Mapping Very-High-Resolution Evapotranspiration from Unmanned Aerial Vehicle (UAV) Imagery

There is a growing concern about water scarcity and the associated decline in Australia’s agricultural production. Efficient water use as a natural resource requires more precise and adequate monitoring of crop water use and irrigation scheduling. Therefore, accurate estimations of evapotranspiration (ET) at proper spatial–temporal scales are critical to understand the crop water demand and uptake and to enable optimal irrigation scheduling. Remote sensing (RS)-based ET estimation has been adopted as a method for large-scale applications when the detailed spatial representation of ET is required. This research aimed to estimate instantaneous ET using very-high-resolution (VHR) multispectral and thermal imagery (GSD < 8 cm) collected using a single flight of a UAV over a high-density peach orchard with a discontinuous canopy. The energy balance component estimation was based on the high-resolution mapping of evapotranspiration (HRMET) model. A tree-by-tree ET map was produced using the canopy surface temperature and the leaf area index (LAI) resampled at the corresponding scale via a systematic feature segmentation method based on pure canopy extraction. Results showed a strong linear relationship between the estimated ET and the leaf transpiration (n = 42) measured using a gas exchange sensor, with a coefficient of determination (R2) of 0.89. Daily ET (5.5 mm d−1) derived from the instantaneous ET map was comparable with daily crop ET (6.4 mm d−1) determined by the meteorological approach over the study site. The proposed approach has important implications for mapping tree-by-tree ET over horticultural fields using VHR imagery.

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Response of four grain legumes to water stress in south-eastern Queensland. IV. Interaction with sowing arrangement

Australian Journal of Agricultural Research ◽

10.1071/ar9830661 ◽

1983 ◽

Vol 34 (6) ◽

pp. 661 ◽

Cited By ~ 2

Author(s):

RJ Lawn

Keyword(s):

Water Stress ◽

Population Density ◽

Water Use ◽

Spatial Arrangement ◽

Crop Growth ◽

Yield Response ◽

Crop Water ◽

Area Index ◽

Crop Water Use ◽

South Eastern

The effect of spatial arrangement and population density on growth, dry matter production, yield and water use of black gram (Vigna mungo cv. Regur), green gram (V. radiata cv. Berken), cowpea (V. unguiculata CPI 28215) and soybean (Glycine rnax CP126671), under irrigated, rain-fed fallowed and rain-fed double-cropped culture was evaluated at Dalby in south-eastern Queensland. Equidistant spacings increased initial rates of leaf area index (LAI) development and crop water use compared with 1-m rows at the same population densities. In the irrigated and rain-fed fallowed treatments, where more water was available for crop growth, both seed yields and total crop water use were higher in the equidistant spacings. However, in the double-cropped treatment, where water availability was limited, there was no yield difference between rows and equidistant spacings, primarily because initially faster growth in the latter was offset by more severe water stress later in the season. Higher population density also increased initial crop growth rate and water use, particularly in the equidistant spacings. However, there was no significant yield response to density, presumably because subsequent competition for light/ water offset initial effects on growth. Although absolute yield differences existed between legume cultivars within cultural treatments, there were no significant differential responses to either spatial arrangement or population density among these four cultivars.

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Irrigation Scheduling Based on Evaporation and Crop Water Requirement for Summer Peanuts1

Peanut Science ◽

10.3146/i0095-3679-11-1-2 ◽

1984 ◽

Vol 11 (1) ◽

pp. 4-6 ◽

Cited By ~ 5

Author(s):

D. K. Pahalwan ◽

R. S. Tripathi

Keyword(s):

Water Use ◽

Irrigation Water ◽

Irrigation Scheduling ◽

Water Requirement ◽

Crop Water Requirement ◽

Pan Evaporation ◽

Crop Water ◽

Formation Stage ◽

Evaporation Ratio ◽

Pod Development

Abstract Field experiment was conducted during dry season of 1981 and 1982 to determine the optimal irrigation schedule for summer peanuts (Arachis hypogaea L.) in relation to evaporative demand and crop water requirement at different growth stages. It was observed that peanut crop requires a higher irrigation frequency schedule during pegging to pod formation stage followed by pod development to maturity and planting to flowering stages. The higher pod yield and water use efficiency was obtained when irrigations were scheduled at an irrigation water to the cumulative pan evaporation ratio of 0.5 during planting to flowering, 0.9 during pegging to pod formation and 0.7 during pod development to maturity stage. The profile water contribution to total crop water use was higher under less frequent irrigation schedules particularly when the irrigations were scheduled at 0.5 irrigation water to the cumulative pan evaporation ratio up to the pod formation stage.

