Percent Green Cover Research Articles

Development of a visual monitoring system for water balance estimation of horticultural crops using low cost cameras

The use of low cost cameras has been extended in all fields of technology in general, and agricultural applications in particular. Images provide useful information on the growing state of horticultural crops, which allow an accurate estimation of water balance and, hence, precise irrigation scheduling. In all of these cases, the temporary images of a crop can provide the percentage of green cover (PCG). This data is calibrated with the irrigation water amount that the crop needs for growing. Therefore, the use of visual monitoring systems in agriculture may reduce water consumption and increase productivity. In this paper, a novel system is presented using low cost cameras and a client-server architecture. It is composed of a set of inexpensive camera modules which communicate with a cloud computing server. Camera modules have been developed using open standard Arduino components; they are able to work independently, with their own connectivity, storage and power supply. On the other hand, the server is responsible for configuring these modules, performing computer vision algorithms and water balance estimation, storing all data in a secure database, and interacting with the user interface using the web. The final result is a complete and inexpensive system that allows continuous monitoring of the state of the crops, providing the user with valuable information about water balance for irrigation management. The proposed method achieves a high accuracy in the estimation of PGC, with an average error below 5%, requiring less than 2s of processing time per image in the server. This is transformed into an error in the computation of the crop coefficient below 1%. Technical details on the hardware and software components of the system are presented. Finally, advantages and weaknesses of the proposed solution are discussed, drawing new lines for future research.

Landsat images and crop model for evaluating water stress of rainfed soybean

Soil water content is a vital resource that plays a central role in agricultural areas. In Argentina the soybean (Glycine max (L.) Merrill) is the most important crop, considering the economic yield and the sown area. Actually, remote sensing allows continuous monitoring of crops and to evaluate the impact of water stress in their development. The combination of Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI) is an indicator that provides information about the condition of the vegetation and surface soil moisture content. In this study we evaluate relationships between indicators of crop water stress and the Temperature Vegetation Dryness Index (TVDI) determined from Landsat, for sites with rainfed soybean in the agricultural central zone of Córdoba (Argentina).Field data were acquired continuously throughout the whole growing season. For each sample date and plot, data of percent green vegetation cover, soil moisture content and phenology were registered. The use of a simulation crop model allowed obtaining indicators of crop water stress indices: (1) soil water deficit, (2) crop water use vs. reference crop evapotranspiration, and (3) fraction of the available water capacity that is readily available.The NDVI/LST spaces presented a trapezoidal form, which indicated that TVDI will have similar sensitivity for the full range of NDVI and showed temporal changes of wet and dry edges.When soybean cover exceeds 60%, the combination of TVDI with (2) and (3) can enhance the ability of detecting crop water stress conditions (R2=0.62 and 0.82, respectively). However, the relationship between TVDI and (1) showed low correlation values (R2=0.21).

Assessing freeze-tolerance in St. Augustinegrass: temperature response and evaluation methods

Winter hardiness is a major-limiting factor for St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] grown in the transitional climatic region of the United States. Lab-based freeze tests that mimic the range of field winter survivability in St. Augustinegrass can contribute to the selection of cold hardy genotypes. This study used a whole container method, four freezing temperatures, and two data collection systems to evaluate the freezing response of nine St. Augustinegrass genotypes ranging in their winter hardiness. Results indicated −3 and −4 °C with average regrowth ratings of 33.6 and 17.8% respectively, were more suitable temperatures for evaluating freeze survival in St. Augustinegrass than −5 and −6 °C with average regrowth ratings of 0.4 and 0%, respectively. Visual ratings of surviving green tissue and regrowth were generally well correlated when evaluated over a six week period post-freeze with Pearson correlation coefficients ranging of 0.17–0.62 for −3 °C freeze tests and 0.79–0.93 for −4 °C freeze tests. Additionally, measurement of percent green cover using digital imaging techniques commonly utilized in turfgrass field studies were significantly correlated (0.66) with visual ratings averaged across weekly post-freeze evaluation measurements for both −3 and −4 °C freezing temperatures. These results provide evidence that digital imaging analyses are useful in estimating surviving green tissue and regrowth in lab-based freeze tests. This study provides additional information regarding freezing temperatures, genotype responses, and data collection methods in St. Augustinegrass, which should aid breeders in the improvement of freeze tolerance in the species.

