基于μC/OS-II嵌入式技术的农业环境远程监控系统实现

针对农业环境远程监测技术特点，提出了一种基于嵌入式系统和无线远程通信技术相结合的系统解决方案。该系统以ARM CPU为硬件核心，通过μC/OS-II嵌入式操作系统的调度与管理，实现农业现场数据的实时采集与处理，然后经由CDMA/GPRS无线移动通信模块将其发送至数据库服务器。在服务器端，采用ASP.NET技术实现动态WEB发布，用户可以通过INTERNET网络随时浏览和下载各种农业信息数据。此方案的实现明显改善了系统的综合性能，在可靠性、集成性、稳定性和扩展性等方面，更能适合分散远程条件下农业环境信息监测与管理的各种需要。     

基于异构数据集成技术的农业信息综合管理网络平台开发

针对中国当前农业无线监测中农业信息化标准尚未建立,监测终端各不相同,监测系统数据结构兼容性差的问题,该文围绕异构数据规范化设计和管理,开发了面向差异化农业信息监测终端的一体化网络平台。根据异构网络数据特点,将不同监测终端上传的数据格式标准化;基于XML(extensible markup language)和Visual Basic 6.0开发了标准化网管数据接口,将不同终端数据按照通讯协议的标准格式解析、存储数据;基于PHP、My SQL数据库和服务器及网站网页技术设计并搭建了远程监测平台。利用开沟机监测终端进行田间试验,监测耕深和跟踪机具,试验表明:网管数据接口能实时接收并正确解析终端数据;监测平台可实现远程数据的曲线显示、数据导出和控制终端的远程控制、轨迹绘制的功能;通过导出数据的轨迹和平台显示轨迹对比,轨迹精确。该研究解决了监测系统异构数据及终端硬件差异问题,把单机测控应用扩展至广域网,可应用于农机信息的远程实时监测和远程控制,对现代化农业信息化共享有着重要作用。     

农业环境远程分布式多功能监控系统

农业环境远程分布式多功能监控系统是一种高度自动化和网络化的监控系统，除了可对农业与生态环境等要素信息（如气象、土壤和作物等）进行实时动态采集监测，而且还可通过图像视频技术对不同声景（如现场景观，作物生长、形态变化等）进行动态监测，真正实现了农业现场图像与数据一体化精准监控。     

基于μC/OS-Ⅱ嵌入式技术的农业环境远程监控系统实现

针对农业环境远程监测技术特点,提出了一种基于嵌入式系统和无线远程通信技术相结合的系统解决方案.该系统以ARM CPU为硬件核心,通过μC/OS-Ⅱ嵌入式操作系统的调度与管理,实现农业现场数据的实时采集与处理,然后经由CDMA/GPRS无线移动通信模块将其发送至数据库服务器.在服务器端,采用ASP.NET技术实现动态WEB发布,用户可以通过INTERNET网络随时浏览和下载各种农业信息数据.此方案的实现明显改善了系统的综合性能,在可靠性、集成性、稳定性和扩展性等方面,更能适合分散远程条件下农业环境信息监测与管理的各种需要.     

中国农业科技入户网数据上报管理系统建设

“中国农业科技入户网”数据上报管理系统是为了配合“农业科技入户工程”的深入开展而建立的,系统采用科技示范县客户端远程上报数据的方式,实现数据的即时性、集中武与规范化管理,目前该系统已成为“农业科技入户工程”数据上报、传输与处理的重要网上管理平台。     

远程农业监测信息系统设计与实现

针对农业信息远程监测服务需求和物联网农业应用背景,设计开发了农业信息远程监测和服务系统。系统将无线数据采集、远程数据传输和网络服务相结合,实现了远程、多目标、多参数的农业信息实时采集、显示、存储、查询和统计等功能。系统通用性和扩展性较强,在数字农业、农作物防灾减灾等领域具有良好的应用前景。     

农业环境远程分布式多功能监控系统

农业环境远程分布式多功能监控系统是一种高度自动化和网络化的监控系统,除了可对农业与生态环境等要素信息（如气象、土壤和作物等）进行实时动态采集监测,而且还可通过图像视频技术对不同场景（如现场景观、作物生长、形态变化等）进行动态监测,真正实现了农业现场图像与数据一体化精准监控。     

