[HTML][HTML] Modelling lidar-derived estimates of forest attributes over space and time: A review of approaches and future trends

NC Coops, P Tompalski, TRH Goodbody… - Remote Sensing of …, 2021 - Elsevier
Light detection and ranging (lidar) data acquired from airborne or spaceborne platforms
have revolutionized measurement and map** of forest attributes. Airborne data are often …

A review of machine learning in processing remote sensing data for mineral exploration

H Shirmard, E Farahbakhsh, RD Müller… - Remote Sensing of …, 2022 - Elsevier
The decline of the number of newly discovered mineral deposits and increase in demand for
different minerals in recent years has led exploration geologists to look for more efficient and …

Land cover classification using Google Earth Engine and random forest classifier—The role of image composition

TN Phan, V Kuch, LW Lehnert - Remote Sensing, 2020 - mdpi.com
Land cover information plays a vital role in many aspects of life, from scientific and economic
to political. Accurate information about land cover affects the accuracy of all subsequent …

Urban land use and land cover change analysis using random forest classification of landsat time series

S Amini, M Saber, H Rabiei-Dastjerdi, S Homayouni - Remote Sensing, 2022 - mdpi.com
Efficient implementation of remote sensing image classification can facilitate the extraction of
spatiotemporal information for land use and land cover (LULC) classification. Map** …

Landsat 9: Empowering open science and applications through continuity

JG Masek, MA Wulder, B Markham, J McCorkel… - Remote Sensing of …, 2020 - Elsevier
The history of Earth observation from space is well reflected through the Landsat program.
With data collection beginning with Landsat-1 in 1972, the program has evolved technical …

Current status of Landsat program, science, and applications

MA Wulder, TR Loveland, DP Roy, CJ Crawford… - Remote sensing of …, 2019 - Elsevier
Formal planning and development of what became the first Landsat satellite commenced
over 50 years ago in 1967. Now, having collected earth observation data for well over four …

A systematic review of landsat data for change detection applications: 50 years of monitoring the earth

MA Hemati, M Hasanlou, M Mahdianpari… - Remote sensing, 2021 - mdpi.com
With uninterrupted space-based data collection since 1972, Landsat plays a key role in
systematic monitoring of the Earth's surface, enabled by an extensive and free …

Spatiotemporal patterns and characteristics of land-use change in China during 2010–2015

J Ning, J Liu, W Kuang, X Xu, S Zhang, C Yan… - Journal of Geographical …, 2018 - Springer
Land use/cover change is an important theme on the impacts of human activities on the
earth systems and global environmental change. National land-use changes of China …

Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures

K Deilami, M Kamruzzaman, Y Liu - International journal of applied earth …, 2018 - Elsevier
Despite research on urban heat island (UHI) effect has increased exponentially over the last
few decades, a systematic review of factors contributing to UHI effect has scarcely been …

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 …