Google Maps API在林业局级林下作物栽培中的应用

林下经济以其能够充分利用林下土地资源及大面积林荫的优势而得到众多农林专家和林农的青睐,其在实现农林资源共享、优势互补和循环生态方面发挥着很大的作用。结合林下经济发展现状及广大林农的需求特点,综合运用当前先进的Google Maps API技术和A-JAX技术,以JSON作为客户端与服务器的数据传送格式,构建基于B/S的林业局级林下作物栽培咨询平台。该平台提供给用户直观化的信息查询与呈现效果,不仅有效提高农户种植的科学性,也可在一定程度上帮助管理层制定决策。     

Satellite-Based Energy Balance to Assess Within-Population Variance of Crop Coefficient Curves

Quantifying evapotranspiration (ET) from agricultural fields is important for field water management, water resources planning, and water regulation. Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (Kc) determined according to the crop type and the crop growth stage. Recent development of satellite remote sensing ET models has enabled us to estimate ET and Kc for large populations of fields. This study evaluated the distribution of Kc over space and time for a large number of individual fields by crop type using ET maps created by a satellite based energy balance (EB) model. Variation of Kc curves was found to be substantially larger than that for the normalized difference vegetation index because of the impacts of random wetting events on Kc, especially during initial and development growth stages. Two traditional Kc curves that are widely used in Idaho for crop management and water rights regulation were compared against the satellite-derived Kc curves. Simple adjustment of the traditional Kc curves by shifting dates for emergence, effective full cover, and termination enabled the traditional curves to better fit Kc curves as determined by the EB model. Applicability of the presented techniques in humid regions having higher chances of cloudy dates was discussed.     

Assessing Reference Evapotranspiration by the Hargreaves Method in Southern Spain

The Hargreaves method enables reference crop evapotranspiration (ET0) estimation in areas where meteorological information is scarce, as, for example, southern Spain. However, this method is known to produce considerable bias in this region, especially during the dry, hot summer months. An evaluation of the method is made by comparing daily estimates with those made by the more commonly recommended Penman–Monteith method at 16 meteorological stations. Computed ET0 values at the coastal stations are, on average, 0.69 mm?d?1 smaller than the Penman–Monteith estimates whereas at inland stations a small average overestimation of 0.13 mm?d?1 is shown. The adjusted Hargreaves coefficient (AHC), obtained through regression analysis, increases at the coastal stations, on average, to 0.0029, and decreases at the inland stations to 0.0022. Adjustment with the Samani method does generally not produce more accurate estimates in this region. Finally a linear relationship between the AHC and the rate of the average temperature to the average daily temperature range is proposed for the regional adjustment of the Hargreaves coefficient.     

Performance-Based Optimization of Land and Water Resources within Irrigation Schemes. II: Application

The area and water allocation model which uses simulation–optimization technique for optimum allocation of land and water resources to different crops cultivated in different allocation units of the irrigation scheme was modified to include both productivity and equity in the process of developing the allocation plans for optimum productivity and/or maximum equity. This paper illustrates the potential of this approach with the help of a case study on Nazare medium irrigation scheme in India. The allocation plans were developed for optimization of different performance parameters (productivity and equity) for different management strategies based on irrigation amount and irrigation interval and cropping distribution strategies of free and fixed cropping. The results indicated that the two performance objectives productivity and equity conflict with each other and in this case, equitable water distribution may be preferred over free water distribution at the cost of a small loss in productivity. Though these results relate to one case study, they show the value of the approach of incorporating productivity and equity in the allocation process with the help of the simulation-optimization model described in the companion paper.     

Development of GIS-Based Model to Estimate Relative Reductions in Crop Yield due to Salinity and Waterlogging

A model is introduced that utilizes geographic information systems (GIS) to predict relative reductions in crop yield due to salinity and waterlogging at a field-scale by incorporating spatially and temporally variable crop, climatic, and irrigation data to simulate crop yields. This model utilizes soil and water data commonly collected in field-scale studies. The model’s algorithms are integrated into a GIS (ARCVIEW 3.2) as an extension. The result is a model that does not require extraordinary data collection but will provide practical insight into the spatial effects of salinity and waterlogging on crop yields.     

Analysis of time-series MODIS 250 m vegetation index data for crop classification in the U.S. Central Great Plains

