Remote Sensing

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13897 KiB

Open AccessArticle

Testing a Modified PCA-Based Sharpening Approach for Image Fusion

by Jan Jelének, Veronika Kopačková, Lucie Koucká and Jan Mišurec

Remote Sens. 2016, 8(10), 794; https://doi.org/10.3390/rs8100794 - 24 Sep 2016

Cited by 29 | Viewed by 7255

Image data sharpening is a challenging field of remote sensing science, which has become more relevant as high spatial-resolution satellites and superspectral sensors have emerged. Although the spectral property is crucial for mineral mapping, spatial resolution is also important as it allows targeted [...] Read more.

Image data sharpening is a challenging field of remote sensing science, which has become more relevant as high spatial-resolution satellites and superspectral sensors have emerged. Although the spectral property is crucial for mineral mapping, spatial resolution is also important as it allows targeted minerals/rocks to be identified/interpreted in a spatial context. Therefore, improving the spatial context, while keeping the spectral property provided by the superspectral sensor, would bring great benefits for geological/mineralogical mapping especially in arid environments. In this paper, a new concept was tested using superspectral data (ASTER) and high spatial-resolution panchromatic data (WorldView-2) for image fusion. A modified Principal Component Analysis (PCA)-based sharpening method, which implements a histogram matching workflow that takes into account the real distribution of values, was employed to test whether the substitution of Principal Components (PC1–PC4) can bring a fused image which is spectrally more accurate. The new approach was compared to those most widely used—PCA sharpening and Gram–Schmidt sharpening (GS), both available in ENVI software (Version 5.2 and lower) as well as to the standard approach—sharpening Landsat 8 multispectral bands (MUL) using its own panchromatic (PAN) band. The visual assessment and the spectral quality indicators proved that the spectral performance of the proposed sharpening approach employing PC1 and PC2 improve the performance of the PCA algorithm, moreover, comparable or better results are achieved compared to the GS method. It was shown that, when using the PC1, the visible-near infrared (VNIR) part of the spectrum was preserved better, however, if the PC2 was used, the short-wave infrared (SWIR) part was preserved better. Furthermore, this approach improved the output spectral quality when fusing image data from different sensors (e.g., ASTER and WorldView-2) while keeping the proper albedo scaling when substituting the second PC. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Remote Sensing (ECRS-1))

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38557 KiB

Open AccessArticle

Physical Layer Definition for a Long-Haul HF Antarctica to Spain Radio Link

by Rosa Ma Alsina-Pagès, Marcos Hervás, Ferran Orga, Joan Lluís Pijoan, David Badia and David Altadill

Remote Sens. 2016, 8(5), 380; https://doi.org/10.3390/rs8050380 - 4 May 2016

Cited by 14 | Viewed by 6932

Abstract

La Salle and the Observatori de l’Ebre (OE) have been involved in a remote sensing project in Antarctica for the last 11 years. The OE has been monitoring the geomagnetic activity for more than twenty years and also the ionospheric activity of the [...] Read more.

La Salle and the Observatori de l’Ebre (OE) have been involved in a remote sensing project in Antarctica for the last 11 years. The OE has been monitoring the geomagnetic activity for more than twenty years and also the ionospheric activity of the last ten years in the Spanish Antarctic Station Juan Carlos I (ASJI) (62.7

^{°}

S, 299.6

^{°}

E). La Salle is finishing the design and testing of a low-power communication system between the ASJI and Cambrils (41.0

^{°}

N, 1.0

^{°}

E) with a double goal: (i) the transmission of data from the sensors located at the ASJI and (ii) the performance of an oblique ionospheric sounding of a 12,760 km HF link. Previously, La Salle has already performed sounding and modulation tests to describe the channel performance in terms of availability, Signal-to-Noise Ratio (SNR), Doppler spread and delay spread. This paper closes the design of the physical layer, by means of the channel error study and the synchronization performance, and concludes with a new physical layer proposal for the Oblique Ionosphere Sounder. Narrowband and wideband frames have been defined to be used when the oblique sounder performs as an ionospheric sensor. Finally, two transmission modes have been defined for the modem performance: the High Robustness Mode (HRM) for low SNR hours and the High Throughput Mode (HTM) for the high SNR hours. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Remote Sensing (ECRS-1))

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4997 KiB

Open AccessArticle

An Automatic Target Detection Algorithm for Swath Sonar Backscatter Imagery, Using Image Texture and Independent Component Analysis

by Elias Fakiris, George Papatheodorou, Maria Geraga and George Ferentinos

Remote Sens. 2016, 8(5), 373; https://doi.org/10.3390/rs8050373 - 29 Apr 2016

Cited by 43 | Viewed by 7577

Abstract

In the present paper, a methodological scheme, bringing together common Acoustic Seabed Classification (ASC) systems and a powerful data decomposition approach, called Independent Component Analysis (ICA), is demonstrated regarding its suitability for detecting small targets in Side Scan Sonar imagery. Traditional ASC systems [...] Read more.