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Optimizing smartphone-based canopy hemispherical photography

10.1101/2021.03.17.435793 ◽

2021 ◽

Author(s):

Gastón Mauro Díaz

Keyword(s):

Large Scale ◽

Forest Canopy ◽

Accuracy Assessment ◽

Low Cost ◽

R Package ◽

Coefficient Of Determination ◽

Native Forest ◽

Hemispherical Photography ◽

Area Index ◽

Plant Area Index

1) Hemispherical photography (HP) is a long-standing tool for forest canopy characterization. Currently, there are low-cost fisheye lenses to convert smartphones into high-portable HP equipment; however, they cannot be used whenever since HP is sensitive to illumination conditions. To obtain sound results outside diffuse light conditions, a deep-learning-based system needs to be developed. A ready-to-use alternative is the multiscale color-based binarization algorithm, but it can provide moderate-quality results only for open forests. To overcome this limitation, I propose coupling it with the model-based local thresholding algorithm. I call this coupling the MBCB approach. 2) Methods presented here are part of the R package CAnopy IMage ANalysis (caiman), which I am developing. The accuracy assessment of the new MBCB approach was done with data from a pine plantation and a broadleaf native forest. 3) The coefficient of determination (R^2) was greater than 0.7, and the root mean square error (RMSE) lower than 20 %, both for plant area index calculation. 4) Results suggest that the new MBCB approach allows the calculation of unbiased canopy metrics from smartphone-based HP acquired in sunlight conditions, even for closed canopies. This facilitates large-scale and opportunistic sampling with hemispherical photography.

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Melt Pond Retrieval Based on the LinearPolar Algorithm Using Landsat Data

Remote Sensing ◽

10.3390/rs13224674 ◽

2021 ◽

Vol 13 (22) ◽

pp. 4674

Author(s):

Yuqing Qin ◽

Jie Su ◽

Mingfeng Wang

Keyword(s):

Remote Sensing ◽

High Resolution ◽

Relative Error ◽

Large Scale ◽

The Arctic ◽

Landsat Data ◽

Melt Pond ◽

Melt Ponds ◽

Very High ◽

Sentinel 2

The formation and distribution of melt ponds have an important influence on the Arctic climate. Therefore, it is necessary to obtain more accurate information on melt ponds on Arctic sea ice by remote sensing. The present large-scale melt pond products, especially the melt pond fraction (MPF), still require verification, and using very high resolution optical satellite remote sensing data is a good way to verify the large-scale retrieval of MPF products. Unlike most MPF algorithms using very high resolution data, the LinearPolar algorithm using Sentinel-2 data considers the albedo of melt ponds unfixed. In this paper, by selecting the best band combination, we applied this algorithm to Landsat 8 (L8) data. Moreover, Sentinel-2 data, as well as support vector machine (SVM) and iterative self-organizing data analysis technique (ISODATA) algorithms, are used as the comparison and verification data. The results show that the recognition accuracy of the LinearPolar algorithm for melt ponds is higher than that of previous algorithms. The overall accuracy and kappa coefficient results achieved by using the LinearPolar algorithm with L8 and Sentinel-2A (S2), the SVM algorithm, and the ISODATA algorithm are 95.38% and 0.88, 94.73% and 0.86, and 92.40%and 0.80, respectively, which are much higher than those of principal component analysis (PCA) and Markus algorithms. The mean MPF (10.0%) obtained from 80 cases from L8 data based on the LinearPolar algorithm is much closer to Sentinel-2 (10.9%) than the Markus (5.0%) and PCA algorithms (4.2%), with a mean MPF difference of only 0.9%, and the correlation coefficients of the two MPFs are as high as 0.95. The overall relative error of the LinearPolar algorithm is 53.5% and 46.4% lower than that of the Markus and PCA algorithms, respectively, and the root mean square error (RMSE) is 30.9% and 27.4% lower than that of the Markus and PCA algorithms, respectively. In the cases without obvious melt ponds, the relative error is reduced more than that of those with obvious melt ponds because the LinearPolar algorithm can identify 100% of dark melt ponds and relatively small melt ponds, and the latter contributes more to the reduction in the relative error of MPF retrieval. With a wider range and longer time series, the MPF from Landsat data are more efficient than those from Sentinel-2 for verifying large-scale MPF products or obtaining long-term monitoring of a fixed area.

