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Remote Sens., Volume 9, Issue 7 (July 2017)

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Cover Story (view full-size image) It has long been assumed that South Asia's ancient Indus Civilization was riverine, but many [...] Read more.
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Open AccessArticle Coastal Waveform Retracking for Jason-2 Altimeter Data Based on Along-Track Echograms around the Tsushima Islands in Japan
Remote Sens. 2017, 9(7), 762; https://doi.org/10.3390/rs9070762
Received: 27 March 2017 / Revised: 18 July 2017 / Accepted: 21 July 2017 / Published: 24 July 2017
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Abstract
Although the Brown mathematical model is the standard model for waveform retracking over open oceans, due to heterogeneous surface reflections within altimeter footprints, coastal waveforms usually deviate from open ocean waveform shapes and thus cannot be directly interpreted by the Brown model. Generally,
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Although the Brown mathematical model is the standard model for waveform retracking over open oceans, due to heterogeneous surface reflections within altimeter footprints, coastal waveforms usually deviate from open ocean waveform shapes and thus cannot be directly interpreted by the Brown model. Generally, the two primary sources of heterogeneous surface reflections are land surfaces and bright targets such as calm surface water. The former reduces echo power, while the latter often produces particularly strong echoes. In previous studies, sub-waveform retrackers, which use waveform samples collected from around leading edges in order to avoid trailing edge noise, have been recommended for coastal waveform retracking. In the present study, the peaky-type noise caused by fixed-point bright targets is explicitly detected and masked using the parabolic signature in the sequential along-track waveforms (or, azimuth-range echograms). Moreover, the power deficit of waveform trailing edges caused by weak land reflections is compensated for by estimating the ratio of sea surface area within each annular footprint in order to produce pseudo-homogeneous reflected waveforms suitable for the Brown model. Using this method, altimeter waveforms measured over the Tsushima Islands in Japan by the Ocean Surface Topography Mission (OSTM)/Jason-2 satellite are retracked. Our results show that both the correlation coefficient and root mean square difference between the derived sea surface height anomalies and tide gauge records retain similar values at the open ocean (0.9 and 20 cm) level, even in areas approaching 3 km from coastlines, which is considerably improved from the 10 km correlation coefficient limit of the conventional MLE4 retracker and the 7 km sub-waveform ALES retracker limit. These values, however, depend on the topography of the study areas because the approach distance limit increases (decreases) in areas with complicated (straight) coastlines. Full article
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Open AccessArticle Application of Sentinel 2 MSI Images to Retrieve Suspended Particulate Matter Concentrations in Poyang Lake
Remote Sens. 2017, 9(7), 761; https://doi.org/10.3390/rs9070761
Received: 27 May 2017 / Revised: 14 July 2017 / Accepted: 19 July 2017 / Published: 23 July 2017
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Abstract
Suspended particulate matter (SPM) is one of the dominant water constituents in inland and coastal waters, and SPM concnetration (CSPM) is a key parameter describing water quality. This study, using in-situ spectral and CSPM measurements as well as Sentinel
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Suspended particulate matter (SPM) is one of the dominant water constituents in inland and coastal waters, and SPM concnetration (CSPM) is a key parameter describing water quality. This study, using in-situ spectral and CSPM measurements as well as Sentinel 2 Multispectral Imager (MSI) images, aimed to develop CSPM retrieval models and further to estimate the CSPM values of Poyang Lake, China. Sixty-eight in-situ hyperspectral measurements and relative spectral response function were applied to simulate Sentinel 2 MIS spectra. Thirty-four samples were used to calibrate and the left samples were used to validate CSPM retrieval models, respectively. The developed models were then applied to two Sentinel 2 MSI images captured in wet and dry seasons, and the derived CSPM values were compared with those derived from MODIS B1 (λ = 645 nm). Results showed that the Sentinel 2 MSI B4–B8b models achieved acceptable to high fitting accuracies, which explained 81–93% of the variation of CSPM. The validation results also showed the reliability of these six models, and the estimated CSPM explained 77–93% of the variation of measured CSPM with the mean absolute percentage error (MAPE) ranging from 36.87% to 21.54%. Among those, a model based on B7 (λ = 783 nm) appeared to be the most accurate one. The Sentinel 2 MSI-derived CSPM values were generally consistent in spatial distribution and magnitude with those derived from MODIS. The CSPM derived from Sentinel 2 MSI B7 showed the highest consistency with MODIS on 15 August 2016, while the Sentinel 2 MSI B4 (λ = 665 nm) produced the highest consistency with MODIS on 2 April 2017. Overall, this study demonstrated the applicability of Sentinel 2 MSI for CSPM retrieval in Poyang Lake, and the Sentinel 2 MSI B4 and B7 are recommended for low and high loadings of SPM, respectively. Full article