农业环境远程分布式多功能监控系统

农业环境远程分布式多功能监控系统是一种高度自动化和网络化的监控系统,除了可对农业与生态环境等要素信息（如气象、土壤和作物等）进行实时动态采集监测,而且还可通过图像视频技术对不同场景（如现场景观、作物生长、形念变化等）进行动态监测,真正实现了农业现场图像与数据一体化精准监控。     

基于GSM的数字农业远程监控系统研究与应用

应用无线网络技术可实现农机作业过程和农田水利设施等的远程监控,为作物生长过程与产量、农业气象等信息的实时采集提供保障。探讨了基于GSM无线技术的数字农业远程测控系统组成结构,阐述了系统监控端软件的实现。在此基础上,采用自行研制的GSM远程通信控制器,开发了智能测产远程数据传输系统,并介绍了该系统的硬件组成和相应软件开发。在测产试验中对现场数据传输的实时性进行了测试,结果表明,GSM无线通信技术能满足农业远程监控的要求。     

基于远程通讯的农田信息管理系统设计与实现

为实现农田信息远程智能化管理,该文按照软件工程思想设计并实现基于远程通讯的农田信息管理系统。远程农田信息管理系统是移动式农业智能服务系统的一个重要组成部分, 是实现农田信息管理的核心。远程农田信息管理系统通过GPRS实时接收来自移动终端（农田PDA）的农田信息数据,将其存放到农田信息数据库中;按照农田处理模型对其进行分析、处理,并进行可视化表达,为农田变量控制提供决策支持。根据系统的主要功能,将系统划分为地图管理、PDA管理、数据管理和系统管理等四大模块。远程农田信息管理系统实现了农田信息的实时采集、处理、可视化和传输,为用户提供全面的决策信息和技术支持。     

Ratio of PAR to broadband solar radiation measured in Cyprus

The relationship between the two radiant fluxes is studied from almost a 3-year data archive of hourly photosynthetically active photon flux (Q_P) and global solar irradiance (R_S) performed at Athalassa, Cyprus. These data are used to determine temporal variability of the ratio (Q_P/R_S) and its dependence on sky conditions. The seasonal variation of the ratio obtained from daily data ranges from 1.942 E MJ⁻¹ (summer) to 1.892 E MJ⁻¹ (winter) with an annual mean value of 1.919 E MJ⁻¹. The ratio increased from 1.865 to 2.01 E MJ⁻¹ (daily values) or from 1.878 to 2.197 μE J⁻¹ (hourly values), as sky conditions changed from clear to overcast. Effective atmospheric parameters such as sky clearness, brightness and path length were found to cause substantial changes to the PAR fraction.     

Revisiting the definitions of the sombric horizon in soil taxonomy and world reference base for soil resources

A review of the literature suggests that the sombric horizon (from French sombre, dark) was established in Soil Taxonomy (ST) and the World Reference Base for Soil Resources (WRB) from limited data and without a clear understanding of how this horizon forms. This paper reviews data on sombric horizons, evaluates four hypotheses regarding their origin, and offers suggestions for improving the identification of sombric horizons. Of the 30 pedons recognized in the literature as having sombric or sombric-like horizons, 12 fully satisfied the existing criteria in ST and the WRB. Soils with a true sombric horizon may be restricted to the highlands of central Africa (Burundi, Rwanda, Congo) on relatively cool (mean annual air temperature 16–20 °C), moist (mean annual precipitation 1450–2000 mm) plateaus and mountains at elevations ranging from 1450 to 2000 m. Soils with a sombric horizon occur primarily on highly weathered materials from a variety of crystalline rocks. The surface of the sombric horizon occurs at depths of 40 to 110 cm from the surface (average = 76 cm) and ranges from 27 to 100 cm in thickness (average = 63 cm). The sombric horizon commonly is dark reddish brown (5YR 3/3), acidic (average pH = 4.7), low in exchangeable bases (average base saturation = 4%), high in organic C (average = 1.3%), and despite abundant clay (average = 56%) has a low cation-exchange capacity (average = 12 cmol(+)/kg soil). Based on existing data, the sombric horizon contains humus that has migrated downward in the soil, possibly in response to climate and vegetation change. Sombric horizons are not to be confused with sombric-like horizons which may contain andic soil properties or spodic materials. In Soil Taxonomy, soils with sombric horizons are classified primarily as Sombriudoxes (8 pedons) and Sombrihumults (4 pedons). In the World Reference Base for Soil Resources, sombric horizons occur primarily in Umbric Ferralsols (Sombric).     

