基于视觉里程计的森林样地调查系统研究

以视觉里程计技术恢复连续摄影序列图像位姿,并以恢复位姿的图像为基础构建样地调查系统。该系统通过对图像位姿尺度恢复、定义样地坐标系、标记立木等过程估计样地中立木位置及胸径。用相机对12块半径为7. 5 m的圆形样地进行连续摄影,获取有序图像序列,并使用构建的样地调查系统对图像序列进行处理,以获取样地中立木位置及胸径。实验结果表明,所有样地立木位置估计值x轴与y轴方向的偏差(BIAS)分别为0. 04、-0. 03 m,均方根误差(RMSE)分别为0. 21、0. 17 m;样地中立木胸径估计值的BIAS及RMSE分别为0. 09 cm(0. 51%)和0. 88 cm(5. 03%)。     

基于提等潜力和主导因素的耕地质量监测类型区划分及布点方法

以江西省南昌县为例,依托江西省耕地质量监测试点项目,依据耕地自然等指数提升潜力大小和对等级提升最大贡献值因子的组合类型来划分耕地质量监测类型区,并依据监测重点及监测类型区面积比例布设监测样点。实证分析表明,南昌县耕地质量等级监测共有14个组合类型,归并14个组合类型得到5个监测类型区:1个常规监测区和4个重点监测区。其中重点监测类型区包括易渍涝区、易干旱区、耕层瘠薄区和肥力缺乏区。依据监测重点和面积大小在各监测类型区内共布设监测样点70个。统计学检验结果证明,同其他常规布点方法对比,在相同监测样点情况下,依据耕地质量等级提升潜力及限制因子组合类型划分耕地质量监测类型区所布置的监测样点,监测的针对性更强,准确性更高。     

基于原型网络的小样本禽蛋图像特征检测方法

机器视觉因具有检测速度快、稳定性高及成本低等优点，已发展成为禽蛋无损检测领域主流检测手段。使用该技术对禽蛋进行无损检测时，需要依赖大量禽蛋图像作为数据支撑才能取得较好的检测效果。由于养殖安全等限制，禽蛋图像数据的采集成本较高，针对该问题，提出了一种适应于小样本禽蛋图像检测的原型网络（Prototypical network）。该网络利用引入注意力机制的逆残差结构搭建的卷积神经网络将不同类别的禽蛋图像映射至嵌入空间，并利用欧氏距离度量测试禽蛋图像在嵌入空间的类别，从而完成禽蛋图像的分类。本文利用该网络分别验证了小样本条件下受精蛋与无精蛋、双黄蛋与单黄蛋及裂纹蛋与正常蛋的分类检测效果，其检测精度分别为95%、98%、88%。试验结果表明本文方法能够有效地解决禽蛋图像检测中样本不足的问题，为禽蛋图像无损检测研究提供了新的思路。     

不同方法及发酵管数量对大肠菌群检测结果的差异性分析

[目的]比较不同方法检测同种水样中大肠菌群含量的结果是否具有差异性,以及多管发酵法中发酵管数量对检测结果的影响。[方法]分别采取污染程度由低至高的A、B、C 3种水样,通过多管发酵法、纸片法、滤膜法检测相同水样中大肠菌群的含量,并在多管发酵管法中利用9、10、15管发酵检测同种水样,采用SPSS软件对试验数据进行差异性分析。[结果]多管发酵法与纸片法差异不显著,结果具有一致性,而滤膜法与其他2种方法获得结果具有显著性差异。对9、10、15管发酵检测3种水样获得的结果进行方差分析,得到的P值分别是0.709、0.964、0.840,均大于0.05,故差异不显著,结果具有一致性。[结论]试验结果为大肠菌群检测方法的研究提供了理论依据。     

欠发达县域乡镇基准地价评估方法研究

[目的]探索欠发达县域内乡镇基准地价评估方法,以解决地价样点资料缺乏情况下基准地价评估问题。[方法]文献研究法、实证研究法、描述性研究法、探索性研究法。[结果]在分析土地质量与地价关系的基础上,提出地价质量控制法,对样点缺乏情况下的县域内乡镇基准地价进行评估,并通过实证研究对方法进行验证。[结论]提出的方法科学合理,降低了样点缺乏对乡镇基准地价评估结果的影响,克服了传统基准地价评估方法的不足,该方法简易,便于实际应用,可为我国乡镇基准地价评估的方法体系提供新的思路。     

An Evaluation of the Loss-on-Ignition Method for Determining the Soil Organic Matter Content of Calcareous Soils

The Loss-on-Ignition (LOI) method is widely employed for measuring the organic matter (OM) content of soil samples. There is a risk of carbonate losses when calcareous soil samples are analyzed through LOI, but this has never been investigated in detail. Moreover, a worldwide standard protocol for determining the carbonate content of soils is not available. The aims of this study were (i) to evaluate two commonly employed carbonate analysis procedures using calcareous and non-calcareous soil samples: the gravimetric method with (GMF) and without (GM) the addition of the antioxidant iron(II) chloride (FeCl₂) and the acetic acid dissolution procedure (AAD); (ii) to evaluate the effect of ignition temperature on losses of pure calcite, calcite-quartz and calcareous soil samples. We found that the average apparent carbonate content of the non-calcareous soils was greatest for the GMF method followed by the AAD procedure. The GM method showed the smallest apparent carbonate contents. For the calcite-quartz sand mixture, ignition losses started at 600°C and increased with temperature in a sigmoidal way. LOI values stabilized at 750°C when 80% of the carbon dioxide was released. We recommend the GM procedure for carbonate analysis because the apparent carbonate contents of the non-calcareous soil samples were smallest. Furthermore, we recommend an LOI temperature of 550°C because at this ignition temperature 99.8% of the total calcite fraction remains in the soil samples.     

