Using ESAP software for predicting the spatial distributions of NDVI and transpiration of cotton

Observations of the normalized difference vegetation index (NDVI) from aerial imagery can be used to infer the spatial variability of basal crop coefficients (Kcb), which in turn provide a means to estimate variable crop water use within irrigated fields. However, monitoring spatial Kcb at sufficient temporal resolution using only aerial acquisitions would likely not be cost-effective for growers. In this study, we evaluated a model-based sampling approach, ESAP (EC_e Sampling, Assessment, and Prediction), aimed at reducing the number of seasonal aerial images needed for reliable Kcb monitoring. Aerial imagery of NDVI was acquired over an experimental cotton field having two treatments of irrigation scheduling, three plant density levels, and two N levels. During both 2002 and 2003, ESAP software used input imagery of NDVI on three separate dates to select three ground sampling designs having 6, 12, and 20 sampling locations. On three subsequent dates during both the years, NDVI data obtained at the design locations were then used to predict the spatial distribution of NDVI for the entire field. Regression of predicted versus imagery observed NDVI resulted in r² values from 0.48 to 0.75 over the six dates, where higher r² values occurred for predictions made near full cotton cover than those made at partial cover. Prediction results for NDVI were generally similar for all three sample designs. Cumulative transpiration (Tr) for periods from 14 to 28 days was calculated for treatment plots using Kcb values estimated from NDVI. Estimated cumulative Tr using either observed NDVI from imagery or predicted NDVI from ESAP procedures compared favorably with measured cumulative Tr determined from soil water balance measurements for each treatment plot. Except during late season cotton senescence, errors in estimated cumulative Tr were between 3.0% and 7.3% using observed NDVI, whereas they were they were between 3.4% and 8.8% using ESAP-predicted NDVI with the 12 sample design. Thus, employing a few seasonal aerial acquisitions made in conjunction with NDVI measurements at 20 or less ground locations optimally determined using ESAP, could provide a cost-effective method for reliably estimating the spatial distribution of crop water use, thereby improving cotton irrigation scheduling and management.     

A spatial reasoning approach to estimating paddy rice water demand in Hwanghaenam-do,North Korea

The primary objective of this study was to estimate the agricultural water demand of paddy fields in Hwanghaenam-do, North Korea. Three Landsat TM images, GIS data including digital elevation maps, a Thiessen network and administration maps of North Korea, and meteorological data were synthesized for this study. In order to estimate water demand for agricultural use, the FAO Blaney–Criddle method and 10-day crop coefficients of the northern areas of South Korea were used. To classify the Landsat images, supervised and unsupervised classification methods were conducted. Topographical constraints based on paddy rice growing conditions, which are under 7% slope and 200 m above sea level, were taken into account. The results showed an annual net water demand of 611.7 mm/year (916.4 Mt/year) is required for the 150,079 ha of paddy fields and the average gross water demand and design water demand for paddy rice were estimated to be 939.6 mm/year (1408 Mt/year) and 1131.97 mm/year (1695.1 Mt/year), respectively.     

Potential, spatial distribution and economic performance of regional biomass chains: The North of the Netherlands as example

This work assesses the viability of regional biomass chains by comparing the economic performance of potential bioenergy crops with the performance of current agricultural land uses. The biomass chains assessed are ethanol production from Miscanthus and from sugar beet in the North of the Netherlands. The competitiveness of bioenergy crops is assessed by comparing the Net Present Value (NPV) of perennial crops, current rotations, and rotation schemes which include additional years of sugar beet. The current land use and soil suitability for present and bioenergy crops are mapped using a geographical information system (GIS) and the spatial distribution of economic profitability is used to indicate where land use change is most likely to occur. Bioethanol production costs are then compared with petrol costs. The productions costs comprise costs associated with cultivation, harvest, transport and conversion to ethanol. The NPVs and cost of feedstock production are calculated for seven soil suitability classes. The results show that bioenergy crops are not competitive with current cropping systems on soils classed as “suitable”. On less suitable soils, the return on intensively managed crops is low and perennial crops achieve better NPVs than common rotations. Our results showed that minimum feedstock production costs are 5.4 €/GJ for Miscanthus and 9.7 €/GJ for sugar beet depending on soil suitability. Ethanol from Miscanthus (24 €/GJ) is a better option than ethanol from sugar beet (27 €/GJ) in terms of costs. The cost of bioethanol production from domestically cultivated crops is not competitive with petrol (12.34 €/GJ) production under current circumstances. We propose that the method demonstrated in this study, provides a generic approach for identifying viable locations for bioenergy crop production based on soil properties and current land use.     

