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排序方式: 共有2907条查询结果,搜索用时 31 毫秒
1.
随着化肥、农膜等在农业生产中的过量投入,耕地面源污染的程度随之加重。文章选取塔里木河流域上游和田地区为研究区域,依据P-S-R框架理论,构建和田地区耕地面源污染生态风险评价指标体系,加入土壤理化数据,使用生态风险评价模型对和田地区1980 年及2016 年耕地面源污染状况进行生态风险评价,运用耕地生态风险模型、生态风险转移矩阵、Arcgis分析和田地区耕地面源污染时空分异状况。研究结论如下:和田地区1980 年耕地生态风险等级均为II级或III级,呈“中间高,两侧低”分布;2016 年耕地生态风险等级上升至IV级或V级,呈“倒W型”分布,各县耕地面源污染程度较1980 年均有较大幅度的上升,其中墨玉县和于田县在2016 年耕地生态风险等级达到最高的V级,而民丰县因自身生态环境的强脆弱性,同样需要提高关注。根据面源污染“从源头治理”的原则,应切实推进和田地区耕地生态环境保护与治理,提高政府重视程度,增强技术指导,开展试点工作,改善和田地区耕地面源污染现状。  相似文献   
2.
李雪梅 《干旱区地理》2019,42(1):180-186
绿洲城镇组群是新疆特殊区域形成的规模相对较小的单一中心空间自组织模式。运用城市中心性指数、城市经济联系模型和Theil系数对新疆八大绿洲城镇组群内部城镇中心性、经济联系及空间差异测度。结果显示:绿洲城镇组群内部的中心城市的中心性职能较强,周边城镇的中心性职能相对较弱,形成了单中心的空间自组织模式;绿洲城镇组群内部经济联系量和经济联系隶属度大小的排序一致,离中心城市的距离越近、经济发展水平越高,经济联系隶属度越高;近10 a年来绿洲城镇组群的整体空间差异一直在扩大,且呈现出继续扩大趋势。在此基础上,提出了建立区域合作协调机制、明确城镇组群发展方向、增强中心城市的辐射带动作用、实现产业合理分工以及构建制度保障体系促进绿洲城镇组群的协同发展。  相似文献   
3.
李鸿宇  袁桂平 《地震》2018,38(1):157-166
收集全国102个地磁台站2008年至2015年数字化地磁资料, 运用地磁空间相关法计算每日凌晨02时各台站地磁总场F之间的空间相关系数。 在使用相同的异常判别标准的情况下, 研究时段的17个中强地震中发现在2009年9月19日陕西宁强5.1级地震, 2011年11月1日四川青川5.4级地震, 2013年1月23日辽宁灯塔5.1级地震, 2013年7月22日甘肃岷县6.6级地震和2013年10月31日吉林前郭5.5级地震前均具有较为明显的空间相关低值异常现象。 通过总结5个震例的异常特征, 笔者发现其异常形态极其相似, 且平均的异常持续时间为20天, 而地震就发生在异常开始后3个月内; 同时, 地震发生在异常集中区中心附近, 且这个异常区域大小在500 km左右。 这一研究结果对于进一步分析地震前地磁空间相关异常特征积累了丰富的资料。  相似文献   
4.
Reliable quantification of savanna vegetation structure is critical for accurate carbon accounting and biodiversity assessment under changing climate and land-use conditions. Inventories of fine-scale vegetation structural attributes are typically conducted from field-based plots or transects, while large-area monitoring relies on a combination of airborne and satellite remote sensing. Both of these approaches have their strengths and limitations, but terrestrial laser scanning (TLS) has emerged as the benchmark for vegetation structural parameterization – recording and quantifying 3D structural detail that is not possible from manual field-based or airborne/spaceborne methods. However, traditional TLS approaches suffer from similar spatial constraints as field-based inventories. Given their small areal coverage, standard TLS plots may fail to capture the heterogeneity of landscapes in which they are embedded. Here we test the potential of long-range (>2000 m) terrestrial laser scanning (LR-TLS) to provide rapid and robust assessment of savanna vegetation 3D structure at hillslope scales. We used LR-TLS to sample entire savanna hillslopes from topographic vantage points and collected coincident plot-scale (1 ha) TLS scans at increasing distances from the LR-TLS station. We merged multiple TLS scans at the plot scale to provide the reference structure, and evaluated how 3D metrics derived from LR-TLS deviated from this baseline with increasing distance. Our results show that despite diluted point density and increased beam divergence with distance, LR-TLS can reliably characterize tree height (RMSE = 0.25–1.45 m) and canopy cover (RMSE = 5.67–15.91%) at distances of up to 500 m in open savanna woodlands. When aggregated to the same sampling grain as leading spaceborne vegetation products (10–30 m), our findings show potential for LR-TLS to play a key role in constraining satellite-based structural estimates in savannas over larger areas than traditional TLS sampling can provide.  相似文献   
5.
