Land use and land cover mapping using Sentinel-2, Landsat-8 Satellite Images, and Google Earth Engine: A comparison of two composition methods

V Nasiri, A Deljouei, F Moradi, SMM Sadeghi, SA Borz - Remote Sensing, 2022 - mdpi.com
Accurate and real-time land use/land cover (LULC) maps are important to provide precise
information for dynamic monitoring, planning, and management of the Earth. With the advent …

[HTML][HTML] Cross-spatiotemporal land-cover classification from VHR remote sensing images with deep learning based domain adaptation

M Luo, S Ji - ISPRS Journal of Photogrammetry and Remote …, 2022 - Elsevier
Automatic land use/land cover (LULC) classification from very high resolution (VHR) remote
sensing images can provide us with rapid, large-scale, and fine-grained understanding of …

Satellite image time series analysis for big earth observation data

R Simoes, G Camara, G Queiroz, F Souza… - Remote Sensing, 2021 - mdpi.com
The development of analytical software for big Earth observation data faces several
challenges. Designers need to balance between conflicting factors. Solutions that are …

An interpretable analytic framework of the relationship between carsharing station development patterns and built environment for sustainable urban transportation

Y Ma, R Miao, Z Chen, B Zhang, L Bao - Journal of Cleaner Production, 2022 - Elsevier
The in-depth understanding of the relationship between development patterns of carsharing
stations and built environment are important to the comprehensive station evaluation, layout …

Exploring Switzerland's land cover change dynamics using a national statistical survey

IN Thomas, G Giuliani - Land, 2023 - mdpi.com
Timely and reliable Land Use and Cover change information is crucial to efficiently mitigate
the negative impact of environmental changes. Switzerland has the ambitious objective of …

Estimation of the conifer-broadleaf ratio in mixed forests based on time-series data

R Yang, L Wang, Q Tian, N Xu, Y Yang - Remote Sensing, 2021 - mdpi.com
Most natural forests are mixed forests, a mixed broadleaf-conifer forest is essentially a
heterogeneously mixed pixel in remote sensing images. Satellite missions rely on modeling …

Tracking the connection between Brazilian agricultural diversity and native vegetation change by a machine learning approach

MAS da Silva, LN Matos… - IEEE Latin America …, 2022 - ieeexplore.ieee.org
In Brazil, agribusiness has a considerable role in the country's GDP. Because of this, the
State needs territorial planning to minimize the impacts on natural resources, especially in …

Long time series high-quality and high-consistency land cover mapping based on machine learning method at heihe river basin

B Zhong, A Yang, K Jue, J Wu - Remote Sensing, 2021 - mdpi.com
Long time series of land cover changes (LCCs) are critical in the analysis of long-term
climate, environmental, and ecological changes. Although several moderate to fine …

Optimized software tools to generate large spatio-temporal data using the datacubes concept: Application to crop classification in cap bon, tunisia

A Chakhar, D Hernández-López, R Zitouna-Chebbi… - Remote Sensing, 2022 - mdpi.com
In the context of a changing climate, monitoring agricultural systems is becoming
increasingly important. Remote sensing products provide essential information for the crop …

Multimodal crop cover identification using deep learning and remote sensing

Z Ramzan, HMS Asif, M Shahbaz - Multimedia Tools and Applications, 2024 - Springer
Remote sensing is increasingly being used in agriculture and smart farming. Crop cover
identification is a major challenge that is useful in the identification of a particular crop at …