High-resolution Data Products Research Articles

Evaluating main drivers of terrestrial water storage depletion in the agro-pastoral ecotone of northern China

With the heightened threat of declining terrestrial groundwater, determining the effects of changing environments on terrestrial water storage anomaly (TWSA) is essential for water resource management. As a critical element of the water cycle, the multi-effects of the natural and artificial factors on TWSA were still not fully understood and quantified. Using multiple high-resolution data products and the structural equation model (SEM), this study discussed how climate, vegetation, and human activities affected terrestrial water storage (TWS) in the West Liao River basin (WLRB), China, from 1990 to 2020. The results confirmed that vegetation showed a greening trend while TWS depleted at 5.93 cm/10a in the WLRB. TWS in greening areas has a negative correlation with vegetation growth. The decline in TWS is mainly dominated by precipitation and runoff variability. By influencing eco-hydrological cycle processes, climate change and human activities affect TWS through direct and indirect(by influencing NDVI) pathways. Land use change, manifested as conversion of grassland into cropland, contributed to the most decline of TWS (51.2 %). Moreover, the crop yield increasing, climate warming, and vegetation greening could lead to TWS depletion. Spatially, the overexploitation of the groundwater for irrigation to support crop production was probably the most critical cause of TWS depletion over upstream of the WLRB. Furthermore, in the West Liao Plain, the intensified vegetation greenness also led to the increasing ecosystem water demand, resulting in the decrease of TWS. This study improves our understanding of the interaction of the basinal eco-hydrological system and provides a hint that reducing groundwater extraction and implementing agriculture fallow is essential to recovering water storage and alleviating the water resource crisis in the agro-pastoral ecotone.

Intraurban NO2 hotspot detection across multiple air quality products

High-resolution air quality data products have the potential to help quantify inequitable environmental exposures over space and across time by enabling the identification of hotspots, or areas that consistently experience elevated pollution levels relative to their surroundings. However, when different high-resolution data products identify different hotspots, the spatial sparsity of ‘gold-standard’ regulatory observations leaves researchers, regulators, and concerned citizens without a means to differentiate signal from noise. This study compares NO2 hotspots detected within the city of Chicago, IL, USA using three distinct high-resolution (1.3 km) air quality products: (1) an interpolated product from Microsoft Research’s Project Eclipse—a dense network of over 100 low-cost sensors; (2) a two-way coupled WRF-CMAQ simulation; and (3) a down-sampled product using TropOMI satellite instrument observations. We use the Getis-Ord Gi * statistic to identify hotspots of NO2 and stratify results into high-, medium-, and low-agreement hotspots, including one consensus hotspot detected in all three datasets. Interrogating medium- and low-agreement hotspots offers insights into dataset discrepancies, such as sensor placement and model physics considerations, data retrieval caveats, and the potential for missing emission inventories. When treated as complements rather than substitutes, our work demonstrates that novel air quality products can enable researchers to address discrepancies in data products and can help regulators evaluate confidence in policy-relevant insights.

A novel approach to quantify metrics of upwelling intensity, frequency, and duration.

The importance of coastal upwelling systems is widely recognized. However, several aspects of the current and future behaviors of these systems remain uncertain. Fluctuations in temperature because of anthropogenic climate change are hypothesized to affect upwelling-favorable winds and coastal upwelling is expected to intensify across all Eastern Boundary Upwelling Systems. To better understand how upwelling may change in the future, it is necessary to develop a more rigorous method of quantifying this phenomenon. In this paper, we use SST data and wind data in a novel method of detecting upwelling signals and quantifying metrics of upwelling intensity, duration, and frequency at four sites within the Benguela Upwelling System. We found that indicators of upwelling are uniformly detected across five SST products for each of the four sites and that the duration of those signals is longer in SST products with higher spatial resolutions. Moreover, the high-resolution SST products are significantly more likely to display upwelling signals at 25 km away from the coast when signals were also detected at the coast. Our findings promote the viability of using SST and wind time series data to detect upwelling signals within coastal upwelling systems. We highlight the importance of high-resolution data products to improve the reliability of such estimates. This study represents an important step towards the development of an objective method for describing the behavior of coastal upwelling systems.

