Mapping water status based on aerial thermal imagery: comparison of methodologies for upscaling from a single leaf to commercial fields

Aerial thermal remote sensing can provide a means for collecting spatial plant water status data. Many studies have shown their potential in irrigation management but the adaptation of this technology is not straight forward. In this paper, knowledge accumulated in recent years on thermal imagery analysis methodology for water status mapping is summarized aiming at indicating alternatives to calculate the Crop Water Stress Index (CWSI) for commercial scale water status mapping. Based on literature overview, four forms of wet-baselines to calculate CWSI were selected, namely: artificial wet reference surface, two theoretical calculations and a statistical bio-indicator. These baselines were used to calculate CWSI based on multi-temporal aerial thermal images of cotton fields. CWSI based on a statistical bio-indicator and one of the theoretical wet-baselines provided the best correlations. It is argued though that the statistical one is preferable since it includes the plant characteristics and it is farmer-friendly. Based on bio-indicators, leaf water potential maps of three commercial fields were produced on several dates through the season. Water status spatial patterns were not static and the effect of static factors like sandy soil patches also changed through the season. The maps show the importance of in-season variability mapping for rational irrigation management. To improve current variable-rate irrigation, the concept of in-season irrigation management zones (IMZ) based on thermal-images should be considered and integrated with the delineation of static irrigation IMZ.     

Crop water stress index derived from multi-year ground and aerial thermal images as an indicator of potato water status

Potato yield and quality are highly dependent on an adequate supply of water. In this study, 3 years of information from thermal and RGB images were collected to evaluate water status in potato fields. Irrigation experiments were conducted in commercial potato fields (Desiree; drippers). Two water-deficit scenarios were tested: a short-term water deficit (by suppressing irrigation for a number of days before image acquisition), and a long-term cumulative water deficit. Ground and aerial images were acquired in various phenological stages along the potato growing season. Effects of irrigation treatments were recorded by thermal indices and biophysical measurements of stomatal conductance (SC), leaf water potential, leaf osmotic potential and gravimetric water potential in soil. Canopy temperature was delineated from the thermal images with and without fused information from the RGB image. Crop water stress index (CWSI) was calculated, using three forms of minimum baseline temperature: empirical, theoretical and statistical. An empirical evaluation of maximum baseline temperature of Tair + 7 °C was used in all CWSI forms examined. Statistical tests and comparison of CWSI with biophysical measurements were performed to evaluate the responses to irrigation treatments. The results indicated a high correlation of CWSI with SC from tuber initiation to maturity based on ground and aerial data (0.64 ≤ R² ≤ 0.99). Similar trends of increasing CWSI from well to deficit-irrigated treatments were found in all three growing seasons. The results also showed that CWSI may be calculated based merely on thermal imagery data.     

Mapping crop water stress index in a ‘Pinot-noir’ vineyard: comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle

Characterizing the spatial variability in water status across vineyards is a prerequisite for precision irrigation. The crop water stress index (CWSI) indicator was used to map the spatial variability in water deficits across an 11-ha ‘Pinot noir’ vineyard. CWSI was determined based on canopy temperatures measured with infrared temperature sensors placed on top of well-watered and water-stressed grapevines in 2009 and 2010. CWSI was correlated with leaf water potential (Ψ_L) (R ² = 0.83). This correlation was also tested with results from high resolution airborne thermal imagery. An unmanned aerial vehicle equipped with a thermal camera was flown over the vineyard at 07:30, 09:30, and 12:30 h (solar time) on 31 July 2009. At about the same time, Ψ_L was measured in 184 grapevines. The image obtained at 07:30 was not useful because it was not possible to separate soil from canopy temperatures. Using the airborne data, the correlation between CWSI and Ψ_L had an R ² value of 0.46 at 09:30 h and of 0.71 at 12:30 h, suggesting that the latter was the more favorable time for obtaining thermal images that were linked with Ψ_L values. A sensitivity analysis of varying pixel size showed that a 0.3 m pixel was needed for precise CWSI mapping. The CWSI maps thus obtained by airborne thermal imagery were effective in assessing the spatial variability of water stress across the vineyard.     

