Multi-temporal Resolution Research Articles

MTR-PET: Multi-temporal resolution PET images for lymphoma segmentation

Lymphoma segmentation on positron emission tomography/computed tomography (PET/CT) is a challenge in clinical diagnosis. Existing methods commonly locate lymphoma candidates on PET images and removes false positive candidates using CT images. However, the combined use of PET with CT in segmentation is not trivial, either requiring CT-based multi-organ segmentation or PET/CT registration. The registration of PET/CT will introduce information change in images. Therefore, accurate lymphoma segmentation on PET images is of great importance for medical diagnoses. In this paper, we propose a novel idea of lymphoma segmentation on multi-temporal resolution PET (MTR-PET) images. Instead of using CT information, this method investigates differences of lymphoma and other tissues on different temporal resolution PET images. Two related features, metabolic variation and metabolic heterogeneity, are proposed and combined with traditional features to construct a statistical analysis model for removing false lymphoma candidates. To obtain accurate boundary results, CNN networks are used for lymphoma segmentation on the region of interesting (ROI) images. Our proposed method is evaluated on 53 MTR-PET images with a detection sensibility of 0.9953 and a segmentation Dice coefficient of 0.8667. Experiments and results demonstrate that information of MTR-PET images can significantly improve the performance of lymphoma segmentation.

Vegetation and Built-Up Area Monitoring in Bandung City Using Multitemporal Imagery

Bandung is West Java's largest metropolitan city and Indonesia's third largest. The city of Bandung is very strategic in various aspects, such as accessibility, communication, public facilities, and the economy. The Increased population in Bandung indicates more complex ongoing human activities, which can then affect changes in land use. The land covers in urban areas tends to change more drastically over a short period e than in rural areas because of rapid urbanization. Therefore, urban phenomenon changes are ideally monitored and detected from satellite images with a multitemporal resolution. Vegetation greenness and built-up areas can identify through multitemporal remote sensing imagery. Changes in vegetation and built-up area can monitor using remote sensing with multitemporal imagery. The analysis of changes in vegetation and built-up area studied in Bandung City represents an area with rapid population growth. This study aims to: 1) Identify changes in vegetation greenness in Bandung City between 2014 and 2021, 2) Identify built-up area changes in Bandung City between 2014 and 2021, 3) Analyze the relevance between vegetation greenness and the built-up area in Bandung City—the correlation between NDBI and NDVI through selected samples is representative of all data in Landsat 8 imagery. The proportion between the values of NDBI and NDVI samples is 0.9034. So, it is concluded that the two variables are positively correlated. Therefore, the study’s results recommend preserving vegetated land cover to conserve natural resources and prevent increased land surface temperature.Keywords: Remote Sensing Imagery, Built-Up Area, Vegetation Greenness, Bandung City

Assessing Sea Surface Temperatures Estimated from Fused Infrared and Microwave Data

Sea surface temperature (SST), a critical parameter of the global ocean–atmosphere system, is an essential element in the study and in the application of marine science. Satellite–infrared observations currently represent the only available method for continuous, large-scale observation of SST. Although passive microwave observations are not blocked by clouds, allowing for data collection in all weather conditions, this technological tool is characterized by low spatial resolution. Conversely, infrared observations offer high resolution but are susceptible to cloud obscuration. Accordingly, a technique that effectively fuses microwave and infrared satellite observations into a high-resolution SST field with global coverage close to the actual distribution is of practical significance. This paper describes fusing MODIS infrared remote sensing and AMSR-2 microwave remote sensing SST data with an optimal interpolation (OI) approach to produce a high-resolution SST data. The study chose the coastal Kuroshio region of China to establish an appropriate scale for examining the spatial structure of SST and attaining a more realistic picture of SST observations and impacts. The included discussion of the sources of error in the fusion process provides a reference for improving the accuracy of fused marine remote sensing data. The study also compared the fused SST results and the current international mainstream multi-temporal resolution of the three using the OI algorithm. We compared the fusion product with ARGO data with and without typhoon impact to explore and practice the OI in SST fusion when evaluating the accuracy of different data in the case of external disturbance being present. The research results have great significance for improving regional SST forecast accuracy while ensuring the applicability of various approaches to fusing SST data by incorporating the influence of typhoons in the offshore region of the East China Sea (ECS). Implications for the future development of SST fusion data are also included in the discussion.