Development and credibility assessment of a metamodel relating water table depth to agricultural production

Phreatic groundwater pumping is affecting water availability for crops in areas with a shallow water table. This can reduce crop growth and so affect farm income. There is a need for a generic and transparent method to assess the agricultural damage caused by water table drawdown. This paper proposes such a method that consists of ‘damage tables’ relating agricultural production losses to the groundwater regime for different soil/crop combinations found in Northern Belgium. The damage tables are constructed based on numerous simulations with the agrohydrological model SWAP, in which the bottom boundary conditions are gradually changed to reflect different groundwater regimes. The credibility of the resulting metamodel is assessed in three ways: using (1) field data, (2) an existing local expert system for land suitability assessment and (3) literature applying to a wider region. Field data of actual transpiration for two grasslands do not systematically deviate from the model predictions. This provides some credibility to the claim that the model captures the processes determining evapotranspiration and agricultural production. The local expert system allows us to evaluate the range of groundwater regimes where optimal growth is expected for maize and grassland across different soil types. Diverging predictions of the optimal groundwater regime between the metamodel and the local expert system can be explained in terms of differences in assumptions underlying both models. One notable limitation of the damage tables is that only direct physiological stress is reckoned while indirect effects of wet conditions (decreased accessibility of the terrain, soil structural damage) may also limit growth on soils with a water table near the surface. Further comparison with literature data focused on two issues: the contribution of groundwater to evapotranspiration and the extinction depth, i.e., the depth at which groundwater no longer contributes to evapotranspiration. This comparison revealed that damage tables developed for our area of interest are only valid under similar climatic conditions for the following two reasons: they assume a relatively small groundwater contribution to evapotranspiration, which is typical for humid climates, and they take into account temporal variations in plant characteristics such as root depth, which is also climate dependent.     

地面多角度农业遥感观测装置设计与试验

针对现有多角度对地观测设备存在机动性差、操作周期长、无法搭载较重仪器等问题,设计了一种面向作物信息快速获取的地面多角度农业遥感观测装置(GAMOD)及信息采集控制系统,利用该装置同步搭载高清相机和可见-近红外成像光谱仪(VNIHS)进行大田观测,耗时10 min(所需时间由观测角度决定)可快速获取太阳主平面(0°、180°)和垂直太阳主平面(90°、270°)下4个观测天顶角(0°、20°、40°、60°)的大豆植被影像数据.结果表明:该装置及控制软件运行良好,在多角度观测方式支持下,能有效捕捉到大豆植被三维立体的结构信息.     

Limits to agricultural growth in the Sistan Closed Inland Delta,Iran

The Sistan Delta in Iran is located at the end of a closed basin with nearly 100% of the supply coming from Afghanistan. This supply is supporting irrigated agriculture in the area and is the source for the lake system around the delta. These Hamoun lakes are ecological very valuable wetlands; a number of them are registered as Ramsar sites. The Iranian government tries to improve the living conditions of the people in the area, among others by providing infrastructure for irrigated agriculture. Further development of the irrigated area will mean less water for the Hamouns with resulting lower average water coverage of the lakes. This will not only endanger the ecosystem that the Hamouns support but also the livelihoods of the people that depend on the goods and services that the lakes provide. This paper describes a study that has been carried out to support decision making on potential development schemes in the delta. The non-availability of data from Afghanistan requires the development of various tools and the use of remote sensing techniques to enable to make estimates for the river flow that Iran can expect from Afghanistan. An IWRM approach has been used for the balancing of interests involved. Some preliminary conclusions are described.     