基于红外热图像的棉花花铃期水分胁迫指数与光合参数的关系

[目的]分析棉花冠层水分胁迫指数(CWSI)与光合参数的相关关系,建立CWSI与光合参数的相关模型,为CWS1用于定量监测新疆棉花冠层水分胁迫状况的研究提供依据.[方法]在棉花生长的花铃期,利用Fluke热像仪获取2个棉花品种4水平水分处理冠层的红外热图像,运用图像处理技术,提取棉花冠层受光叶片的温度,并将湿人工参考表面(WARS)的温度运用到Jones定义的作物水分胁迫指数(CWSI)的经验公式中,计算CWSI;同时,采用LI-6400便携式光合仪测得棉花叶片净光合速率(Pn)、气孔导度(Gs)和蒸腾速率(Tr),并探索棉花水分胁迫指数与其光合参数的定量关系.[结果]水分胁迫下CWSI值升高,而Pn、Gs和Tr值相应降低.花铃期的4个关键生育时期CWSI分别与Pn、Gs和Tr呈极显著的线性负相关关系,CWSI与Pn、Gs和Tr的平均相关系数分别为rCWSI-Pn=-0.8823**、rCWSI-GS=-0.9073**和rCWSI-Tr,=-0.9356**.[结论]棉花水分胁迫指数CWSI与光合参数Pn、Gs和Tr同步反映棉花冠层的水分状况.     

基于作物水分生产函数和胁迫指数的棉花产量估算模式

将作物水分胁迫指数(CWSI)与作物水分生产函数相结合,得到了用CWSI表示的作物水分生产 函数,进而推导出基于作物水分生产函数和CWSI的作物产量估算模式。该估算模式利用了易于获取的红外遥感 数据,克服了水分生产函数中作物蒸发蒸腾量准确资料难于获取的限制,并且通过CWSI和作物水分生产函数的 耦合使该估产方法具有一定的物理意义。经大田膜下滴灌棉花实测资料检验表明,该模型计算值的相对误差基本 保持在10％左右。     

Spatial patterns of wilting in sugar beet as an indicator for precision irrigation

Precision irrigation requires the mapping of within-field variations of water requirement. Conventional remote sensing techniques provide estimates of water status at only shallow soil depths. The ability of a water sensitive crop, sugar beet, to act as an intermediate sensor providing an integrated measure of water status throughout its rooting depth is tested here. Archive aerial photographs and satellite imagery of Eastern England show crop patterns resulting from past periglacial processes. The patterns were found to be spatially and temporally consistent. Field sampling of soil cores to 1 m depth established that the within-field wilting zones were significantly associated with coarser or shallow soils. The stress classes, determined by classification of the digitised images, were weakly correlated with total available water (Pearson correlation r = 0.588, P < 0.05). These results suggest that wilting in sugar beet can be used as an intermediate sensor for quantifying potential soil water availability within the root zone. Within-field stress maps generated in 1 year could be applied as a strategic tool allowing precision irrigation to be applied to high-value crops in following years, helping to make more sustainable use of water resources.     

基于冠层温度的夏玉米旱情指数理论模型和经验模型的比较

对水分胁迫指数(CWSI)的经验模型和理论模型在华北平原夏玉米中的应用进行了对比,分析了2种模型与土壤含水量以及叶水势之间的关系,对比了2种模型得到的CWSI的日际变化.结果表明,经验模型经常性地溢出0～1的范围,理论模型则很少出现溢出0～1的范围,经验模型的日际变化较理论模型大,理论模型1 d中得到的CWSI变化很小;2种CWSI模型与土壤含水量均显著相关,可用于指导作物灌溉时间;CWSI理论模型与夏玉米叶水势的相关性较好,更能反映作物本身的水分状况.     

