Novel Dry Soil and Vegetation Indices to Predict Soil Contents from Landsat 8 Satellite Data-Reference-Cited by-同舟云学术

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Novel Dry Soil and Vegetation Indices to Predict Soil Contents from Landsat 8 Satellite Data

Published:2023-11-28 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Digital Image Computing: Techniques and Applications (DICTA)
language:
Short-container-title:

Author:

Datta Dristi¹,Paul Manoranjan¹,Murshed Manzur²,Teng Shyh Wei³,Schmidtke Leigh M.⁴

Affiliation:

1. Charles Sturt University,School of Computing, Mathematics, and Engineering,Bathurst,NSW,Australia,2795

2. Deakin University,School of Info Technology,Burwood,VIC,Australia,3125

3. Cooperative Research Centre for High Performance Soils,Callaghan,NSW,Australia,2308

4. Gulbali Institue, Charles Sturt University,Wagga Wagga,NSW,Australia,2678

Funder

Australian Government

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10410651/10410903/10410940.pdf?arnumber=10410940

Reference24 articles.

1. Evaluation of Airborne HySpex and Spaceborne PRISMA Hyperspectral Remote Sensing Data for Soil Organic Matter and Carbonates Estimation

2. Remote sensing prediction and characteristic analysis of cultivated land salinization in different seasons and multiple soil layers in the coastal area

3. Soil Moisture, Organic Carbon, and Nitrogen Content Prediction with Hyperspectral Data Using Regression Models

4. Determination of Munsell Soil Colour Using Smartphones

5. Estimating Agricultural Soil Moisture Content through UAV-Based Hyperspectral Images in the Arid Region

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Unveiling Soil-Vegetation Interactions: Reflection Relationships and an Attention-Based Deep Learning Approach for Carbon Estimation;2024 IEEE International Conference on Multimedia and Expo Workshops (ICMEW);2024-07-15

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