基于RS数据和GIS方法的冬小麦水分生产函数估算

以冬小麦遥感监测耗水与产量为数据支持,开展了多种水分生产函数模型的对比研究,探求与研究区相适宜的水分生产函数模型及其参数,其中全生育期水分生产函数模型分别选择直线模型、抛物线模型、D-K模型及指数模型;而分生育阶段水分生产函数模型分别选择Jensen、Minhas、Blank、Stewart及Singh模型。研究结果表明,冬小麦全生育水分生产函数模型推荐采用抛物线模型;而分生育阶段水分生产函数模型推荐采用Stewart模型;冬小麦对水分最敏感的阶段是抽穗期,其次为扬花-成熟期,而出苗-拔节期最小。为此,在北京市大兴区的冬小麦灌溉应优先满足抽穗灌浆期的需水,而在出苗-拔节期适度减少灌溉量,可达到节水增效目的。     

基于遥感的农业用水效率评价方法研究进展

遥感技术的发展为区域尺度蒸散发计算、作物分布识别及估产提供了一条有效途径,为基于遥感信息的灌区灌溉水利用效率及作物水分利用效率定量评价奠定了基础。回顾总结了遥感蒸散发模型、瞬时蒸散发升尺度方法、日蒸散发插值方法、作物分布识别方法及作物估产模型的研究进展,评述了遥感蒸散发及作物估产结果在灌区灌溉水利用效率及作物水分利用效率评价中的应用情况。提出了相关领域需要进一步研究的问题,包括适合非均匀下垫面特点且具有较强物理基础的灌区遥感蒸散发模型、日蒸散发插值中灌溉或降雨引起土壤含水量突变情况的处理、农田蒸散发中灌溉水有效消耗量的准确估算、能适应复杂种植结构并且适用于多年的作物分布遥感识别模型以及精度较高且可操作性强的遥感估产模型等。     

Mapping agricultural responses to water supply shocks in large irrigation systems, southern India

Irrigated agriculture experienced a water supply shock during a drought in southern India in 2002-2003. In this paper, hotspots of agricultural change were mapped and put in the context of hydrology and water management. Time series of MODIS imagery taken every eight days before (2001-2002) and during (2002-2003) the supply shock were combined with agricultural census data to document changes in cropping patterns in four large irrigation projects in the downstream sections of the Krishna and Godavari River basins (total command area 18,287 km²). The area cropped in rice in the four irrigated command areas decreased by 32% during the drought year, and rice production in the two districts that experienced the largest flow reductions fell below production levels of 1980. The irrigation project that showed the largest change in double cropped area (−90%) was upstream of the Krishna Delta. In the Krishna Delta, large areas changed from rice-rice to rice-gram double cropping. Historical water management contributed to the vulnerability of rice production to drought: the main reservoir in the system was drained to dead storage levels by the end of each growing season over 1968-2000, with little carryover storage. The land cover change maps suggested that the lower Krishna Basin has experienced a “hard landing” during basin closure, and revised management strategies that account for the new flow regime will be required to maintain agricultural production during droughts.     

An approach for precision farming under pivot irrigation system using remote sensing and GIS techniques

The current work is aimed to realizing land and water use efficiency and determining the profitability of precision farming economically and environmentally. The studied area is represented by an experimental pivot irrigation field cultivated with maize in Ismailia province, Egypt. Two field practices were carried out during the successive summer growing seasons (2008 and 2009) to study the response of maize plants single hybrid 10 (S.H.10) to traditional and precision farming practices. Traditional farming (TF) as handled by the farm workers were observed and noted carefully. On the other hand precision farming (PF) practices included field scouting, grid soil sampling, variable rate technology and its applications. After applying PF a dramatic change in management zones was noticed and three management zones (of total four) were merged to be more homogenous representing 84.3% of the pivot irrigation field.Under PF Remote Sensing and Geographic Information System techniques have played a vital role in the variable rate applications that were defined due to management zones requirements. Fertilizers were added in variable rates, so that rationalization of fertilizers saved 23.566 tonnes/experimental pivot area. Natural drainage system was improved by designing vertical holes to break down massive soil layers and to leach excessive salts. Crop water requirements were determined in variable rate according to the actual plant requirements using SEBAL model with the aid of FAO Cropwat model. Irrigation schedule of maize was adopted considering soil water retention, depletion, gross and net irrigation saving an amount of water equal to 93,718 m³ in the pivot irrigation field (153.79 acre). However costs of applying PF were much higher than TF, the economic profitability (returns-costs) achieved remarkable increase of 29.89% as a result of crop yield increment by 1000, 2100, 800 and 200 kg/acre in the management zones 1, 2, 3 and 4, respectively. Finally applying adequate amounts of fertilizers beside water control the environmental hazards was reduced to the acceptable limits.     