Comparative Performance of Three Tropical Turfgrasses Digitaria longiflora, Axonopus compressus and St. Augustinegrass under Simulated Shade Conditions

Shade affects turf quality by reducing light for photosynthesis. The shade tolerance of the tropical grasses, Digitaria longiflora and Axonopus compressus were evaluated against Stenotaphrum secundatum (St. Augustinegrass). The grasses were established under shade structures that provide 0%, 50%, 75% or 90% shade level for 30 days. A suite of leaf traits, recorded from similar leaf developmental stage, displayed distinct responses to shade conditions. Leaf length, relative to control, increased in all three species as shade level increased. The mean leaf extension rate was lowest in St. Augustinegrass (80.42%) followed by A. compressus (84.62%) and D. longiflora (90.78%). The higher leaf extension rate in D. longiflora implied its poor shade tolerance. Specific leaf area (SLA) increased in all species with highest mean SLA increase in D. longiflora (348.55 cm2 mg−1) followed by A. compressus (286.88 cm2 mg−1) and St. Augustinegrass (276.28 cm2 mg−1). The highest SLA increase in D. longiflora suggested its lowest performance under shade. The percent green cover, as estimated by digital image analysis, was lowest in D. longiflora (53%) under 90% shade level compared to both species. The relative shade tolerance of the three turfgrasses could be ranked as St. Augustinegrass > A. compressus > D. longiflora.

A reliable and non-destructive method for estimating forage shrub cover and biomass in arid environments using digital vegetation charting technique

Despite the importance of fodder shrubs to small ruminant diets and production in arid and semi-arid ecosystems, they are often not considered when quantifying grazing land potential. This oversight is mainly due to the time consuming and costly traditional techniques used to estimate shrub biomass. The shrub fodder component should be measured to avoid underestimation of the carrying capacity of rangelands. In this study, we present a fast, reliable and non-destructive method to estimate canopy vegetation cover to obtain aboveground shrub biomass. The experiment was conducted under field conditions in northwest Syria, where seedlings of seven shrub species were monitored for one year: Atriplex leucoclada (Moq.) Boiss., A. halimus L., A. lentiformis (Torr.) S. Watson, A. canescens (Pursh) Nutt., A. nummularia Lindl., Salsola vermiculata L. and Haloxylon aphyllum (C.A. Meyer) Bunge. The experimental layout was a randomized complete block design with five replications. We explored the effectiveness of digital vegetation charting technique (DVCT) for estimating shrub canopy cover. Aboveground shrub biomass was clipped to estimate the dry matter (DM) weight per species and to determine its relationship to canopy cover. In this study, an estimate of greenness (percent green vegetation cover) was extracted by way of greenness algorithms. Simple linear regressions between vegetation cover and biomass for 210 plots were performed. The cover of the seven species differed (P < 0.01): A. leucoclada had the highest vegetation cover (56%) and H. aphyllum the lowest (7%). Vegetation cover and DM biomass were positively correlated (P < 0.01) with R-squared ranging from 0.66 (H. aphyllum) to 0.84 (S. vermiculata). Our method provided reasonable estimations of canopy coverage which could predict aboveground phytomass. We conclude that DVCT offers a rapid, reliable and consistent measurement of shrub cover and biomass provided that shrubs have open architecture. This study shows the potential of digital cameras and image processing to determine cover/biomass in a non-destructive, timely and cost efficient way.

