N、P、K 等大量元素的测定结果看土壤的不均一性[J]. 浙江农业科学,1988,(6):268-270.
[6]胡克林.农田尺度下土壤属性的空间变异性及硝酸盐淋失的随机模拟[D]北京:中国农业大学,2000.
[7]李菊梅,李生秀.几种营养元素在土壤中的空间变异[J].干旱地区农业研究,1995,16(2):58—64.
[8]黄绍文,金继运.土壤特性空间变异研究进展.土壤肥料,2002,(l):8—14.
[9]BerndtssonR,BahriA,Jinno K.SPatial dependence of geochemical elements in a semiarid agricultUral field:Ⅱ.Geostatistical ProPerties[J].Soil Sci,1993,57:1323-1329.
[10]Stolt MH,Baker JC,Simpson TW.Soil-landscape relationships in Virginia Soil variability and Parent material uniformity[J].Soil Sci,1993,57:414-421.
[11]徐尚平,陶澍,徐福留.内蒙土壤微量元素含量的空间结构特征[J].地理学报,2000,55(3):337-345.
[12]孙波,赵其国,间国年.低丘红壤肥力的时空变异[J].土壤学报,2002,39(2):190-198.
[13]Issaks EH,Srivastava R M.An introduction to applied geostatistics[M]. New York:Oxford Univ press,1989
[14]Matheron G .PrinciPles of geostatistics[J].Economic Geology. 1963 ,58:1246-1266.
[15]Hillel D.Research in 5011 Phsics:a review[J].Soil Sci,1991,151:30-34.
[16]王军,傅伯杰,邱扬等.黄土丘陵小流域土壤水分的时空变异特征-半变异函数[J].地理学报,2000,55(4):428-438.
[17]王建红,傅庆林,吴玉卫等.土壤空间变异性理论在海涂土壤研究中的初步应用[J].浙江农业学报,1998,10(5):230-234.
[18]CamPbell J B.SPatial variation of sand content and pH within single contiguous delineation of two Soil mapping units[J]. Soil Sci,1978,42:460-464.
[19]Kollias VJ,Kalivas D P,Yassoglou NJ·Mapping the soil resources of a recent alluvial plaint in Greece using fuzzy sets in a GIS environment[J]. EuroPean Journal of soil Science,1999,50:26-273.
[20]Mallarino A P. Patterns of spatial variability for phosphorus and potassium in no- tilled soils for two sampling scales. Soil Sci. Soc. Am. J. 1996, 60: 1473-1481.
[21] Ahn C W, Baumgardner M F and BiehI L L. Delineation of soil variability using geostatistics and fuzzy clustering analyses of hyperspectral data. Soil Sci. Soc. Am. J. 1999, 63: 142-150.
[22] Cambardella C A, Moorman T B, Novak J M, et al. Field-scale variability of soil properties in central Iowa soils. Soil Sci. Soc. Am. J, 1994, 58: 1501-1511.
[23] 王政权编著. 地质统计学及在生态学中的应用. 北京:科学出版社,1999.
[24] Trangmar B B, Yost R S and Uehara G. Application of geostatistics to spatial studies of soil properties. Advance in Agronomy, Academic Press. 1985, 38: 45-94.
[25]Shropshire G, Peterson C, Fisher K. Field Experience with Differential GPS, American Society of Agricultural Engineers, 1993: 1073-1085.
[26] Reetz H F. Site-specific Nutrient Management Systems for the 1990s. Better Crops with Plant Food. 1994,78(4): 14-19.
[27] Clark R L and McGuckin R L. Variable rate Application Equipment for Precision Farming. Presented at the 1996 Beltwide Cotton Conference. National Cotton Council of America, Nashville, Tennessee. January, 1996: 8-12.
[28] Malzer G L. Corn Yield Rresponse Variability and Potential Profitability of Site-specific Nitrogen Management. Better Crop with Plant Food. 1996,80(3): 6-8.