(This article belongs to the Special Issue Remote Sensing of Floodpath Lakes and Wetlands)
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Open AccessArticle Mapping Development Pattern in Beijing-Tianjin-Hebei Urban Agglomeration Using DMSP/OLS Nighttime Light Data
Remote Sens. 2017, 9(7), 760; https://doi.org/10.3390/rs9070760
Received: 29 May 2017 / Revised: 7 July 2017 / Accepted: 17 July 2017 / Published: 23 July 2017
Cited by 4 | PDF Full-text (7256 KB) | HTML Full-text | XML Full-text
Abstract
Spatial inequality of urban development may cause problems like inequality of living conditions and the lack of sustainability, drawing increasing academic interests and societal concerns. Previous studies based on statistical data can hardly reveal the interior mechanism of spatial inequality due to the
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Spatial inequality of urban development may cause problems like inequality of living conditions and the lack of sustainability, drawing increasing academic interests and societal concerns. Previous studies based on statistical data can hardly reveal the interior mechanism of spatial inequality due to the limitation of statistical units, while the application of remote sensing data, such as nighttime light (NTL) data, provides an effective solution. In this study, based on the DMSP/OLS NTL data, the urbanization type of all towns in the Beijing-Tianjin-Hebei urban agglomeration was analyzed from the aspects of development level and speed. Meanwhile, spatial cluster analysis of development level by local Moran’s I was used to explore spatial inequality, and the trend was discussed by comparing the development characteristics on both sides of the transition line of different development levels (inequality boundary). The results showed that the development level of the whole region increased dramatically as the mean DN value increased by 65.99%, and 83.72% of the towns showed a positive development during 2000–2012. The spatial distribution of urbanization types showed that Beijing and Tianjin were at a high urbanization level with rapid speed of development, with the southern region having a medium development level and the northwestern region lagging behind. The spatial cluster analysis also revealed a gradually intensifying trend of inequality as the number of towns with balanced development reduced by 319 during 2000–2012, while the towns in the high-high areas increased by 99 and those in the low-low areas increased by 229. Moreover, the development speed inside the inequality boundary was obviously higher than that outside, indicating an increasingly serious situation for spatial inequality of urban development in the whole region. Full article
(This article belongs to the Special Issue Recent Advances in Remote Sensing with Nighttime Lights)
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Open AccessArticle Ku-, X- and C-Band Microwave Backscatter Indices from Saline Snow Covers on Arctic First-Year Sea Ice
Remote Sens. 2017, 9(7), 757; https://doi.org/10.3390/rs9070757
Received: 19 June 2017 / Revised: 13 July 2017 / Accepted: 19 July 2017 / Published: 23 July 2017
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Abstract
In this study, we inter-compared observed Ku-, X- and C-band microwave backscatter from saline 14 cm, 8 cm, and 4 cm snow covers on smooth first-year sea ice. A Ku-, X- and C-band surface-borne polarimetric microwave scatterometer system was used to measure fully-polarimetric
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In this study, we inter-compared observed Ku-, X- and C-band microwave backscatter from saline 14 cm, 8 cm, and 4 cm snow covers on smooth first-year sea ice. A Ku-, X- and C-band surface-borne polarimetric microwave scatterometer system was used to measure fully-polarimetric backscatter from the three snow covers, near-coincident with corresponding in situ snow thermophysical measurements. The study investigated differences in co-polarized backscatter observations from the scatterometer system for all three frequencies, modeled penetration depths, utilized co-pol ratios, and introduced dual-frequency ratios to discriminate dominant polarization-dependent frequencies from these snow covers. Results demonstrate that the measured co-polarized backscatter magnitude increased with decreasing snow thickness for all three frequencies, owing to stronger gradients in snow salinity within thinner snow covers. The innovative dual-frequency ratios suggest greater sensitivity of Ku-band microwaves to snow grain size as snow thickness increases and X-band microwaves to snow salinity changes as snow thickness decreases. C-band demonstrated minimal sensitivity to changes in snow salinities. Our results demonstrate the influence of salinity associated dielectric loss, throughout all layers of the three snow covers, as the governing factor affecting microwave backscatter and penetration from all three frequencies. Our “plot-scale” observations using co-polarized backscatter, co-pol ratios and dual-frequency ratios suggest the future potential to up-scale our multi-frequency approach to a “satellite-scale” approach, towards effective development of snow geophysical and thermodynamic retrieval algorithms on smooth first-year sea ice. Full article