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Optimization of irrigation water in South Africa for sustainable and beneficial use

10.51415/10321/2467 ◽

2017 ◽

Author(s):

◽

Akinola Mayowa Ikudayisi

Keyword(s):

South Africa ◽

Water Use ◽

Crop Yield ◽

Optimization Algorithm ◽

Irrigation Water ◽

Irrigation Scheduling ◽

Crop Water ◽

Land Area ◽

Water Requirements ◽

Irrigation Water Use

Water is an essential natural resource for human existence and survival on the earth. South Africa, a water stressed country, allocates a high percentage of its available consumptive water use to irrigation. Therefore, it is necessary that we optimize water use in order to enhance food security. This study presents the development of mathematical models for irrigation scheduling of crops, optimal irrigation water release and crop yields in Vaal Harts irrigation scheme (VIS) of South Africa. For efficient irrigation water management, an accurate estimation of reference evapotranspiration (ETₒ) should be carried out. However, due to non-availability of enough historical data for the study area, mathematical models were developed to estimate ETₒ. A 20-year monthly meteorological data was collected and analysed using two data–driven modeling techniques namely principal component analysis (PCA) and adaptive neuro-fuzzy inference systems (ANFIS). Furthermore, an artificial neural network (ANN) model was developed for real time prediction of future ETₒ for the study area. The real time irrigation scheduling of potatoes was developed using a crop growth simulation model called CROPWAT. It was used to determine the crop water productivity (CWP), which is a determinant of the relationship between water applied and crop yield. Finally, a new and novel evolutionary multi-objective optimization algorithm called combined Pareto multi-objective differential evolution (CPMDE) was applied to optimize irrigation water use and crop yield on the VIS farmland. The net irrigation benefit, land area and irrigation water use of maize, potatoes and groundnut were optimized. Results obtained show that ETₒ increases with temperature and windspeed. Other variables such as rainfall and relative humidity have less significance on the value of ETₒ. Also, ANN models with one hidden layer showed better predictive performance compared with other considered configurations. A 5-day time step irrigation schedule data and graphs showing the crop water requirements and irrigation water requirements was generated. This would enable farmers know when, where, and how much water to apply to a given farmland. Finally, the employed CPMDE optimization algorithm produced a set of non-dominated Pareto optimal solutions. The best solution suggests that maize, groundnut and potatoes should be planted on 403543.44 m2, 181542.00 m2 and 352876.05 m2areas of land respectively. This solution generates a total net benefit of ZAR 767,961.49, total planting area of 937961.49 m2 and irrigation water volume of 391,061.52 m3. Among the three crops optimized, maize has the greatest land area, followed by potatoes and groundnut. This shows that maize is more profitable than potatoes and groundnut with respect to crop yield and water use in the study area.

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High Resolution Satellite Images for Instantaneous Shoreline Extraction Using New Enhancement Algorithms

Geosciences ◽

10.3390/geosciences9030123 ◽

2019 ◽

Vol 9 (3) ◽

pp. 123 ◽

Cited By ~ 5

Author(s):

Donatella Dominici ◽

Sara Zollini ◽

Maria Alicandro ◽

Francesca Della Torre ◽

Paolo Buscema ◽

...

