[HTML][HTML] Downscaling satellite night-time lights imagery to support within-city applications using a spatially non-stationary model

N Tziokas, C Zhang, GC Drolias, PM Atkinson - International Journal of …, 2023 - Elsevier
For mapping and monitoring socioeconomic activities in cities, night-time lights (NTL)
satellite sensor images are used widely, measuring the light intensity during the night …

Understanding Dynamics of Land Use & Land Cover Change Using GIS & Change Detection Techniques in Tartous, Syria

A Younes, A Ahmad, AD Hanjagi… - European Journal of …, 2023 - eurogeojournal.eu
Although Tartous governorate accounts for only 1% of the total land area of Syria, it recorded
the highest burden of Internally Displaced Persons (IDPs) during the Syrian crisis, with …

Characterizing the effect of scaling errors on the spatial downscaling of mountain vegetation gross primary productivity

X Xie, A Li - Geo-spatial Information Science, 2023 - Taylor & Francis
ABSTRACT High spatial resolution Gross Primary Productivity (GPP) estimation makes it
feasible to better understand the spatial heterogeneity of mountain vegetation …

[HTML][HTML] Not just a pretty picture: Mapping Leaf Area Index at 10 m resolution using Sentinel-2

R Fernandes, G Hong, LA Brown, J Dash… - Remote Sensing of …, 2024 - Elsevier
Abstract Achieving the Global Climate Observing System goal of 10 m resolution leaf area
index (LAI) maps is critical for applications related to climate adaptation, sustainable …

A cross-resolution, spatiotemporal geostatistical fusion model for combining satellite image time-series of different spatial and temporal resolutions

Y Kim, PC Kyriakidis, NW Park - Remote Sensing, 2020 - mdpi.com
Dense time-series with coarse spatial resolution (DTCS) and sparse time-series with fine
spatial resolution (STFS) data often provide complementary information. To make full use of …

An object-based weighting approach to spatiotemporal fusion of high spatial resolution satellite images for small-scale cropland monitoring

S Park, NW Park, S Na - Agronomy, 2022 - mdpi.com
Continuous crop monitoring often requires a time-series set of satellite images. Since
satellite images have a trade-off in spatial and temporal resolution, spatiotemporal image …

Introducing Variations of Predictors as Optional Predictors Offers the Potential to Improve the Downscaling Performance of Geographically Weighted Regression …

H Zhang, J Bai, S Dai, P Qi, S Wang, H Fan - IEEE Access, 2023 - ieeexplore.ieee.org
Are the variations of the fine predictors at the spatial scale of the target variable to be
downscaled helpful for spatial downscaling? However, few studies have explored this topic …

[PDF][PDF] Cloud removal using Gaussian process regression for optical image reconstruction

S Park, NW Park - Korean J. Remote Sens, 2022 - researchgate.net
Cloud removal is often required to construct time-series sets of optical images for
environmental monitoring. In regression-based cloud removal, the selection of an …

Sensitivity Analysis of Regression-Based Trend Estimates to Input Errors in Spatial Downscaling of Coarse Resolution Remote Sensing Data

GH Kwak, S Hong, NW Park - Applied Sciences, 2023 - mdpi.com
This paper compared the predictive performance of different regression models for trend
component estimation in the spatial downscaling of coarse resolution satellite data using …

Delineating Potential Groundwater Recharge Zones in the Semi‐Arid Eastern Plains of Rajasthan, India

V Garg, M Kumar, M Dashora, R Kumar… - CLEAN–Soil, Air …, 2024 - Wiley Online Library
Surface and subsurface anomalies, hydrological conditions, and dynamic interactions
between embedded thematic layers influence groundwater recharge potential (GRP) …