农业遥感研究与应用进展

农业是遥感技术应用最重要和广泛的领域之一,本文回顾了遥感技术在国内外农业研究与应用中的进展,概括和总结了农田辐射传输机理及作物参量遥感反演、作物遥感分类与识别、农田养分遥感与变量施肥决策、作物产量与品质预测、农情遥感监测与预报、农业遥感监测空间决策支持系统6个主要研究与应用方面。在此基础上,针对农业遥感技术面临的问题与发展趋势,指出了农业遥感技术今后的重点发展方向。     

Spectral vegetation indices for benchmarking water productivity of irrigated cotton and sugarbeet crops

Irrigation performance and water productivity can be benchmarked if estimates of spatially distributed yield and crop water use are available. A commonly used method to estimate crop evapotranspiration in irrigated areas is to multiply reference evapotranspiration values by appropriate crop coefficients. This study evaluated convenient ways to derive such coefficients using multispectral vegetation indices obtained by remote sensing. Detailed ground radiometric measurements were taken in small plots perpendicular to the crop rows to obtain canopy reflectance values. Ancillary measurements of green ground cover, plant height, leaf area index and biomass were taken in the cropped strip covered by the radiometer field-of-view. The results were up-scaled using 10 Landsat-5 and 1 Landsat-7 images. Crop measurements and ground radiometry were made at the time of Landsat overpass on two commercial fields, one grown with sugarbeet and the other with cotton. Crop height and ground cover were determined weekly in these two fields, three additional sugarbeet fields and one additional cotton field. The ground and satellite observations of canopy reflectance yielded similar results. Two vegetation indices, the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI) were evaluated. Both indices described the crop growth well, but SAVI was used in further evaluations because it could be conveniently related to both ground cover and the basal crop coefficient using a simple model. Based on these findings, crop water use variability was analyzed in a large sample of sugarbeet and cotton fields, within a homogeneous irrigation scheme in Southern Spain. The yield versus evapotranspiration data points were highly scattered for both cotton and sugarbeet. The yield values obtained from the sugarbeet fields and cotton fields were substantially lower than values predicted by a linear yield function, and close to a curvilinear yield function, respectively. Evapotranspired water productivity varied in the cotton fields from 0.3 to 0.78 kg m⁻³, and in the sugarbeet fields from 7.15 to 14.8 kg m⁻³.     

基于MODIS数据的冬小麦种植面积快速提取与长势监测

利用MODIS-NDVI数据,以中国冬小麦主产区为例,探讨了基于遥感影像全覆盖的大尺度冬小麦种植面积遥感综合自动识别及长势监测的方法。通过分析冬小麦的种植结构、物候历特征及其生物学特性和时序NDVI曲线特征,确定了冬小麦信息提取的NDVI阈值,建立了冬小麦面积提取模型,并最终获取了2010—2011年中国农情遥感监测中冬小麦长势监测所需的空间分布数据,与多年平均统计数据比较,总体精度达到81%以上。基于提取的冬小麦面积信息空间分布数据,利用MODIS-NDVI差值模型,对冬小麦2011年的长势进行监测。结果表明,与近5年平均状况对比,2011年冬小麦在其整个生育期内长势基本与常年持平,但时空分布差异较大。     

Assessment of vine development according to available water resources by using remote sensing in La Mancha, Spain

The relevance of growing vines under semiarid conditions is universally accepted because of its impacts on social, economic and environmental aspects. Improving the knowledge of the soil–plant–atmosphere system related to the expression of vine growth allows the study of vine cover in wide areas. Several aspects of vine growing under semiarid conditions, related to weather, soil, and plant cover are analysed in this paper. Once the ground truth is achieved, multitemporal studies by remote sensing are especially useful for vine growth monitoring. The purpose of this work is focussed on determining changes of vine cover development according to available water resources in relation to present remote sensing methods. The method is based on using multitemporal masking classification techniques based on the ground truth knowledge achieved during previous research.     