In the present paper, a methodological scheme, bringing together common Acoustic Seabed Classification (ASC) systems and a powerful data decomposition approach, called Independent Component Analysis (ICA), is demonstrated regarding its suitability for detecting small targets in Side Scan Sonar imagery. Traditional ASC systems extract numerous texture descriptors, leading to a large feature vector, the dimensionality of which is reduced by means of data decomposition techniques, usually Principal Component Analysis (PCA), prior to classification. However, in the target detection issue, data decomposition should point towards finding components that represent sub-ordinary image information (i.e., small targets) rather than a dominant one. ICA has long been proved to be suitable for separating targets from a background, and this study represents a novel exhibition of its applicability to Side Scan Sonar (SSS) images. The present study attempts to build a fully automated target detection approach that combines image based feature extraction, ICA, and unsupervised classification. The suitability of the proposed approach has been demonstrated using an SSS data-set containing more than 70 manmade targets, most of them metallic, validated through a marine magnetic survey or ground truthing inspection. The method exhibited very good performance as it was able to detect more than 77% of the targets and it produced less than seven false alarms per km². Moreover, it was compared to cases where, in the exact same methodological scheme, no decomposition technique is used, or PCA is employed instead of ICA, achieving the highest detection rate, but, more importantly, producing more than six times less false alarms, thus proving that ICA successfully manages to maximize target to background separation. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Remote Sensing (ECRS-1))

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1810 KiB

Open AccessArticle

The Use of Remotely Sensed Rainfall for Managing Drought Risk: A Case Study of Weather Index Insurance in Zambia

by Emily Black, Elena Tarnavsky, Ross Maidment, Helen Greatrex, Agrotosh Mookerjee, Tristan Quaife and Matthew Brown

Remote Sens. 2016, 8(4), 342; https://doi.org/10.3390/rs8040342 - 20 Apr 2016

Cited by 43 | Viewed by 11225

Abstract

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially [...] Read more.

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Remote Sensing (ECRS-1))

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9452 KiB

Open AccessArticle

The Combined Use of Airborne Remote Sensing Techniques within a GIS Environment for the Seismic Vulnerability Assessment of Urban Areas: An Operational Application

by Antonio Costanzo, Antonio Montuori, Juan Pablo Silva, Malvina Silvestri, Massimo Musacchio, Fawzi Doumaz, Salvatore Stramondo and Maria Fabrizia Buongiorno

Remote Sens. 2016, 8(2), 146; https://doi.org/10.3390/rs8020146 - 16 Feb 2016

Cited by 16 | Viewed by 7915

Abstract

The knowledge of the topographic features, the building properties, and the road infrastructure settings are relevant operational tasks for managing post-crisis events, restoration activities, and for supporting search and rescue operations. Within such a framework, airborne remote sensing tools have demonstrated to be [...] Read more.

The knowledge of the topographic features, the building properties, and the road infrastructure settings are relevant operational tasks for managing post-crisis events, restoration activities, and for supporting search and rescue operations. Within such a framework, airborne remote sensing tools have demonstrated to be powerful instruments, whose joint use can provide meaningful analyses to support the risk assessment of urban environments. Based on this rationale, in this study, the operational benefits obtained by combining airborne LiDAR and hyperspectral measurements are shown. Terrain and surface digital models are gathered by using LiDAR data. Information about roads and roof materials are provided through the supervised classification of hyperspectral images. The objective is to combine such products within a geographic information system (GIS) providing value-added maps to be used for the seismic vulnerability assessment of urban environments. Experimental results are gathered for the city of Cosenza, Italy. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Remote Sensing (ECRS-1))

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4057 KiB

Open AccessArticle

Evaluating Multi-Sensor Nighttime Earth Observation Data for Identification of Mixed vs. Residential Use in Urban Areas

by Christoph Aubrecht and José Antonio León Torres

Remote Sens. 2016, 8(2), 114; https://doi.org/10.3390/rs8020114 - 4 Feb 2016

Cited by 14 | Viewed by 6269

Abstract

This paper introduces a novel top-down approach to geospatially identify and distinguish areas of mixed use from predominantly residential areas within urban agglomerations. Under the framework of the World Bank’s Central American Country Disaster Risk Profiles (CDRP) initiative, a disaggregated property stock exposure [...] Read more.

This paper introduces a novel top-down approach to geospatially identify and distinguish areas of mixed use from predominantly residential areas within urban agglomerations. Under the framework of the World Bank’s Central American Country Disaster Risk Profiles (CDRP) initiative, a disaggregated property stock exposure model has been developed as one of the key elements for disaster risk and loss estimation. Global spatial datasets are therefore used consistently to ensure wide-scale applicability and transferability. Residential and mixed use areas need to be identified in order to spatially link accordingly compiled property stock information. In the presented study, multi-sensor nighttime Earth Observation data and derivative products are evaluated as proxies to identify areas of peak human activity. Intense artificial night lighting in that context is associated with a high likelihood of commercial and/or industrial presence. Areas of low light intensity, in turn, can be considered more likely residential. Iterative intensity thresholding is tested for Cuenca City, Ecuador, in order to best match a given reference situation based on cadastral land use data. The results and findings are considered highly relevant for the CDRP initiative, but more generally underline the relevance of remote sensing data for top-down modeling approaches at a wide spatial scale. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Remote Sensing (ECRS-1))