Evaluating Hybrid Bermudagrass Using Spectral Reflectance under Different Mowing Heights and Trinexapac-ethyl Applications

Quantitative spectral reflectance data have the potential to improve the evaluation of turfgrasses in variety trials when management practices are factors in the testing of turf aesthetics and functionality. However, the practical application of this methodology has not been well developed. The objectives of this research were 1) to establish a relationship between spectral reflectance and turfgrass quality (TQ) and percent green cover (PGC) using selected reference plots; 2) to compare aesthetic performance (TQ, PGC, and vegetation indices) and functional performance (surface firmness); and 3) to evaluate lignin content as an alternate means to predict surface firmness in turfgrass variety trials of hybrid bermudagrass [Cynodon dactylon × C. transvaalensis]. A field study was conducted on mature stands of three varieties (‘TifTuf’, ‘TifSport’, and ‘Tifway’) and two experimental lines (04-47 and 04-76) at two mowing heights (0.5 and 1.5 inch) and trinexapac-ethyl application (0.15 kg·ha−1 and nontreated control) treatments. Aesthetic performance was estimated by vegetation indices, spectral reflectance, visual TQ, and PGC. The functional performance of each variety/line was measured through surface firmness and fiber analysis. Regression analyses were similar when using only reference plots or all the plots to determine the relationship between individual aesthetic characteristics. Experimental line 04-47 had lower density in Apr. 2010, whereas varieties ‘TifTuf’, ‘TifSport’, and ‘Tifway’ were in the top statistical group for aesthetic performance when differences were found. ‘TifSport’ and ‘Tifway’ produced the firmest surfaces, followed by ‘TifTuf’, and finally 04-76 and 04-47, which provided the least firm surface. Results of leaf fiber analysis were not correlated with turf surface firmness. This study indicates that incorporating quantitative measures of spectral reflectance could reduce time and improve precision of data collection as long as reference plots with adequate range of green cover are present in the trials.

A new model for water balance estimation on lettuce crops using effective diameter obtained with image analysis

Digital processing and analysis of vegetation cover images allow a precise calculation of some parameters related to crop development, which are linked to the estimation of irrigation requirements of the plants. In this paper, a new methodology for visual monitoring of horticultural crops and computation of the corresponding water needs is presented. The proposed approach is based on the concept of effective diameter, defined as the equivalent diameter of a plant biomass as seen from a top view. It has been applied to a ‘Little Gem’ lettuce crop. The percentage of green cover (PGC), computed by means of a digital processing of captured coverage images, is used to provide accurate estimates of the effective diameter of the plants. Then, this value can be precisely related with some important parameters in agronomy such as root depth, height of the plants, and crop coefficient Kc. Since Kc is an essential parameter in most existing methodologies for water balance estimation, an extensive comparative study on the accuracy of the proposed approach with respect to two alternative methods has been conducted. The first approach is based on PGC and crop density data, while the second is exclusively based on image analysis. The proposed method behaved significantly better in all cases, yielding a coefficient of determination, R2, to the actual Kc values obtained with a Bowen station always above 0.95, and a maximum relative error of only 2.1%. Moreover, the proposed methodology also produced accurate estimates of root depth with R2 values above 0.986 and maximum error below 9%. This approach not only leads to a reduction of water consumption compared to traditional estimation methods, but it also simplifies the required computations and field equipment.

Using green infrastructure for urban climate-proofing: An evaluation of heat mitigation measures at the micro-scale