Foliage temperature extraction from thermal imagery for crop water stress determination

Crop water stress determination methods from canopy temperatures, derived from the surface energy balance equations, treat the canopy temperature under the assumption that the canopy behaves as a virtual “big-leaf”, covering the ground surface. Introduction of very high-resolution thermal imagery, 0.01–0.3-m pixel size, acquired from low altitude platforms, enabled finely detailed observation of the whole canopy, raising the question how to select the relevant canopy temperatures. One approach is to select the sunlit leaves confirming to the “big leaf” energy balance paradigm. However, thermal imagery alone is incomplete and needs additional marking or synchronized visible imagery for interpretation, which makes the process complicated and expensive. The other approach, used in reference surface based water stress evaluation, is to use full frame pixel statistics without pattern recognition by selecting the mean temperature of the cold fraction from the pixel histogram. That greatly simplifies processing for large-scale aerial thermography. Here are presented the results of experiments conducted in cotton and vine grapes, where both approaches were evaluated simultaneously. Ground referenced thermal and visible images were overlapped, and sunlit, shaded and whole canopy leaves were selected for crop temperature evaluation. The pixel histograms of the same images were analyzed in a two-step method, after discarding soil pixels where their temperature was 7 °C higher than air temperature at step one, and calculation of the mean temperatures of the lowest 33 and 100 % of the remaining pixels for step two. Several crop water stress indices were compared with leaf and stem water potentials and stomatal conductance. Good agreement was found between both image segmentation and histogram analysis methods, demonstrating the suitability of both methods in canopy temperature evaluation for crop water stress evaluation.     

Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard

This paper deals with the assessment of heterogeneity in water status in a commercial orchard, as a prerequisite for precision irrigation management. Remote sensing-derived indicators could be suitable for mapping water stress over large areas, and recent studies have demonstrated that high resolution airborne thermal imagery enables the assessment of discontinuous canopies as pure tree crowns can be targeted, thus eliminating the background effects. Airborne campaigns were conducted over a drip-irrigated commercial orchard in Southwestern Spain composed of five different orchard tree crops. An unmanned aerial vehicle with a thermal camera onboard was flown three times during the day on 8 July 2010, at 9, 11 and 13 h (local time). Stem water potential was measured at the same time of the flights. In some irrigation units, irrigation was stopped prior to the measurement date to induce water deficits for comparative purposes. Several approaches for using the thermal data were proposed. Daily evolution of the differential between canopy and air temperature (T _c  ? T _a ) was compared to tree water status. The slope of the evolution of T _c  ? T _a with time was well correlated with water status and is proposed as a novel indicator linked with the stomatal behavior. The Crop Water Stress Index (CWSI) was calculated with the temperature data from the 13.00 h flight using an empirical approach for defining the upper and lower limits of T _c  ? T _a . The assessment of variability in water status was also performed using differences in relative canopy temperatures. Ample variability was detected among and within irrigation units, demonstrating that the approach proposed was viable for precision irrigation management. The assessment led to the identification of water-stressed areas, and to the definition of threshold CWSI values and associated risks. Such thresholds may be used by growers for irrigation management based on crop developmental stages and economic considerations.     

Predicting Cotton Lint Yield Maps from Aerial Photographs

It is generally accepted that aerial images of growing crops provide spatial and temporal information about crop growth conditions and may even be indicative of crop yield. The focus of this study was to develop a straightforward technique for creating predictive cotton yield maps from aerial images. A total of ten fields in southern Georgia, USA, were studied during three growing seasons. Conventional (true color) aerial photographs of the fields were acquired during the growing season in two to four week intervals. The aerial photos were then digitized and analyzed using an unsupervised classification function of image analysis software. During harvest, conventional yield maps were created for each of the fields using a cotton picker mounted yield monitor. Classified images and yield maps were compared quantitatively and qualitatively. A pixel by pixel comparison of the classified images and yield maps showed that spatial agreement between the two gradually increased in the weeks after planting, maintained spatial agreement of between 40% and 60% during weeks eight to fourteen, and then gradually declined again. The highest spatial agreement between a classified image and a yield map was 78%. The highest average agreement was 52% and occurred 9.9 weeks after planting. The visual similarity between the classified images and the yield maps were striking. In all cases, the dates with the best visual agreement occurred between eight and ten weeks after planting, and generally, during July for southern Georgia. This method offers great potential for offering cotton farmers early-season maps that predict the spatial distribution of yield. Although these maps can not provide magnitudes, they clearly show the resulting yield patterns. With inherent knowledge of past performance, farmers can use this information to allocate resources, address crop growth problems, and, perhaps, improve the profitability of their farm operation. These maps are well suited to be offered to farmers as a service by a crop consultant or a cooperative.     

