黑料网

Mr Eduardo Sandoval Cruz staff profile picture

Contact details +6469517886

Eduardo Sandoval Cruz MAgrSc, PGDipAgrSc

Senior Technical Officer

Contract Research Unit

As a GIS analyst at MAF Digital Lab, my primary responsibility involves processing and analysing satellite and airborne imagery collected from our Hyperspectral, RGB, and multispectral cameras supporting projects in the academia, government agencies, and the private sector. The objective is to extract meaningful information pertaining to the land material. To achieve this, I utilize different kind of remote sensing devices and software tools such as ArcGIS, ENVI, and photogrammetry software to perform image classification, feature extraction, and change detection. Apart from this, I also coordinate fieldwork, assist in logistics, and provide cost quotations as required. In addition, I automate GIS tasks when necessary for fieldwork and create maps for stakeholders using ArcGIS. I am responsible for the capture and post-processing of lab-captured hyperspectral imagery from the camera facilities (SPECIM), remote sensing equipment, and aerial drone equipment. Lastly, I perform high-accuracy GPS RTK surveying, which is essential for creating high quality visualization maps.

 

Eduardo Sandoval, Senior Technical Officer at 黑料网's School of Food Technology, holds BSc degrees in Agriculture from UC, Chile (2001) and Business Management from UNAP, Chile (2006). He expanded his education, achieving a PGDip in AgriScience in 2012 and an MSc in AgriScience from 黑料网, New Zealand, in 2014. Eduardo specializes in Precision Agriculture and GIS Spatial Analysis, focusing on remote sensing devices and hyperspectral data analysis. Field leader in the data collection all over New Zealand for the Precision Primary Growth Partnership (PGP) project, which enhances hill country fertilization assessment and precision fertilizer application via hyperspectral imagery.

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Professional

Contact details

  • Ph: ext 84886
    Location: Precision Team, John Littleton Building
    Campus: Turitea, AgResearch Campus

Qualifications

  • Master of Agricultural Science - 黑料网 (2014)
  • Postgraduate Diploma in Agricultural Science - 黑料网 (2013)

Research Expertise

Research Interests

  1. Remote sensing applications in agriculture, forestry, and land-use management
  2. UAV applications for environmental monitoring and mapping
  3. Hyperspectral imaging for mineral exploration and geological mapping
  4. Remote sensing and UAV-based applications in disaster management and emergency response
  5. Remote sensing and hyperspectral imaging for atmospheric and climate research
  6. UAV-based applications in infrastructure inspection and monitoring.
  7. Use of hyperspectral scanning to asess green house gases

Area of Expertise

Field of research codes
Agricultural And Veterinary Sciences (070000): Agriculture, Land and Farm Management (070100): Agronomy (070302): Animal Nutrition (070204): Animal Production (070200): Crop and Pasture Improvement (Selection and Breeding) (070305): Crop and Pasture Production (070300): Crop and Pasture Protection (Pests, Diseases and Weeds) (070308):
Earth Sciences (040000):
Forestry Sciences (070500): Horticultural Production (070600)

Keywords

  • Satellite Imaging
  • Aerial Photography
  • LiDAR
  • Digital Elevation Models (DEM)
  • Orthophoto
  • Image Processing
  • Image Analysis
  • Spectral Reflectance
  • Radiometric Calibration
  • Atmospheric Correction
  • Spectral Unmixing
  • Feature Extraction
  • Object-Based Image Analysis (OBIA)
  • Machine Learning Algorithms
  • 3D Modeling
  • Structure from Motion (SfM)
  • Point Cloud Processing
  • Topographic Mapping
  • Spatial Data Management
  • Geodatabase Design
  • Cartography
  • Geospatial Analysis
  • Python in GIS

