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Estimation Of Soil Moisture At Different Soil Levels Using Machine Learning Techniques And Unmanned Aerial Vehicle (Uav) Multispectral Imagery, Mahyar Aboutalebi, L. Niel Allen, Alfonso F. Torres-Rua, Mac Mckee, Calvin Coopmans

AggieAir Publications

Soil moisture is a key component of water balance models. Physically, it is a nonlinear function of parameters that are not easily measured spatially, such as soil texture and soil type. Thus, several studies have been conducted on the estimation of soil moisture using remotely sensed data and data mining techniques such as artificial neural networks (ANNs) and support vector machines (SVMs). However, all models developed based on these techniques are limited to site-specific applications where they are trained and their parameters are tuned. Moreover, since the system of non-linear equations produced by and conducted in the machine learning process …

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The Impact Of Shadows On Partitioning Of Radiometric Temperature To Canopy And Soil Temperature Based On The Contextual Two-Source Energy Balance Model (Tseb-2t), Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, Hector Nieto, William Kustas, Calvin Coopmans

AggieAir Publications

Tests of the most recent version of the two-source energy balance model have demonstrated that canopy and soil temperatures can be retrieved from high-resolution thermal imagery captured by an unmanned aerial vehicle (UAV). This work has assumed a linear relationship between vegetation indices (VIs) and radiometric temperature in a square grid (i.e., 3.6 m x 3.6 m) that is coarser than the resolution of the imagery acquired by the UAV. In this method, with visible, near infrared (VNIR), and thermal bands available at the same high-resolution, a linear fit can be obtained over the pixels located in a grid, where …

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Estimation Of Surface Thermal Emissivity In A Vineyard For Uav Microbolometer Thermal Cameras Using Nasa Hytes Hyperspectral Thermal, And Landsat And Aggieair Optical Data, Alfonso F. Torres-Rua, Mahyar Aboutalebi, Timothy Wright, Ayman Nassar, Pierre Guillevic, Lawrence Hipps, Feng Gao, Kevin Jim, Maria Mar Alsina, Calvin Coopmans, Mac Mckee, William Kustas

AggieAir Publications

Microbolometer thermal cameras in UAVs and manned aircraft allow for the acquisition of highresolution temperature data, which, along with optical reflectance, contributes to monitoring and modeling of agricultural and natural environments. Furthermore, these temperature measurements have facilitated the development of advanced models of crop water stress and evapotranspiration in precision agriculture and heat fluxes exchanges in small river streams and corridors. Microbolometer cameras capture thermal information at blackbody or radiometric settings (narrowband emissivity equates to unity). While it is customary that the modeler uses assumed emissivity values (e.g. 0.99– 0.96 for agricultural and environmental settings); some applications (e.g. Vegetation Health …

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Validation Of Digital Surface Models (Dsms) Retrieved From Unmanned Aerial Vehicle (Uav) Point Clouds Using Geometrical Information From Shadows, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, William Kustas, Héctor Nieto, Calvin Coopmans

AggieAir Publications

Theoretically, the appearance of shadows in aerial imagery is not desirable for researchers because it leads to errors in object classification and bias in the calculation of indices. In contrast, shadows contain useful geometrical information about the objects blocking the light. Several studies have focused on estimation of building heights in urban areas using the length of shadows. This type of information can be used to predict the population of a region, water demand, etc., in urban areas. With the emergence of unmanned aerial vehicles (UAVs) and the availability of high- to super-high-resolution imagery, the important questions relating to shadows …

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Assessment Of Different Methods For Shadow Detection In High-Resolution Optical Imagery And Evaluation Of Shadow Impact On Calculation Of Ndvi And Evapotranspiration, Mahyar Aboutalebi, Alfonso F. Torres-Rua, William P. Kustas, Héctor Nieto, Calvin Coopmans, Mac Mckee

AggieAir Publications

Significant efforts have been made recently in the application of high-resolution remote sensing imagery (i.e., sub-meter) captured by unmanned aerial vehicles (UAVs) for precision agricultural applications for high-value crops such as wine grapes. However, at such high resolution, shadows will appear in the optical imagery effectively reducing the reflectance and emission signal received by imaging sensors. To date, research that evaluates procedures to identify the occurrence of shadows in imagery produced by UAVs is limited. In this study, the performance of four different shadow detection methods used in satellite imagery was evaluated for high-resolution UAV imagery collected over a California …

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The Grape Remote Sensing Atmospheric Profile And Evapotranspiration Experiment, William P. Kustas, Martha C. Anderson, Joseph G. Alfieri, Kyle Knipper, Alfonso F. Torres-Rua, Christopher K. Parry, Hector Nieto, Nurit Agam, William A. White, Feng Gao, Lynn Mckee, John H. Prueger, Lawrence E. Hipps, Sebastian A. Los, Maria Mar Alsina, Luis Sanchez, Brent Sams, Nick Dokoozlian, Mac Mckee, Scott B. Jones, Yun Yang, Tiffany G. Wilson, Fangni Lei, Andrew Mcelrone, Josh L. Heitman, Adam M. Howard, Kirk Post, Forrest Melton, Christopher Hain

AggieAir Publications

Particularly in light of California’s recent multiyear drought, there is a critical need for accurate and timely evapotranspiration (ET) and crop stress information to ensure long-term sustainability of high-value crops. Providing this information requires the development of tools applicable across the continuum from subfield scales to improve water management within individual fields up to watershed and regional scales to assess water resources at county and state levels. High-value perennial crops (vineyards and orchards) are major water users, and growers will need better tools to improve water-use efficiency to remain economically viable and sustainable during periods of prolonged drought. To develop …