干旱区不同地下水埋深膜下滴灌灌溉制度模拟研究

通过在新疆巴州灌溉试验站进行的膜下滴灌棉花灌溉制度试验,得出了适合当地的常规滴灌制度。为进一步研究浅层地下水对灌溉的补偿效应,利用Hydrus软件对不同地下水埋深下膜下滴灌棉花生育期耗水量进行了模拟。通过引入关键点土壤含水率的概念,提出了膜下滴灌棉花受水分胁迫的标准。结果表明：地下水对棉花的耗水具有一定的补偿作用,地下水埋深越浅,则所需的灌溉定额越小。当地下水埋深小于1.5 m时,滴灌定额为3 300 m³·hm^-2;当地下水埋深为2.0 m时,滴灌定额为4 500 m³·hm^-2;当地下水埋深很大而对作物根区没有补给时,棉花完全依赖于灌溉所需的滴灌定额则为5 550 m³·hm^-2。考虑到干旱区内具有较高的潜在蒸发势,会导致土壤的次生盐渍化,从而危及作物的生长,1.5～3.0 m的地下水埋深是灌区内较理想的水位区间。     

滴灌条件下灌溉量和频率对杂交棉生长和产量的影响

[目的]研究滴灌条件下不同灌溉量和灌溉频率对杂交棉生长和产量的影响.[方法]试验设置2个灌溉水平400和520 mm(分别用W400和W520表示)和2种灌溉频率5和10 d(分别用F5和F10表示).[结果]高灌溉频率可以维持0～40 cm土壤含水量稳定在较高水平,有利于作物生长.灌水量和灌溉频率对杂交棉干物质积累的影响主要是在花铃期(播种后90 d),此时增加灌溉量或灌溉频率都可以促进杂交棉干物质积累,尤其是提高灌溉频率可明显促进棉花生长.[结论]增加灌溉量和灌溉频率可促进棉花干物质积累量,增加棉花产量;尤其是提高灌溉频率可以显著增加棉花干物质积累量、产量和水分利用率.不同处理棉花产量和水分利用率的顺序均为:W520F5 > W400F5、W520F10 > W400F10.在水资源缺乏的地区或时期,通过提高灌溉频率可以有效的增加棉花产量、提高水分利用率.     

A cost-effective canopy temperature measurement system for precision agriculture: a case study on sugar beet

Increasing agricultural efficiency in a sustainable manner will contribute to feed a growing population under limited land, nutrient and water resources. Water scarcity and the increasing social concern for this resource are already requiring more sophisticated irrigation and decision-support systems. To address the heterogeneity in crop water status in a commercial field, precision irrigation requires accurate information about crops (e.g., crop water status), soil (e.g., moisture content) and weather (e.g., wind speed and vapor pressure deficit). Numerous studies have shown that plant canopy temperature can be used to derive reliable plant water stress indicators, thus making it a promising tool for irrigation water management. However, efficient and cost-effective measurement techniques are still lacking. This paper assesses the potential of infrared thermometry and thermal imaging for monitoring plant water stress in a commercial sugar beet field by comparing canopy temperature data acquired from a conventional thermal camera with an inexpensive infrared sensor, both mounted on a rotary-wing unmanned aerial vehicle (UAV). Measurements were taken at various phenological stages of the sugar beet growing season. Laboratory tests were performed to determine the key features for accurate temperature measurements and flight altitude. Experiments were conducted in 2014 and 2015 in experimental and commercial sugar beet fields in Southwestern Spain to (i) develop an affordable infrared temperature system suitable for mounting on a UAV to obtain thermal information, (ii) compare sugar beet canopy temperature measurements collected with the low-cost platform with those obtained from a conventional thermal camera, both mounted on a rotary-wing UAV, (iii) identify the factors that will limit the use of the low-cost system to derive temperature-based water stress indices. To accomplish these objectives, well-watered and deficit irrigated plots were established. Results indicated that the lightweight canopy temperature system was robust and reliable, although there were some constraints related to weather conditions and delimitation of the area covered by the infrared sensor.     