Research Outputs

Journal

Lyu, H., Grafton, M., Ramilan, T., Irwin, M., & Sandoval, E. (2024). Hyperspectral Imaging Spectroscopy for Non-Destructive Determination of Grape Berry Total Soluble Solids and Titratable Acidity. Remote Sensing. 16(10)
[Journal article]Authored by: Grafton, M., Irwin, M., Ramilan, T., Sandoval Cruz, E.Contributed to by: Grafton, M.
Lyu, H., Grafton, M., Ramilan, T., Irwin, M., Wei, HE., & Sandoval, E. (2023). Using Remote and Proximal Sensing Data and Vine Vigor Parameters for Non-Destructive and Rapid Prediction of Grape Quality. Remote Sensing. 15(22)
[Journal article]Authored by: Grafton, M., Irwin, M., Ramilan, T., Sandoval Cruz, E.
Lyu, H., Grafton, M., Ramilan, T., Irwin, M., Wei, H-E., & Sandoval, E. (2023). Using Remote and Proximal Sensing Data and Vine Vigor Parameters for Non-Destructive and Rapid Prediction of Grape Quality. Remote Sensing. 15(22), Retrieved from https://www.mdpi.com/2072-4292/15/22/5412
[Journal article]Authored by: Grafton, M., Irwin, M., Ramilan, T., Sandoval Cruz, E.Contributed to by: Grafton, M.
Wei, H-E., Grafton, M., Bretherton, M., Irwin, M., & Sandoval, E. (2023). Evaluation of the use of two-stage calibrated PlanetScope images and environmental variables for the development of the grapevine water status prediction model. Technology in Agronomy. 3, Retrieved from https://www.maxapress.com/article/doi/10.48130/TIA-2023-0006
[Journal article]Authored by: Grafton, M., Irwin, M., Sandoval Cruz, E.Contributed to by: Grafton, M.
Lyu, H., Grafton, M., Ramilan, T., Irwin, M., & Sandoval, E. (2023). Assessing the Leaf Blade Nutrient Status of Pinot Noir Using Hyperspectral Reflectance and Machine Learning Models. Remote Sensing. 15(6)
[Journal article]Authored by: Grafton, M., Irwin, M., Ramilan, T., Sandoval Cruz, E.
Lyu, H., Grafton, M., Ramilan, T., Irwin, M., & Sandoval, E. (2023). Assessing the Leaf Blade Nutrient Status of Pinot Noir Using Hyperspectral Re铿俥ctance and Machine Learning Models. Remote Sensing. 15(6), Retrieved from https://www.mdpi.com/2072-4292/15/6/1497
[Journal article]Authored by: Grafton, M., Irwin, M., Ramilan, T., Sandoval Cruz, E.Contributed to by: Grafton, M.
Wei, H-E., Grafton, M., Bretherton, M., Irwin, M., & Sandoval, E. (2022). Evaluation of the Use of UAV-Derived Vegetation Indices and Environmental Variables for Grapevine Water Status Monitoring Based on Machine Learning Algorithms and SHAP Analysis. Remote Sensing. 14(23), Retrieved from https://www.mdpi.com/2072-4292/14/23/5918
[Journal article]Authored by: Grafton, M., Irwin, M., Sandoval Cruz, E.Contributed to by: Grafton, M.
Grafton, MCE., Irwin, ME., & Sandoval-Cruz, EA. (2022). Measuring the response of variable bulk solid fertiliser application by computer-controlled delivery from aircraft. New Zealand Journal of Agricultural Research. 65(6), 507-519
[Journal article]Authored by: Grafton, M., Irwin, M., Sandoval Cruz, E.
Wei, HE., Grafton, M., Bretherton, M., Irwin, M., & Sandoval, E. (2021). Evaluation of point hyperspectral reflectance and multivariate regression models for grapevine water status estimation. Remote Sensing. 13(16)
[Journal article]Authored by: Grafton, M., Irwin, M., Sandoval Cruz, E.Contributed to by: Grafton, M.
Sandoval Cruz, EA., McGill, CR., Southward, RC., McKenzie, CM., Card, SD., He, XZ., . . . Chynoweth, RJ. (2018). Does chemical control of blind seed disease (Gloeotinia temulenta) affect endophyte transmission in ryegrass seed crops?. Australasian Plant Pathology. 47(6), 561-569
[Journal article]Authored by: He, X., McGill, C., Sandoval Cruz, E.

Conference

Wei, HE., Grafton, M., Bretherton, M., Irwin, M., & Sandoval, E.Evaluation of the Use of UAV-Derived Vegetation Indices and Environmental Variables for Grapevine Water Status Monitoring Based on Machine Learning Algorithms and SHAP Analysis. Remote Sensing. 14 (23)
[Conference]Authored by: Grafton, M., Irwin, M., Sandoval Cruz, E.Contributed to by: Grafton, M.

Other

Pullanagari, R., Wilson, R., Yule, I., Sandoval Cruz, E., Hume, D., & Stuart, C. (2022). Hyperspectral imaging in seed evaluation. ISTA
[Other]Authored by: Sandoval Cruz, E.Contributed to by: Sandoval Cruz, E.

Consultancy and Languages

Languages

  • Spanish
    Last used: always used
    Spoken ability: Excellent
    Written ability: Excellent
  • Japanese
    Last used: Always used
    Spoken ability: Average
    Written ability: Average

Teaching and Supervision

Teaching Statement

-Teacher paper 284.703 Vegetable Production Science

-Studying vine vigour as an important parameter to predict the grape yield, quality but also can guide intra-seasonal pruning.Supporting PhD Student Hongyi Lyu for the data collection and processing using remote sensing devices and photogrammetry softwares.

-Use of diverse species to compose pastures, and the ecosystem.Supporting PhD Student Bia Oliveira through the collection of remote sensing data and its process for her PhD.

Media and Links

Other Links