Related papers: A Geospatial Functional Model For OCO-2 Data with …
To limit global warming to pre-industrial levels, global governments, industry and academia are taking aggressive efforts to reduce carbon emissions. The evaluation of anthropogenic carbon dioxide (CO$_2$) emissions, however, depends on the…
Atmospheric Carbon Monoxide (CO) provides a window on the chemistry of the atmosphere since it is one of few chemical constituents that can be remotely sensed, and it can be used to determine budgets of other greenhouse gases such as ozone…
Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for big scattered datasets in $n-$dimensional space. It is a non-separable approximation, as it is…
Atmospheric retrievals are widely used to constrain exoplanet properties from observed spectra. We investigate how the common nonphysical retrieval assumptions of vertically constant molecule abundances and cloud-free atmospheres affect our…
Accurate soil moisture (SM) estimation is critical for precision agriculture, water resources management and climate monitoring. Yet, existing satellite SM products are too coarse (>1km) for farm-level applications. We present a…
As a test-bed for future investigations of directly imaged terrestrial exoplanets, we present the recovery of the surface components of the Earth from multi-band diurnal light curves obtained with the EPOXI spacecraft. We find that the…
Future astrophysics missions will seek extraterrestrial life via transmission and direct imaging observations. To assess habitability and biosignatures, we need robust retrieval tools to analyze observed spectra, and infer surface and…
Solar irradiance is fundamental data crucial for analyses related to weather and climate. High-precision estimation models are necessary to create areal data for solar irradiance. In this study, we developed a novel estimation model by…
We measure the visible and near-infrared reflectance of icy analogues of the Martian surface made of CO$_2$ ice associated in different ways with H$_2$O ice and the regolith simulant JSC Mars-1. Such experimental results obtained with…
Land use classification of low resolution spatial imagery is one of the most extensively researched fields in remote sensing. Despite significant advancements in satellite technology, high resolution imagery lacks global coverage and can be…
The growing availability of Earth Observation (EO) data and recent advances in Computer Vision have driven rapid progress in machine learning for EO, producing domain-specific models at ever-increasing scales. Yet this progress risks…
Accurate assessment of atmospheric nitrogen dioxide (NO$_2$) and sulfur dioxide (SO$_2$) is essential for understanding climate-air quality interactions, supporting environmental policy, and protecting public health. Traditional monitoring…
In this paper, we address the challenge of land use and land cover classification using Sentinel-2 satellite images. The Sentinel-2 satellite images are openly and freely accessible provided in the Earth observation program Copernicus. We…
Motivated by the development of high-dispersion spectrographs in the mid-infrared (MIR) range, we study their application to the atmospheric characterization of nearby non-transiting temperate terrestrial planets around M-type stars. We…
Environmental variables are increasingly affecting agricultural decision-making, yet accessible and scalable tools for soil assessment remain limited. This study presents a robust and scalable modeling system for estimating soil properties…
The conventional observables to identify a habitable or inhabited environment in exoplanets, such as an ocean glint or abundant atmospheric O$_2$, will be challenging to detect with present or upcoming observatories. Here we suggest a new…
This paper proposes a novel framework for fusing multi-temporal, multispectral satellite images and OpenStreetMap (OSM) data for the classification of local climate zones (LCZs). Feature stacking is the most commonly-used method of data…
Spectrum sensing is an essential functionality that enables cognitive radios to detect spectral holes and opportunistically use under-utilized frequency bands without causing harmful interference to primary networks. Since individual…
Converting CO$_2$ to useful compounds through the solar photocatalytic reduction has been one of the most promising strategies for artificial carbon recycling. The highly relevant photocatalytic substrate for CO$_2$ conversion has been the…
We present near infrared spectroscopic observations of 19 molecular clouds made using the AKARI satellite, and the data reduction pipeline written to analyse those observations. The 2.5 --~5 $\mu$m spectra of 30 objects -- 22 field stars…