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1.
《Communications in Soil Science and Plant Analysis》2012,43(5):329-335
Abstract Corn yields and leaf samples vere obtained from experimental plots receiving various rates and combinations of N, P and K. Yields were regressed on leaf N, P, K, Ca and Mg as independent variables expressed in milliequivalents per 100 grams and percentages in three regression models. The fit of two models was shown to be equivalent regardless of method of expressing the independent variables. For the other model the choice of milliequivalents per 100 grams or percentages determines a unique function. 相似文献
2.
黑龙江省黑土区拉林河流域土壤侵蚀强度评价方法比较 总被引：2，自引：0，他引：2
为了保护水土资源、改善生态环境,进行区域土壤侵蚀强度评价,以黑龙江省黑土区拉林河流域为研究区,选取坡度、坡向、土壤类型、土地利用状况和标准化植被指数等5项评价指标,分别采用逻辑回归和广义回归神经网络模型,在ArcGIS平台上进行土壤侵蚀强度评价。应用受试者工作特征曲线对2种方法的评价结果进行对比。结果表明:逻辑回归模型和广义回归神经网络模型的受试者工作特征曲线下面积值分别为0.857和0.881,与实际的土壤侵蚀强度情况基本吻合;2种模型的评价结果可以相互校验,广义回归神经网络模型评价结果的精度较高。 相似文献
3.
Apparent electrical conductivity of soil (ECa) is a property frequently used as a diagnostic tool in precision agriculture, and is measured using vehicle‐mounted proximal sensors. Crop‐yield data, which is measured by harvester‐mounted sensors, is usually collected at a higher spatial density compared to ECa. ECa and crop‐yield maps frequently exhibit similar spatial patterns because ECa is primarily controlled by the soil clay content and the interrelated soil moisture content, which are often significant contributors to crop‐yield potential. By quantifying the spatial relationship between soil ECa and crop yield, it is possible to estimate the value of ECa at the spatial resolution of the crop‐yield data. This is achieved through the use of a local regression kriging approach which uses the higher‐resolution crop‐yield data as a covariate to predict ECa at a higher spatial resolution than would be prudent with the original ECa data alone. The accuracy of the local regression kriging (LRK) method is evaluated against local kriging (LK) and local regression (LR) to predict ECa. The results indicate that the performance of LRK is dependent on the performance of the inherent local regression. Over a range of ECa transect survey densities, LRK provides greater accuracy than LK and LR, except at very low density. Maps of the regression coefficients demonstrated that the relationship between ECa and crop yield varies from year to year, and across a field. The application of LRK to commercial scale ECa survey data, using crop yield as a covariate, should improve the accuracy of the resultant maps. This has implications for employing the maps in crop‐management decisions and building more robust calibrations between field‐gathered soil ECa and primary soil properties such as clay content. 相似文献
4.
基于133个滨海湿地土样的全氮（TN）含量和光谱反射率（R）及其对数（lgR）、对数的一阶微分（（lgR）''）、倒数（1/R）、倒数的一阶微分（（1/R）''）、一阶微分（R''）、平方根（√R）、一阶微分的倒数（1/（R）''）变换，采用偏最小二乘回归（PLSR）、随机森林回归（RFR）和支持向量机回归（SVR）3种算法分别建立土壤TN含量估测模型。结果表明：①土壤TN含量与光谱变换形式相关性由高到低为：（1/R）''> R''> （lgR）''> 1/R > lgR > 1/（R）''> √R > > R，经光谱变换，土壤TN含量与变换光谱的相关性均高于R，其中与（1/R）''的Pearson相关系数最大为0.746。②PLSR和SVR基于R''、（1/R）''、（lgR）''和1/（R）''变换构建的模型、RFR方法构建的所有模型R2均大于0.732，均可用于滨海湿地土壤TN含量的估算。③基于1/（R）''建立的SVR模型预测精度最高，其R2为0.987，RMSE为0.057 g/kg，MAE为0.050 g/kg，是预测滨海湿地土壤TN含量的最优模型，可为准确获取滨海湿地土壤TN含量提供稳定方法。 相似文献
5.
