Dr. Christopher M. U. Neale Profile

Dr. Christopher M. U. Neale

Director of Research at Daugherty Water for Food Global Institute

SPIE Involvement:

Conference Chair | Author | Editor

Publications (26)

Proceedings Article | 20 November 2024 Presentation

Using the hybrid SETMI model to estimate soil water content and conduct irrigation scheduling

Christopher M. Neale

Proceedings Volume PC13191, PC1319109 (2024) https://doi.org/10.1117/12.3038091

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Proceedings Article | 17 October 2023 Presentation + Paper

Remote sensing-based evapotranspiration modeling for several land uses using SETMI model for Nebraska

I. Goncalves, C. M. Neale, S. Akasheh, B. Barker

Proceedings Volume 12727, 127270Z (2023) https://doi.org/10.1117/12.2684084

KEYWORDS: Modeling, Satellites, Covariance, Land cover, Data modeling, Landsat, Satellite imaging, Remote sensing, Meteorological satellites

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Proceedings Article | 17 October 2023 Presentation + Paper

Regional daily evapotranspiration estimation using remote sensing data and atmospheric-land exchange inverse energy model in Brazil

Sammy Akasheh, Christopher M. Neale, Martha Anderson, Christopher Hain, Debora Roberti, Vanessa Souza, Ivo Goncalves, Mitchell Schull

Proceedings Volume 12727, 127270X (2023) https://doi.org/10.1117/12.2680247

KEYWORDS: Atmospheric modeling, Data modeling, Covariance, Remote sensing, Spatial resolution, Atmospheric sensing, Vegetation, Thermal modeling, Shape memory alloys, Satellites

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Proceedings Article | 4 June 2022 Presentation + Paper

Irrigation scheduling using hybrid remote sensing-based evapotranspiration model informed by unmanned aerial system acquired multispectral and thermal imagery

Mitchell Maguire, Christopher M. Neale

Proceedings Volume 12114, 121140H (2022) https://doi.org/10.1117/12.2623262

KEYWORDS: Thermal modeling, Soil science, Multispectral imaging, Satellites, Reflectivity, Thermography, Satellite imaging, Earth observing sensors, Spatial resolution

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Proceedings Article | 12 September 2021 Presentation

Comparison of modeled evapotranspiration from the SETMI hybrid model informed with multispectral and thermal infrared imagery acquired with an unmanned aerial system

Mitch Maguire, Christopher M. Neale, Wayne Woldt

Proceedings Volume 11856, 118560J (2021) https://doi.org/10.1117/12.2604207

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Proceedings Article | 20 September 2020 Presentation

Opening Remarks by Conference Chairs

Christopher M. Neale, Antonino Maltese

Proceedings Volume 11528, 1152803 (2020) https://doi.org/10.1117/12.2584221

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Proceedings Article | 20 September 2020 Presentation

Modeling energy balance fluxes and evapotranspiration of maize and soybean using multispectral and thermal infrared imagery acquired with an unmanned aerial system

Mitch Maguire, Christopher M. Neale, Wayne Woldt

Proceedings Volume 11528, 115280I (2020) https://doi.org/10.1117/12.2577131

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SPIE Journal Paper | 8 December 2018 Open Access

Special Section Guest Editorial: Advances in Agro-Hydrological Remote Sensing for Water Resources Conservation

Antonino Maltese, Christopher M. Neale

JARS, Vol. 12, Issue 04, 042801, (December 2018) https://doi.org/10.1117/12.10.1117/1.JRS.12.042801

KEYWORDS: Remote sensing, Agriculture, Ecosystems, Aerospace engineering, Satellites, Vegetation, Soil science, Environmental monitoring, Environmental sensing, Sensor technology

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Proceedings Article | 5 December 2016 Presentation

Stable nocturnal spectral characteristics over a vineyard (Conference Presentation)

John Prueger, joesph Alfieri, Lawrence Hipps, William Kustas, Christopher Neale

Proceedings Volume 9998, 99980Q (2016) https://doi.org/10.1117/12.2241451

KEYWORDS: Turbulence, Agriculture, Remote sensing, Atmospheric sensing, Profiling, Temperature metrology, Hydrology, Ecosystems, Current controlled current source

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Proceedings Article | 25 October 2016 Paper

Water productivity mapping using Landsat 8 satellite together with weather stations