Satellite-based estimation of evapotranspiration of an old-growth temperate mixed forest

Evapotranspiration (ET) is a key flux in the water cycle and has strong seasonal dynamics for forest ecosystems. Recently eddy flux covariance measurements are continuously taken at a temperate mixed forest in Northeastern China since 2002. In an effort to better understanding the factors that control the seasonal dynamics of ET, here we (1) calculate ecosystem-level water use efficiency (WUE) from observed water and CO₂ flux data, and (2) relate the resultant WUE with satellite-derived vegetation indices, and (3) develop and evaluate a simple model that uses satellite images and climate data as input data to predict ET on the coupling of photosynthesis and transpiration processes. Ground WUE estimates obtained from eddy covariance tower were correlated with moderate resolution imaging spectroradiometer (MODIS) vegetation indexes (VIs) and ground micrometeorological data over 3 years (2003–2005). The enhanced vegetation index (EVI) was more closely correlated (r = 0.82) with WUE than the normalized difference vegetation index (NDVI; r = 0.64). Air temperature (T_A) measured over the canopy was the meteorological variable that was most closely correlated with WUE (r = 0.74) over years. For the significant correlation between EVI and T_A (r = 0.82, P < 0.05), EVI was selected as the single variable to predict WUE to simplify calculation. We calculated ET by ET = GPP/WUE, gross primary production (GPP) was predicted by vegetation photosynthesis model (VPM) that uses satellite images and meteorological variables. At a temporal resolution of 8 days, the annual curves showed good correspondence between measured and predicted values of WUE and ET in terms of phase and magnitude for each year. Seasonally integrated predicted ET was +4% (in 2003), +2% (in 2004), +0.4% (in 2005) higher than observed values.     

Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks

Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Although soil moisture may be highly variable in space and time, if measurements of soil moisture at the field or small watershed scale are repeatedly observed, certain locations can often be identified as being temporally stable and representative of the an area average. This study is aimed at determining the adequacy of long term point-scale surface soil moisture measurements in representing local field scale averages which may ultimately serve as in situ locations for the calibration and validation of remotely sensed soil moisture. Experimental data were obtained by frequency-domain reflectometry (FDR) sensors permanently installed in two agricultural fields, AS1 and AS2 (2.23 and 2.71 ha, respectively) at a depth of 5 cm. Twenty additional FDR sensors, spaced 35 m apart, were installed horizontally at a depth of 5 cm in each field with automated data collection being transmitted every 30 min from July 15 through September 20, 2009. Additionally, meteorological data were obtained from existing weather stations in each field. The FDR sensors revealed persistent patterns in surface soil moisture within each field and identified sites that were temporally stable. The locations that were optimal for estimating the area-average field water contents were different from the permanent sensor locations in both fields. Permanent sensor data showed approximately 4 and 10% mean relative differences for fields AS1 and AS2, respectively, with relatively large standard deviations. Thus, minimum offset values could be applied to the temporally stable field sites to obtain representative field average values of surface soil moisture. However, use of permanent sensor data for offset estimates gave poor results. These findings are of relevance for applications of geospatial surface soil moisture data assimilation in hydrologic modeling when only point-scale observations are available, as well as, remotely sensed surface soil moisture calibration and validation studies.     

Difference in spatiotemporal patterns of wildlife road-crossings and wildlife-vehicle collisions

Human–wildlife conflicts like wildlife–vehicle collisions pose major challenges for the management and conservation of mobile wildlife in human-dominated landscapes, particularly when large species are involved. Mitigation measures to reduce risk of collisions may be based on information given by wildlife movement and collision data. To test whether movement and collision data indicate different spatiotemporal risk zones, we predicted year-around probabilities of road-crossings of GPS-marked female moose (Alces alces) (n = 102), and compared them with spatiotemporal patterns of police recorded moose-vehicle collisions (n = 1158). Probability of moose road-crossings peaked in May, June, and between mid November and the beginning of January, i.e. during moose migration. Moose-vehicle collisions were more likely during autumn and winter. Comparing environmental attributes of crossing and collision sites showed significant differences. The likelihood of collisions increased with the abundance of human-modified areas and higher allowed speed, and was lower on forest roads. We found that animal movement data alone are insufficient to predict collision risk zones, while analyses of collision data alone overestimate the collision risk in certain habitats. Our findings suggest that higher collision risk is largely due to low light and poor road surface conditions rather than to more animal road-crossings. This suggests that efforts to reduce wildlife collisions should focus on driver attitudes and road conditions rather than animal movement, and any efforts to model the collision risk will require actual collision data, and not just movement data.     