滴灌模式下不同灌量对长绒棉生长发育及产量的影响

[目的]研究滴灌长绒棉实现高产的灌溉用水量,为制定滴灌长绒棉配套栽培技术及水资源的合理利用提供理论依据.[方法]在长绒棉主产地阿瓦提县的中高肥力滴灌棉田,选用新海24号,在生育期设置6个不同灌量处理,研究不同滴灌量对长绒棉生长发育及产量的影响.[结果](1)低灌量处理的土壤耕层硝态氮含量高于高灌量处理,后期尤为明显;(2)头水后,随滴灌量的增加,长绒棉生育进程相对后延;相同时期长绒棉单株叶面积指数(LAI)与滴灌量呈正相关,7月21日为最大值,随后开始下降,下降速率随滴灌量的增加而减缓;(3)各处理单株干物质积累呈Logistic生长曲线,经济产量快速积累期的积累速率(△V)及出现的时间(T)差异较大;(4)W4处理(灌量为240 m3/667 m2)的单株成铃数及籽棉产量最高.[结论]方程Y=-762.571 4 +8.828 6 X-0.0171 43X2(R2=0.958 2**)为滴灌量与籽棉产量关系式.计算得出:当滴灌量X=257.5 m3/667 m2,长绒棉籽棉产量有最大值374.1 kg/667 m2.高于或低于此值都会造成产量下降,不同灌量对长绒棉籽棉产量的影响主要是通过影响单株成铃数实现的,而对内在遗传品质决定的单铃重及衣分基本无影响.     

Use of aerial thermal imaging to estimate water status of palm trees

A methodology to estimate water status of palm trees from aerial thermal images was developed. Deficit irrigation of 80% in three drip-irrigated date-palm plots in the northern Dead Sea region was manipulated during the winter of 2007 and 2008. An uncooled thermal camera was used for extensive aerial imaging to detect palm trees and pure-canopy pixels by using only aerial thermal images. An automatic procedure, based on watershed segmentation analysis, was developed which enabled detection of all palm trees in the thermal images. Two new methods were developed to select palm trees and pure pixels within them: basin-based and pixel-based. From the temperatures of pure-canopy pixels, significant differences were found between palm trees under commercial and deficit irrigation regimes, in all three plots. Automated detection of canopy, based on aerial thermal images, is a key step towards commercial mapping of within-plot water-status variability. A protocol, based on the developed methodology, was suggested for mapping water status variability in a palm plot, and for irrigation scheduling.     

膜下滴灌棉田杂草群落组成及特点的初步研究——以阿瓦提县为例

[目的]摸清滴灌模式下棉田杂草群落种类、数量,为南疆早中熟塔哈次棉花亚区滴灌棉田杂草的科学防治提供理论依据.[方法]以阿瓦提县具有多年膜下滴灌种植条件的乡(场)为重点,调查研究杂草群落种类及数量,并与该县不同植棉模式下棉田杂草群落进行比较.[结果]不同植棉模式下杂草种类均较多,滴灌棉田杂草主要有9科15种,以禾本科、菊科、藜科对棉花生长影响较大.[结论]通过与露地直播、常规灌棉田杂草比较,膜下滴灌棉田杂草根的干重明显较低,一年生浅根杂草及阔叶杂草呈增多趋势.杂草在棉花生育期有两个危害高峰,且危害高峰提前并持续时间较长.     