Renato A. Franco, Fernando B. Hernandez, Antônio H. de C. Teixeira, Janice Freitas Leivas, Daniel Noe Coaguila, Christopher Neale

Proceedings Volume 9998, 99981H (2016) https://doi.org/10.1117/12.2242003

KEYWORDS: Landsat, Agriculture, Satellites, Remote sensing, Biological research, Data modeling, Solar radiation models, Solar radiation, Vegetation, Earth observing sensors

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Proceedings Article | 25 October 2016 Presentation + Paper

Energy balance in the watershed of Ipê, Northwestern São Paulo State, Brazil

Diego Feitosa, Fernando T. Hernandez, Renato A. Franco, Antonio H. Teixeira, Christopher Neale

Proceedings Volume 9998, 99980O (2016) https://doi.org/10.1117/12.2242137

KEYWORDS: Heat flux, Remote sensing, Landsat, Radon, Roentgenium, Satellites, Meteorology, Satellite imaging, Earth observing sensors, Soil science

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Proceedings Article | 25 October 2016 Paper

Annual variability of water productivity components in the watershed of Cabeceira Comprida stream, Santa Fé do Sul, Brazil

Daniel Coaguila, Fernando B. Hernandez, Antônio H. de C. Teixeira, Christopher Neale, Renato A. Franco, Janice Leivas

Proceedings Volume 9998, 99981E (2016) https://doi.org/10.1117/12.2242007

KEYWORDS: Landsat, Agriculture, Earth observing sensors, Remote sensing, Climatology, Roentgenium, Calibration, Sensors, Wind energy, Satellites

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Proceedings Article | 29 October 2014 Paper

Improvements in irrigation system modelling when using remotely sensed ET for calibration

J. van Opstal, C. M. Neale, S. Lecina

Proceedings Volume 9239, 92390P (2014) https://doi.org/10.1117/12.2067565

KEYWORDS: Systems modeling, Data modeling, Remote sensing, Agriculture, Modeling, Calibration, Satellite imaging, Earth observing sensors, Satellites, Water

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SPIE Journal Paper | 25 August 2014

Analyzing the effect of shadow on the relationship between ground cover and vegetation indices by using spectral mixture and radiative transfer models

Isidro Campos, Christopher Neale, Maria-Llanos López, Claudio Balbontín, Alfonso Calera

JARS, Vol. 8, Issue 01, 083562, (August 2014) https://doi.org/10.1117/12.10.1117/1.JRS.8.083562

KEYWORDS: Reflectivity, Vegetation, Landsat, Near infrared, Data modeling, Sun, Satellites, Soil science, Radiative transfer, Earth observing sensors

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Proceedings Article | 16 October 2013 Paper

Retrieving water productivity parameters by using Landsat images in the Nilo Coelho irrigation scheme, Brazil

Antônio H. de C. Teixeira, Hélio Lopes, Fernando Hernandez, Morris Scherer-Warren, Ricardo Andrade, Christopher Neale

Proceedings Volume 8887, 888713 (2013) https://doi.org/10.1117/12.2027490

KEYWORDS: Vegetation, Remote sensing, Biological research, Landsat, Agriculture, Satellites, Solar radiation, Solar radiation models, Ecosystems, Earth observing sensors

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Proceedings Article | 16 October 2013 Paper

Application of MODIS images for modeling the energy balance components in the semi-arid conditions of Brazil

Antônio H. de C. Teixeira, Morris Sherer-Warren, Hélio Lopes, Fernando Hernandez, Ricardo Andrade, Christopher Neale

Proceedings Volume 8887, 888719 (2013) https://doi.org/10.1117/12.2025388

KEYWORDS: Vegetation, Radon, Remote sensing, MODIS, Heat flux, Solar radiation, Satellites, Solar radiation models, Ecosystems, Agriculture

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Proceedings Article | 22 October 2012 Paper

Thermal remote sensing of snow cover to identify the extent of hydrothermal areas in Yellowstone National Park

Christopher Neale, S. Sivarajan, A. Masih, C. Jaworowski, H. Heasler

Proceedings Volume 8531, 853110 (2012) https://doi.org/10.1117/12.981778

KEYWORDS: Thermography, Infrared imaging, Infrared radiation, Snow cover, Remote sensing, Image resolution, Infrared sensors, Imaging systems, Infrared cameras, Calibration

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Proceedings Article | 18 October 2011 Paper