Ground-based remote sensing for assessing water and nitrogen status of broccoli

Remote sensing (RS) can facilitate the management of water and nutrients in irrigated cropping systems. Our objective for this study was to evaluate the ability of several RS indices to discriminate between limited water and limited nitrogen induced stress for broccoli. The Agricultural Irrigation Imaging System (AgIIS) was used over a 1-ha broccoli field in central Arizona to measure green (550 nm), red (670 nm), far red (720 nm), and near infrared (NIR-790 nm) reflectances, and thermal infrared radiation. Measurements were taken at a 1 m × 1 m resolution, every several days during the season. The following indices were calculated: ratio vegetation index (RVI), normalized difference vegetation index (NDVI), normalized difference based on NIR and green reflectance (NDNG), canopy chlorophyll concentration index (CCCI), and the water deficit index (WDI). The experimental design was a two-factor, nitrogen × water, Latin square with four treatments (optimal and low water and optimal and low nitrogen) and four replicates. In addition to RS measurements, the following in-situ measurements were taken: SPAD chlorophyll (closely related to nitrogen status), plant petiole nitrate-nitrogen concentrations, soil water content, and plant height, width, and leaf area index (LAI). Fresh marketable broccoli yield was harvested from plots 130 days after planting.Seasonal water application (irrigation plus rainfall) was 14% greater for optimal than low water treatments, whereas total nitrogen application was 35% greater for optimal than low N treatments. Although both nitrogen and water treatments affected broccoli growth and yield, nitrogen effects were much more pronounced. Compared to the optimal water and nitrogen treatment, broccoli yield was 20% lower for low water but optimal nitrogen, whereas yield was 42% lower for optimal water but low nitrogen. The RVI, NDVI, and NDNG indices detected treatment induced growth retardation but were unable to distinguish between the water and nitrogen effects. The CCCI, which was developed as an index to infer differences in nitrogen status, was found to be highly sensitive to nitrogen, but insensitive to water stress. The WDI provided appropriate information on treatment water status regardless of canopy cover conditions and effectively detected differences in water status following several irrigation events when water was withheld from low but not optimal water treatments. Using a RS ground-based monitoring system to simultaneously measure vegetation, nitrogen, and water stress indices at high spatial and temporal resolution could provide a successful management tool for differentiating between the effects of nitrogen and water stress in broccoli.     

Remote sensing of biotic and abiotic stress for irrigation management of cotton

The applicability of commercially available remote sensing instrumentation was evaluated for site-specific management of abiotic and biotic stress on cotton (Gossypium hirsutum L.) grown under a center pivot low energy precision application (LEPA) irrigation system. This study was conducted in a field where three irrigation regimes (100%, 75%, and 50% ET_c) were imposed on areas of Phymatotrichum (root rot) with the specific objectives to (1) examine commercial remote sensing instrumentation for locating areas showing biotic and abiotic stress symptomology in a cotton field, (2) compare data obtained from commercial aerial infrared photography to that collected by infrared transducers (IRTs) mounted on a center pivot, (3) evaluate canopy temperature changes between irrigation regimes and their relationship to lint yield with IRTs and/or IR photography, and (4) explore the use of deficit irrigation and the use of crop coefficients for irrigation scheduling. Pivot-mounted IRTs and an IR camera were able to differentiate water stress among irrigation regimes. The IR camera distinguished between biotic (root rot) and abiotic (drought) stress with the assistance of groundtruthing. The 50% ET_c regime had significantly higher canopy temperatures than the other two regimes, which was reflected in significantly lower lint yields when compared to the 75% and 100% ET_c regimes. Deficit irrigation down to 75% ET_c had no impact on lint yield, indicating that water savings were possible without reducing yield.     