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Evaluation Of Tseb Turbulent Fluxes Using Different Methods For The Retrieval Of Soil And Canopy Component Temperatures From Uav Thermal And Multispectral Imagery, Héctor Nieto, William P. Kustas, Alfonso F. Torres-Rúa, Joseph G. Alfieri, Feng Gao, Martha C. Anderson, W. Alex White, Lisheng Song, María Del Mar Alsina, John H. Prueger, Mac Mckee, Manal Elarab, Lynn G. Mckee

AggieAir Publications

The thermal-based Two-Source Energy Balance (TSEB) model partitions the evapotranspiration (ET) and energy fluxes from vegetation and soil components providing the capability for estimating soil evaporation (E) and canopy transpiration (T). However, it is crucial for ET partitioning to retrieve reliable estimates of canopy and soil temperatures and net radiation, as the latter determines the available energy for water and heat exchange from soil and canopy sources. These two factors become especially relevant in row crops with wide spacing and strongly clumped vegetation such as vineyards and orchards. To better understand these effects, very high spatial resolution remote-sensing data from …

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Multispectral Remote Sensing For Yield Estimation Using High-Resolution Imagery From An Unmanned Aerial Vehicle, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Niel Allen

AggieAir Publications

Satellites and autonomous unmanned aerial vehicles (UAVs) are two major platforms for acquiring remotely-sensed information of the earth’s surface. Due to the limitations of satellite-based imagery, such as coarse spatial resolution and fixed schedules, applications of UAVs as low-cost remote sensing systems are rapidly expanding in many research areas, particularly precision agriculture. UAVs can provide imagery with high spatial resolution (finer than 1 meter) and acquire information in visible, near infrared, and even thermal bands. In agriculture, vegetation characteristics such as health, water stress, and the amount of biomass, can be estimated using UAV imagery. In this study, three sets …

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Implications Of Sensor Inconsistencies And Remote Sensing Error In The Use Of Small Unmanned Aerial Systems For Generation Of Information Products For Agricultural Management, Mac Mckee, Ayman Nassar, Alfonso F. Torres-Rua, Mahyar Aboutalebi, William Kustas

AggieAir Publications

Small, unmanned aerial systems (sUAS) for remote sensing represent a relatively new and growing technology to support decisions for agricultural operations. The size and power limitations of these systems present challenges for the weight, size, and capability of the sensors that can be carried, as well as the geographical coverage that is possible. These factors, together with a lack of standards for sensor technology, its deployment, and data analysis, lead to uncertainties in data quality that can be difficult to detect or characterize. These, in turn, limit comparability between data from different sources and, more importantly, imply limits on the …

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Retrieval Of Spectral Reflectance Of High Resolution Multispectral Imagery Acquired With An Autonomous Unmanned Aerial Vehicle: Aggieair™, Bushra Zaman, Austin Jensen, Shannon R. Clemens, Mac Mckee

AggieAir Publications

This research presents a new semi-automatic model for converting raw AggieAir™ footprints in visible and near-infrared (NIR) bands into reflectance images. AggieAir, a new unmanned aerial vehicle (UAV) platform, is flown autonomously using pre-programmed flight plans at low altitudes to limit atmospheric effects. The UAV acquires high-resolution, multispectral images and has a flight duration of about 30 minutes. The sensors on board are twin cameras with duplicate settings and automatic mode disabled. A white Barium Sulfate (BaSO4) panel is used for reflectance calibration and in situ irradiance measurements. The spatial resolution of the imagery is 25 cm; the radiometric resolution …

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Full-Text Articles in Engineering

Estimation Of Soil Moisture At Different Soil Levels Using Machine Learning Techniques And Unmanned Aerial Vehicle (Uav) Multispectral Imagery, Mahyar Aboutalebi, L. Niel Allen, Alfonso F. Torres-Rua, Mac Mckee, Calvin Coopmans

AggieAir Publications

The Impact Of Shadows On Partitioning Of Radiometric Temperature To Canopy And Soil Temperature Based On The Contextual Two-Source Energy Balance Model (Tseb-2t), Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, Hector Nieto, William Kustas, Calvin Coopmans

AggieAir Publications

AggieAir Publications

Validation Of Digital Surface Models (Dsms) Retrieved From Unmanned Aerial Vehicle (Uav) Point Clouds Using Geometrical Information From Shadows, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Mac Mckee, William Kustas, Héctor Nieto, Calvin Coopmans

AggieAir Publications

Assessment Of Different Methods For Shadow Detection In High-Resolution Optical Imagery And Evaluation Of Shadow Impact On Calculation Of Ndvi And Evapotranspiration, Mahyar Aboutalebi, Alfonso F. Torres-Rua, William P. Kustas, Héctor Nieto, Calvin Coopmans, Mac Mckee

AggieAir Publications

AggieAir Publications

AggieAir Publications

Multispectral Remote Sensing For Yield Estimation Using High-Resolution Imagery From An Unmanned Aerial Vehicle, Mahyar Aboutalebi, Alfonso F. Torres-Rua, Niel Allen

AggieAir Publications

Implications Of Sensor Inconsistencies And Remote Sensing Error In The Use Of Small Unmanned Aerial Systems For Generation Of Information Products For Agricultural Management, Mac Mckee, Ayman Nassar, Alfonso F. Torres-Rua, Mahyar Aboutalebi, William Kustas

AggieAir Publications

Retrieval Of Spectral Reflectance Of High Resolution Multispectral Imagery Acquired With An Autonomous Unmanned Aerial Vehicle: Aggieair™, Bushra Zaman, Austin Jensen, Shannon R. Clemens, Mac Mckee

AggieAir Publications