[29] Hilde D .Fine-tuning sugar beet fertility management in the red river valley. Better crops with plant food,1994,4(9):26-27.
[30] 金继运.精准农业及其在我国的应用前景.植物营养与肥料学报,2000,37(4):289-295.
[31]王慧,赵晓东.中国土壤肥料信息系统.北京:科学出版社,1998.
[32]赵春江,杨宝祝.智能技术与农业,计算机与农业,1998, (增刊)(16):13-17.
[33]邝继双.变量施肥智能空间决策支持系统 VRF-ISDSS-地理信息系统ArcViewGIS 在精细农业中的应用. 河北农业大学学报,2000, 23(3): 91-97.
[34]张书慧,马成林,余春玲.应用于精确农业变量施肥地理信息系统的开发研究.农业工程学报,2002, 18(2): 153-155.
[35]金继运. 精准农业及其在我国的应用前景.金继运,白由路.精准农业与土壤养分管理,北京:中国大地出版社, 2001,1-2
[36] 危常州,侯振安,朱和明等.基于 GIS 的棉田精准施肥和土壤养分管理系统的研究.中国农业科学,2002,35(6):678—685.
[37]BerndtssonR,Bahri A,Jinno K. SPatial dependence of geochemical elements in a semiarid agricultUral field:Ⅱ .Geostatistical ProPerties[J].Soil Sci. Soc.Am.J.,1993,(57):1323-1329.
[38]路 鹏,彭佩钦, 宋变兰等.洞庭湖平原区土壤全磷含量地统计学 GIS 分析. 中国农业科学, 2005,38(6):1204-1212
[39]刘杏梅, 张蔚文. 中尺度上水稻田质量与精确农业. 浙江大学学报(农业与生命科学版), 2005, 31(6) : 745～749 ,
[40]McGratha D, Zhang C, Cartona O T. Geostatistical analyses and hazard assessment on soil lead in Silvermines area, Ireland[J]. Environmental Pollution, 2004,(127):229-238.
[41] 黄金生, 熊柳梅, 周柳强. 香蕉种植场土壤有效态 Cu 的空间变异性研究. 广西农业科学,2005,36(6):532-534
[42]苏 伟 ,聂宜民 ,于振文. 基于 GIS 的优质小麦变量施肥信息系统研究. 农业工程学报, 2005,21(7):94-98
[43] 郝黎仁, 樊元, 郝哲欧等编著.SPSS 实用统计分析.北京:中国水利水电出版社,2002, 189-190
[44] 陈 述 彭 , 鲁 学 军 , 周 成 虎 . 地 理 信 息 系 统 导 论 [M]. 北 京 : 科 学 出 版社,2000,124-125
[45]白由路,金继运,等.基于 GIS 的土壤养分分区管理模式研究.中国农业科学,2001,34(1):46-50
[46]王长耀,牛铮,唐华俊等.对地观测技术与精细农业.北京:科学出版社.2001, 140-147
[47]秦耀东.土壤空间变异研究中的定量分析. 地球科学进展,1992,7(1) 44-49
[48]ANDREW,CUNTER B,RODGER B G Geostatistical characterisation of soil moisture pattens in Tarrawarra catchment[J] Journal of Hydrology,1998,205:20-37.
[49]BAHRI A,BERNDTSSON R.Nitrogen source impact On the spatial variability of organic carbon and nitrogen in soil[J].Soil Sci,1996,161(5):288—297
[50]李亮亮 ,依艳丽 ,凌国鑫等. 地统计学在土壤空间变异研究中的应用. 土壤通报, 2005, 36(2):265-268
[2] Blackmore B S, Wheeler P N. The role of precision farming in sustainable agriculture. Technology Innovation and Sustainable Agculture, 1994, 5(6): 13-17.