The global environmental change research community requires improved and up-to-date land use/land cover (LULC) datasets at regional to global scales to support a variety of science and policy applications. Considerable strides have been made to improve large-area LULC datasets, but little emphasis has been placed on thematically detailed crop mapping, despite the considerable influence of management activities in the cropland sector on various environmental processes and the economy. Time-series MODIS 250 m Vegetation Index (VI) datasets hold considerable promise for large-area crop mapping in an agriculturally intensive region such as the U.S. Central Great Plains, given their global coverage, intermediate spatial resolution, high temporal resolution (16-day composite period), and cost-free status. However, the specific spectral-temporal information contained in these data has yet to be thoroughly explored and their applicability for large-area crop-related LULC classification is relatively unknown. The objective of this research was to investigate the general applicability of the time-series MODIS 250 m Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) datasets for crop-related LULC classification in this region. A combination of graphical and statistical analyses were performed on a 12-month time-series of MODIS EVI and NDVI data from more than 2000 cropped field sites across the U.S. state of Kansas. Both MODIS VI datasets were found to have sufficient spatial, spectral, and temporal resolutions to detect unique multi-temporal signatures for each of the region's major crop types (alfalfa, corn, sorghum, soybeans, and winter wheat) and management practices (double crop, fallow, and irrigation). Each crop's multi-temporal VI signature was consistent with its general phenological characteristics and most crop classes were spectrally separable at some point during the growing season. Regional intra-class VI signature variations were found for some crops across Kansas that reflected the state's climate and planting time differences. The multi-temporal EVI and NDVI data tracked similar seasonal responses for all crops and were highly correlated across the growing season. However, differences between EVI and NDVI responses were most pronounced during the senescence phase of the growing season.     

Hydrology and Nitrogen Components of a Simple Rye Growth Model

Cover cropping practices are being researched to reduce artificial subsurface drainage nitrate-nitrogen (nitrate-N) losses from agricultural lands in the upper Mississippi watershed. A soil-plant-atmosphere simulation model, RyeGro, was developed to quantify the influence of a winter cereal rye cover crop on nitrate-N losses given climatic variability in the region. This paper describes the hydrology and nitrogen cycle submodels of RyeGro, which was developed with a low level of complexity and conceptualizes the soil profile as three soil layers. The model was calibrated with data from a three-year rye cover crop field study conducted at Lamberton, Minnesota, and validated with data from a previous study. During model calibration, field subsurface drainage nitrate-N loadings were predicted within 0.2, 0, and 1.6?kg?N?ha?1 (1, 0, and ?3%) of measured loadings for the corn-soybean treatment and within 1.2, 0, and 1.6?kg?N?ha?1 (11, 0, and 3%) of measured loadings for the corn-rye-soybean treatment. The model validation showed nitrate-N loading differences of 7 and 1?kg?N?ha?1 (?22 and 4%) for the two years tested.     

The PhytO3 Tech Crop Protection Technology – Trial Results in a 2,700 ha (6,500 acre) Soy Farm in Brazil

Extended field trial testing of the PhytO3 technology (applying sequentially and rapidly electrolyzed water, ozone in water, and UV-C radiation to control insects and replace chemical sprays) was conducted in Brazil on growing soy bean crops during December 2006 to March 2007. Despite the very poor growing conditions because of excessive rainfalls, the test crops all reached harvest and provided significant economic benefits to the farmer. Details of the testing program are described. In addition to eliminating the need for pesticides and insecticides, crops treated by the PhytO3 technology qualify as organic-grown crops, and therefore command about double prices on world markets.     

Estimating Evaporation from Bare Soil and the Crop Coefficient for the Initial Period Using Common Soils Information

The crop coefficient during the initial period (Kc?ini) varies with wetting frequency, evaporative demand, and water-holding capacity of the upper soil layer. It is possible to develop a semitheoretical integrated function to predict the average Kc?ini representing the initial period of a growing season when the soil is mostly bare and that incorporates these three factors. The function is based on a two-stage evaporation function as used in the Food and Agriculture Organization Irrigation and Drainage Paper No. 56 (FAO-56) dual crop coefficient method. Parameters in the integrated equation are soil based and can be calculated a priori without field measurements. The procedure can be used to produce graphical figures similar to that introduced in FAO-24 for Kc?ini. Similar to FAO-24, the function utilizes the mean time between wetting events and reference evapotranspiration. In this paper, the development of the procedure and figures for Kc?ini are described. Comparisons with measured evaporation and Kc?ini in southern California indicate relatively good performance by the function without calibration.     

Exploration of the land potential for the production of biomass for energy in the Netherlands

The energy potential for energy crops and biomass residues in the Netherlands is assessed. The analysis explores the possible use of land for biomass production in the future. Various government memorandums and analyses of the expected future land use in various sectors have served as the basis for the assessment of the supply of and the demand for land in the future. In this study the potential supply of agricultural land is based on expected productivity increments in agriculture and assumptions with respect to the future demand for agricultural products. Various future claims for infrastructure, forestry, urban areas and nature are subtracted from the expected supply. The net projected supply of land ranges from zero to 52 000 ha in 2000 to 110 000-250 000 ha in 2015. The supply of agricultural land depends however on a number of supra-national factors, such as the European agricultural policy, world market developments and the agricultural production in the countries in Eastern Europe. Uncertainties remain, therefore, and the projected supply of agricultural land should be considered as a possible scenario based on current trends. If the calculated land potential is used for energy crops like miscanthus and short rotation coppice, this land could contribute 0-10 PJ in 2000 and 27-59 PJ in 2015. Secondary biomass yields, such as those from forestry, agricultural residues, wood from prunings, etc., could contribute a further 34 PJ in 2000, decreasing to approximately 28 PJ in 2015. Taken together these potentials could satisfy 1-1.5% of the energy requirements of the Netherlands in 2000 and 1.5-2.5% in 2015, provided that energy farming is an economically feasible activity for farmers.