scholarly journals High Resolution Geospatial Evapotranspiration Mapping of Irrigated Field Crops Using Multispectral and Thermal Infrared Imagery with METRIC Energy Balance Model

Drones ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 52 ◽  
Author(s):  
Abhilash K. Chandel ◽  
Behnaz Molaei ◽  
Lav R. Khot ◽  
R. Troy Peters ◽  
Claudio O. Stöckle
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Thermal Infrared ◽  
Balance Model ◽  
Crop Water ◽  
Field Scale ◽  
Site Specific ◽  
Field Crops ◽  
Landsat 7 ◽  
Thermal Infrared Imagery

Geospatial crop water use mapping is critical for field-scale site-specific irrigation management. Landsat 7/8 satellite imagery with a widely adopted METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) energy balance model (LM approach) estimates accurate evapotranspiration (ET) but limits field-scale spatiotemporal (30 m pixel−1, ~16 days) mapping. A study was therefore conducted to map actual ET of commercially grown irrigated-field crops (spearmint, potato, and alfalfa) at very high-resolution (7 cm pixel−1). Six small unmanned aerial system (UAS)-based multispectral and thermal infrared imagery campaigns were conducted (two for each crop) at the same time as the Landsat 7/8 overpass. Three variants of METRIC model were used to process the UAS imagery; UAS-METRIC-1, -2, and -3 (UASM-1, -2, and -3) and outputs were compared with the standard LM approach. ET root mean square differences (RMSD) between LM-UASM-1, LM-UASM-2, and LM-UASM-3 were in the ranges of 0.2–2.9, 0.5–0.9, and 0.5–2.7 mm day−1, respectively. Internal calibrations and sensible heat fluxes majorly resulted in such differences. UASM-2 had the highest similarity with the LM approach (RMSD: 0.5–0.9, ETdep,abs (daily ET departures): 2–14%, r (Pearson correlation coefficient) = 0.91). Strong ET correlations between UASM and LM approaches (0.7–0.8, 0.7–0.8, and 0.8–0.9 for spearmint, potato, and alfalfa crops) suggest equal suitability of UASM approaches as LM to map ET for a range of similar crops. UASM approaches (Coefficient of variation, CV: 6.7–24.3%) however outperformed the LM approach (CV: 2.1–11.2%) in mapping spatial ET variations due to large number of pixels. On-demand UAS imagery may thus help in deriving high resolution site-specific ET maps, for growers to aid in timely crop water management.

scholarly journals On the Utility of High-Resolution Soil Moisture Data for Better Constraining Thermal-Based Energy Balance over Three Semi-Arid Agricultural Areas

2021 ◽  
Vol 13 (4) ◽  
pp. 727
Author(s):  
Bouchra Ait Hssaine ◽  
Abdelghani Chehbouni ◽  
Salah Er-Raki ◽  
Said Khabba ◽  
Jamal Ezzahar ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Energy Balance ◽  
High Resolution ◽  
Energy Balance Model ◽  
Balance Model ◽  
Wheat Crop ◽  
Field Scale ◽  
Thermal Data ◽  
Agricultural Areas ◽  
Semi Arid