[3] Larscheid G, Blackmore B S, Moore M. Management Decision Based on Yield Maps. Technology Innovation and Sustainable Agriculture, 1997, 10(8): 58-63.
[4]卢彦舫.当前施肥中存在的问题及提高肥效的途径.农业工程学报,2001, 7(8):21-23.
[5]方樟法.从同一田块 N、P、K 等大量元素的测定结果看土壤的不均一性[J]. 浙江农业科学,1988,(6):268-270.
[6]胡克林.农田尺度下土壤属性的空间变异性及硝酸盐淋失的随机模拟[D]北京:中国农业大学,2000.
[7]李菊梅,李生秀.几种营养元素在土壤中的空间变异[J].干旱地区农业研究,1995,16(2):58—64.
[8]黄绍文,金继运.土壤特性空间变异研究进展.土壤肥料,2002,(l):8—14.
[9]BerndtssonR,BahriA,Jinno K.SPatial dependence of geochemical elements in a semiarid agricultUral field:Ⅱ.Geostatistical ProPerties[J].Soil Sci,1993,57:1323-1329.
[10]Stolt MH,Baker JC,Simpson TW.Soil-landscape relationships in Virginia Soil variability and Parent material uniformity[J].Soil Sci,1993,57:414-421.
[11]徐尚平,陶澍,徐福留.内蒙土壤微量元素含量的空间结构特征[J].地理学报,2000,55(3):337-345.
[12]孙波,赵其国,间国年.低丘红壤肥力的时空变异[J].土壤学报,2002,39(2):190-198.
[13]Issaks EH,Srivastava R M.An introduction to applied geostatistics[M]. New York:Oxford Univ press,1989
[14]Matheron G .PrinciPles of geostatistics[J].Economic Geology. 1963 ,58:1246-1266.
[15]Hillel D.Research in 5011 Phsics:a review[J].Soil Sci,1991,151:30-34.
[16]王军,傅伯杰,邱扬等.黄土丘陵小流域土壤水分的时空变异特征-半变异函数[J].地理学报,2000,55(4):428-438.
[17]王建红,傅庆林,吴玉卫等.土壤空间变异性理论在海涂土壤研究中的初步应用[J].浙江农业学报,1998,10(5):230-234.
[18]CamPbell J B.SPatial variation of sand content and pH within single contiguous delineation of two Soil mapping units[J]. Soil Sci,1978,42:460-464.
[19]Kollias VJ,Kalivas D P,Yassoglou NJ·Mapping the soil resources of a recent alluvial plaint in Greece using fuzzy sets in a GIS environment[J]. EuroPean Journal of soil Science,1999,50:26-273.
[20]Mallarino A P. Patterns of spatial variability for phosphorus and potassium in no- tilled soils for two sampling scales. Soil Sci. Soc. Am. J. 1996, 60: 1473-1481.
[21] Ahn C W, Baumgardner M F and BiehI L L. Delineation of soil variability using geostatistics and fuzzy clustering analyses of hyperspectral data. Soil Sci. Soc. Am. J. 1999, 63: 142-150.
[22] Cambardella C A, Moorman T B, Novak J M, et al. Field-scale variability of soil properties in central Iowa soils. Soil Sci. Soc. Am. J, 1994, 58: 1501-1511.
[23] 王政权编著. 地质统计学及在生态学中的应用. 北京:科学出版社,1999.
[24] Trangmar B B, Yost R S and Uehara G. Application of geostatistics to spatial studies of soil properties. Advance in Agronomy, Academic Press. 1985, 38: 45-94.
[25]Shropshire G, Peterson C, Fisher K. Field Experience with Differential GPS, American Society of Agricultural Engineers, 1993: 1073-1085.
[26] Reetz H F. Site-specific Nutrient Management Systems for the 1990s. Better Crops with Plant Food. 1994,78(4): 14-19.
[27] Clark R L and McGuckin R L. Variable rate Application Equipment for Precision Farming. Presented at the 1996 Beltwide Cotton Conference. National Cotton Council of America, Nashville, Tennessee. January, 1996: 8-12.
