All pixels are useful, but some are more useful: Efficient in situ data collection for crop-type mapping using sequential exploration methods-Reference-Cited by-同舟云学术

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All pixels are useful, but some are more useful: Efficient in situ data collection for crop-type mapping using sequential exploration methods

Published:2020-09 Issue: Volume:91 Page:102114
ISSN:0303-2434
Container-title:International Journal of Applied Earth Observation and Geoinformation
language:en
Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Fowler Jared,Waldner François,Hochman Zvi

Funder

CSIRO

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Reference34 articles.

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2. Burn-in and mixed populations;Block;J. Appl. Probab.,1993

3. Unsupervised retraining of a maximum likelihood classifier for the analysis of multitemporal remote sensing images;Bruzzone;IEEE Trans. Geosci. Rem. Sens.,2001

4. An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images;Bruzzone;IEEE Trans. Image Process.,2002

5. Active learning for object classification: from exploration to exploitation;Cebron;Data Mining Knowl. Discov.,2009

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1. Cropland and Crop Type Classification with Sentinel-1 and Sentinel-2 Time Series Using Google Earth Engine for Agricultural Monitoring in Ethiopia;Remote Sensing;2024-02-29

2. The Impact and Correction of Sensitive Environmental Factors on Spectral Reflectance Measured In Situ;Remote Sensing;2023-11-12

3. Investigating the Use of Street-Level Imagery and Deep Learning to Produce In-Situ Crop Type Information;Geographies;2023-08-30

4. Tree Species Diversity Mapping—Success Stories and Possible Ways Forward;Remote Sensing;2023-06-12

5. Optimal Sample Size and Composition for Crop Classification with Sen2-Agri’s Random Forest Classifier;Remote Sensing;2023-01-19

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