Urban green infrastructure (UGI) has been increasingly promoted as a key measure to mitigate heat stress in cities caused by the urban heat island effect and climate change impacts, including climate variability and extremes. However, comparable information concerning the performance of different UGI types to moderate such impacts is mostly lacking. This creates serious challenges for urban planners who need to decide on the most effective measures while considering spatial and administrative constraints. This study investigates how different types and quantities of UGI, i.e. trees, green roofs, and green facades, affect pedestrian thermal comfort. The study was applied to high-density residential areas under current and future climatic conditions. Climate change will on average increase afternoon Physiological Equivalent Temperature (PET) values by 2.4K; however, this could be vastly reduced by different UGI scenarios. Planting trees had the strongest impact with an average PET reduction of 13% compared with existing vegetation. Trees shade open spaces and provide evapotranspirative cooling. Another valuable adaptation option is green facades, which have mitigating effects of 5%–10%. In contrast, the effects of green roofs were negligible. Our results indicate that increasing the share of green cover did not directly correspond to the magnitude of the PET reduction. Placing vegetation strategically in heat-exposed areas is more effective than just aiming at a high percentage of green cover. We conclude that our extensive comparative analysis provides empirical evidence to support UGI on the micro-scale and assists planners and decision-makers to effectively select and prioritise concrete measures to adapt to climate change.

Web application for analysis of digital photography in the estimation of irrigation requirements for lettuce crops

Different studies in the field of agricultural engineering have successfully related irrigation needs of plants with the percentage of green cover in crop images, by using simple allometric equations. Therefore, the problem of segmenting plants from soil in digital images becomes a key component of many water management systems. The development of automatic computer vision algorithms avoids slow and expensive procedures which require the supervision of human experts. In this sense, color analysis techniques have shown to yield the best results in accuracy and efficiency. This paper describes the design and development of a new web application with two different color segmentation techniques to estimate the percentage of green cover. The system allows a remote monitoring of crops, including functionality to upload images, analyze images, database storage, and graphical visualization of the results. An extensive experimental validation of this tool has been carried out on a lettuce crop of variety ‘Little Gem’. The two segmentation methods – based on probabilistic color models using histograms, and clustering in the RGB space using the fuzzy c-means algorithm – are compared with respect to a manual segmentation technique which allows the human expert to validate the outcome of the process for each image. The experimental results demonstrate the feasibility of these two automatic methods as substitutes of the supervised process. The first method achieves a relative error below 2.4% in the obtained segmentation, while the second method has an error below 4.8%. Both techniques require less than 1s of processing time in the server. Equations to compute the crop coefficient parameter are also included and validated for the same kind of crop.

A new portable application for automatic segmentation of plants in agriculture

The achievement of the objectives of precision agriculture requires not only the development of new technologies, but also the availability of portable tools that can be used in the field. This paper describes the creation of a novel application for mobile devices called pCAPS (portable classification application for plants and soil) that integrates several computer vision techniques for plant segmentation and analysis in crop pictures. This tool allows monitoring of agricultural crops in real time, providing information that can be used to automate and optimize the calculation of water needs. The three main modules of pCAPS are: capture and cropping, image analysis, and historical record. First, a robust algorithm to detect rectangular markers located in the field is proposed; images are trimmed accordingly, in order to achieve a uniform analysis over long periods of time. Then color segmentation is applied using a probabilistic approach based on histograms in the optimum color space. Finally, an object counting process is performed on the binarized images, which is useful in applications that require the number of objects and their average size. Using pCAPS, the user can go with a portable device to a crop field, take a picture with the camera, automatically cut out the image, and perform on the ground an analysis of the vegetation, obtaining the percentage of green cover (PGC), number of plants, date, time, and GPS coordinates. This information can be sent by email to the central offices of the agricultural business, where appropriate decisions on fertirrigation needs would be taken. pCAPS is intuitive, user-friendly and has been developed for use by farm managers, requiring minimal skills in the use of mobile devices.

