Remote sensing in forestry: current challenges, considerations and directions

FE Fassnacht, JC White, MA Wulder… - … An International Journal …, 2024 - academic.oup.com
Remote sensing has developed into an omnipresent technology in the scientific field of
forestry and is also increasingly used in an operational fashion. However, the pace and level …

A review of regional and Global scale Land Use/Land Cover (LULC) map** products generated from satellite remote sensing

Y Wang, Y Sun, X Cao, Y Wang, W Zhang… - ISPRS Journal of …, 2023 - Elsevier
Abstract Land Use and Land Cover (LULC) map** products are essential for various
environmental studies, including ecological environmental assessments, resource …

[HTML][HTML] The segment anything model (sam) for remote sensing applications: From zero to one shot

LP Osco, Q Wu, EL De Lemos, WN Gonçalves… - International Journal of …, 2023 - Elsevier
Segmentation is an essential step for remote sensing image processing. This study aims to
advance the application of the Segment Anything Model (SAM), an innovative image …

30 m annual land cover and its dynamics in China from 1990 to 2019

J Yang, X Huang - Earth System Science Data Discussions, 2021 - essd.copernicus.org
Land cover (LC) determines the energy exchange, water and carbon cycle between Earth's
spheres. Accurate LC information is a fundamental parameter for the environment and …

Comparison of land use land cover classifiers using different satellite imagery and machine learning techniques

S Basheer, X Wang, AA Farooque, RA Nawaz, K Liu… - Remote Sensing, 2022 - mdpi.com
Accurate land use land cover (LULC) classification is vital for the sustainable management
of natural resources and to learn how the landscape is changing due to climate. For …

Deep learning for time series classification and extrinsic regression: A current survey

N Mohammadi Foumani, L Miller, CW Tan… - ACM Computing …, 2024 - dl.acm.org
Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …

Machine learning in modelling land-use and land cover-change (LULCC): Current status, challenges and prospects

J Wang, M Bretz, MAA Dewan, MA Delavar - Science of the Total …, 2022 - Elsevier
Land-use and land-cover change (LULCC) are of importance in natural resource
management, environmental modelling and assessment, and agricultural production …

[HTML][HTML] Identifying the land use land cover (LULC) changes using remote sensing and GIS approach: A case study at Bhaluka in Mymensingh, Bangladesh

MMH Seyam, MR Haque, MM Rahman - Case Studies in Chemical and …, 2023 - Elsevier
LULC is vital to investigate land use patterns and hel** forecast future sustainable land
management. The study area is a freshly emerging and quickly industrialized area in …

Land use and land cover as a conditioning factor in landslide susceptibility: a literature review

R Pacheco Quevedo, A Velastegui-Montoya… - Landslides, 2023 - Springer
Landslide occurrence has become increasingly influenced by human activities. Accordingly,
changing land use and land cover (LULC) is an important conditioning factor in landslide …

SinoLC-1: The first 1-meter resolution national-scale land-cover map of China created with the deep learning framework and open-access data

Z Li, W He, M Cheng, J Hu, G Yang… - Earth System Science …, 2023 - essd.copernicus.org
In China, the demand for a more precise perception of the national land surface has become
most urgent given the pace of development and urbanization. Constructing a very-high …