[28] Malzer G L. Corn Yield Rresponse Variability and Potential Profitability of Site-specific Nitrogen Management. Better Crop with Plant Food. 1996,80(3): 6-8.
[29] Hilde D .Fine-tuning sugar beet fertility management in the red river valley. Better crops with plant food,1994,4(9):26-27.
[30] 金继运.精准农业及其在我国的应用前景.植物营养与肥料学报,2000,37(4):289-295.
[31]王慧,赵晓东.中国土壤肥料信息系统.北京:科学出版社,1998.
[32]赵春江,杨宝祝.智能技术与农业,计算机与农业,1998, (增刊)(16):13-17.
[33]邝继双.变量施肥智能空间决策支持系统 VRF-ISDSS-地理信息系统ArcViewGIS 在精细农业中的应用. 河北农业大学学报,2000, 23(3): 91-97.
[34]张书慧,马成林,余春玲.应用于精确农业变量施肥地理信息系统的开发研究.农业工程学报,2002, 18(2): 153-155.
[35]金继运. 精准农业及其在我国的应用前景.金继运,白由路.精准农业与土壤养分管理,北京:中国大地出版社, 2001,1-2
[36] 危常州,侯振安,朱和明等.基于 GIS 的棉田精准施肥和土壤养分管理系统的研究.中国农业科学,2002,35(6):678—685.
[37]BerndtssonR,Bahri A,Jinno K. SPatial dependence of geochemical elements in a semiarid agricultUral field:Ⅱ .Geostatistical ProPerties[J].Soil Sci. Soc.Am.J.,1993,(57):1323-1329.
[38]路 鹏,彭佩钦, 宋变兰等.洞庭湖平原区土壤全磷含量地统计学 GIS 分析. 中国农业科学, 2005,38(6):1204-1212
[39]刘杏梅, 张蔚文. 中尺度上水稻田质量与精确农业. 浙江大学学报(农业与生命科学版), 2005, 31(6) : 745～749 ,
[40]McGratha D, Zhang C, Cartona O T. Geostatistical analyses and hazard assessment on soil lead in Silvermines area, Ireland[J]. Environmental Pollution, 2004,(127):229-238.
[41] 黄金生, 熊柳梅, 周柳强. 香蕉种植场土壤有效态 Cu 的空间变异性研究. 广西农业科学,2005,36(6):532-534
[42]苏 伟 ,聂宜民 ,于振文. 基于 GIS 的优质小麦变量施肥信息系统研究. 农业工程学报, 2005,21(7):94-98
[43] 郝黎仁, 樊元, 郝哲欧等编著.SPSS 实用统计分析.北京:中国水利水电出版社,2002, 189-190
[44] 陈 述 彭 , 鲁 学 军 , 周 成 虎 . 地 理 信 息 系 统 导 论 [M]. 北 京 : 科 学 出 版社,2000,124-125
[45]白由路,金继运,等.基于 GIS 的土壤养分分区管理模式研究.中国农业科学,2001,34(1):46-50
[46]王长耀,牛铮,唐华俊等.对地观测技术与精细农业.北京:科学出版社.2001, 140-147
[47]秦耀东.土壤空间变异研究中的定量分析. 地球科学进展,1992,7(1) 44-49
[48]ANDREW,CUNTER B,RODGER B G Geostatistical characterisation of soil moisture pattens in Tarrawarra catchment[J] Journal of Hydrology,1998,205:20-37.
[49]BAHRI A,BERNDTSSON R.Nitrogen source impact On the spatial variability of organic carbon and nitrogen in soil[J].Soil Sci,1996,161(5):288—297
[50]李亮亮 ,依艳丽 ,凌国鑫等. 地统计学在土壤空间变异研究中的应用. 土壤通报, 2005, 36(2):265-268