s: The farmland shelterbelts in Northeastern Plain of China have formed relatively complete net system. The func-tions of shelterbelt net in omnibearing wind check and prevention of frostbite as well as the field of ...s: The farmland shelterbelts in Northeastern Plain of China have formed relatively complete net system. The func-tions of shelterbelt net in omnibearing wind check and prevention of frostbite as well as the field of integrated climate effect within shelterbelt net were analyzed, through located observation of meteorological factors. Within the shelterbelt net, the area with more than 10% efficiency of omnibearing wind check was determined as benefited area. The analysis of yield and quality of crops indicated that the sheltering range of shelterbelt net was 25 times tree height. The mature heights of the various varieties of poplar composed the shelterbelts were determined according to their height growth. Based on the comprehensive analysis above, the suitable size of farmland shelterbelt net in Northeastern Plain of China was decided to be 400 m×400 m.展开更多
On the basis of landscape ecology, combining the Spot 5 high resolution satellite imagery with GIS, a method evaluating the spatial heterogeneity of shelterbelts distribution at landscape scale is put forward in this ...On the basis of landscape ecology, combining the Spot 5 high resolution satellite imagery with GIS, a method evaluating the spatial heterogeneity of shelterbelts distribution at landscape scale is put forward in this paper. The distance coefficients of reasonable and existing landscape indexes of farmland shelterbelt networks were com-puted, and then through the classification of the distance coefficients, and the establishment of evaluation rules, the spatial heterogeneity of farmland shelterbelts was evaluated. The method can improve the evaluating system of previ-ous studies on shelterbelts distribution, resolve the disadvantages of lacking spatiality of overall evaluation, and make the evaluation results have more directive significance for shelterbelt management. Based on this method, spatial het-erogeneity of shelterbelt networks was evaluated in the midwest of Jilin Province, China. The results show that the re-gions with fewer shelterbelts and no closed network account for 34.7% of the total area, but only 4.9% of the area has relative reasonable pattern of shelterbelt networks. Many problems exist in the distribution pattern of shelterbelts, therefore, much attention should be paid to construct farmland shelterbelts in the study area.展开更多
The black soil region of northeast China is one of the most important grain-producing areas in China. Increasingly severe gully erosion in this region has destroyed much farmland and reduced grain production. We analy...The black soil region of northeast China is one of the most important grain-producing areas in China. Increasingly severe gully erosion in this region has destroyed much farmland and reduced grain production. We analyzed SPOT5 imagery from 2007 and TM imagery from 2008 to describe the distributions of gullies and farmland shelterbelts in Kedong County and to assess the effect of farmland shelterbelts on gully erosion. The ima- gery revealed 2311 gullies with average density of 418.51 m km-2, indicating very serious gully erosion. With increasing slope gradient there was an inverse trend between gully density and shelterbelt density, indicating that farmland shelterbelts can prevent gully erosion. The defense effect of farmland shelterbelts against gullyerosion varied with distance: for distances 〈120 m, the defense effect was consistent and very strong; for distances of 120-240 m, a weak linear decrease was found in the defense effect; and for distances 〉240 m, the defense effect of the shelterbelts was significantly weaker. We recommend an optimal planting density of farmland shel- terbelts for the prevention of gully erosion at 1100-1300 m km-2.展开更多