Fully Convolutional Neural Network for Impervious Surface Segmentation in Mixed Urban Environment

The urgency of creating appropriate, high-resolution data products such as impervious cover information has increased as cities face rapid growth as well as climate change and other environmental challenges. This work explores the use of fully convolutional neural networks (FCNNs )—specifically UNet with a ResNet-152 encoder—in mapping impervious surfaces at the pixel level from WorldView-2 in a mixed urban/residential environment. We investigate three-, four-, and eight-band multispectral inputs to the FCNN. Resulting maps are promising in both qualitative and quantitative assessment when compared to automated land use/land cover products. Accuracy was assessed by F1 and average precision (AP) scores, as well as receiver operating characteristic curves, with area under the curve (AUC ) used as an additional accuracy metric. The four-band model shows the highest average test-set accuracies (F1, AP, and AUC of 0.709, 0.82, and 0.807, respectively), with higher AP and AUC than the automated land use/land cover products, indicating the utility of the blue-green-red-infrared channels for the FCNN. Improved performance was seen in residential areas, with worse performance in more densely developed areas.

The Oasis impact structure, Libya: geological characteristics from ALOS PALSAR-2 data interpretation

Optical and infrared remote sensing may provide first-order clues for the identification of potential impact structures on the Earth. Despite the free availability of at least optical image data at highest resolution, research has shown that remote sensing analysis always remains inconclusive and extensive groundwork is needed for the confirmation of the impact origin of such structures. Commonly, optical image data and digital terrain models have been employed mainly for such remote sensing studies of impact structures. With the advent of imaging radar data, a few excursions have been made to also employ radar datasets. Despite its long use, capabilities of imaging radar for studying surface and subsurface structures have not been exploited quantitatively when applied for the identification and description of such features due to the inherent complexity of backscatter processes. In this work, we make use of higher-level derived radar datasets in order to gain clearer qualitative insights that help to describe and identify potential impact structures. We make use of high-resolution data products from the ALOS PALSAR-1 and ALOS PALSAR-2 L-band sensors to describe the heavily eroded Oasis impact structure located in the Libyan Desert. While amplitude radar data with single polarization have usually been utilized to accompany the suite of remote sensing datasets when interpreting impact structures in the past, we conclude that the integration of amplitude data with HH/HV/HH–HV polarization modes in standard and, in particular, in Ultra-Fine mode, as well as entropy–alpha decomposition data, significantly helps to identify and discriminate surface units based on their consolidation. Based on the overarching structural pattern, we determined the diameter of the eroded Oasis structure at 15.6 ± 0.5 km.Graphical .

Interannual variability of upwelling indices in the Southeastern Arabian Sea: A satellite based study

Increase in sea surface temperature with global warming has an impact on coastal upwelling. Past two decades (1988 to 2007) of satellite observed sea surface temperatures and space borne scatterometer measured winds have provided an insight into the dynamics of coastal upwelling in the southeastern Arabian Sea, in the global warming scenario. These high resolution data products have shown inconsistent variability with a rapid rise in sea surface temperature between 1992 and 1998 and again from 2004 to 2007. The upwelling indices derived from both sea surface temperature and wind have shown that there is an increase in the intensity of upwelling during the period 1998 to 2004 than the previous decade. These indices have been modulated by the extreme climatic events like El-Nino and Indian Ocean Dipole that happened during 1991–92 and 1997–98. A considerable drop in the intensity of upwelling was observed concurrent with these events. Apart from the impact of global warming on the upwelling, the present study also provides an insight into spatial variability of upwelling along the coast. Noticeable fact is that the intensity of offshore Ekman transport off 8°N during the winter monsoon is as high as that during the usual upwelling season in summer monsoon. A drop in the meridional wind speed during the years 2005, 2006 and 2007 has resulted in extreme decrease in upwelling though the zonal wind and the total wind magnitude are a notch higher than the previous years. This decrease in upwelling strength has resulted in reduced productivity too.