Effect of mulch on initial coverage of four groundcover species for low input landscaping in a Mediterranean climate

Groundcovers play a very important role in the creation of urban green spaces. They provide many agronomic and environmental benefits while simplifying the urban landscape management.In the areas with a Mediterranean-type climate, the development of low-input landscapes, with the ability to maintain their functions and aesthetical appeal, is pivotal. The aim of this study was to identify groundcover species that could be suited to the local environmental conditions and to evaluate the effect of different mulching systems on plant growth and weed suppression.Digital image analysis was used to measure the green cover percentage of four species (Hedera helix L., Hypericum calycinum L., Rosmarinus officinalis L., Vinca minor L.) grown on two different types of mulch (EcoCover® and wood-chips) and on bare soil. Changes in plant coverage, NDVI (Normalized Difference Vegetation Index) and weed biomass were recorded over a two year period.The prostrate R. officinalis established rapidly and reached more than 80% of coverage within 3 months after planting. Also, it was not affected by weed competition. Non-native H. calycinum also exhibited a quick spread, but it was unsuitable for low-input Mediterranean landscapes because it died during late summer from fungal disease. H. helix and V. minor were also adversely affected by pathogens and, due to their slow initial growth and low percent cover in the second year, they did not control weeds during the study. With the exception of R. officinalis, mulching materials did not significantly improve the establishment and cover ability of the tested species, but had significant effects on weed suppression. Digital image analysis and spectral reflectance proved to be reliable and objective techniques to assess groundcover performance.

Integrated Pest Management of Nematodes on Bermudagrass Turf

Use of bermudagrass (Cynodon dactylon) cultivars resistant/tolerant to plant‐parasitic nematodes is an important component of integrated pest management (IPM) for sustainable turf nematode management in sandy coastal soils of the southeastern United States. A multiyear field experiment evaluated five bermudagrass genotypes (‘Tifway’, standard susceptible; two commercial cultivars, ‘TifSport’ and ‘Celebration’; and two experimental germplasm, BA132 and PI 291590, that were identified as tolerant to sting nematode [Belonolaimus longicaudatus]) and four different nematicide regimes (untreated control, Curfew Soil Fumigant [1,3‐dichloropropene], monitoring‐based IPM [action threshold nematicide program], and calendar‐based IPM [nematicide rotation]). Nematode samples were collected at 3‐month intervals from February 2012 to November 2014. No significant differences among the genotypes with regard to population density of sting nematode were documented, but there were differences among genotypes with regard to some of the other plant‐parasitic nematodes, particularly spiral (Helicotylenchus paxilli) and ring (Mesocriconema ornatum) nematodes. There were significant nematicide regime responses on nematode population level after August 2013. A calendar‐based IPM program rotating Nortica (Bacillus firmus strain I‐1582), Multiguard Protect (furfural), MustGrow Invest (Brassica juncea), and Avid (abamectin) significantly reduced the nematode population density compared with a monitoring‐based IPM program and the standard soil fumigant nematicide Curfew. In the untreated control, nematode population densities were significantly higher than in the other treatments. Celebration and PI 291590 bermudagrass genotypes had better percent green cover throughout the study.

Performance of Zoysia spp. and Axonopus compressus Turf on Turf-Paver Complex under Simulated Traffic

Vehicular traffic on turf results in loss of green cover due to direct tearing of shoots and indirect long-term soil compaction. Protection of turfgrass crowns from wear could increase the ability of turf to recover from heavy traffic. Plastic turfpavers have been installed in trafficked areas to reduce soil compaction and to protect turfgrass crowns from wear. The objectives of this study were to evaluate traffic performance of turfgrasses (Zoysia matrella and Axonopus compressus) and soil mixture (high, medium and low sand mix) combinations on turf-paver complex. The traffic performance of turf and recovery was evaluated based on percent green cover determined by digital image analysis and spectral reflectance responses by NDVI-meter. Bulk density cores indicated significant increase in soil compaction from medium and low sand mixtures compared to high sand mixture. Higher reduction of percent green cover was observed from A. compressus (30-40%) than Z. matrella (10-20%) across soil mixtures. Both turf species displayed higher wear tolerance when established on higher sand (>50% sand) than low sand mixture. Positive turf recovery was also supported by complementary spectral responses. Establishment of Zoysia matrella turf on turfpaver complex using high sand mixture will result in improved wear tolerance.