针对太阳辐射、大气温度、空气湿度和风速等气象因素对大豆归一化植被指数(normalized difference vegetation index,NDVI)在每天不同时间的影响,提高大豆NDVI的监测精度。该研究采用Green Seeker手持式光谱仪对大豆苗期、花荚期和成熟期3个主要生育阶段的NDVI值以小时为单位进行连续监测,并收集测量时的太阳辐射、大气温度、空气湿度和风速等气象数据,采用偏最小二乘法、逐步回归和岭回归方法,建立不同气象因素对大豆NDVI值影响的回归模型,并分析其定量关系。结果表明,影响大豆不同生育期NDVI变化的主要气象因素为太阳辐射和大气温度,风速和空气湿度的影响较小,可以忽略不计。经对3种模型进行预测精度评价后得出,岭回归模型的预测精度最佳,其在3个阶段的预测均方根误差(RMSE)分别为0.034、0.018和0.016,决定系数(R2)分别为0.820、0.908和0.934,其次为逐步回归法,偏最小二乘法的预测精度最低。 相似文献
6.
Areas of the landscape that are priorities for conservation should be those that are both vulnerable to threatening processes and that if lost or degraded, will result in conservation targets being compromised. While much attention is directed towards understanding the patterns of biodiversity, much less is given to determining the areas of the landscape most vulnerable to threats. We assessed the relative vulnerability of remaining areas of native forest to conversion to plantations in the ecologically significant temperate rainforest region of south central Chile. The area of the study region is 4.2 million ha and the extent of plantations is approximately 200 000 ha. First, the spatial distribution of native forest conversion to plantations was determined. The variables related to the spatial distribution of this threatening process were identified through the development of a classification tree and the generation of a multivariate, spatially explicit, statistical model. The model of native forest conversion explained 43% of the deviance and the discrimination ability of the model was high. Predictions were made of where native forest conversion is likely to occur in the future. Due to patterns of climate, topography, soils and proximity to infrastructure and towns, remaining forest areas differ in their relative risk of being converted to plantations. Another factor that may increase the vulnerability of remaining native forest in a subset of the study region is the proposed construction of a highway. We found that 90% of the area of existing plantations within this region is within 2.5 km of roads. When the predictions of native forest conversion were recalculated accounting for the construction of this highway, it was found that approximately 27 000 ha of native forest had an increased probability of conversion. The areas of native forest identified to be vulnerable to conversion are outside of the existing reserve network. 相似文献
7.
Guanghui ZHENG Caixia JIAO Xianli XIE Xuefeng CUI Gang SHANG Chengyi ZHAO Rong ZENG 《土壤圈》2023,(6):849-856
Soil bulk density(BD) is an important physical property and an essential factor for weight-to-volume conversion. However, BD is often missing from soil databases because its direct measurement is labor-intensive, time-consuming, and sometimes impractical, particularly on a large scale. Therefore, pedotransfer functions(PTFs) have been developed over several decades to predict BD. Here, six previously revised PTFs(including five basic functions and stepwise multiple linear regression(SMLR)) and t... 相似文献
8.
基于环境变量的中国土壤有机碳空间分布特征 总被引：3，自引：0，他引：3
研究中国土壤有机碳(Soil Organic Carbon,SOC)的空间分布特征对SOC储量估算以及农业生产管理具有重要意义。以全国第二次土壤普查2473个土壤典型剖面的表层(A层)SOC含量为研究对象,探寻地形、气候和植被等环境因素对SOC空间异质性分布的影响;以普通克里格法为对照,利用地理加权回归、地理加权回归克里格、多元线性回归和回归克里格模型建立SOC空间预测模型;并分别绘制了中国SOC的空间分布预测图。结果表明:(1)SOC含量与年均降水量、年均温、归一化植被指数、高程以及地形粗糙指数呈极显著相关关系;(2)平均绝对估计误差、均方根误差、平均相对误差和皮尔逊相关系数等模型验证指标表明地理加权回归的预测精度优于其他模型,可以更好地绘制SOC在大尺度上的空间分布特征;(3)较高SOC含量主要分布在研究区东北部、西南部以及东南部,而西北部SOC含量普遍偏低。本文以期从大尺度上探讨土壤属性与环境变量之间的相关关系,为全国土壤属性的空间制图提供一定的解决方案和思路。 相似文献
9.
