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This study provides an overview of the techniques, shortcomings, and strengths of remote sensing (RS) applications in the effective retrieval and monitoring of water quality parameters (WQPs) such as chlorophyll-a concentration, turbidity, total suspended solids, colored dissolved organic matter, total dissolved solids among others. To be effectively retrieved by RS, these WQPs are categorized as optically active or inactive based on their influence on the optical characteristics measured by RS sensors. RS applications offer the opportunity for decisionmakers to quantify and monitor WQPs on a spatiotemporal scale effectively. The use of RS for water quality monitoring has been explored in many studies using empirical, analytical, semi-empirical, and machine-learning algorithms. RS spectral signatures have been applied for the estimation of WQPs using two categories of RS, namely, microwave and optical sensors. Optical RS, which has been heavily applied in the estimation of WQPs, is further grouped as spaceborne and airborne sensors based on the platform they are on board. The choice of a particular sensor to be used in any RS application depends on various factors including cost, and spatial, spectral, and temporal resolutions of the images. Some of the known satellite sensors used in the literature and reviewed in this paper include the Multispectral Instrument aboard Sentinel-2A/B, Moderate Resolution Imaging Spectroradiometer, Landsat Thematic Mapper, Enhanced Thematic Mapper, and Operational Land Imager.

Spatially extensive Arctic stable isotope data are sparse, inhibiting the climatic understanding required to interpret paleoclimate proxy records. To fill this need, we constrained the climatic and physiographic controls on δ18O and δD values of stream waters across Alaska and the Yukon to derive interpolated isoscape maps. δ18O is strongly correlated to winter temperature parameters and similarity of the surface water line (δ2H = 8.0 × δ18O + 6.4) to the Global Meteoric Water Line suggests stream waters are a proxy for meteoric precipitation. We observe extreme orographic δ18O decreases and a trans‐Alaskan continental gradient of −8.3‰ 1000 km−1. Continental gradients are high in coastal zones and low in the interior. Localized δ18O increases indicate inland air mass penetration via topographic lows. Using observed δ18O/temperature gradients, we show that δ18O decreases in a ∼24 ka permafrost ice wedge relative to the late Holocene indicate mean annual and coldest quarter temperature reductions of 8.9 ± 1.7°C and 17.2 ± 3.2°C, respectively.

Abstract-The Sahara desert includes large expanses of sand dunes called ergs. These dunes are formed and constantly reshaped by prevailing winds. Previous study shows that Saharan ergs exhibit significant radar backscatter ( ) modulation with azimuth angle ( ). We use measurements observed at various incidence angles and from the NASA Scatterometer (NSCAT), the SeaWinds scatterometer, the ERS scatterometer (ESCAT), and the Tropical Rainfall Measuring Mission's Precipitation Radar to model the response from sand dunes. Observations reveal a characteristic relationship between the backscatter modulation and the dune type, i.e., the number and orientation of the dune slopes. Sand dunes are modeled as a composite of tilted rough facets, which are characterized by a probability distribution of tilt with a mean value, and small ripples on the facet surface. The small ripples are modeled as cosinusoidal surface waves that contribute to the return signal at Bragg angles only. Longitudinal and transverse dunes are modeled with rough facets having Gaussian tilt distributions. The model results in a response similar to NSCAT and ESCAT observations over areas of known dune types in the Sahara. The response is high at look angles equal to the mean tilts of the rough facets and is lower elsewhere. This analysis provides a unique insight into scattering by large-scale sand bedforms.

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