IRS-LISS-III and PAN data analysis for landslide susceptibility mapping using heuristic approach in active tectonic region of Himalaya

Structurally disturbed zones of Himalaya are among the worst landslide affected regions in the world. Although landslides are induced/triggered either by torrential rain during monsoon or by seismic activity in the region, the inherent terrain conditions characterize the prevailing basic conditions susceptible to landslides. Using remotely sensed data and Geographic Information System (GIS), geological and terrain factors can be integrated for preparation of factor maps and demarcation of areas susceptible to landslides. Moderate to high resolution data products available from Indian Remote Sensing satellites have been utilized for deriving geological and terrain factor maps, which were integrated using knowledge driven heuristic approach in Integrated Land and Water Information System (ILWIS) GIS. The resultant map shows division of the area into landslide susceptibility classes ranked in terms of hazard potential in one of the structurally disturbed zones in western Himalaya around Rishikesh.

High Resolution Fossil Fuel Combustion CO2 Emission Fluxes for the United States

Quantification of fossil fuel CO2 emissions at fine space and time resolution is emerging as a critical need in carbon cycle and climate change research. As atmospheric CO2 measurements expand with the advent of a dedicated remote sensing platform and denser in situ measurements, the ability to close the carbon budget at spatial scales of approximately 100 km2 and daily time scales requires fossil fuel CO2 inventories at commensurate resolution. Additionally, the growing interest in U.S. climate change policy measures are best served by emissions that are tied to the driving processes in space and time. Here we introduce a high resolution data product (the "Vulcan" inventory: www.purdue.edu/eas/carbon/vulcan/) that has quantified fossil fuel CO2 emissions for the contiguous U.S. at spatial scales less than 100 km2 and temporal scales as small as hours. This data product completed for the year 2002, includes detail on combustion technology and 48 fuel types through all sectors of the U.S. economy. The Vulcan inventory is built from the decades of local/regional air pollution monitoring and complements these data with census, traffic, and digital road data sets. The Vulcan inventory shows excellent agreement with national-level Department of Energy inventories, despite the different approach taken by the DOE to quantify U.S. fossil fuel CO2 emissions. Comparison to the global 1degree x 1 degree fossil fuel CO2 inventory, used widely by the carbon cycle and climate change community prior to the construction of the Vulcan inventory, highlights the space/time biases inherent in the population-based approach.

The contribution of environmental biomonitoring with lichens to assess human exposure to dioxins

The contribution of environmental biomonitoring with lichens to assess human exposure to dioxins was the main purpose of this work. For that, polychlorinated dibenzofurans (PCDD/F) were measured in 66 lichen sampling points. The obtained information significantly improved the basic knowledge on the environmental exposure to dioxins through distinction between effective control areas from areas with moderate atmospheric deposition. It allowed the integration of PCDD/F atmospheric deposition for much longer periods, allowing to relate low levels with long-term chronic effects on health. Thus, the production of high-resolution data on environmental exposure essential to perform reliable environmental health studies was possible. It was argued that PCDD/F in lichens may be used as spatial estimators of the potential risk of inhalation by the population present in the area. An example of the application of this data to select control and exposed areas for environmental health studies was presented.

Neutron Diffraction with an Excess-Water Cell

As part of a study of the molecular basis of membrane fusion by enveloped viruses, we have used neutron diffraction to study the lamellar (L(α)) to inverse hexagonal (H(II)) phase transition in the phospholipid N-methylated dioleoylphosphatidylethanolamine. This lipid was chosen because its phase transitions are particularly sensitive to the presence of agents that have been demonstrated to promote or inhibit membrane fusion. Two different geometries of neutron diffraction were used: small angle scattering (SANS) and a membrane diffractometer. The SANS measurements were carried out on the SWAN instrument at KEK, Japan, using dispersions of multilamellar vesicles (MLVs). The diffractometer measurements used the V1 instrument at BeNSC-HMI, Germany, with a specially-constructed cell that holds a stack of lipid bilayers in an excess-water state. The two approaches are compared and discussed. Although the diffractometer takes considerably longer to collect the data, it records much higher resolution than the SANS instrument. The samples recorded in the excess-water cell were shown to be well aligned, despite the lipids being fully hydrated, allowing for the production of high-resolution data. Trial measurements performed have demonstrated that sample alignment is preserved throughout the L(α) to H(II) phase transition, thereby opening up possibilities for obtaining high-resolution data from non-lamellar phases.