[Objectives]To explore the effects of spatial density of farmland shelterbelts on NDVI on the northern slope of Tianshan Mountains.[Methods]Taking the economic belt of the northern slope of the Tianshan Mountains as t...[Objectives]To explore the effects of spatial density of farmland shelterbelts on NDVI on the northern slope of Tianshan Mountains.[Methods]Taking the economic belt of the northern slope of the Tianshan Mountains as the research area and using the grid method,the spatial density distribution of farmland shelterbelts can be known.Combining the grid method with NDVI data,the average value of normalized difference vegetation index(NDVI)during the growing period of crops can be obtained.In addition,the protection benefits of the shelterbelts on crops were analyzed through comparing the growth of crops within the protection zone with and without protection.[Results]The grids with shelterbelt distribution were better than the grids without shelterbelt distribution,and the shelterbelt played a great role in promoting crop growth.In the middle stage of crop growth,the protection benefit of shelterbelt was significant.The spatial density of shelterbelts was unevenly distributed in the range of 0.6 to 0.8,and the protection benefits were poor.[Conclusions]It is expected to explore the effects of shelterbelts on crop growth at a larger regional scale,so as to provide a basis for the management and design of shelterbelts in the future,and to provide a theoretical basis for studying the protective effect of farmland shelterbelts on crops.展开更多
樟子松(Pinus sylvestris var. mongolica)是我国“三北”地区主要造林树种之一,樟子松防护林具有较强的防风固沙能力。本研究以樟子松防护林为研究对象,开展了5种行带式配置防护林防风效益风洞试验研究,测定了不同配置防护林防护区不...樟子松(Pinus sylvestris var. mongolica)是我国“三北”地区主要造林树种之一,樟子松防护林具有较强的防风固沙能力。本研究以樟子松防护林为研究对象,开展了5种行带式配置防护林防风效益风洞试验研究,测定了不同配置防护林防护区不同距离范围内风速及其流场特征,研究了樟子松防护林不同行带配置与防护效益关系,为常绿针叶树种农田防护林营造提供理论依据。结果表明:(1)防风效能随着林带行数的增加而增强,且林带后1 H~3 H内风速显著降低,形成风影区,风影区面积随着林带行数的增加而变大。(2)樟子松防护林带后风速流场发生显著变化,在12 m·s^(-1)风速条件下,1~5行1带的5种林带防风效能分别为15.1%、26.2%、37.5%、51.7%和51.9%,4行1带、5行1带结构配置防风效能均在50.0%以上。(3)樟子松防护林具有较强的防风效果,建议在干旱区农田防护林建设与更新中可采用樟子松造林,最适结构配置为4行1带。展开更多
【目的】系统评价中国农田防护林对作物产量的影响。【方法】在中国知网和Web of Science公开发表的文献中,通过检索关键词“农田防护林和产量”构建目标数据库,利用整合分析研究农田防护林对作物产量的影响及其在不同环境条件下的变化...【目的】系统评价中国农田防护林对作物产量的影响。【方法】在中国知网和Web of Science公开发表的文献中,通过检索关键词“农田防护林和产量”构建目标数据库,利用整合分析研究农田防护林对作物产量的影响及其在不同环境条件下的变化。【结果】1)中国农田防护林对作物的平均增产率为16.4%,考虑林带占地因素后为5.6%;2)不同作物的增产效应有显著差异(Q_(M)=8.55,p=0.02),玉米(22.02%)增产率最大,小麦(14.36%)和水稻(11.15%)较低;3)不同气候类型(Q_(M)=1.8,p=0.79)和不同林网规格(Q_(M)=3.25,p=0.16)条件下农田防护林对作物产量的影响无显著差异;4)作物的增产效应和背景产量呈负相关,在产量低于9727.5 kg·hm^(-2)时具有显著增产效应。【结论】农田防护林可有效提高作物产量,是保障粮食安全和应对气候变化的有效途径,未来研究应适当关注政策工具的制定和综合经济效益的提升。展开更多
The more information obtained about the driving environment,the more ensures driving safety.Due to the complex driving environment of farmland roads,targets beside the road sometimes have an important impact on drivin...The more information obtained about the driving environment,the more ensures driving safety.Due to the complex driving environment of farmland roads,targets beside the road sometimes have an important impact on driving safety.To achieve this goal,a novel real-time detection and prediction algorithm of targets was proposed.The whole image was divided into four parts by RCM:driving region,crossroad region,roadside region,and the other region.In addition,a safety policy for every part was enforced by the algorithm,which was based mainly on the combination of the YOLACT and GPM.On this basis,a self-collected data set of 5000 test samples is used for testing.The detection accuracy of the algorithm in the data set could reach up to 90%,and the processing speed to 30.4 fps.In addition,experiments were carried out on actual farmland roads,and the results showed that the proposed algorithm was able to detect,track,and predict targets on the farmland road,and alarm to driver in time before the targets rush into the road.This study provides an important reference for the safe driving of agricultural vehicles.展开更多
The application of autonomous agricultural vehicles is gaining popularity as a way to increase production efficiency and lower operational costs.To achieve high performance,perception tasks(such as obstacle detection,...The application of autonomous agricultural vehicles is gaining popularity as a way to increase production efficiency and lower operational costs.To achieve high performance,perception tasks(such as obstacle detection,road extraction,and drivable area extraction)are of great importance.Compared with structured roads,field roads between farmlands,including unstructured roads and semi-structured roads,are unfavorable for autonomous agricultural vehicle driving due to their bumpiness and unstructured nature.This study proposed an extraction method for the straight field roads between farmlands.The proposed method was based on the point cloud data acquired by LiDAR(Velodyne VLP-16)mounted on a John Deere 12046B-1204 tractor.The proposed method has three aspects:Euclidean Clustering-based extraction,boundary-based extraction,and road point