Machine Learning Approach to LULC Forecasting-Reference-Cited by-同舟云学术

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Machine Learning Approach to LULC Forecasting

Published:2024-04-15 Issue: Volume: Page:59-63
ISSN:
Container-title:2024 IEEE Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS)
language:
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Author:

Riche Abdelkader¹,Ricci Riccardo²,Melgani Farid²,Drias Ammar¹,Souissi Boularbah³

Affiliation:

1. University of Sciences and Technology Houari Boumediene,Department of Geography and Territorial Planning

2. University of Trento,Department of Information Engineering and Computer Science

3. University of Sciences and Technology Houari Boumediene,Department of Telecommunication

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10537232/10537239/10537270.pdf?arnumber=10537270

Reference11 articles.

1. Modeling dynamic land use changes in the eastern portion of the hexi corridor, China by cnn-gru hybrid model

2. Coupling cellular automata with area partitioning and spatiotemporal convolution for dynamic land use change simulation

3. Spatio-temporal simulation and prediction of land-use change using conventional and machine learning models: a review

4. Classification of hyperspectral remote sensing images with support vector machines

5. Crop Type Identification and Mapping Using Machine Learning Algorithms and Sentinel-2 Time Series Data

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