Influence of Nitrogen Source and Application Timing on Large Patch of Zoysiagrass

Large patch of zoysiagrass (Zoysia spp.), caused by Rhizoctonia solani AG2‐2 LP, is a troublesome disease on golf course fairways in the upper transition zone of the United States. Turfgrass managers incur significant fungicide costs to control the disease over large acreages, and integrating cultural practices into an overall scheme of disease management may result in reduced inputs. Our objective was to assess the impact of applying different nitrogen sources at defined soil temperature thresholds during the fall and spring infection periods on large patch severity in field experiments conducted in Kansas and Missouri. From 2013 to 2015, ammonium sulfate [(NH4)2SO4], calcium nitrate [Ca(NO3)2], and urea were applied at 0.75 lb nitrogen (N)/1000 ft2 when 5‐day 2‐inch soil temperatures reached 60 or 70°F in the spring or declined to 70°F in the fall. Summer applications of urea at 0.5 lb N/1000 ft2 were utilized as a standard for comparison, with all treatments receiving a total of 1.5 lb N/1000 ft2 per year. In spring 2014, when large patch severity was greatest, percent green cover was higher in ammonium sulfate treatments compared with urea and the standard summer program in Missouri, and higher in ammonium sulfate–treated plots compared with calcium nitrate– and urea‐treated plots in Kansas. Although the effect was not consistent among sites, spring nitrogen applications made during the large patch infection period did not result in higher large patch severity than the standard summer fertilization schedule.

Performance of Winter Overseeded and Colorant-treated ‘Tifway’ Bermudagrass Receiving Weekly Irrigation and Simulated Traffic

Municipal water restrictions across the southern and southwestern United States have created additional challenges for maintaining safe playing surfaces on recreational turf facilities. In recent years, many cities within these regions have begun to impose irrigation restrictions during winter months. Although winter overseeding has been regularly practiced in these areas, interest and use of colorants as an alternative to overseeding has grown due to decreasing water availability and budget concerns. Data on relative performance of colorant-treated vs. overseeded dormant turf would be of interest to turf managers, because colorants may be more cost-effective and require less water than winter overseeding. The objectives of this 2-year field study were to evaluate effects of winter treatments on performance (green cover, surface hardness, and soil moisture attributes), turfgrass injury resulting from simulated traffic, and spring transition of ‘Tifway’ bermudagrass (Cynodon dactylon L. × Cynodon transvaalensis Burtt-Davy) under a 1-day per week irrigation schedule. Treatments included 1) untreated bermudagrass, 2) fall colorant-treated bermudagrass, 3) perennial ryegrass (Lolium perenne L.) overseeded bermudagrass, and 4) turf-type annual ryegrass (Lolium multiflorum Lam.) overseeded bermudagrass. In both years, treatment differences were detected for percent green cover, soil volumetric water content (VWC), percent visual turfgrass injury, surface hardness, and percent bermudagrass transition. Percent green cover and visual turfgrass injury levels were similar between annual and perennial ryegrass in year 1, whereas loss of green cover and greater turfgrass injury were noted in annual ryegrass during the spring of year 2. Residual benefits of fall colorant applications extended into February of year 1, but dissipated by late December of year 2, likely due to higher rainfall and warmer temperatures, which prevented full bermudagrass shoot dormancy. Overseeding reduced bermudagrass spring transition by up to 50% compared with untreated and colorant-treated plots. Fall colorant treatments did not accelerate bermudagrass transition compared with untreated plots. Results of the study demonstrate that environmental differences from season to season can impact the relative benefits derived from colorant applications, as well as the performance of annual and perennial ryegrass.