提出了一种综合利用快速点特征直方图(FPFH)描述符和同名点引导ICP优化的地面激光扫描(TLS)点云配准方法。该方法包括3个步骤:1)点云金字塔构建;2)基于FPFH的粗配准;3)同名点引导的ICP精配准。首先使用体素网格滤波器构造点云的金字塔结构,在粗配准时,FPFH描述符用于金字塔顶层上点云的鲁棒匹配,在此基础上,再进行两层级同名点引导的ICP精配准优化,使用3组典型TLS点云对进行实验,结果表明本文方法可以高效地完成TLS点云的配准。  相似文献   
6.
The phase identification and travel time picking are critical for seismic tomography, yet it will be challenging when the numbers of stations and earthquakes are huge. We here present a method to quickly obtain P and S travel times of pre-determined earthquakes from mobile dense array with the aid from long term phase records from co-located permanent stations. The records for 1 768 M ≥ 2.0 events from 2011 to 2013 recorded by 350 ChinArray stations deployed in Yunnan Province are processed with an improved AR-AIC method utilizing cumulative envelope and rectilinearity. The reference arrivals are predicted based on phase records from 88 permanent stations with similar spatial coverage, which are further refined with AR-AIC. Totally, 718 573 P picks and 512 035 S picks are obtained from mobile stations, which are 28 and 22 times of those from permanent stations, respectively. By comparing the automatic picks with manual picks from 88 permanent stations, for M ≥ 3.0 events, 81.5% of the P-pick errors are smaller than 0.5 second and 70.5% of S-pick errors are smaller than 1 second. For events with a lower magnitude, 76.5% P-pick errors fall into 0.5 second and 69.5% S-pick errors are smaller than 1 second. Moreover, the Pn and Sn phases are easily discriminated from directly P/S, indicating the necessity of combining traditional auto picking and integrating machine learning method.  相似文献   
7.
Spatial predictions of forest variables are required for supporting modern national and sub-national forest planning strategies, especially in the framework of a climate change scenario. Nowadays methods for constructing wall-to-wall maps and calculating small-area estimates of forest parameters are becoming essential components of most advanced National Forest Inventory (NFI) programs. Such methods are based on the assumption of a relationship between the forest variables and predictor variables that are available for the entire forest area. Many commonly used predictors are based on data obtained from active or passive remote sensing technologies. Italy has almost 40% of its land area covered by forests. Because of the great diversity of Italian forests with respect to composition, structure and management and underlying climatic, morphological and soil conditions, a relevant question is whether methods successfully used in less complex temperate and boreal forests may be applied successfully at country level in Italy.For a study area of more than 48,657 km2 in central Italy of which 43% is covered by forest, the study presents the results of a test regarding wall-to-wall, spatially explicit estimation of forest growing stock volume (GSV) based on field measurement of 1350 plots during the last Italian NFI. For the same area, we used potential predictor variables that are available across the whole of Italy: cloud-free mosaics of multispectral optical satellite imagery (Landsat 5 TM), microwave sensor data (JAXA PALSAR), a canopy height model (CHM) from satellite LiDAR, and auxiliary variables from climate, temperature and precipitation maps, soil maps, and a digital terrain model.Two non-parametric (random forests and k-NN) and two parametric (multiple linear regression and geographically weighted regression) prediction methods were tested to produce wall-to-wall map of growing stock volume at 23-m resolution. Pixel level predictions were used to produce small-area, province-level model-assisted estimates. The performances of all the methods were compared in terms of percent root mean-square error using a leave-one-out procedure and an independent dataset was used for validation. Results were comparable to those available for other ecological regions using similar predictors, but random forests produced the most accurate results with a pixel level R2 = 0.69 and RMSE% = 37.2% against the independent validation dataset. Model-assisted estimates were more precise than the original design-based estimates provided by the NFI.  相似文献   
8.
