[HTML][HTML] The role of remote sensing data and methods in a modern approach to fertilization in precision agriculture

D Radočaj, M Jurišić, M Gašparović - Remote Sensing, 2022 - mdpi.com
The precision fertilization system is the basis for upgrading conventional intensive
agricultural production, while achieving both high and quality yields and minimizing the …

Species-distribution modeling: advantages and limitations of its application. 2. MaxEnt

AA Lissovsky, SV Dudov - Biology Bulletin Reviews, 2021 - Springer
The MaxEnt software package is one of the most popular tools for species-distribution
modeling. Despite its popularity, researchers usually underestimate the influence of the …

A standardized catalogue of spectral indices to advance the use of remote sensing in Earth system research

D Montero, C Aybar, MD Mahecha, F Martinuzzi… - Scientific Data, 2023 - nature.com
Spectral Indices derived from multispectral remote sensing products are extensively used to
monitor Earth system dynamics (eg vegetation dynamics, water bodies, fire regimes). The …

[HTML][HTML] Global climate-related predictors at kilometer resolution for the past and future

P Brun, NE Zimmermann, C Hari… - Earth System …, 2022 - essd.copernicus.org
A multitude of physical and biological processes on which ecosystems and human societies
depend are governed by the climate, and understanding how these processes are altered …

LCZ Generator: a web application to create Local Climate Zone maps

M Demuzere, J Kittner, B Bechtel - Frontiers in Environmental Science, 2021 - frontiersin.org
Since their introduction in 2012, Local Climate Zones (LCZs) emerged as a new standard for
characterizing urban landscapes, providing a holistic classification approach that takes into …

Predicting long-term dynamics of soil salinity and sodicity on a global scale

A Hassani, A Azapagic, N Shokri - … of the National Academy of Sciences, 2020 - pnas.org
Knowledge of spatiotemporal distribution and likelihood of (re) occurrence of salt-affected
soils is crucial to our understanding of land degradation and for planning effective …

[HTML][HTML] Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables

T Hengl, M Nussbaum, MN Wright, GBM Heuvelink… - PeerJ, 2018 - peerj.com
Random forest and similar Machine Learning techniques are already used to generate
spatial predictions, but spatial location of points (geography) is often ignored in the modeling …

Soil carbon debt of 12,000 years of human land use

J Sanderman, T Hengl, GJ Fiske - Proceedings of the National Academy of …, 2017 - pnas.org
Human appropriation of land for agriculture has greatly altered the terrestrial carbon
balance, creating a large but uncertain carbon debt in soils. Estimating the size and spatial …

Topographic Wetness Index calculation guidelines based on measured soil moisture and plant species composition

M Kopecký, M Macek, J Wild - Science of the Total Environment, 2021 - Elsevier
Soil moisture controls environmental processes and species distributions, but it is difficult to
measure and interpolate across space. Topographic Wetness Index (TWI) derived from …

African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning

T Hengl, MAE Miller, J Križan, KD Shepherd, A Sila… - Scientific reports, 2021 - nature.com
Soil property and class maps for the continent of Africa were so far only available at very
generalised scales, with many countries not mapped at all. Thanks to an increasing quantity …