Estimating evapotranspiration of riparian vegetation using high resolution multispectral, thermal infrared and lidar data

Christopher Neale, Hatim Geli, Saleh Taghvaeian, Ashish Masih, Robert Pack, Ronald Simms, Michael Baker, Jeff Milliken, Scott O'Meara, Amy Witherall

Proceedings Volume 8174, 81740P (2011) https://doi.org/10.1117/12.903246

KEYWORDS: Vegetation, LIDAR, Thermography, Infrared radiation, Infrared imaging, Multispectral imaging, Remote sensing, Calibration, Image resolution, Imaging systems

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High resolution airborne multispectral and thermal infrared imagery was acquired over the Mojave River, California with the Utah State University airborne remote sensing system integrated with the LASSI imaging Lidar also built and operated at USU. The data were acquired in pre-established mapping blocks over a 2 day period covering approximately 144 Km of the Mojave River floodplain and riparian zone, approximately 1500 meters in width. The multispectral imagery (green, red and near-infrared bands) was ortho-rectified using the Lidar point cloud data through a direct geo-referencing technique. Thermal Infrared imagery was rectified to the multispectral ortho-mosaics. The lidar point cloud data was classified to separate ground surface returns from vegetation returns as well as structures such as buildings, bridges etc. One-meter DEM's were produced from the surface returns along with vegetation canopy height also at 1-meter grids. Two surface energy balance models that use remote sensing inputs were applied to the high resolution imagery, namely the SEBAL and the Two Source Model. The model parameterizations were slightly modified to accept high resolution imagery (1-meter) as well as the lidar-based vegetation height product, which was used to estimate the aerodynamic roughness length. Both models produced very similar results in terms of latent heat fluxes (LE). Instantaneous LE values were extrapolated to daily evapotranspiration rates (ET) using the reference ET fraction, with data obtained from a local weather station. Seasonal rates were obtained by extrapolating the reference ET fraction according to the seasonal growth habits of the different species. Vegetation species distribution and area were obtained from classification of the multispectral imagery. Results indicate that cottonwood and salt cedar (tamarisk) had the highest evapotranspiration rates followed by mesophytes, arundo, mesquite and desert shrubs. This research showed that high-resolution airborne multispectral and thermal infrared imagery integrated with precise full-waveform lidar data can be used to estimate evapotranspiration and water use by riparian vegetation.

Proceedings Article | 18 September 2009 Paper

Monitoring geothermal activity in Yellowstone National Park using airborne thermal infrared remote sensing

C. Neale, S. Sivarajan, O. Akasheh, C. Jaworowski, H. Heasler

Proceedings Volume 7472, 747210 (2009) https://doi.org/10.1117/12.834225

KEYWORDS: Thermography, Infrared imaging, Infrared radiation, Infrared sensors, Remote sensing, Calibration, Image acquisition, Imaging systems, Cameras, Infrared cameras

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Proceedings Article | 2 October 2008 Paper

Airborne remote sensing applications in hydrology and water resources

Christopher Neale

Proceedings Volume 7104, 71040G (2008) https://doi.org/10.1117/12.804036

KEYWORDS: Vegetation, Airborne remote sensing, Agriculture, Hydrology, Imaging systems, Remote sensing, Satellites, Sensors, Cameras, Reflectivity

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Proceedings Article | 9 October 2007 Paper

A hybrid approach for estimating spatial evapotranspiration from satellite imagery

C. M. U. Neale, M. P. González Dugo, L. Mateos, W. Kustas, Y Kaheil

Proceedings Volume 6742, 674209 (2007) https://doi.org/10.1117/12.740261

KEYWORDS: Data modeling, Satellites, Soil science, RGB color model, Satellite imaging, Earth observing sensors, Heat flux, Solar radiation models, Atmospheric modeling, Remote sensing

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Proceedings Article | 17 October 2006 Paper

A real-time crop classification system for evapotranspiration estimates in irrigated areas

C. Neale, L. Mateos, M. Gonzalez-Dugo

Proceedings Volume 6359, 63590W (2006) https://doi.org/10.1117/12.690043

KEYWORDS: Image classification, Satellites, Satellite imaging, Earth observing sensors, Logic, Soil science, Reflectivity, Vegetation, Landsat, Classification systems

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Proceedings Article | 17 October 2006 Paper

A methodology for conducting diagnostic analyses and operational simulation in large-scale pressurized irrigation systems