On the Use of Sentinel-2 NDVI Time Series and Google Earth Engine to Detect Land-Use/Land-Cover Changes in Fire-Affected Areas

This study aims to assess the potential of Sentinel-2 NDVI time series and Google Earth Engine to detect small land-use/land-cover changes (at the pixel level) in fire-disturbed environs. To capture both slow and fast changes, the investigations focused on the analysis of trends in NDVI time series, selected because they are extensively used for the assessment of post-fire dynamics mainly linked to the monitoring of vegetation recovery and fire resilience. The area considered for this study is the central–southern part of the Italian peninsula, in particular the regions of (i) Campania, (ii) Basilicata, (iii) Calabria, (iv) Toscana, (v) Umbria, and (vi) Lazio. For each fire considered, the study covered the period from the year after the event to the present. The multi-temporal analysis was performed using two main data processing steps (i) linear regression to extract NDVI trends and enhance changes over time and (ii) random forest classification to capture and categorize the various changes. The analysis allowed us to identify changes occurred in the selected case study areas and to understand and evaluate the trend indicators that mark a change in land use/land cover. In particular, different types of changes were identified: (i) woodland felling, (ii) remaking of paths and roads, and (ii) transition from wooded area to cultivated field. The reliability of the changes identified was assessed and confirmed by the high multi-temporal resolution offered by Google Earth. Results of this comparison highlighted that the overall accuracy of the classification was higher than 0.86.

Multi-temporal resolution aerosols impacted techno-economic assessment of concentrated solar power in arid regions: Case study of solar power tower in Kuwait

This work evaluates the Solar Power Tower performance in arid regions where elevated aerosols levels and water scarcity threaten solar applications feasibility. The work conducts an aerosols aware modelling and techno-economic assessment by considering possible aerosols effects on the solar field’s reflected irradiance; an effect that is typically ignored in the literature. Aerosols effect inclusion’s modifies the thermal input to the solar field and this, in turn, provides a more accurate assessment. A parametric analysis has been performed using a 50 MW model by varying the Thermal Energy Storage and Solar Multiple based on three aerosols temporal resolutions: a typical year’s average, daily and no-aerosols schemes. Further, water consumption is examined over four different condenser scenarios: dry, wet and two hybrid set ups. The assessment performed in Kuwait reveals that the wet-cooled condenser scenario with a 16h of storage and a solar multiple of 3.2 yields the lowest Levelized Cost of Energy of 12.06 $/kWh when the no-aerosols scheme is considered. This increases to 12.87 $/kWh when the daily aerosols are considered as the generated energy decreases by 6.7%. Besides, both hybrid condenser scenarios offer a trade-off as they result in a 55.1–68.7% of water saving for only 2.1–2.3% less energy generation.

Volumetric prediction of breathing and slow drifting motion in the abdomen using radial MRI and multi-temporal resolution modeling

Abdominal organ motions introduce geometric uncertainties to radiotherapy. This study investigates a multi-temporal resolution 3D motion prediction scheme that accounts for both breathing and slow drifting motion in the abdomen in support of MRI-guided radiotherapy. Ten-minute MRI scans were acquired for 8 patients using a volumetric golden-angle stack-of-stars sequence. The first five-minutes was used for patient-specific motion modeling. Fast breathing motion was modeled from high temporal resolution radial k-space samples, which served as a navigator signal to sort k-space data into different bins for high spatial resolution reconstruction of breathing motion states. Slow drifting motion was modeled from a lower temporal resolution image time series which was reconstructed by sequentially combining a large number of breathing-corrected k-space samples. Principal components analysis (PCA) was performed on deformation fields between different motion states. Gaussian kernel regression and linear extrapolation were used to predict PCA coefficients of future motion states for breathing motion (340 ms ahead of acquisition) and slow drifting motion (8.5 s ahead of acquisition) respectively. k-space data from the remaining five-minutes was used to compare ground truth motions states obtained from retrospective reconstruction/deformation with predictions. Median distances between predicted and ground truth centroid positions of gross tumor volume (GTV) and organs at risk (OARs) were less than 1 mm on average. 95- percentile Hausdorff distances between predicted and ground truth GTV contours of various breathing motions states were 2 mm on average, which was smaller than the imaging resolution and 95-percentile Hausdorff distances between predicted and ground truth OAR contours of different slow drifting motion states were less than 0.2 mm. These results suggest that multi-temporal resolution motion models are capable of volumetric predictions of breathing and slow drifting motion with sufficient accuracy and temporal resolution for MRI-based tracking, and thus have potential for supporting MRI-guided abdominal radiotherapy.