Partitioning beta diversity into its two components of spatial turnover and nestedness is a more robust method for checking spatial variability in biological communities than calculating the total beta diversity alone. The relative contribution of spatial turnover and nestedness has been used to test the effects of climatic, environmental, spatial and temporal variables on community composition. In this study, we tested the effects of environmental factors and microhabitat features on total beta diversity and its spatial turnover and nestedness components using a comprehensive dataset of aquatic Heteroptera collected from four types of permanent freshwater habitats (i.e. streams, ponds, rock tanks and reservoirs) in the Western Ghats of India. We observed that communities in all four types of habitats were predominantly shaped by dissimilarity caused due to spatial turnover (>85 %). Each type of habitat showed the presence of one or more species uniquely associated with it, which might contribute to the turnover between communities. The abiotic environment (climatic factors, topological factors, soil characteristics and microhabitat features) as well as assemblage structure differed significantly between habitat types. Communities in each type of habitat were affected by different environmental factors, such as precipitation and temperature patterns for streams, altitude and rocky substrate for rock tanks, and soil characteristics and the presence of aquatic macrophytes for ponds and reservoirs. Assemblages observed in the four types of permanent habitats are thus compositionally distinct due to species replacements between local communities, which in turn are strongly influenced by environmental variables. Similar to previous studies, our results show that spatial turnover largely measures the same phenomenon as total beta diversity on a regional scale.  相似文献   
9.
To support the adoption of precision agricultural practices in horticultural tree crops, prior research has investigated the relationship between crop vigour (height, canopy density, health) as measured by remote sensing technologies, to fruit quality, yield and pruning requirements. However, few studies have compared the accuracy of different remote sensing technologies for the estimation of tree height. In this study, we evaluated the accuracy, flexibility, aerial coverage and limitations of five techniques to measure the height of two types of horticultural tree crops, mango and avocado trees. Canopy height estimates from Terrestrial Laser Scanning (TLS) were used as a reference dataset against height estimates from Airborne Laser Scanning (ALS) data, WorldView-3 (WV-3) stereo imagery, Unmanned Aerial Vehicle (UAV) based RGB and multi-spectral imagery, and field measurements. Overall, imagery obtained from the UAV platform were found to provide tree height measurement comparable to that from the TLS (R2 = 0.89, RMSE = 0.19 m and rRMSE = 5.37 % for mango trees; R2 = 0.81, RMSE = 0.42 m and rRMSE = 4.75 % for avocado trees), although coverage area is limited to 1–10 km2 due to battery life and line-of-sight flight regulations. The ALS data also achieved reasonable accuracy for both mango and avocado trees (R2 = 0.67, RMSE = 0.24 m and rRMSE = 7.39 % for mango trees; R2 = 0.63, RMSE = 0.43 m and rRMSE = 5.04 % for avocado trees), providing both optimal point density and flight altitude, and therefore offers an effective platform for large areas (10 km2–100 km2). However, cost and availability of ALS data is a consideration. WV-3 stereo imagery produced the lowest accuracies for both tree crops (R2 = 0.50, RMSE = 0.84 m and rRMSE = 32.64 % for mango trees; R2 = 0.45, RMSE = 0.74 m and rRMSE = 8.51 % for avocado trees) when compared to other remote sensing platforms, but may still present a viable option due to cost and commercial availability when large area coverage is required. This research provides industries and growers with valuable information on how to select the most appropriate approach and the optimal parameters for each remote sensing platform to assess canopy height for mango and avocado trees.  相似文献   
10.
Abstract

Compared with traditional methods, the three-dimensional laser-scanning (3D-LS) technique can efficiently acquire many high-quality geometric properties of rock discontinuities. In practice, engineers usually prefer to simplify the processing by using single-station point data and roughly orienting owing to the complexity of registration/georeferencing multi-station point data. However, prior published studies have paid little attention to the accuracy and reliability when determining discontinuity orientations using 3D-LS. We propose a reliable and accurate method with robust on-site applicability. As part of an ongoing effort, we are evaluating the precision of the commonly used coarse registration method and the fine registration method, and promoted the optimized coarse- and fine-registration methods and evaluated their precision. It is found that: (1) the common and the optimized registration method can meet our project’s engineering requirements, and the optimized registration method improved accuracy in the dip direction by approximately 1°; (2) fine registration using an iterative closest point (ICP) algorithm can correct both dip direction and dip angle; and (3) the orientation is of high precision with commonly used coarse and fine registration, whereas the optimization effect to correct the orientation is slightly limited.  相似文献   
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