Keyword(s):

High Resolution ◽

Large Scale ◽

Satellite Images ◽

Human Life ◽

Essential Element ◽

Action Planning ◽

High Resolution Satellite Images ◽

High Resolution Images ◽

Territorial Government ◽

Very High

Knowledge of a territory is an essential element in any future planning action and in appropriate territorial and environmental requalification action planning. The current large-scale availability of satellite data, thanks to very high resolution images, provides professional users in the environmental, urban planning, engineering, and territorial government sectors, in general, with large amounts of useful data with which to monitor the territory and cultural heritage. Italy is experiencing environmental emergencies, and coastal erosion is one of the greatest threats, not only to the Italian heritage and economy, but also to human life. The aim of this paper is to find a rapid way of identifying the instantaneous shoreline. This possibility could help government institutions such as regions, civil protection, etc., to analyze large areas of land quickly. The focus is on instantaneous shoreline extraction in Ortona (CH, Italy), without considering tides, using WorldView-2 satellite images (50-cm resolution in panchromatic and 2 m in multispectral). In particular, the main purpose of this paper is to compare commercial software and ACM filters to test their effectiveness.

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WATER USE EFFICIENCY AND WATER DISTRIBUTION RESPONSE TO DIFFERENT PLANTING PATTERNS IN MAIZE–SOYBEAN RELAY STRIP INTERCROPPING SYSTEMS

Experimental Agriculture ◽

10.1017/s0014479716000260 ◽

2016 ◽

Vol 53 (2) ◽

pp. 159-177 ◽

Cited By ~ 9

Author(s):

TANZEELUR RAHMAN ◽

LIN YE ◽

XIN LIU ◽

NASIR IQBAL ◽

JUNBO DU ◽

...

Keyword(s):

Water Use Efficiency ◽

Water Use ◽

Water Distribution ◽

Crop Water ◽

Planting Pattern ◽

Leaf Transpiration ◽

Sole Cropping ◽

Use Efficiency ◽

Narrow Row ◽

Strip Intercropping

SUMMARYUnderstanding crop water use in mixed crops over sole cropping is vital for developing optimum water management systems for crop production. In this study, a two-year field experiment with typical maize (Zea mays L.) and soybean [Glycine max (L.) Merr.] relay strip intercropping (2:2 maize-to-soybean rows; 200 cm bandwidth) was carried out in the 2013 and 2014 growing seasons. The quantitative effects of various planting patterns on the water-use efficiency (WUE) and water distribution were investigated. Our results indicated that soil volumetric water content and soil evaporation in the intercropping systems showed decreasing trends in the order: maize row (MM) < maize-to-soybean row (MS) < soybean row (SS). The highest leaf transpiration (1.91 and 2.07 mmol m−2 s−1) for the intercropped maize was measured in each of the two years in the 20 cm maize narrow-row planting pattern and decreased thereafter. Opposite trend was observed for the intercropped soybean; the highest soybean leaf transpiration (7.01 and 6.80 mmol m−2 s−1 for 2013 and 2014, respectively) was recorded in the 70 cm. The WUE of maize and soybean intercrops was lower than that of sole crop counterparts. However, the maximum group water use efficiency (GWUE) of 26.08 and 26.20 kg ha−1 mm−1 in the 40–50 cm maize narrow-row planting pattern was, respectively, 39.6% and 23% higher compared with that of sole crops. The water equivalent ratio (WER) values ranged from 1.60–1.79, suggesting better crop water use in the intercrops over sole cropping. Planting patterns provided by 40–50 cm maize narrow-row spacing were considered the most efficient in terms of maximum total yields, GWUE and WER. These results suggest that an appropriate reduction in the spacing of narrow maize row with wide soybean row could be an efficient crop management method to achieve optimal WUE and homogeneous water distribution in maize–soybean intercropping systems.

