Spatiotemporal change analysis and prediction of future land use and land cover changes using QGIS MOLUSCE plugin and remote sensing big data: a case study of …

R Muhammad, W Zhang, Z Abbas, F Guo… - Land, 2022 - mdpi.com
Land use and land cover (LULC) change analysis is a systematic technique that aids in the
comprehension of physical and non-physical interaction with the natural habitat and the …

A survey on uncertainty quantification methods for deep neural networks: An uncertainty source perspective

W He, Z Jiang - arXiv preprint arXiv:2302.13425, 2023 - arxiv.org
Deep neural networks (DNNs) have achieved tremendous success in making accurate
predictions for computer vision, natural language processing, as well as science and …

[HTML][HTML] Assessing the spatial sensitivity of a random forest model: Application in gridded population modeling

P Sinha, AE Gaughan, FR Stevens, JJ Nieves… - … Environment and Urban …, 2019 - Elsevier
Gridded human population data provide a spatial denominator to identify populations at risk,
quantify burdens, and inform our understanding of human-environment systems. When …

A survey on spatial prediction methods

Z Jiang - IEEE transactions on knowledge and Data …, 2018 - ieeexplore.ieee.org
With the advancement of GPS and remote sensing technologies, large amounts of
geospatial data are being collected from various domains, driving the need for effective and …

Deep Learning for Spatiotemporal Big Data: A Vision on Opportunities and Challenges

Z Jiang - arXiv preprint arXiv:2310.19957, 2023 - arxiv.org
With advancements in GPS, remote sensing, and computational simulation, an enormous
volume of spatiotemporal data is being collected at an increasing speed from various …

Agricultural big data and methods and models for food security analysis—a mini-review

KA Ammar, AMS Kheir, I Manikas - PeerJ, 2022 - peerj.com
Background Big data and data analysis methods and models are important tools in food
security (FS) studies for gap analysis and preparation of appropriate analytical frameworks …

A data science framework for movement

S Dodge - Geographical Analysis, 2021 - Wiley Online Library
Movement is the driving force behind the form and function of many ecological and human
systems. Identification and analysis of movement patterns that may relate to the behavior of …

A graph neural network framework for spatial geodemographic classification

S De Sabbata, P Liu - International Journal of Geographical …, 2023 - Taylor & Francis
Geodemographic classifications are exceptional tools for geographic analysis, business and
policy-making, providing an overview of the socio-demographic structure of a region by …

Modeling the Temporal Population Distribution of Mosquito Using Big Earth Observation Data

O Mudele, FM Bayer, LFR Zanandrez, AE Eiras… - Ieee …, 2020 - ieeexplore.ieee.org
Over 50% of the world population is at risk of mosquito-borne diseases. Female Ae. aegypti
mosquito species transmit Zika, Dengue, and Chikungunya. The spread of these diseases …

Machine learning meets big spatial data

I Sabek, MF Mokbel - 2020 IEEE 36th International Conference …, 2020 - ieeexplore.ieee.org
The proliferation in amounts of generated data has propelled the rise of scalable machine
learning solutions to efficiently analyze and extract useful insights from such data …