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4013 KiB

Open AccessArticle

Detection of Spatio-Temporal Changes of Norway Spruce Forest Stands in Ore Mountains Using Landsat Time Series and Airborne Hyperspectral Imagery

by Jan Mišurec, Veronika Kopačková, Zuzana Lhotáková, Petya Campbell and Jana Albrechtová

Remote Sens. 2016, 8(2), 92; https://doi.org/10.3390/rs8020092 - 26 Jan 2016

Cited by 20 | Viewed by 6761

Abstract

The study focuses on spatio-temporal changes in the physiological status of the Norway spruce forests located at the central and western parts of the Ore Mountains (northwestern part of the Czech Republic), which suffered from severe environmental pollution from the 1970s to the [...] Read more.

The study focuses on spatio-temporal changes in the physiological status of the Norway spruce forests located at the central and western parts of the Ore Mountains (northwestern part of the Czech Republic), which suffered from severe environmental pollution from the 1970s to the 1990s. The situation started improving after the pollution loads decreased significantly at the end of the 1990s. The general trends in forest recovery were studied using the tasseled cap transformation and disturbance index (DI) extracted from the 1985–2015 time series of Landsat data. In addition, 16 vegetation indices (VIs) extracted from airborne hyperspectral (HS) data acquired in 1998 using the Advanced Solid-State Array Spectroradiometer (ASAS) and in 2013 using the Airborne Prism Experiment (APEX) were used to study changes in forest health. The forest health status analysis of HS image data was performed at two levels of spatial resolution; at a tree level (original 2.0 m spatial resolution), as well as at a forest stand level (generalized to 6.0 m spatial resolution). The temporal changes were studied primarily using the VOG₁ vegetation index (VI) as it was showing high and stable sensitivity to forest damage for both spatial resolutions considered. In 1998, significant differences between the moderately to heavily damaged (central Ore Mountains) and initially damaged (western Ore Mountains) stands were detected for all the VIs tested. In 2013, the stands in the central Ore Mountains exhibited VI values much closer to the global mean, indicating an improvement in their health status. This result fully confirms the finding of the Landsat time series analysis. The greatest difference in Disturbance Index (DI) values between the central (1998: 0.37) and western Ore Mountains stands (1998: −1.21) could be seen at the end of the 1990s. Nonetheless, levelling of the physiological status of Norway spruce was observed for the central and western parts of the Ore Mountains in 2013 (mean DI values −1.04 (western) and −0.66 (central)). Although the differences between originally moderately-to-heavily damaged, and initially damaged stands generally levelled out by 2013, it is still possible to detect signs of the previous damage in some cases. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Remote Sensing (ECRS-1))

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8904 KiB

Open AccessArticle

Narrowband and Wideband Channel Sounding of an Antarctica to Spain Ionospheric Radio Link

by Marcos Hervás, Rosa Ma Alsina-Pagès, Ferran Orga, David Altadill, Joan Lluís Pijoan and David Badia

Remote Sens. 2015, 7(9), 11712-11730; https://doi.org/10.3390/rs70911712 - 14 Sep 2015

Cited by 18 | Viewed by 6496

Abstract

La Salle and Ebro Observatory have been involved in remote sensing projects in Antarctica for the last 11 years (approximately one solar cycle). The Ebro Observatory has been monitoring and analyzing the geomagnetic and the ionospheric activity in the Antarctic Spanish station Juan [...] Read more.

La Salle and Ebro Observatory have been involved in remote sensing projects in Antarctica for the last 11 years (approximately one solar cycle). The Ebro Observatory has been monitoring and analyzing the geomagnetic and the ionospheric activity in the Antarctic Spanish station Juan Carlos I (ASJI) (62.7°S, 299.6°E) for more than eighteen and ten years, respectively. La Salle has two main goals in the project. The first one is the data transmission and reception from Antarctica to Spain to obtain a historical series of measurements of channel sounding of this 12,760-km ionospheric HF (high frequency) radio link. The second one is the establishment of a stable data low power communication system between the ASJI and Cambrils, Spain (41.0°N, 1.0°E), to transmit the data from the remote sensors located on the island. In this paper, both narrowband and wideband soundings have been carried out to figure out the channel availability performed using a frequency range from 2 to 30 MHz with 0.5 MHz step during the 24 h of the day, encompassing wider channel measurements than previously done, in terms of hours and frequency. This paper presents the results obtained for the austral summer in 2014, using a monopole antenna at the transmitter and an inverted V on the receiver side. These results led us to the final physical layer design for the long Remote Sens. 2015, 7 11713 haul link, dividing the day into two parts: daytime, with low data throughput design, and nighttime, reaching high data throughput. Full article

(This article belongs to the Special Issue Selected Papers from the 1st International Electronic Conference on Remote Sensing (ECRS-1))

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