Machine learning for digital soil map**: Applications, challenges and suggested solutions

AMJC Wadoux, B Minasny, AB McBratney - Earth-Science Reviews, 2020 - Elsevier
The uptake of machine learning (ML) algorithms in digital soil map** (DSM) is
transforming the way soil scientists produce their maps. Within the past two decades, soil …

[HTML][HTML] The spatial allocation of population: a review of large-scale gridded population data products and their fitness for use

S Leyk, AE Gaughan, SB Adamo… - Earth System …, 2019 - essd.copernicus.org
Population data represent an essential component in studies focusing on human–nature
interrelationships, disaster risk assessment and environmental health. Several recent efforts …

Combining multi-source data and machine learning approaches to predict winter wheat yield in the conterminous United States

Y Wang, Z Zhang, L Feng, Q Du, T Runge - Remote Sensing, 2020 - mdpi.com
Winter wheat (Triticum aestivum L.) is one of the most important cereal crops, supplying
essential food for the world population. Because the United States is a major producer and …

A building volume adjusted nighttime light index for characterizing the relationship between urban population and nighttime light intensity

B Wu, C Yang, Q Wu, C Wang, J Wu, B Yu - Computers, Environment and …, 2023 - Elsevier
The brightness of nighttime lights (NTL) has been proven to be strongly related to population
density and thus has been widely used for population estimation from national to county …

Determinants of passengers' ticketing channel choice in rail transit systems: New evidence of e-payment behaviors from ** review of the field and strategic research agenda

DR Thomson, DA Rhoda, AJ Tatem… - International journal of …, 2020 - Springer
Introduction In low-and middle-income countries (LMICs), household survey data are a main
source of information for planning, evaluation, and decision-making. Standard surveys are …

Evaluating the accuracy of gridded population estimates in slums: a case study in Nigeria and Kenya

DR Thomson, AE Gaughan, FR Stevens, G Yetman… - Urban Science, 2021 - mdpi.com
Low-and middle-income country cities face unprecedented urbanization and growth in
slums. Gridded population data (eg,~ 100× 100 m) derived from demographic and spatial …

Bare‐Earth DEM generation in urban areas for flood inundation simulation using global digital elevation models

Y Liu, PD Bates, JC Neal… - Water Resources …, 2021 - Wiley Online Library
Accurate terrain representation is critical to estimating flood risk in urban areas. However, all
current global elevation data sets can be regarded as digital surface models in urban areas …