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Context-Enabled Extraction of Large-Scale Urban Functional Zones from Very-High-Resolution Images: A Multiscale Segmentation Approach

Remote Sensing ◽

10.3390/rs11161902 ◽

2019 ◽

Vol 11 (16) ◽

pp. 1902 ◽

Cited By ~ 4

Author(s):

Shouji Du ◽

Shihong Du ◽

Bo Liu ◽

Xiuyuan Zhang

Keyword(s):

High Resolution ◽

Large Scale ◽

Satellite Images ◽

Nearest Neighbor ◽

Context Information ◽

Functional Zone ◽

High Resolution Satellite Images ◽

Segmentation Approach ◽

Functional Zones ◽

Very High

Urban functional-zone (UFZ) analysis has been widely used in many applications, including urban environment evaluation, and urban planning and management. How to extract UFZs’ spatial units which delineates UFZs’ boundaries is fundamental to urban applications, but it is still unresolved. In this study, an automatic, context-enabled multiscale image segmentation method is proposed for extracting spatial units of UFZs from very-high-resolution satellite images. First, a window independent context feature is calculated to measure context information in the form of geographic nearest-neighbor distance from a pixel to different image classes. Second, a scale-adaptive approach is proposed to determine appropriate scales for each UFZ in terms of its context information and generate the initial UFZs. Finally, the graph cuts algorithm is improved to optimize the initial UFZs. Two datasets including WorldView-2 image in Beijing and GaoFen-2 image in Nanchang are used to evaluate the proposed method. The results indicate that the proposed method can generate better results from very-high-resolution satellite images than widely used approaches like image tiles and road blocks in representing UFZs. In addition, the proposed method outperforms existing methods in both segmentation quality and running time. Therefore, the proposed method appears to be promising and practical for segmenting large-scale UFZs.

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Evaluation of Evapotranspiration from Eddy Covariance Using Large Weighing Lysimeters

Agronomy ◽

10.3390/agronomy9020099 ◽

2019 ◽

Vol 9 (2) ◽

pp. 99 ◽

Cited By ~ 8

Author(s):

Jerry Moorhead ◽

Gary Marek ◽

Prasanna Gowda ◽

Xiaomao Lin ◽

Paul Colaizzi ◽

...

Keyword(s):

Energy Balance ◽

Eddy Covariance ◽

Water Use ◽

Growing Season ◽

Irrigation Scheduling ◽

Error Rates ◽

Energy Balance Closure ◽

Crop Water ◽

Crop Water Use ◽

Hourly Data

Evapotranspiration (ET) is an important component in the water budget and used extensively in water resources management such as water planning and irrigation scheduling. In semi-arid regions, irrigation is used to supplement limited and erratic growing season rainfall to meet crop water demand. Although lysimetery is considered the most accurate method for crop water use measurements, high-precision weighing lysimeters are expensive to build and operate. Alternatively, other measurement systems such as eddy covariance (EC) are being used to estimate crop water use. However, due to numerous explicit and implicit assumptions in the EC method, an energy balance closure problem is widely acknowledged. In this study, three EC systems were installed in a field containing a large weighing lysimeter at heights of 2.5, 4.5, and 8.5 m. Sensible heat flux (H) and ET from each EC system were evaluated against the lysimeter. Energy balance closure ranged from 64% to 67% for the three sensor heights. Results showed that all three EC systems underestimated H and consequently overestimated ET; however, the underestimation of H was greater in magnitude than the overestimation of ET. Analysis showed accuracy of ET was greater than energy balance closure with error rates of 20%–30% for half-hourly values. Further analysis of error rates throughout the growing season showed that energy balance closure and ET accuracy were greatest early in the season and larger error was found after plants reached their maximum height. Therefore, large errors associated with increased biomass may indicate unaccounted-for energy stored in the plant canopy as one source of error. Summing the half-hourly data to a daily time-step drastically reduced error in ET to 10%–15%, indicating that EC has potential for use in agricultural water management.

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Large scale flow visualization and anemometry applied to lab-on-a-chip models of porous media

Lab on a Chip ◽

10.1039/c6lc00703a ◽

2016 ◽

Vol 16 (15) ◽

pp. 2851-2859 ◽

Cited By ~ 2

Author(s):

Johan Paiola ◽

Harold Auradou ◽

Hugues Bodiguel

Keyword(s):

Porous Media ◽

High Resolution ◽

Velocity Field ◽

Flow Visualization ◽

Experimental Technique ◽

Large Scale ◽

Lab On A Chip ◽

Large Scale Flow ◽

Very High

The following is a report on an experimental technique that allows one to quantify and map the velocity field with very high resolution and simple equipment in large 2D devices.

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