Over semi-arid agricultural areas, the surface energy balance and its components are largely dependent on the soil water availability. In such conditions, the land surface temperature (LST) retrieved from the thermal bands has been commonly used to represent the high spatial variability of the surface evaporative fraction and associated fluxes. In contrast, however, the soil moisture (SM) retrieved from microwave data has rarely been used thus far due to the unavailability of high-resolution (field scale) SM products until recent times. Soil evaporation is controlled by the surface SM. Moreover, the surface SM dynamics is temporally related to root zone SM, which provides information about the water status of plants. The aim of this work was to assess the gain in terms of flux estimates when integrating microwave-derived SM data in a thermal-based energy balance model at the field scale. In this study, SM products were derived from three different methodologies: the first approach inverts SM, labeled hereafter as ‘SMO20’, from the backscattering coefficient and the interferometric coherence derived from Sentinel-1 products in the water cloud model (WCM); the second approach inverts SM from Sentinel-1 and Sentinel-2 data based on machine learning algorithms trained on a synthetic dataset simulated by the WCM noted ‘SME16’; and the third approach disaggregates the soil moisture active and passive SM at 100 m resolution using Landsat optical/thermal data ‘SMO19’. These SM products, combined with the Landsat based vegetation index and LST, are integrated simultaneously within an energy balance model (TSEB-SM) to predict the latent (LE) and sensible (H) heat fluxes over two irrigated and rainfed wheat crop sites located in the Haouz Plain in the center of Morocco. H and LE were measured over each site using an eddy covariance system and their values were used to evaluate the potential of TSEB-SM against the classical two source energy balance (TSEB) model solely based on optical/thermal data. Globally, TSEB systematically overestimates LE (mean bias of 100 W/m2) and underestimates H (mean bias of −110 W/m2), while TSEB-SM significantly reduces those biases, regardless of the SM product used as input. This is linked to the parameterization of the Priestley Taylor coefficient, which is set to αPT = 1.26 by default in TSEB and adjusted across the season in TSEB-SM. The best performance of TSEB-SM was obtained over the irrigated field using the three retrieved SM products with a mean R2 of 0.72 and 0.92, and a mean RMSE of 31 and 36 W/m2 for LE and H, respectively. This opens up perspectives for applying the TSEB-SM model over extended irrigated agricultural areas to better predict the crop water needs at the field scale.

scholarly journals A Semiempirical Microscale Model of the Surface Energy Balance and Its Application to Two Urban Rooftops

2008 ◽  
Vol 47 (3) ◽  
pp. 819-834 ◽  
Author(s):  
Timothy M. Barzyk ◽  
John E. Frederick
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Balance Model ◽  
Site Specific ◽  
City Hall ◽  
Microscale Model ◽  
Dry Conditions ◽  
Stone Concrete ◽  
The City

Abstract Individual structures within the same local-scale (102–104 m) environment may experience different microscale (<103 m) climates. Urban microclimate variations are often a result of site-specific features, including spatial and material characteristics of surfaces and surrounding structures. A semiempirical surface energy balance model is presented that incorporates radiative and meteorological measurements to statistically parameterize energy fluxes that are not measured directly, including sensible heat transport, storage heat flux through conduction, and evaporation (assumed to be negligible under dry conditions). Two Chicago rooftops were chosen for detailed study. The City Hall site was located in an intensely developed urban area characterized by close-set high-rise buildings. The University rooftop was in a highly developed area characterized by three- to seven-story buildings of stone, concrete, and brick construction. Two identical sets of instruments recorded measurements contemporaneously from these rooftops during summer 2005, and results from the week of 29 July to 5 August are presented here. The model explains 83.7% and 96% of the variance for the City Hall and University sites, respectively. Results apply to a surface area of approximately 1260 m2, at length scales similar to the dimensions of built structures and other urban elements. A site intercomparison revealed variations in surface energy balance components caused by site-specific features and demonstrated the relevance of the model to urban applications.

EFFICACITE DES IMAGES RADAR ET INFRAROUGE THERMIQUE, ET DE LA PHOTO COULEUR INFRAROUGE POUR L’INVENTAIRE DES CULTURES

1980 ◽  
Vol 60 (4) ◽  
pp. 1077-1085
Author(s):  
ROGER PAQUIN ◽  
GILLES LADOUCEUR
Keyword(s):  
Remote Sensing ◽  
Ground Truth ◽  
Thermal Infrared ◽  
Infrared Imagery ◽  
Ground Truth Data ◽  
Infrared Photography ◽  
Remote Sensing Technique ◽  
Field Crops ◽  
Radar Imagery ◽  
Thermal Infrared Imagery

Crops from 888 fields in a 300-km2 area between Rougemont and St-Hyacinthe were surveyed to compare the efficiency of radar (3–80 cm) and thermal infrared (8–14 μm) imagery with color infrared photography for crop identification. The color infrared photography and the thermal infrared imagery were taken by the Canadian Centre for Remote Sensing on 11 Aug. 1978, and the radar imagery by Intera on 19 Aug. The analysis of the thermal infrared imagery showed some correlations with the ground truth data, but the image could not be used in crop identification. Accordingly, observations from radar imagery could not serve in crop identification. However, similarities were observed between the radar and the thermal infrared imageries. The results showed once more that the color infrared photography as a remote sensing technique is the most useful to survey field crops.