氧化铁是土壤中含铁矿物的主体,是土壤发育和土壤分类最明显和最有用的指标之一。本文以湖南省大围山森林土壤为研究对象,通过实验室化学成分测定和光谱采集,在光谱预处理及组合变换基础上,采用相关性分析筛选土壤氧化铁全量的敏感波段,并分别建立多元逐步回归和偏最小二乘回归反演模型。结果表明:不同土壤光谱曲线趋势基本一致,均形似陡坎,且在420～580 nm波段,土壤氧化铁全量与光谱反射率呈负相关关系;不同的光谱数据变换方式可以提高光谱与氧化铁全量的相关性,Savitzky-Golay(S-G)平滑和去包络线相结合优于其他预处理方法;土壤氧化铁全量的特征波段主要为392、427、529、523、549、559、565、570、994和1040nm,偏最小二乘回归模型比多元逐步回归模型具有更好的稳定性,适合于快速估算红黄壤区森林土壤氧化铁全量。 相似文献
10.
Afshin Honarbakhsh Mohammad Tahmoures Yaser Ostovari Somaye Noroozi 《Communications in Soil Science and Plant Analysis》2017,48(21):2485-2495
Using pedotransfer functions (PTF) is a useful way for field capacity (FC) and permanent wilting point (PWP) prediction. The aim of this study was to model PTF to estimate FC and PWP using regression tree (RT) and stepwise multiple linear regressions (SMLR). For this purpose, 165 and 45 soil samples from UNSODA and HYPRES datasets were used for development and validation of new PTFs, respectively. %Clay, geometric mean diameter (dg), and bulk density (BD) were selected as predictor variables due to the highest correlation and lowest multicollinearity. The results showed that clay percentage with W* = 0.89 and dg with W* = ?0.57 were the most effective variables to predict PWP and FC, respectively. The RT method had a better performance (R2 = 0.80, ME = ?0.002 cm3cm?3, RMSE = 0.05 cm3cm?3 for FC and R2 = 0.85, ME = 0.003 cm3cm?3, RMSE = 0.03 cm3 cm?3 for PWP) than SMLR in estimation of FC and PWP. 相似文献
11.
玉米倒伏胁迫影响因子的空间回归分析 总被引：9，自引：4，他引：5
为指导玉米新品种的推广,采用回归模型分析玉米主产区倒伏胁迫空间分布成因。该文用多元逐步线性回归法筛选黄淮海夏播玉米区的倒伏胁迫的决定因素,比较普通最小二乘法线性回归模型和地理加权回归模型的结果,以确定倒伏胁迫及其决定因素是否存在空间非平稳性和空间依赖性。结果表明：在探索倒伏的空间异质性时,地理加权回归模型显著优于普通最小二乘法线性回归模型;日降水量是玉米倒伏胁迫的主要环境成因,且倒伏程度随日降水量增加而加重;土壤含氮量、留苗密度和日平均风速与倒伏的关系随空间位置而发生正负向变化,因地制宜的分析倒伏成因才能客观有效的指导农民种植生产。 相似文献
12.
Yaser Ostovari Shoja Ghorbani-Dashtaki Lalit Kumar Farzin Shabani 《Archives of Agronomy and Soil Science》2013,59(12):1688-1703
ABSTRACTPedotransfer functions (PTFs) have been used to save time and cost in predicting certain soil properties, such as soil erodibility (K-factor). The main objectives of this study were to develop appropriate PTFs to predict the K-factor, and then compare new PTFs with Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) K-factor models. The K-factor was measured using 40 erosion plots under natural rainfall in Simakan Watershed, an area of 350 km2 in central of Iran. The Regression Tree (RT) and Multiple Linear Regression (MLR) were used to develop PTFs for predicting the K-factor. The result showed that the mean of measured K was 0.01 t h MJ?1 mm?1. The mean K value predicted by USLE and RUSLE was 2.08 and 2.84 times more than the measured K, respectively. Although calcium carbonate was not considered in the original USLE and RUSLE K-factors, it appeared in the advanced PTFs due to its strong positive significant impact on aggregate stability and soil infiltration rate, resulting in decreased K-factor. The results also showed that the RT with R2 = 0.84 had higher performance than developed MLR, USLE and RUSLE for the K estimation. 相似文献
13.