cloud curve segment modification.Firstly,Euclidean Clustering with K-Dimensional(KD)-Tree data structure was adopted to extract the road curve segments close to the LiDAR composed of road points.Secondly,the boundary lines constraint was constructed to extract the distant road curve segments.Thirdly,the local distance ratio was used to modify the extracted road curve segments.The average extraction accuracy for both semi-structured and unstructured roads exceeded 98%,and the false positive rate(FPR)was less than 0.5%.These experimental findings demonstrated that the proposed road extraction method was precise and effective.The proposed method of this study can be applied to enhance the perception ability of autonomous agricultural vehicles thereby increasing the efficiency and safety of field road driving.展开更多
文摘s: The farmland shelterbelts in Northeastern Plain of China have formed relatively complete net system. The func-tions of shelterbelt net in omnibearing wind check and prevention of frostbite as well as the field of integrated climate effect within shelterbelt net were analyzed, through located observation of meteorological factors. Within the shelterbelt net, the area with more than 10% efficiency of omnibearing wind check was determined as benefited area. The analysis of yield and quality of crops indicated that the sheltering range of shelterbelt net was 25 times tree height. The mature heights of the various varieties of poplar composed the shelterbelts were determined according to their height growth. Based on the comprehensive analysis above, the suitable size of farmland shelterbelt net in Northeastern Plain of China was decided to be 400 m×400 m.
基金Under the auspices of Knowledge Innovation Programs of Chinese Academy of Sciences (No. KZCX1-YW-08-02)
文摘On the basis of landscape ecology, combining the Spot 5 high resolution satellite imagery with GIS, a method evaluating the spatial heterogeneity of shelterbelts distribution at landscape scale is put forward in this paper. The distance coefficients of reasonable and existing landscape indexes of farmland shelterbelt networks were com-puted, and then through the classification of the distance coefficients, and the establishment of evaluation rules, the spatial heterogeneity of farmland shelterbelts was evaluated. The method can improve the evaluating system of previ-ous studies on shelterbelts distribution, resolve the disadvantages of lacking spatiality of overall evaluation, and make the evaluation results have more directive significance for shelterbelt management. Based on this method, spatial het-erogeneity of shelterbelt networks was evaluated in the midwest of Jilin Province, China. The results show that the re-gions with fewer shelterbelts and no closed network account for 34.7% of the total area, but only 4.9% of the area has relative reasonable pattern of shelterbelt networks. Many problems exist in the distribution pattern of shelterbelts, therefore, much attention should be paid to construct farmland shelterbelts in the study area.
基金supported by the National Natural Science Foundation of China(31400612,41271305)the Key Technologies Research and Development Program of Henan Province(142102110147)
文摘The black soil region of northeast China is one of the most important grain-producing areas in China. Increasingly severe gully erosion in this region has destroyed much farmland and reduced grain production. We analyzed SPOT5 imagery from 2007 and TM imagery from 2008 to describe the distributions of gullies and farmland shelterbelts in Kedong County and to assess the effect of farmland shelterbelts on gully erosion. The ima- gery revealed 2311 gullies with average density of 418.51 m km-2, indicating very serious gully erosion. With increasing slope gradient there was an inverse trend between gully density and shelterbelt density, indicating that farmland shelterbelts can prevent gully erosion. The defense effect of farmland shelterbelts against gullyerosion varied with distance: for distances 〈120 m, the defense effect was consistent and very strong; for distances of 120-240 m, a weak linear decrease was found in the defense effect; and for distances 〉240 m, the defense effect of the shelterbelts was significantly weaker. We recommend an optimal planting density of farmland shel- terbelts for the prevention of gully erosion at 1100-1300 m km-2.
基金Basic Scientific Research Project of Non-profit Scientific Research Institutes in Xinjiang Uygur Autonomous Region(KY2022137).