Modeling intra-fractional abdominal configuration changes using breathing motion-corrected radial MRI

Abdominal organ motions introduce geometric uncertainties to gastrointestinal radiotherapy. This study investigated slow drifting motion induced by changes of internal anatomic organ arrangements using a 3D radial MRI sequence with a scan length of 20 min. Breathing motion and cyclic GI motion were first removed through multi-temporal resolution image reconstruction. Slow drifting motion analysis was performed using an image time series consisting of 72 image volumes with a temporal sampling rate of 17 s. B-spline deformable registration was performed to align image volumes of the time series to a reference volume. The resulting deformation fields were used for motion velocity evaluation and patient-specific motion model construction through principal component analysis (PCA). Geometric uncertainties introduced by slow drifting motion were assessed by Hausdorff distances between unions of organs at risk (OARs) at different motion states and reference OAR contours as well as probabilistic distributions of OARs predicted using the PCA model. Thirteen examinations from 11 patients were included in this study. The averaged motion velocities ranged from 0.8 to 1.9 mm min−1, 0.7 to 1.6 mm min−1, 0.6 to 2.0 mm min−1 and 0.7 to 1.4 mm min−1 for the small bowel, colon, duodenum and stomach respectively; the averaged Hausdorff distances were 5.6 mm, 5.3 mm, 5.1 mm and 4.6 mm. On average, a margin larger than 4.5 mm was needed to cover a space with OAR occupancy probability higher than 55%. Temporal variations of geometric uncertainties were evaluated by comparing across four 5 min sub-scans extracted from the full scan. Standard deviations of Hausdorff distances across sub-scans were less than 1 mm for most examinations, indicating stability of relative margin estimates from separate time windows. These results suggested slow drifting motion of GI organs is significant and geometric uncertainties introduced by such motion should be accounted for during radiotherapy planning and delivery.

Coupling Satellite Images and Unmanned Aerial Vehicle Data to Monitor the Exploitation of Open-Pit Mine

Discovering the variation of an open-pit mine in vertical, horizontal, and temporal dimensions as well to characterize the stages and the trends of the exploitation are indispensable tasks which provide information supporting decision making and planning for sustainable development of the mining industry. Remote sensing technique with the advantages of multi-spatial, multi-spectral, multi-temporal resolution is a promising solution to meet the information requirement. This study proposes an approach of coupling the high-resolution satellite images and Unmanned Aerial Vehicle (UAV) data to observe the variation of Tan An open rocky mine during its lifetime. Five satellite images with the resolution of 0.5 m acquired in 2006, 2012, 2014, 2016, 2018, and two ortho-images with 0.034 m resolution constructed from UAV photos captured in 2019, 2020 are used to make land cover maps. The analysis of land cover changes discovers 3 stages of open-pit mine exploitation consisting of unprompted exploitation, exploiting outbreak and stable exploitation corresponding to the changes in the mine. Besides, two Digital Surface Models (DSM) constructed by UAV photos are compared to calculate the elevation and volume changes. The assessment of the correlation between elevation change and land cover change indicates that the mineral exploitation is in the vertical range from 645 m to 660 m, and the exploitation trend is following the horizontal expansion rather than the deep excavation. Additionally, this experiment results in 79,422 m3 of mineral taken from the mine, and 34,022 m3 of soil used for the restoration within a year from June 2019 to June 2020.