Scale analysis of evapotranspiration estimates from an energy-water balance model and remotely sensed LST

2021 ◽  
Author(s):  
Nicola Paciolla ◽  
Chiara Corbari ◽  
Giuseppe Ciraolo ◽  
Antonino Maltese ◽  
Marco Mancini
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Water Balance ◽  
Surface Temperature ◽  
Remotely Sensed ◽  
Water Balance Model ◽  
Balance Model ◽  
Source Surface ◽  
Scale Analysis ◽  
Energy Fluxes

<p>Remote Sensing (RS) information has progressively found, in recent years, more and more applications in hydrological modelling as a valuable tool for easy and frequent collection of geophysical data. However, this kind of data should be handled carefully, minding its characteristics, spatial resolution and the heterogeneity of the target area.</p><p>In this work, a scale analysis on evapotranspiration estimates over heterogeneous crops is performed combining a distributed energy-water balance model (FEST-EWB) and high-resolution remotely-sensed Land Surface Temperature (LST) and vegetation data.</p><p>The FEST-EWB model is calibrated on measured LST, based on a procedure where every single pixel is modified independently one from the other; hence in each pixel of the analysed domain the minimum of the pixel difference between modelled RET and satellite observed LST is searched over the period of calibration.</p><p>The case study is a Sicilian vineyard, with test dates in the summer of 2008. Meteorological and energy fluxes data are available from an eddy-covariance station, while LST and vegetation data are obtained from low-altitude flights at the high resolution of 1.7 metres.</p><p>After a preliminary calibration on LST data and validation on energy fluxes, the scale analysis is performed in two ways: model input aggregation and model output aggregation. Four coarser scales are selected in reference to some common satellite products resolution: 10.2 m (in reference to Sentinel’s 10 m), 30.6 m (Landsat, 30 m), 244.8 m (MODIS visible, 250 m) and 734.4 m (MODIS, 1000 m). First, modelled surface temperature and evapotranspiration are aggregated to each scale by progressive averaging. Then, model inputs are upscaled to the same spatial resolutions and the model is calibrated anew, obtaining independent results directly at the target scale.</p><p>The results of the two procedures are found to be quite similar, testifying to the capacity of the model to provide accurate products for a heterogeneous area even at low resolutions. The robustness of the analysis is strengthened by a further comparison with two well-established energy-balance algorithms: the one source Surface Energy Balance Algorithm for Land (SEBAL) and the Two-Source Energy Balance (TSEB) model.</p>

scholarly journals Determining water use of sorghum from two-source energy balance and radiometric temperatures

2011 ◽  
Vol 15 (10) ◽  
pp. 3061-3070 ◽  
Author(s):  
J. M. Sánchez ◽  
R. López-Urrea ◽  
E. Rubio ◽  
V. Caselles
Keyword(s):  
Energy Balance ◽  
Water Use ◽  
Irrigation Management ◽  
Crop Coefficient ◽  
Balance Model ◽  
Crop Water ◽  
Phenological Stages ◽  
Crop Water Use ◽  
Promising Tool ◽  
Experimental Campaign

Abstract. Estimates of surface actual evapotranspiration (ET) can assist in predicting crop water requirements. An alternative to the traditional crop-coefficient methods are the energy balance models. The objective of this research was to show how surface temperature observations can be used, together with a two-source energy balance model, to determine crop water use throughout the different phenological stages of a crop grown. Radiometric temperatures were collected in a sorghum (Sorghum bicolor) field as part of an experimental campaign carried out in Barrax, Spain, during the 2010 summer growing season. Performance of the Simplified Two-Source Energy Balance (STSEB) model was evaluated by comparison of estimated ET with values measured on a weighing lysimeter. Errors of ±0.14 mm h−1 and ±1.0 mm d−1 were obtained at hourly and daily scales, respectively. Total accumulated crop water use during the campaign was underestimated by 5%. It is then shown that thermal radiometry can provide precise crop water necessities and is a promising tool for irrigation management.

