Categorisation of mango orchard age groups using Object-Based Image Analysis-Reference-Cited by-同舟云学术

Categorisation of mango orchard age groups using Object-Based Image Analysis

Published:2024-01-17 Issue:2 Volume:17 Page:
ISSN:1866-7511
Container-title:Arabian Journal of Geosciences
language:en
Short-container-title:Arab J Geosci

Author:

Stephen Steena^ORCID,Haldar Dipanwita

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s12517-024-11857-z.pdf

Reference78 articles.

1. Akcay O, Avsar EO, Inalpulat M, Genc L, Cam A (2018) Assessment of segmentation parameters for object-based land cover classification using color-infrared imagery. ISPRS 7:4247. https://doi.org/10.3390/IJGI7110424

2. Amani M et al (2020) Google Earth Engine cloud computing platform for remote sensing big data applications: a comprehensive review. EEE J Sel Top Appl Earth Obs Remote Sens 13:5326–5350. https://doi.org/10.1109/JSTARS.2020.3021052

3. APDEA (2010) Product profiles of mango. https://apeda.in/agriexchange/MarketProfile/one/MANGO.aspx.

4. Baatz M, Schape A (2000) Multiresolution segmentation-an optimization approach for high quality multiscale image segmentation. In: Angewandte Geographische Informationsverarbeitung XII, pp 12–23

5. Belgiu M, Drǎguţ L (2014) Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery. ISPRS 96:67–75. https://doi.org/10.1016/J.ISPRSJPRS.2014.07.002

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