A wide range of methods for analysis of airborne- and satellite-derived imagery continues to
be proposed and assessed. In this paper, we review remote sensing implementations of …

Since coastal waters are one of the most vulnerable marine systems to environmental pollution,
it is very important to operationally monitor coastal water quality. This study attempts to …

While existing remote sensing-based drought indices have characterized drought conditions
in arid regions successfully, their use in humid regions is limited. We propose a new remote …

This study introduces change detection based on object/neighbourhood correlation image
analysis and image segmentation techniques. The correlation image analysis is based on the …

This study introduces a change detection model based on Neighborhood Correlation Image
(NCI) logic. It is based on the fact that the same geographic area (eg, a 3×3 pixel window) …

During the past decade, procedures for forest biomass quantification from light detection
and ranging (LiDAR) data have been improved at a rapid pace. The scope of these methods …

This study evaluated the synergistic use of high spatial resolution multispectral imagery (ie,
QuickBird, 2.4m) and low-posting-density LIDAR data (3m) for forest species classification …

Forecasts of maximum and minimum air temperatures are essential to mitigate the damage
of extreme weather events such as heat waves and tropical nights. The Numerical Weather …

Particulate matter (PM) is a widely used indicator of air quality. Satellite-derived aerosol
products such as aerosol optical depth (AOD) have been a useful source of data for ground-level …

Vegetation indices are important remotely sensed metrics for ecosystem monitoring and
land surface process assessment, among which Normalized Difference Vegetation Index (NDVI) …