文摘[Objectives]To explore the effects of spatial density of farmland shelterbelts on NDVI on the northern slope of Tianshan Mountains.[Methods]Taking the economic belt of the northern slope of the Tianshan Mountains as the research area and using the grid method,the spatial density distribution of farmland shelterbelts can be known.Combining the grid method with NDVI data,the average value of normalized difference vegetation index(NDVI)during the growing period of crops can be obtained.In addition,the protection benefits of the shelterbelts on crops were analyzed through comparing the growth of crops within the protection zone with and without protection.[Results]The grids with shelterbelt distribution were better than the grids without shelterbelt distribution,and the shelterbelt played a great role in promoting crop growth.In the middle stage of crop growth,the protection benefit of shelterbelt was significant.The spatial density of shelterbelts was unevenly distributed in the range of 0.6 to 0.8,and the protection benefits were poor.[Conclusions]It is expected to explore the effects of shelterbelts on crop growth at a larger regional scale,so as to provide a basis for the management and design of shelterbelts in the future,and to provide a theoretical basis for studying the protective effect of farmland shelterbelts on crops.
文摘【目的】系统评价中国农田防护林对作物产量的影响。【方法】在中国知网和Web of Science公开发表的文献中,通过检索关键词“农田防护林和产量”构建目标数据库,利用整合分析研究农田防护林对作物产量的影响及其在不同环境条件下的变化。【结果】1)中国农田防护林对作物的平均增产率为16.4%,考虑林带占地因素后为5.6%;2)不同作物的增产效应有显著差异(Q_(M)=8.55,p=0.02),玉米(22.02%)增产率最大,小麦(14.36%)和水稻(11.15%)较低;3)不同气候类型(Q_(M)=1.8,p=0.79)和不同林网规格(Q_(M)=3.25,p=0.16)条件下农田防护林对作物产量的影响无显著差异;4)作物的增产效应和背景产量呈负相关,在产量低于9727.5 kg·hm^(-2)时具有显著增产效应。【结论】农田防护林可有效提高作物产量,是保障粮食安全和应对气候变化的有效途径,未来研究应适当关注政策工具的制定和综合经济效益的提升。
基金supported by Beijing Jiaotong University(C18A800090)China North Vehicle Research Institute.All the support from the above organizations is gratefully acknowledged.
文摘The more information obtained about the driving environment,the more ensures driving safety.Due to the complex driving environment of farmland roads,targets beside the road sometimes have an important impact on driving safety.To achieve this goal,a novel real-time detection and prediction algorithm of targets was proposed.The whole image was divided into four parts by RCM:driving region,crossroad region,roadside region,and the other region.In addition,a safety policy for every part was enforced by the algorithm,which was based mainly on the combination of the YOLACT and GPM.On this basis,a self-collected data set of 5000 test samples is used for testing.The detection accuracy of the algorithm in the data set could reach up to 90%,and the processing speed to 30.4 fps.In addition,experiments were carried out on actual farmland roads,and the results showed that the proposed algorithm was able to detect,track,and predict targets on the farmland road,and alarm to driver in time before the targets rush into the road.This study provides an important reference for the safe driving of agricultural vehicles.
基金financially supported by the National Key Research&Development Project(Grant No.2021YFB3901302)the Beijing Municipal Science and Technology Project(Grant No.Z201100008020008).
文摘The application of autonomous agricultural vehicles is gaining popularity as a way to increase production efficiency and lower operational costs.To achieve high performance,perception tasks(such as obstacle detection,road extraction,and drivable area extraction)are of great importance.Compared with structured roads,field roads between farmlands,including unstructured roads and semi-structured roads,are unfavorable for autonomous agricultural vehicle driving due to their bumpiness and unstructured nature.This study proposed an extraction method for the straight field roads between farmlands.The proposed method was based on the point cloud data acquired by LiDAR(Velodyne VLP-16)mounted on a John Deere 12046B-1204 tractor.The proposed method has three aspects:Euclidean Clustering-based extraction,boundary-based extraction,and road point cloud curve segment modification.Firstly,Euclidean Clustering with K-Dimensional(KD)-Tree data structure was adopted to extract the road curve segments close to the LiDAR composed of road points.Secondly,the boundary lines constraint was constructed to extract the distant road curve segments.Thirdly,the local distance ratio was used to modify the extracted road curve segments.The average extraction accuracy for both semi-structured and unstructured roads exceeded 98%,and the false positive rate(FPR)was less than 0.5%.These experimental findings demonstrated that the proposed road extraction method was precise and effective.The proposed method of this study can be applied to enhance the perception ability of autonomous agricultural vehicles thereby increasing the efficiency and safety of field road driving.