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Open AccessArticle Saturation Correction for Nighttime Lights Data Based on the Relative NDVI
Remote Sens. 2017, 9(7), 759; https://doi.org/10.3390/rs9070759
Received: 3 June 2017 / Revised: 8 July 2017 / Accepted: 21 July 2017 / Published: 22 July 2017
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Abstract
DMSP/OLS images are widely used as data sources in various domains of study. However, these images have some deficiencies, one of which is digital number (DN) saturation in urban areas, which leads to significant underestimation of light intensity. We propose a new method
[...] Read more.
DMSP/OLS images are widely used as data sources in various domains of study. However, these images have some deficiencies, one of which is digital number (DN) saturation in urban areas, which leads to significant underestimation of light intensity. We propose a new method to correct the saturation. With China as the study area, the threshold value of the saturation DN is screened out first. A series of regression analyses are then carried out for the 2006 radiance calibrated nighttime lights (RCNL) image and relative NDVI (RNDVI) to determine a formula for saturation correction. The 2006 stable nighttime lights (SNL) image (F162006) is finally corrected and evaluated. It is concluded that pixels are saturated when the DN is larger than 50, and that the saturation is more serious when the DN is larger. RNDVI, which was derived by subtracting the interpolated NDVI from the real NDVI, is significantly better than the real NDVI for reflecting the degree of human activity. Quadratic functions describe the relationship between DN and RNDVI well. The 2006 SNL image presented more variation within urban cores and stronger correlations with the 2006 RCNL image and Gross Domestic Product after correction. However, RNDVI may also suffer “saturation” when it is lower than −0.4, at which point it is no longer effective at correcting DN saturation. In general, RNDVI is effective, although far from perfect, for saturation correction of the 2006 SNL image, and could be applied to the SNL images for other years. Full article
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Open AccessArticle Two-Step Downscaling of Trmm 3b43 V7 Precipitation in Contrasting Climatic Regions With Sparse Monitoring: The Case of Ecuador in Tropical South America
Remote Sens. 2017, 9(7), 758; https://doi.org/10.3390/rs9070758
Received: 2 June 2017 / Revised: 28 June 2017 / Accepted: 17 July 2017 / Published: 22 July 2017
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Abstract
Spatial prediction of precipitation with high resolution is a challenging task in regions with strong climate variability and scarce monitoring. For this purpose, the quasi-continuous supply of information from satellite imagery is commonly used to complement in situ data. However, satellite images of
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Spatial prediction of precipitation with high resolution is a challenging task in regions with strong climate variability and scarce monitoring. For this purpose, the quasi-continuous supply of information from satellite imagery is commonly used to complement in situ data. However, satellite images of precipitation are available at coarse resolutions, and require adequate methods for spatial downscaling and calibration. The objective of this paper is to introduce and evaluate a 2-step spatial downscaling approach for monthly precipitation applied to TRMM 3B43 (from 0 . 25 27 km to 5 km resolution), resulting in 5 downscaled products for the period 01-2001/12-2011. The methodology was evaluated in 3 contrasting climatic regions of Ecuador. In step 1, bilinear resampling was applied over TRMM, and used as a reference product. The second step introduces further variability, and consists of four alternative gauge-satellite merging methods: (1) regression with in situ stations, (2) regression kriging with in situ stations, (3) regression with in situ stations and auxiliary variables, and (4) regression kriging with in situ stations and auxiliary variables. The first 2 methods only use the resampled TRMM data set as an independent variable. The last 2 methods enrich these models with auxiliary environmental factors, incorporating atmospheric and land variables. The results showed that no product outperforms the others in every region. In general, the methods with residual kriging correction outperformed the regression models. Regression kriging with situ data provided the best representation in the Coast, while regression kriging with in situ and auxiliary data generated the best results in the Andes. In the Amazon, no product outperformed the resampled TRMM images, probably due to the low density of in situ stations. These results are relevant to enhance satellite precipitation, depending on the availability of in situ data, auxiliary satellite variables and the particularities of the climatic regions. Full article