scholarly journals Development of a 10 year (2001–2010) 0.1° dataset of land-surface energy balance for mainland China

2014 ◽  
Vol 14 (10) ◽  
pp. 14471-14518 ◽  
Author(s):  
X. Chen ◽  
Z. Su ◽  
Y. Ma ◽  
S. Liu ◽  
Q. Yu ◽  
...  
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Water Cycle ◽  
Surface Radiation ◽  
Balance Model ◽  
Wave Radiation ◽  
The Tibetan Plateau

Abstract. In the absence of high resolution estimates of the components of surface energy balance for China, we developed an algorithm based on the surface energy balance system (SEBS) to generate a dataset of land-surface energy and water fluxes on a monthly time scale from 2001 to 2010 at a 0.1° × 0.1° spatial resolution by using multi-satellite and meteorological forcing data. A remote-sensing-based method was developed to estimate canopy height, which was used to calculate roughness length and flux dynamics. The land-surface flux dataset was validated against "ground-truth" observations from 11 flux tower stations in China. The estimated fluxes correlate well with the stations' measurements for different vegetation types and climatic conditions (average bias = 15.3 W m−2, RMSE = 26.4 W m−2). The quality of the data product was also assessed against the GLDAS dataset. The results show that our method is efficient for producing a high-resolution dataset of surface energy flux for the Chinese landmass from satellite data. The validation results demonstrate that more accurate downward long-wave radiation datasets are needed to be able to accurately estimate turbulent fluxes and evapotranspiration when using the surface energy balance model. Trend analysis of land-surface radiation and energy exchange fluxes revealed that the Tibetan Plateau has undergone relatively stronger climatic change than other parts of China during the last 10 years. The capability of the dataset to provide spatial and temporal information on water-cycle and land–atmosphere interactions for the Chinese landmass is examined. The product is free to download for studies of the water cycle and environmental change in China.

scholarly journals Energy Balance of Rural Ecosystems In India

2014 ◽  
Vol XL-8 ◽  
pp. 411-417 ◽  
Author(s):  
A. Chhabra ◽  
V. Madhava Rao ◽  
R. R. Hermon ◽  
A. Garg ◽  
T. Nag ◽  
...  
Keyword(s):  
Energy Balance ◽  
High Resolution ◽  
Primary Production ◽  
Geographical Location ◽  
Integrated Approach ◽  
High Energy ◽  
Balance Model ◽  
Net Energy ◽  
Output Analysis ◽  
Rural Ecosystem

India is predominantly an agricultural and rural country. Across the country, the villages vary in geographical location, area, human and livestock population, availability of resources, agricultural practices, livelihood patterns etc. This study presents an estimation of net energy balance resulting from primary production vis-a-vis energy consumption through various components in a "Rural Ecosystem". Seven sites located in different agroclimatic regions of India were studied. An end use energy accounting "Rural Energy Balance Model" is developed for input-output analysis of various energy flows of production, consumption, import and export through various components of crop, trees outside forest plantations, livestock, rural households, industry or trade within the village system boundary. An integrated approach using field, ancillary, GIS and high resolution IRS-P6 Resourcesat-2 LISS IV data is adopted for generation of various model inputs. The primary and secondary field data collection of various energy uses at household and village level were carried out using structured schedules and questionnaires. High resolution multi-temporal Resourcesat-2 LISS IV data (2013–14) was used for generating landuse/landcover maps and estimation of above-ground Trees Outside Forests phytomass. The model inputs were converted to energy equivalents using country-specific energy conversion factors. A comprehensive geotagged database of sampled households and available resources at each study site was also developed in ArcGIS framework. Across the study sites, the estimated net energy balance ranged from −18.8 Terra Joules (TJ) in a high energy consuming Hodka village, Gujarat to 224.7 TJ in an agriculture, aquaculture and plantation intensive Kollaparru village, Andhra Pradesh. The results indicate that the net energy balance of a Rural Ecosystem is largely driven by primary production through crops and natural vegetation. This study provides a significant insight to policy relevant recommendations for Energy Sustainable Rural India.

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