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Remote sensing in forestry: current challenges, considerations and directions
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 …
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 …
environmental studies, including ecological environmental assessments, resource …
[HTML][HTML] The segment anything model (sam) for remote sensing applications: From zero to one shot
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 …
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
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 …
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
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 …
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
Time Series Classification and Extrinsic Regression are important and challenging machine
learning tasks. Deep learning has revolutionized natural language processing and computer …
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
Land-use and land-cover change (LULCC) are of importance in natural resource
management, environmental modelling and assessment, and agricultural production …
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
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 …
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
Landslide occurrence has become increasingly influenced by human activities. Accordingly,
changing land use and land cover (LULC) is an important conditioning factor in landslide …
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
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 …
most urgent given the pace of development and urbanization. Constructing a very-high …