基于无人机多光谱影像的棉叶螨识别方法

【目的】利用无人机遥感在空间分辨率和光谱分辨率上的优势,研究大面积棉田棉叶螨监测方法,为类似的农作物虫害遥感监测研究提供参考。【方法】选20种光谱指数作为螨害监测的特征因子,使用赤池信息准则作为模型优选依据,获取最佳建模特征,建立棉田螨害监测识别的logistic回归模型。【结果】在所分析的全部光谱指数中,TVI、DVI和RDVI为螨害监测的最佳特征因子,基于该3个因子构建的logistic回归模型的分类准确率为95%,F1值为95.1%,能够较好地实现棉田螨害识别。【结论】监测模型可以实现区域范围的棉叶螨快速识别。     

Soil water status mapping and two variable-rate irrigation scenarios

Irrigation is the major user of allocated global freshwaters, and scarcity of freshwater threatens to limit global food supply and ecosystem function—hence the need for decision tools to optimize use of irrigation water. This research shows that variable alluvial soil ideally requires variable placement of water to make the best use of irrigation water during crop growth. Further savings can be made by withholding irrigation during certain growth stages. The spatial variation of soil water supplied to (1) pasture and (2) a maize crop was modelled and mapped by relating high resolution apparent electrical conductivity maps to soil available water holding capacity (AWC) at two contrasting field sites. One field site, a 156-ha pastoral farm, has soil with wide ranging AWCs (116–230 mm m⁻¹); the second field site, a 53-ha maize field, has soil with similar AWCs (161–164 mm m⁻¹). The derived AWC maps were adjusted on a daily basis using a soil water balance prediction model. In addition, real-time hourly logging of soil moisture in the maize field showed a zone where poorly drained soil remained wetter than predicted. Variable-rate irrigation (VRI) scenarios are presented and compared with uniform-rate irrigation scenarios for 3 years of climate data at these two sites. The results show that implementation of VRI would enable significant potential mean annual water saving (21.8% at Site 1; 26.3% at Site 2). Daily soil water status mapping could be used to control a variable rate irrigator.     

盐分条件下棉花相关生理特性的变化及水分胁迫指数模型的构建

【目的】构建盐土棉田棉花水分胁迫指数模型,以确定适宜的棉花水分运筹方式,为提高盐碱地棉花产量和品质提供理论依据。【方法】试验于2008—2009年在江苏南京（118°50′ E,32°02′ N）南京农业大学牌楼试验站进行,以耐盐品种中棉所44和盐敏感性品种苏棉12号为材料,将碳酸钠、重碳酸钠、氯化钠、氯化钙、氯化镁、硫酸镁、硫酸钠7种盐类等摩尔混合,按盐土比掺入基础土壤中,形成5种不同含盐水平的土壤（0：1.25 dS•m-1;0.35%：5.80 dS•m-1;0.60%：9.61 dS•m-1;0.85%：13.23 dS•m-1;1.00%：14.65 dS•m-1）,研究土壤盐分对棉花功能叶含水量和温度的影响,明确棉花叶气温差与空气饱和气压差的定量关系。【结果】随土壤盐分水平的升高,棉花功能叶的蒸腾速率、含水量和净光合速率均下降,叶片温度升高。以1.25 dS•m-1盐分处理作为充分灌水（即无水分胁迫）建立了棉花水分胁迫指数模型下基线方程,以此构建了不同土壤盐分下棉花水分胁迫指数模型。【结论】综合分析不同土壤盐分水平下棉花水分胁迫指数与叶片含水量和净光合速率的关系,认为棉花水分胁迫指数模型可以很好地反映盐分条件下棉花的受胁迫程度。用棉花CWSI实时监测盐分条件下棉花的水分胁迫状况,可为盐碱地确定适宜的棉花水分运筹提供理论依据。