Spatial Configuration and Extent Explains the Urban Heat Mitigation Potential due to Green Spaces: Analysis over Addis Ababa, Ethiopia

Urban green space (UGS) is considered a mitigative intervention for urban heat. While increasing the UGS coverage is expected to reduce the urban heat, studies on the effects of UGS configuration have produced inconsistent results. To investigate this inconsistency further, this study conducted a multi-spatial and multi-temporal resolution analysis in the Addis Ababa city metropolitan area for assessing the relationship between UGS patterns and land surface temperature (LST). Landsat images were used to generate land cover and LST maps. Regression models were developed to investigate whether controlling for the proportion of the green area (PGS), fragmentation, shape, complexity, and proximity distance can affect surface temperature. Results indicated that the UGS patches with aggregated, regular and simple shapes and connectivity throughout the urban landscape were more effective in decreasing the LST as compared to the fragmented and complicated spatial patterns. This finding highlighted that in addition to increasing the amount of UGS, optimizing the spatial structure of UGS, could be an effective and useful action to mitigate the urban heat island (UHI) impacts. Changing the spatial size had a significant influence on the interconnection between LST and UGS patterns as well. It also noted that the spatial arrangement of UGS was more sensitive to spatial scales than that of its composition. The relationship between the spatial configuration of UGS and LST could be changed when applying different statistical methods. This result underlined the importance of controlling the effects of the share of green spaces when calculating the impacts of the spatial configuration of UGS on LST. Furthermore, the study highlighted that applying different statistical approaches, spatial scale, and coverage of UGS can help determine the effectiveness of the association between LST and UGS patterns. These outcomes provided new insights regarding the inconsistent findings from earlier studies, which might be a result of the different approaches considered. Indeed, these findings are expected to be of help more broadly for city planning and urban heat mitigation.

Understanding Ridesourcing Mobility and the Future of Electrification: A Comparative Study in Beijing

ABSTRACT The development of mobile Internet, smartphones, and location-based services has enabled ridesourcing, which pools vehicles and drivers to provide on-demand travel services. As an alternative transportation option, ridesourcing has significant impacts on urban travel. However, the unique mobility pattern of ridesourcing and its impact on vehicle electrification have not been well studied. To address this gap, this paper presents a comparative, big-data-driven framework to characterize the ridesourcing mobility pattern, and evaluate the acceptance potential of electric vehicles for ridesourcing in comparison with other types of vehicle use. Multi-temporal resolution ridesourcing trips are extracted from raw GPS trajectories. The patterns of three urban travel (household, ridesourcing, and taxis) are extracted from GPS trajectories in Beijing, and compared. The electrification potentials of these types of travel under different charging levels are then evaluated. The results demonstrate that mobility patterns of household, ridesourcing, and taxi drivers are similar when a single trip is considered but differ significantly when total vehicle travel is considered. We show that potential acceptance of electric vehicles decreases significantly from household to ridesourcing and taxi vehicle use. These findings provide useful insights into of the role vehicle electrification can play in sustainability of urban personal transportation across a range of drivers.

Shoreline Change Monitoring in Nellore Coast at East Coast Andhra Pradesh District Using Remote Sensing and GIS

The shoreline is one of the most important features on earth’s surface. They are highly dynamic and ever changing. Changes are over time scales including minutes, hours, decades and Centuries. Spatial scales vary from local to regional to worldwide. Although change is continuously occurring, it doesn’t occur in a constant manner. Many factors influence these changes including the type of shoreline (rocky, sandy), wave activity, tidal variations, storms and human impacts. The shoreline change study is necessary for updating the shoreline change maps and management of natural resources. Shorelines are the key element in coastal GIS and provide the most information on coastal landform dynamics. The frequently monitoring coast only to accesses variation of shoreline changes. In this paper investigate the shoreline changes of Nellore district in Andhra Pradesh coast, as well as find the quantity of the erosion and accretion rate. Using multi-temporal resolution satellite data (TM & LISS III, IV) and Geographic information system (GIS) for past 25 years period i.e., from 1989 to 2015. Nellore having length of coast line is 167 km for this study used. The resultant coastal maps were used to estimate the geomorphologic changes and shifting of the shoreline position. This integrated study is found useful for exploring accretion and erosion processes in the region. About 87.6 km of coastline was found to be accreting nature with average of +1.40 m/yr followed by 38.4 km of coastal line eroding with average of -1.36 m/yr and stable coastline of 41.4 km was found. This study demonstrates that combined use of satellite imagery and statistical method such as linear regression for shoreline change analysis are helpful for erosion monitoring and preventive measure.

