Development of a convolutional neural network to accurately detect land use and land cover

Author:

Acuña-Alonso CarolinaORCID,García-Ontiyuelo Mario,Barba-Barragáns Diego,Álvarez Xana

Publisher

Elsevier BV

Reference24 articles.

1. Land use land cover change modeling by integrating artificial neural network with cellular Automata-Markov chain model in Gidabo river basin, main Ethiopian rift;Girma;Environ. Challeng.,2022

2. Modelling and evaluation of land use changes through satellite images in a multifunctional catchment: social, economic and environmental implications;Acuña-Alonso;Ecol. Inform.,2022

3. Coastline extraction and land use change analysis using remote sensing (RS) and geographic information system (GIS) technology–a review of the literature;Yasir;Rev. Environ. Health,2020

4. PlanetScope contributions compared to Sentinel-2, and Landsat-8 for LULC mapping;Acharki;Remote Sens. Appl.,2022

5. Selecting features for LULC simultaneous classification of ambiguous classes by artificial neural network;Tolentino;Remote Sens. Appl.,2021

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. Research on Landscape Feature Recognition Based on Three-branch Fusion with Convolutional Neural Network;2024 Second International Conference on Data Science and Information System (ICDSIS);2024-05-17

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