Plant Health Characteristics of Creeping Bentgrass Affected by Strobilurin Fungicide Applications and Turfgrass Diseases

Previous research has indicated that strobilurin fungicide applications may mitigate the effects of summer heat stress on creeping bentgrass (Agrostis stolonifera L.). Two multi‐year experiments were conducted in 2011 and 2012 to evaluate plant health characteristics following strobilurin fungicide applications to creeping bentgrass putting greens. In Exp. 1, pyraclostrobin, azoxystrobin, fluoxastrobin, or trifloxystrobin were integrated within a conventional summer fungicide program. In Exp. 2, repeated applications of strobilurin fungicides were evaluated in absence of visible foliar disease. To limit foliar disease, overspray applications of chlorothalonil (2,4,5,6‐tetrachloroisophthalonitrile) and iprodione [3‐(3,5‐dichlorophenyl)‐N‐isopropyl‐2,4‐dioxoimidazolidine‐1‐carboxamide] were applied over the experimental units. The plant health characteristics evaluated were visual quality, spectral reflectance, percent green cover, and root morphology. Disease incidence and severity was also quantified visually. In Exp. 1, the nontreated control was similar to strobilurin fungicide programs in all parameters in 2011. In 2012, strobilurin fungicide programs exhibited improved normalized difference vegetation index (NDVI), ratio vegetation index (RVI), turfgrass quality, and percent green cover compared to the nontreated control. Disease severity also increased in 2012 compared to 2011. In Exp. 2, repeated applications of strobilurin fungicides did not affect measured parameters compared to the nontreated control when foliar diseases were managed with fungicides chlorothalonil and iprodione. In these experiments, differences in NDVI, RVI, turfgrass quality, and percent green cover often coincided with differences in disease severity in our evaluations. Under the conditions of these studies, applications of strobilurin fungicides have limited effects on NDVI, RVI, turfgrass quality, and percent green cover in the absence of visible disease.

Studies on Well-Being of Urban Residents from the Perspective of Green Growth-Based on Empirical Analysis on Residents in Chengdu City of Western China

In this paper, we make empirical analysis on the well-being of urban residents and its influencing factors from the perspective of green growth by using the survey data from the studying team which made the Urban Green Growth and Public Well-Being Investigation on 19 jurisdictional counties (districts and cities) of Chengdu City in August, 2015. The results suggest that residents’ well-being has obvious regional differences, and the main city zone has the lowest green well-being while the third city cycle-layer has the highest green well-being. From the view of internal influencing factors of the resident well-being, the results show that age and income are positively correlated with the residents’ green well-being, and the former correlation is significant, while residents’ well-being of Chengdu is negatively correlated with the educational level. From the view of external influencing factors, green cover percentage, air quality and water quality are positively correlated with the residents’ green well-being, while waste treatment and amount of factory have no significant correlations with residents’ green well-being.

Optimal color space selection method for plant/soil segmentation in agriculture

Color analysis techniques in agriculture should be able to deal with non-trivial capture conditions such as shadows, noise, pixel saturation, low lighting, different varieties of crops and intrinsic parameters of the cameras. Previous studies have shown the importance of selecting the optimum color space for each application domain. This paper presents a new probabilistic approach to color processing capable not only to create optimum color models for the plant/soil segmentation, but also to select the most adequate color space for each problem. The system evaluates all the possible alternatives, producing color models in the optimum space and channels. Thereby, the dependences on the kind of crop, camera and capture conditions are avoided, since the method is adapted to the training conditions. The basis of the proposal is the use of non-parametric models for the probability density functions of plant/soil colors. The proposed method has been implemented and validated in a new software tool, called ACPS (Automatic Classification of Plants and Soil), thus proving its practical feasibility. The final purpose of this system is the analysis of the vegetal ground cover, in order to obtain the PGC (percentage of green cover) parameter. The ACPS software has been developed to be used by professionals, researchers, technicians and anyone working in the agricultural area. Furthermore, the models created can be exported to a defined file format which can be used in applications in the cloud, mobile devices and compact controllers that are currently being developed.

