Results 91 to 100 of about 401 (164)

GEOBIA 2016: Solutions and synergies [PDF]

, 2016
openaire   +2 more sources

Mapping abandoned cropland using Within-Year Sentinel-2 time series. [PDF]

Catena (Amst), 2023
Liu B, Song W.
europepmc   +1 more source

A Semi-Automated Object-Based Gully Networks Detection Using Different Machine Learning Models: A Case Study of Bowen Catchment, Queensland, Australia. [PDF]

Sensors (Basel), 2019
Shahabi H, Jarihani B, Tavakkoli Piralilou S, Chittleborough D, Avand M, Ghorbanzadeh O.   +5 more
europepmc   +1 more source

An integrated learning algorithm for early prediction of melon harvest. [PDF]

Sci Rep, 2022
Qian C, Du T, Sun S, Liu W, Zheng H, Wang J.   +5 more
europepmc   +1 more source

Active Actions in the Extraction of Urban Objects for Information Quality and Knowledge Recommendation with Machine Learning. [PDF]

Sensors (Basel), 2022
Silva LA, Sales Mendes A, Sánchez San Blas H, Caetano Bastos L, Leopoldo Gonçalves A, Fabiano de Moraes A.   +5 more
europepmc   +1 more source

A review on advancements in lithological mapping utilizing machine learning algorithms and remote sensing data. [PDF]

Heliyon, 2023
El-Omairi MA, El Garouani A.
europepmc   +1 more source

Climate-Triggered Insect Defoliators and Forest Fires Using Multitemporal Landsat and TerraClimate Data in NE Iran: An Application of GEOBIA TreeNet and Panel Data Analysis. [PDF]

Sensors (Basel), 2019
Abdi O.
europepmc   +1 more source

Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso. [PDF]

Parasit Vectors, 2021
Taconet P, Porciani A, Soma DD, Mouline K, Simard F, Koffi AA, Pennetier C, Dabiré RK, Mangeas M, Moiroux N.   +9 more
europepmc   +1 more source

GeOBIA Approaches to Remote Sensing of Fossil Landscapes: Two Case Studies from Northern Italy

This paper presents the preliminary results of an object-based image analysis aimed at the implementation of a package of procedures of remotely sensed object/ pattern/ scenery recognition specificallydesigned for the semi-automatic and automatic recognition of a batch of critical archaeological and ethnoarchaeological features. The research focuses on
DE GUIO, ARMANDO, MAGNINI, LUIGI, BETTINESCHI, CINZIA   +2 more
openaire   +6 more sources

Intelligent Object Recognition of Urban Water Bodies Based on Deep Learning for Multi-Source and Multi-Temporal High Spatial Resolution Remote Sensing Imagery. [PDF]

Sensors (Basel), 2020
Song S, Liu J, Liu Y, Feng G, Han H, Yao Y, Du M.   +6 more
europepmc   +1 more source