Vegetation indices and field spectroradiometric measurements for validation of buried architectural remains: verification under area surveyed with geophysical campaigns

This study presents an alternative approach for detecting possible archaeological crop marks using medium multitemporal resolution satellite data and field spectroscopy measurements during a whole phenological cycle of the crops and normalized difference vegetation index (NDVI) values. Geophysical surveys have been carried out on areas where archaeological remains with crops existed for validation and verification. The study presents the results obtained by applying the NDVI for a series of multitemporal Landsat TM/ETM+ images acquired from June 2009 to June 2010, intended for detecting archaeological crop marks in the Paphos District area in Cyprus. The results were validated using in situ spectroradiometric measurements using the GER 1500 field spectroradiometer. The authors compared the NDVI values between three sites in which barley crop is cultivated during a complete phenological cycle. The first site was a known archaeological area (Site 1), while the other two sites were healthy cultivated areas (Sites 2 and 3). The sites had similar soil and climatic characteristics. It has been found that during the phenological cycle, the NDVI plot for Site 1 was significantly different from the healthy areas. The detection of possible archaeological areas was based on anomalies observed and measured on vegetation indices, during the phenological cycle, of the "stressed" barley compared to healthy "nonstressed" barley in all three sites. At the end of the life cycle (after June 2010), the local authorities commenced excavation work at Site 1. Buried archaeological remains, 20 to 30 cm below ground surface were found. Anomalies found in the NDVI phenological cycle, as in Site 1, could be used for detecting areas with buried archeological remains.

Remote sensing for the sea ice effect monitoring in petroleum development: Take the Nanpu sea area as an example

Abstract Sea ice monitoring is one of the important guarantees for marine operation and transport. The space borne remote sensing techniques have the advantages of wide area surveillance, multi-temporal resolution, prompt acquisition, and high precision. They have become one of the key sea ice monitoring techniques. The new Chinese satellite HJ-1A/B CCD images were used in the sea ice monitoring of the Nanpu sea area in winter, during the time from Nov. 29, 2008 to Feb. 21, 2009. A fast processing work flow was established based on the object-oriented information extraction technology. It was used to map the change of the ice area during the period. According to the ice area change, the ice sea distribution, and the historical meteorological information, the ice period was divided into: initial ice (early Dec., 2008 to the end of Dec., 2008), abounding ice (from the end of Dec., 2008 to the end of Jan., 2009), ice thawing (from the end of Jan., 2009 to the end of Feb., 2009). The work contributes to the safe construction of the artificial islands in the Nanpu-4 structure during the icebound season. The study shows that the remote sensing technology is a practical and effective technical means for the sea ice security monitoring of oil fields' exploration, development and engineering construction in beaches.

A Hybrid Method Combining the Multitemporal Resolution Time-Domain Method of Moments With the Time-Domain Geometrical Theory of Diffraction for Thin-Wire Antenna Problems

In this paper, a hybrid method combining a multitemporal resolution (MTR) enhanced time-domain method of moments (TD-MoM) with the TD geometrical theory of diffraction (GTD) is presented, which allows to efficiently calculate the transient fields radiated by antennas in presence of large objects. The MTR scheme tailors the time step size-and thus implicitly the duration of the temporal basis function-on the basis of the distance between source and test element. Additionally, the voltage induced by source elements far away from the test element is interpolated in time. The hybrid method is applied to calculate the radiation properties of thin-wire antennas in presence of perfectly conducting flat scatterers to demonstrate its basic features and advantages