気象観測点における土地被覆状況と地域微気候の関係

In recent years, global warming and the urban heat island phenomenon have become a serious problem not only in urban cities but also in local cities in Japan. One of the main causes is the change in land cover especially the loss of natural cover such as green spaces and water bodies and increase of artificial land cover such as buildings and asphalt coverage. In this study, we aimed to extract the degree of influence of the heat island phenomenon on the air temperature by analyzing the change in land cover and climate over the past 30 years across Japan. The study investigated the factors that influenced change in temperature at 288 weather observation points. Climate classification and geographical features analysis of all the stations was conducted. The results showed that the pacific side to the north from central Japan experienced a severe rise in temperature. Furthermore, the results showed that there was a moderate increase in temperature at points close to high altitude or latitude areas. In addition, we confirmed restraint in temperature at points close to the sea which were influenced by the effect of the water body. Investigation of the relationship between land cover and climate change showed that in the past 15 years there were many weather stations where there was decrease in natural land cover such as green spaces and an increase in artificial land cover. Moreover, in comparison to points with higher percentage of green cover, points with a higher percentage of artificial land cover showed a more rapid increase in air temperature. degree at which urban heat island phenomenon affects temperature was extracted from the yearly change in land cover of the selected regions. The results showed that in the period between 1985 to 2000, the average temperature gradient was 0.008°C per year. 14.3% of the temperature rise within the period was caused but the urban heat island phenomenon. In the period between 2000 to 2014, the average temperature gradient was 0.002°C per year. 22.2% of the temperature rise within the period was caused by the increase in urban heat phenomenon. Furthermore, as a secondary result, we found that after a certain percentage of green land cover is exceeded, the effect of restriction of temperature increase reaches its absolute peak. In order to understand the degree at which certain factors influence the air temperature increase, land cover condition, geographical features and wind patterns were stipulated as influencing factors. We quantified these factors and analyzed them using Hayashi's Quantification Method I. The analysis showed that latitude and land cover change had the greatest influence on the air temperature. From the above, this study extracted the degree at which the urban heat island phenomenon influences the temperature increase. In addition, we confirmed the influence of land cover change on the microclimate in an area. However, we could not analyze all the weather stations across Japan due to lack of satellite images in some points. Therefore, inclusion and analysis of these points and detailed investigation of the directional temperature around the weather stations are some of the points for further improvement in this study.

Root Zone Construction Affects Hybrid Bermudagrass (C. Dactylon x C. Transvaalensis) Responses to Simulated Traffic

Few studies have directly compared the types of root zones used for athletic fields. A two-year field study was conducted from 2012-2013 at the University of Tennessee Center for Athletic Field Safety (Knoxville, TN) to compare the performance of four root zones: a silt loam root zone, a sand-based root zone constructed to United States Golf Association (USGA) specifications, a sand-based root zone constructed to ASTM International (ASTM) specifications, and a sand-cap root zone (CAP) consisting of silt loam capped with 15cm of sand that conformed to USGA particle size specifications. Hybrid bermudagrass (C. dactylon x C. transvaalensis, cv. ‘Tifway’) was established over all root zones. In addition to the bermudagrass treatments, two different synthetic turf surfaces varying in fiber type and infill ratio were included for comparison. All treatments were subjected to 30 simulated traffic events each autumn at rates of 0, 3 or 10 simulated traffic events per week in a split-plot design. Differences were only detected in percent green cover only for traffic rate in 2012. In 2013, bermudagrass on silt loam was reduced to 50% cover after ∼10 simulated traffic events, compared to ∼18 simulated traffic events on USGA and ASTM sand-based root zones. Surface hardness varied between treatments and years of the study; however, at no time did any surface exceed surface hardness thresholds associated with head injury (200 Gmax). Despite the loss of hybrid bermudagrass cover from the repeated simulated traffic events, few differences in surface hardness were detected between synthetic turf and hybrid bermudagrass plots in this study, regardless of root zone.