Microwave Digestion for Colorimetric Determination of Total Si in Plant and Mineral Samples

A new method for determining the soluble silicon (Si) concentrations in nonliquid plant and mineral samples was developed using sodium hydroxide (NaOH)–hydrogen peroxide (H₂O₂) matrix for microwave digestion (MWD-Na) followed by colorimetric Si testing. MWD-Na was compared with autoclave-induced digestion and alkali fusion. The data have shown no significant difference between these three methods. HNO₃–H₂O₂ or HNO₃?–H₂O₂?–HF microwave technique results in Si loss. The reduction of the total Si can be realized via low solubility of Si in the acid solutions or silicon tetrafluoride formation. The Mullen and Riley method for colorimetric testing of Si in a solution that uses ascorbic acid to reduce the silicomolybdate complex formed under acid conditions to an intensely blue complex was modified using iron sulfate. The combination of MWD-Na and modified colorimetric blue method provides cheap and valid data on determining the total Si in both plant and mineral samples.     

运用机载LiDAR数据对橡胶林地上生物量估测的采样尺度效应分析

气候变化下,森林生物量遥感监测是当前研究的热点,机载LiDAR作为重要的遥感信息源,其采样大小对生物量估测精度有着一定的影响。以机载LiDAR数据为信息源,以44块30m×30m的方形橡胶林实测样地数据为基础,对机载激光雷达数据进行不同尺寸采样(共21个采样尺寸,边长从10m至30m,间隔为1m),提取不同采样尺寸下的激光雷达参数,并与橡胶林地上生物量建立PLSR模型,就机载激光雷达采样大小对橡胶林地上生物量估测精度的影响进行研究。研究表明:当采样尺寸小于18m时,估测精度随着采样尺寸的增大而增大;而当采样尺寸大于18m时,估测精度随着采样尺寸的增大而减小,进而趋于平缓。结果虽然呈现出一定的规律性,但是差异并不是很明显。当采样尺寸为18m时估测效果最佳,模型决定系数(R^2)为0.718,均方根误差(RMSE)为17.830 t/hm^2;交叉验证精度P和RMSEcv分别为82.741%和18.874t/hm^2。相较于实际样地(30m)尺寸下的估测结果,18m采样尺寸下的R^2提高了1.989%,RMSEcv降低了2.611%。因此,生物量的估测精度受机载激光雷达数据采样尺寸大小的影响,在生物量估测过程中需结合研究对象和研究区的实际情况对采样尺寸进行选择,从而提高生物量估测精度。     

Improving wood volume predictions in dry tropical forest in the semi-arid Brazil

The volumetric variability of dry tropical forests in Brazil and the scarcity of studies on the subject show the need for the development of techniques that make it possible to obtain adequate and accurate wood volume estimates. In this study, we analyzed a database of thinning trees from a forest management plan in the Contendas de Sincorá National Forest, southwestern Bahia State, Brazil. The data set included a total of 300 trees with a trunk diameter ranging from 5 to 52 cm. Adjustments, validation and statistical selection of four volumetric models were performed. Due to the difference in height values for the same diameter and the low correlation between both variables, we do not suggest models which only use the diameter at breast height (DBH) variable as a predictor because they accommodate the largest estimation errors. In comparing the best single entry model (Hohenald-Krenn) with the Spurr model (best fit model), it is noted that the exclusion of height as a predictor causes the values of 136.44 and 0.93 for Akaike information criterion (AIC) and adjusted determination coefficient (R2 adj), which are poorer than the second best model (Schumacher-Hall). Regarding the minimum sample size, errors in estimation (root mean square error (RMSE) and bias) of the best model decrease as the sample size increases, especially when a larger number of trees with DBH≥15.0 cm are randomly sampled. Stratified sampling by diameter class produces smaller volume prediction errors than random sampling, especially when considering all trees. In summary, the Spurr and Schumacher-Hall models perform better. These models suggest that the total variance explained in the estimates is not less than 95%, producing reliable forecasts of the total volume with shell. Our estimates indicate that the bias around the average is not greater than 7%. Our results support the decision to use regression methods to build models and estimate their parameters, seeking stratification strategies in diameter classes for the sample trees. Volume estimates with valid confidence intervals can be obtained using the Spurr model for the studied dry forest. Stratified sampling of the data set for model adjustment and selection is necessary, since we find significant results with mean error square root values and bias of up to 70% of the total database.