Daniele Zaccaria, Christopher Neale, Nicola Lamaddalena

Proceedings Volume 6359, 635910 (2006) https://doi.org/10.1117/12.690406

KEYWORDS: Satellites, Remote sensing, Multispectral imaging, Computer simulations, Diagnostics, Earth observing sensors, Satellite imaging, Data modeling, Soil science, Agriculture

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This paper describes a methodology, which is currently being tested, aimed at generating flow hydrographs and the operational simulation of existing pressurized irrigation delivery networks in southern Italy. The approach involves a combined use of high-resolution remote sensing and of a simplified agro-hydrological model to simulate the soil water balance at the level of each delivery node of the irrigation network. High resolution multispectral satellite imagery was acquired on a single date overpass for an existing irrigation district located in southern Italy. The use of high-resolution imagery enables mapping the land use, identifying the specific extent of different cropped areas, and accounting for the spatial variability of parameters related to crop evapotranspiration over the irrigated areas. In the rationale of the proposed methodology, the agro-hydrological model uses spatially-distributed inputs derived from the high-resolution multispectral image and, by maintaining a soil-water balance in the cropped fields downstream from the delivery hydrants, would allow generating disaggregated information on soil water deficits and thus on timing and volumes of irrigation demand for the area served by the distribution network. The aggregation of hydrant hydrographs would allow generating the flow hydrographs at the upstream end of the irrigation network. Results from simulations will then be compared with historical datasets of irrigation events that will be obtained by downloading data records from multiuser electronically-fed hydrants equipped with the AcquaCARD^(R) technology. These comparisons will allow investigating any deviation of actual water deliveries to farm fields from the simulation results, accounting for various uncertainties, including the ones related to farmers' water management strategy. The overall objective of the study being conducted is validating the reliability of the proposed methodology for modernization of large-scale irrigation systems.

Proceedings Article | 17 October 2006 Paper

Comparison of remote sensing-based energy balance methods for estimating crop evapotranspiration

M. Gonzalez-Dugo, C. Neale, L. Mateos, W. Kustas, F. Li

Proceedings Volume 6359, 63590Z (2006) https://doi.org/10.1117/12.690056

KEYWORDS: Remote sensing, Heat flux, Data modeling, Vegetation, Aerodynamics, Satellites, Temperature metrology, Calibration, Atmospheric modeling, Earth observing sensors

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Proceedings Article | 19 October 2005 Paper

Integration and weighting of remotely sensed energy balance fluxes

Christopher Neale, Jose Chavez, Raghuveer Vinukollu

Proceedings Volume 5976, 59760M (2005) https://doi.org/10.1117/12.631070

KEYWORDS: Satellites, Remote sensing, Satellite imaging, Heat flux, Landsat, Earth observing sensors, Airborne remote sensing, Calibration, Aerodynamics, Thermography

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Proceedings Article | 16 September 1994 Paper

Computation-efficient algorithms for image registration

Xin Qiu, Chai Chong, Chien-Min Huang, Christopher Neale

Proceedings Volume 2308, (1994) https://doi.org/10.1117/12.185912

KEYWORDS: Image registration, Fuzzy logic, Image processing, Reliability, Algorithm development, Image quality, Distance measurement, Digital filtering, Feature extraction, Video

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Showing 5 of 26 publications

Proceedings Volume Editor (18)

SPIE Conference Volume | 7 November 2023

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV

SPIE Conference Volume | 31 October 2022

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV

SPIE Conference Volume | 12 October 2021

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII

SPIE Conference Volume | 13 October 2020

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXII

SPIE Conference Volume | 11 December 2019

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI

Showing 5 of 18 publications

Conference Committee Involvement (32)

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXVI

16 September 2024 | Edinburgh, United Kingdom

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV

3 September 2023 | Amsterdam, Netherlands

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXV

3 September 2023 | Amsterdam, Netherlands

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV

5 September 2022 | Berlin, Germany

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIV

5 September 2022 | Berlin, Germany

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII

13 September 2021 | Online Only, Spain

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXIII

13 September 2021 | Online Only, Spain

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXII

22 September 2020 | Online Only, United Kingdom

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXII

22 September 2020 | Online Only, United Kingdom

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI

9 September 2019 | Strasbourg, France

Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI

9 September 2019 | Strasbourg, France

SPIE Remote Sensing

9 September 2019 | Strasbourg, France