Estimation of evaporation using a dual-beam surface layer scintillometer and component energy balance measurements

A dual-beam surface layer scintillometer (SLS), for the estimation of sensible heat flux density H for a path length of 101 m, was used in a mixed grassland community in the eastern seaboard of South Africa for 30 months. Measurements also included Bowen ratio (BR) and eddy covariance (EC) estimates of H. Acceptable SLS data between 0600 h and 1800 h, judged by the percent of error-free 1 kHz data exceeding 25% and an inner scale of turbulence exceeding 2 mm, showed little seasonal variation and was consistently high—between 86.7% and 94.8%. An analysis of the various Monin–Obukhov similarity theory (MOST) empirical dimensionless stability functions used for estimating H from the SLS measurements showed percent differences in H that varied from ?30% to 28% for neutral to unstable conditions, respectively and for stable continuous conditions the differences in H were within 60 W m^?2 with much larger differences for stable sporadic conditions. The good agreement in measurements of H over an extended period for the SLS, BR and EC methods demonstrates the applicability and robustness of the SLS method and the associated MOST empirical functions used for estimating H for a range of canopy heights, stability conditions and diurnal and seasonal weather conditions. Furthermore, there was no evidence for an underestimation in EC sensible heat compared to SLS and BR measurements, which implies that any lack of energy balance closure points to possible latent energy EC underestimation or due to energy fluxes not included in the shortened energy balance if the net irradiance and soil heat flux components are correct. A sensitivity analysis was used to determine the relative importance of the SLS data inputs of air temperature, atmospheric pressure, beam path length and beam height on H estimates. Worst-case errors in air temperature, atmospheric pressure, beam path length and beam height resulted in errors in H within 1.0%, 1.3%, 3.0% and 4.0%, respectively. Overall, the worst-case total percent error in SLS-estimated H is within 5.3% and the typical percent error is within 3.9%. Accounting for the error in net irradiance and soil heat flux measurements, the seasonal variation in the error in daily evaporation estimated as a residual of the energy balance is generally less than 0.2 mm (0.49 MJ m^?2) in winter when the daily evaporation was about 1 mm (2.45 MJ m^?2) and typically less than 0.4 mm (0.98 MJ m^?2) when the evaporation exceeded 4 mm (9.8 MJ m^?2). Soil heat flux density measurements can contribute significantly to the overall error.     

Impact of agriculture,forest and cloud feedback on the surface energy budget in BOREAS

We explore the impact of agriculture, forest and cloud feedback on the surface energy budget using data obtained using a research aircraft, mesonet towers and model data. The forest has an order of magnitude larger roughness length, a lower albedo, a much smaller seasonal cycle in surface Bowen ratio (BR) and a weak mid-summer maximum of CO₂ uptake compared to agricultural areas, which have much smaller BR and much higher mid-summer CO₂ uptake, but a net CO₂ release and much reduced evaporation in spring and fall. Higher surface temperatures and the higher albedo over agricultural land reduce R_net near local noon in the warm season by about 50 W m⁻² in comparison with the adjacent boreal forest. The annual averaged R_net, derived from 2 years of tower data, is 14 W m⁻² less over grass sites than over forest sites. A reanalysis time-series for the BOREAS southern study area shows the coupling on daily timescales between the surface energy partition, the mean boundary layer depth, the cloud field and the long-wave and short-wave radiation fields. The albedo of the cloud field, the cloud short-wave forcing at the surface, varies over the range 0.1–0.8 with decreasing surface BR, and plays a major role in the surface energy budget. We estimate that this cloud feedback may increase albedo by 0.13 and reduce R_net by 25 W m⁻² in summer over agricultural land.     

