Remote sensing and forest inventories in Nordic countries–roadmap for the future

A Kangas, R Astrup, J Breidenbach… - … Journal of Forest …, 2018 - Taylor & Francis
The Nordic countries have long traditions in forest inventory and remote sensing (RS). In
sample-based national forest inventories (NFIs), utilization of aerial photographs started …

Towards optimizing riparian buffer zones: Ecological and biogeochemical implications for forest management

L Kuglerová, A Ågren, R Jansson, H Laudon - Forest Ecology and …, 2014 - Elsevier
Riparian forests (RFs) along streams and rivers in forested landscapes provide many
ecosystem functions that are important for the biodiversity and biogeochemistry of both …

Contrasting responses of above-and belowground diversity to multiple components of land-use intensity

G Le Provost, J Thiele, C Westphal, C Penone… - Nature …, 2021 - nature.com
Land-use intensification is a major driver of biodiversity loss. However, understanding how
different components of land use drive biodiversity loss requires the investigation of multiple …

[HTML][HTML] Google Earth Engine, open-access satellite data, and machine learning in support of large-area probabilistic wetland map**

JN Hird, ER DeLancey, GJ McDermid, J Kariyeva - Remote sensing, 2017 - mdpi.com
Modern advances in cloud computing and machine-leaning algorithms are shifting the
manner in which Earth-observation (EO) data are used for environmental monitoring …

TWI computation: a comparison of different open source GISs

P Mattivi, F Franci, A Lambertini, G Bitelli - Open Geospatial Data, Software …, 2019 - Springer
The opportunities of retrieving geospatial datasets as open data and the reliability of Free
and Open Source Software (FOSS) GIS increased the possibilities of performing a large …

Landscape‐variability of the carbon balance across managed boreal forests

M Peichl, E Martínez‐García… - Global Change …, 2023 - Wiley Online Library
Boreal forests are important global carbon (C) sinks and, therefore, considered as a key
element in climate change mitigation policies. However, their actual C sink strength is …

A tree-based intelligence ensemble approach for spatial prediction of potential groundwater

M Avand, S Janizadeh, D Tien Bui… - … Journal of Digital …, 2020 - Taylor & Francis
The objective of this research is to propose and confirm a new machine learning approach
of Best-First tree (BFtree), AdaBoost (AB), MultiBoosting (MB), and Bagging (Bag) …

[HTML][HTML] Use of multiple LIDAR-derived digital terrain indices and machine learning for high-resolution national-scale soil moisture map** of the Swedish forest …

AM Ågren, J Larson, SS Paul, H Laudon, W Lidberg - Geoderma, 2021 - Elsevier
Spatially extensive high-resolution soil moisture map** is valuable in practical forestry
and land management, but challenging. Here we present a novel technique involving use of …

Digital map** of soil texture classes for efficient land management in the Piedmont plain of Iran

A Keshavarzi, MÁS del Árbol, F Kaya… - Soil Use and …, 2022 - Wiley Online Library
Accurate prediction of digital soil maps allows for the evaluation of larger areas with respect
to the design of efficient land management plans at the regional scale. Nowadays, there is …

A comparative assessment of machine learning models for landslide susceptibility map** in the rugged terrain of northern Pakistan

N Shahzad, X Ding, S Abbas - Applied Sciences, 2022 - mdpi.com
This study investigated the performances of different techniques, including random forest
(RF), support vector machine (SVM), maximum entropy (maxENT), gradient-boosting …