GIS tools applied to the sustainable management of water resources: Application to the aquifer system 08-29

The sustainable exploitation of water resources requires planning and control methods that allow the incorporation of a great number of spatial and temporal variables. Because of its features, a Geographic Information System (GIS) seems the most suitable tool to aid in the management of available hydric resources. In this study, we have developed a specific GIS within the GESMO Project in order to better manage the 08-29 aquifer system (Mancha Oriental). This tool is intended for use by the JCRMO: Junta Central de Regantes de la Mancha Oriental (General Board of Irrigation Users of Eastern La Mancha), the organism responsible for aquifer management.This system is designed to integrate information from different sources, such as remote sensing, fieldwork data or administrative files with the cadastral subplot as a common reference. One of its functions is to expedite the control and monitoring, in real time, of the exploitation plans, which constitute the legal instrument to regulate water extractions. It will allow us to estimate the spatial and temporal distribution of water extractions needed for crops and their irrigation systems. These estimates will be highly valuable for aquifer modelling. The system also permits display of information on maps for easy handling. This visualisation allow users to more readily participate in decision-making processes.     

Individual-based models in the analysis of disease transmission in plant production chains: An application to potato brown rot

Spread of plant disease in production chains of planting material is a process of great economic importance, but has received little attention from plant disease epidemiologists. Disease control in production chains is therefore often based on rules of thumb and expert judgement by regulatory bodies, rather than on an explicit analysis and evaluation of the epidemiological and economic consequences of alternative strategies. This paper puts forward the idea that individual-based models may be used as a framework to simulate the spread of disease-causing organisms in plant production chains. The “individuals” in this context are the trading units (e.g., batches, lots) of a production chain. The quarantine disease “potato brown rot”, caused by the bacterium Ralstonia solanacearum, is used as an illustrative example. The model simulates the spread of potato brown rot over all potato growing farms and fields in the Netherlands over a chosen time frame. It addresses the relevant infection pathways for this disease in potato production and is spatially explicit.

Model outputs of simulations based on the control strategy as applied in the Netherlands until 2004 are presented. The effects of minor adjustments to this strategy are investigated. The simulations show an irregular pattern of brown rot dynamics in the potato production chain, as is observed in practice. Simulations quantify the relative importance of different infection pathways, and elucidate the effect of testing frequency on these pathways and on the over-all brown rot incidence. The study shows that individual-based modelling (IBM) provides a powerful platform for modelling the epidemiology and impact of diseases in plant production chains. IBM can be effectively used for the analysis, evaluation and design of cost-effective disease management policies.     

Quantitative evaluation of soil salinity and its spatial distribution using electromagnetic induction method

In the Lower Yellow River Delta, soil salinity is a problem due to the presence of a shallow, saline water table and marine sediments. Spatial information on soil salinity at the field level is increasingly needed, particularly for better soil management and crop allocation in this area. In this paper, a mobile electromagnetic induction (EMI) system including EM38 and EM31 is employed to perform field electromagnetic (EM) survey, and fast determination and quantitative evaluation of the spatial pattern of soil salinity is discussed using the field EM survey data. Optimal operation modes of EM38 and EM31 are determined to establish multiple linear regression models for estimating salinity from apparent soil electrical conductivity (EC_a). Spatial trend and semivariogram are illustrated and spatial distribution of field salinity status is further visualized and quantitatified. The results suggest that EC_a (EM38 and EM31) data is highly correlated with salinity, and that the interpretation precision of soil salinity at various layers can be improved using EM_38h and EM_31h (where h represents the horizontal mode of EM measurement). Both EM_38h and EM_31h exhibit significant geographic trend. Nested spherical models fit the semivariance of EM_38h and EM_31h better than single spherical models. Spatial autocorrelation of EM_31h is stronger than that of EM_38h, and short-range variation is the chief constitute of spatial heterogeneity for both EM_38h and EM_31h. Quantitative classification shows that soil salinity exhibits the trend of accumulation in the root zone. In 0-1.0 m solum, heavy salinized and saline soils are the predominant soil types, accounting for 54% and 41% of total survey area, respectively. The area of light and moderate salinized soils is comparatively small, which accounts for only 0.4% and 4.6%, respectively.     

农作土壤深耕深松机械化技术

耕地是农业生产的一项重要措施,目的在于为作物的播种发芽、生长发育提供良好的土壤环境.利用机械深耕深松,可以使耕层疏松绵软、结构良好、活土层厚、平整肥沃,使固相、液相、气相比例相互协调,适应作用生长发育的要求.大力提倡和推广深耕深松机械化地技术,对广大农业区特别是以人畜力和小型拖拉机为主要耕作动力的农业区,具有十分重要的现实意义.