Limiting factors in the restoration of UK grassland beetle assemblages

Grasslands restoration is a key management tool contributing to the long-term maintenance of insect populations, providing functional connectivity and mitigating against extinction debt across landscapes. As knowledge of grassland insect communities is limited, the lag between the initiation of restoration and the ability of these new habitats to contribute to such processes is unclear. Using ten data sets, ranging from 3 to 14 years, we investigate the lag between restoration and the establishment of phytophagous beetle assemblages typical of species rich grasslands. We used traits and ecological characteristics to determine factors limiting beetle colonisation, and also considered how food-web structure changed during restoration. For sites where seed addition of host-plants occurred the success in replicating beetle assemblages increased over time following a negative exponential function. Extrapolation beyond the existing data set tentatively suggested that success would plateau after 20 years, representing a c. 60% increase in assemblage similarity to target grasslands. In the absence of seed addition, similarity to the target grasslands showed no increase over time. Where seed addition was used the connectance of plant–herbivore food webs decreased over time, approaching values typical of species rich grasslands after c. 7 years. This trend was, however, dependent on the inclusion of a single site containing data in excess of 6 years of restoration management. Beetles not capable of flight, those showing high degrees of host-plant specialisation and species feeding on nationally rare host plants take between 1 and 3 years longer to colonise. Successful grassland restoration is underpinned by the establishment of host-plants, although individual species traits compound the effects of poor host-plant establishment to slow colonisation. The use of pro-active grassland restoration to mitigate against future environmental change should account for lag periods in excess of 10 years if the value of these habitats is to be fully realised.     

The temperature dependence of dicyandiamide (DCD) degradation in soils: A data synthesis

Dicyandiamide (DCD, C₂H₄N₄) is a nitrification inhibitor that has been studied for more than 80 years. However, there are few papers that have examined the use of DCD on dairy farms where cattle graze pasture and where urine is the primary form of nitrogen (N) deposited onto soils. After DCD was applied (10 kg DCD ha^?1) with bovine urine (700–1200 kg N ha^?1) to five soils throughout New Zealand, the reduction in direct nitrous oxide (N₂O) emissions was significant and remarkably consistent (71 ± 8%, average ± standard error). The application of DCD to these soils occurred in autumn and winter; daily average soil temperature (T) was reported but these data were not further analysed. Perusal of the literature suggested no consensus on the temperature dependence of DCD degradation in soils. Based on published data from controlled-environment studies of soils sampled in four countries, we quantified the relation between T and the time for DCD concentration in soils to decline to half its application value (t_½) as t_½ (T) = 168e^?0.084T with parameter standard errors of ±16 d and ±0.011 d^?1, respectively (n = 16). For example, at 5 °C a 1 °C increase in T reduced t_½ from 110 to 101 d whereas at 25 °C the reduction was 20–19 d. Analysing T data from the New Zealand trials using our t_½ (T) function, over 43–89 d when direct N₂O emissions from treated plots became indistinguishable from the controls, the estimated percentage of applied DCD remaining in the soil averaged 43 ± 10%. These calculations suggested the apparently remaining DCD was ineffective with respect to direct N₂O emissions. In the absence of measurements, explanations for this interpretation included vertical displacement of the DCD and sorption onto organic matter in soils. The consistent DCD efficacy from these trials corresponded with T generally <10 °C, so it is suggested as an application criteria for the reduction of direct N₂O emissions from pastoral soils subjected to urine excretion by grazing cattle.     

Spatial modeling of soil erosion potential in a tropical watershed of the Colombian Andes

Soil erosion potential of a 58 km² watershed in the coffee growing region of the Colombian Andes was assessed using the Revised Universal Soil Loss Equation (RUSLE) in a GIS environment. The RUSLE factors were developed from local rainfall, topographic, soil and land use data. Seasonal erosivity factors (R) were calculated for six pluviographic stations (1987–1997) located within 22 km of the basin. Two regression models, one for the wet and one for the dry seasons, were created and used to estimate seasonal erosivity for 10 additional stations with pluviometric data. Erosivity was on average higher in the wet seasons (4686 MJ mm ha^− 1 h^− 1 season^− 1) than the dry ones (2599 MJ mm ha^− 1 h^− 1 season^− 1). Seasonal erosivity surfaces were generated using the local polynomial interpolation method, and showed increases from west to east in accordance with regional elevation. Soil erodibility was calculated from field measurements of water stable aggregates (> 2 mm) and infiltration, which were influenced by land use. Three erodibility scenarios were considered (high, average and low) to represent the variability in infiltration measurements within each land use. The topographic and land cover factors were developed from existing contour and land use data. Model results indicated that in the dry seasons, and under the average erodibility scenario, 534 ha (11%) of the basin's rural area were within the extreme erosion potential category (above 3.5 t ha^− 1 season^− 1). During the wet seasons, this area increased to 1348 ha (28%). In general, areas under forest and shrub had low erosion potential values, while those under coffee and pasture varied according to topography. Modeling of probable land use change scenarios indicated that the erosion potential of the basin would decrease as a result of coffee conversion to pasture.