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 …

Support vector machine versus random forest for remote sensing image classification: A meta-analysis and systematic review

M Sheykhmousa, M Mahdianpari… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
Several machine-learning algorithms have been proposed for remote sensing image
classification during the past two decades. Among these machine learning algorithms …

Implementation of machine-learning classification in remote sensing: An applied review

AE Maxwell, TA Warner, F Fang - International journal of remote …, 2018 - Taylor & Francis
Machine learning offers the potential for effective and efficient classification of remotely
sensed imagery. The strengths of machine learning include the capacity to handle data of …

[HTML][HTML] Tree species classification from airborne hyperspectral and LiDAR data using 3D convolutional neural networks

J Mäyrä, S Keski-Saari, S Kivinen… - Remote Sensing of …, 2021 - Elsevier
During the last two decades, forest monitoring and inventory systems have moved from field
surveys to remote sensing-based methods. These methods tend to focus on economically …

PEATMAP: Refining estimates of global peatland distribution based on a meta-analysis

J Xu, PJ Morris, J Liu, J Holden - Catena, 2018 - Elsevier
Peatlands play important ecological, economic and cultural roles in human well-being.
Although considered sensitive to climate change and anthropogenic pressures, the spatial …

A meta-analysis of remote sensing research on supervised pixel-based land-cover image classification processes: General guidelines for practitioners and future …

R Khatami, G Mountrakis, SV Stehman - Remote sensing of environment, 2016 - Elsevier
Classification of remotely sensed imagery for land-cover map** purposes has attracted
significant attention from researchers and practitioners. Numerous studies conducted over …

Distribution of ecological restoration projects associated with land use and land cover change in China and their ecological impacts

X Chen, L Yu, Z Du, Y Xu, J Zhao, H Zhao… - Science of The Total …, 2022 - Elsevier
China is prone to broad land degradation and thus has been implementing ecological
restoration projects (ERPs) since the reform and opening up. The extent of ERPs, as well as …

[HTML][HTML] Who launched what, when and why; trends in global land-cover observation capacity from civilian earth observation satellites

AS Belward, JO Skøien - ISPRS Journal of Photogrammetry and Remote …, 2015 - Elsevier
This paper presents a compendium of satellites under civilian and/or commercial control
with the potential to gather global land-cover observations. From this we show that a …

Automated production of a land cover/use map of Europe based on Sentinel-2 imagery

R Malinowski, S Lewiński, M Rybicki, E Gromny… - Remote Sensing, 2020 - mdpi.com
Up-to-date information about the Earth's surface provided by land cover maps is essential for
numerous environmental and land management applications. There is, therefore, a clear …

Comparing deep neural networks, ensemble classifiers, and support vector machine algorithms for object-based urban land use/land cover classification

SE Jozdani, BA Johnson, D Chen - Remote Sensing, 2019 - mdpi.com
With the advent of high-spatial resolution (HSR) satellite imagery, urban land use/land cover
(LULC) map** has become one of the most popular applications in remote sensing. Due …