最小二乘与分位数回归方法在河流水沙研究中的应用——以陕北延河流域为例 总被引：1，自引：0，他引：1
基于延河流域1956-2010年气象水沙数据,研究流域降水、径流和输沙量动态变化趋势及时间序列分布特征,并分别采用最小二乘法和分位数回归分析方法研究降水、径流及输沙三者间的相关关系.结果表明：1956-2010年流域年降水量、径流量、输沙量整体呈下降趋势,具有阶段性波动特征,并存在不同程度的异常值;最小二乘回归（OLSR）分析可以描述降水、径流和输沙量三者之间的平均相关关系,但当数据存在偏态、异常值或数据随机误差项为异方差时,最小二乘回归分析受到一定限制;分位数回归（QR）分析更加符合实际的气象、水文数据特征,特别是在分位数τ位于高分位部分,分位数回归拟合的有效性比最小二乘回归更好,可以更真实、准确地反映更多的局部信息.研究结果为河流水沙动态分析提供了一种新方法,可为客观准确地认识河流水沙关系提供参考. 相似文献
14.
基于非线性PLSR模型的气候变化对粮食产量的影响分析 总被引：1，自引：0，他引：1
考虑气候因子间多重共线性及其与粮食产量间复杂的非线性关系,本文在HP滤波分离出气候产量的基础上,尝试引入基于三次B样条变换(Spline-PLSR)和内部嵌入GRNN的两种非线性偏最小二乘模型(GRNN-PLSR),利用1961-2008年气候因子数据建立气候产量计算模型,以2009—2013年数据进行拟合检验,并与常用的C-D生产函数法计算的气候产量进行比较。结果表明,Spline-PLSR法在拟合气候因子变化对粮食产量影响时预测精度较高。而且,与C-D生产函数法相比,Spline-PLSR所需要素较少,操作简单,相对误差最高仅为13.6%;与GRNN-PLSR法拟合结果相比,Spline-PLSR相对误差波动较小,因此,基于三次B样条变换的非线性偏最小二乘法建模较适合拟合气候产量。 相似文献
15.
Summary Patterns of N mineralization vary widely between ecosystems, making intra- and interexperimental comparisons difficult at best. A flexible model, the Richards model, is suggested as a way of making comparisons. By changing its shape parameter, a flexible model can fit multiple mechanistic models, including first-order and logistic models. The scale-independent shape parameter (m) is a continuous variable that can be statistically analyzed to determine changes or differences in patterns. The model was tested with (1) simulations based on other mechanistic models; and with N mineralization data on soils from (2) urban and rural sites in New York; (3) forest soils in Alberta, Canada; and (4) arid and semiarid soils in Morocco. In all examples, the model was capable of fitting the data nearly as well as other specific models. With data based on the m values, soils in Morocco and organic horizons of coniferous forests in Alberta showed the same range in N mineralization patterns, although the soils varied in the amount of mineralizable N by an order of magnitude and time to reach maximum mineral N production by two-fold. 相似文献
16.
霍林河下游典型洪泛区湿地土壤pH值和土壤含水量分布特征 总被引：5，自引：1，他引：4
以霍林河下游洪泛区湿地为研究区,采用网格采样法研究了土壤pH值和土壤含水量的时空变化及其相互关系。结果显示,研究区湿地土壤含水量和pH值存在明显的季节性差异,7月份土壤含水量高于9月份土壤,但7月份土壤pH平均值则低于9月份,9月份湿地土壤,尤其是亚表层发生明显碱化。湿地土壤含水量和pH值均呈现出条带状和斑块状的空间分布格局,尤其在9月份的空间变异性较高,且土壤pH值与土壤含水量间存在较显著的负相关关系,即含水量高的区域对应土壤pH值较低。土壤含水量和pH值的回归分析表明当土壤pH值>8.8时,非线性回归更适宜描述研究区土壤含水量和土壤pH值的显著负相关关系。 相似文献
17.
旋转回归设计在农机试验中的应用 总被引：5，自引：1，他引：4
提出采用多因素旋转回归设计的方法进行农机优化设计和调整,并以Ｓ１９５柴油机为例,介绍了五因素二次正交旋转回归试验在农机优化调整中的具体应用,建立了该柴油机的功率、油耗随供油提前角、气门间隙、最高空转转速、喷油开启压力和气缸压缩压力而变化的数学模型,指出了内燃机调整应根据使用后技术状态变化情况而进行。 相似文献
18.
环渤海沿海区域耕地格局及影响因子分析 总被引：8，自引：6，他引：2
为分析环渤海省市沿海区域耕地格局与影响因子的关系,以耕地在5 km×5 km网格单元所占比例为因变量,选用地形、距离、气候及人口等10个影响因子为自变量,分别建立普通最小二乘法线性回归模型、空间滞后模型、空间误差模型、地理加权回归模型。结果表明:耕地格局及各影响因子均呈现较强的空间正相关,并随距离增大而减少;针对该研究,空间滞后模型、空间误差模型和地理加权回归模型模拟效果均优于普通最小二乘法线性回归模型,空间误差模型优于空间滞后模型;从全局上来讲,高程、坡度、到最近公路距离与耕地格局呈负相关影响,距最近海岸线、铁路、居民点距离、多年平均气温和多年平均降水与耕地格局呈正相关。从局部上来讲,除了多年平均降水对各网格单元内耕地面积均呈正向影响外,其余影响因子随网格单元变化正负向影响均存在。多年平均气温和多年平均降水是主要的、最敏感的正向影响因子,高程、坡度和距最近水系距离为主要的、最敏感的负向影响因子。 相似文献
19.
《Land Degradation \u0026amp; Development》2017,28(1):345-354
Industrial activities can contribute to the accumulation of heavy metals in soils, which could potentially threaten public health and the environment. This research was conducted to investigate the relationships between pH and total organic carbon (TOC) with soil chemical parameters, including exchangeable and total Cu, Zn, Cd, Pb, K, and Mg concentrations in soils near Panevėžys and Kaunas, Lithuania. Principal component regression (PCR) and non‐linear regression were used to find statistical relationships between pH, TOC, and the other soil properties studied. The results of correlation tests indicated that pH and TOC had strong relationships with most of the soil properties. The results of PCR [R 2 = 0·87, RMSE = 0·046] and non‐linear regression [R 2 = 0·91, RMSE = 0·041] (pH and the entire parameters), PCR [R 2 = 0·777, RMSE = 0·058] and non‐linear regression [R 2 = 0·871, RMSE = 0·046] (pH and the exchangeable parameters) to model the relationships between pH and soil chemical properties were promising and significant. Exchangeable heavy metal concentrations increased for pH > 5. Even though the relationships between TOC and heavy metals were significant, they were not as powerful as the relationships between pH and these metals. It was concluded that total metal concentrations in the study soils can be predicted by either pH or TOC. Metal mobility could most likely be controlled at the study site by manipulating soil pH and/or TOC. Finally, it is suggested that when there are financial and time limitations, assessment of total exchangeable metal concentrations using soil pH and/or TOC could be productive. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
20.
滩涂土壤有机质含量的反射光谱估算 总被引：5，自引：0，他引：5
Rapid determination of soil organic matter (SOM) using regression models based on soil reflectance spectral data serves an important function in precision agriculture. “deviation of arch”(DOA)-based regression and partial least squares regression (PLSR) are two popular modeling approaches to predict SOM. However, few studies have explored the accuracy of the DOA-based regression and PLSR models. Therefore, the DOA-based regression and PLSR were applied to the visible near-infrared (VNIR) spectra to estimate SOM content in the case of various dataset divisions. A two-fold cross-validation scheme was adopted and repeated 10 000 times for rigorous evaluation of the DOA-based models in comparison with the widely used PLSR model. Soil samples were collected for SOM analysis in the coastal area of northern Jiangsu Province, China. The results indicated that both modelling methods provided reasonable estimates of SOM, with PLSR outperforming DOA-based regression in general. However, the performance of PLSR for the validation dataset decreased more noticeably. Among the four DOA-based models, the linear model of the DOA provided the best estimation of SOM and a cutoff of SOM content (19.76 g kg-1), and the performance for calibration and validation datasets was consistent. As the SOM content exceeded 19.76 g kg-1, SOM became more effective in masking the spectral features of other soil properties to a certain extent. This work confirmed that reflectance spectroscopy combined with PLSR could serve as a non-destructive and cost-efficient way for rapid determination of SOM when hyperspectral data were available. The DOA-based model, which requires only 3 bands in the visible spectra, also provided SOM estimation with acceptable accuracy. 相似文献