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Open AccessArticle Passive Radar Array Processing with Non-Uniform Linear Arrays for Ground Target’s Detection and Localization
Remote Sens. 2017, 9(7), 756; https://doi.org/10.3390/rs9070756
Received: 1 May 2017 / Revised: 10 July 2017 / Accepted: 19 July 2017 / Published: 22 July 2017
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Abstract
The problem of ground target detection with passive radars is considered. The design of an antenna array based on commercial elements is presented, based on a non-uniform linear array optimized according to sidelobe level requirements. Array processing techniques are applied in the cross-ambiguity
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The problem of ground target detection with passive radars is considered. The design of an antenna array based on commercial elements is presented, based on a non-uniform linear array optimized according to sidelobe level requirements. Array processing techniques are applied in the cross-ambiguity function domain to exploit integration gain, system resolution and the sparsity of targets in this domain. A modified two-stage detection scheme is described, which is based on a previously-published one by other authors. All of these contributions are validated in a real semiurban scenario, proving the capabilities of detection, the direction of arrival estimation and the tracking of ground targets in the presence of big buildings that generate strong clutter returns. Detection performance is validated through the probability of false alarm and the probability of detection estimation with specified estimation errors. Full article
(This article belongs to the Special Issue Radar Systems for the Societal Challenges)
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Open AccessArticle Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) of the 30-m Reflective Wavelength Bands to Sentinel-2 20-m Resolution
Remote Sens. 2017, 9(7), 755; https://doi.org/10.3390/rs9070755
Received: 16 June 2017 / Revised: 16 July 2017 / Accepted: 20 July 2017 / Published: 22 July 2017
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Abstract
The Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) method to downscale Landsat-8 Operational Land Imager (OLI) 30-m data to Sentinel-2 multi-spectral instrument (MSI) 20-m resolution is presented. The method first downscales the Landsat-8 30-m OLI bands to 15-m using the spatial detail provided by the
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The Landsat 15-m Panchromatic-Assisted Downscaling (LPAD) method to downscale Landsat-8 Operational Land Imager (OLI) 30-m data to Sentinel-2 multi-spectral instrument (MSI) 20-m resolution is presented. The method first downscales the Landsat-8 30-m OLI bands to 15-m using the spatial detail provided by the Landsat-8 15-m panchromatic band and then reprojects and resamples the downscaled 15-m data into registration with Sentinel-2A 20-m data. The LPAD method is demonstrated using pairs of contemporaneous Landsat-8 OLI and Sentinel-2A MSI images sensed less than 19 min apart over diverse geographic environments. The LPAD method is shown to introduce less spectral and spatial distortion and to provide visually more coherent data than conventional bilinear and cubic convolution resampled 20-m Landsat OLI data. In addition, results for a pair of Landsat-8 and Sentinel-2A images sensed one day apart suggest that image fusion should be undertaken with caution when the images are acquired under different atmospheric conditions. The LPAD source code is available at GitHub for public use. Full article
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Open AccessTechnical Note LACO-Wiki: A New Online Land Cover Validation Tool Demonstrated Using GlobeLand30 for Kenya
Remote Sens. 2017, 9(7), 754; https://doi.org/10.3390/rs9070754
Received: 6 May 2017 / Revised: 30 June 2017 / Accepted: 19 July 2017 / Published: 22 July 2017
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Abstract
Accuracy assessment, also referred to as validation, is a key process in the workflow of developing a land cover map. To make this process open and transparent, we have developed a new online tool called LACO-Wiki, which encapsulates this process into a set
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Accuracy assessment, also referred to as validation, is a key process in the workflow of developing a land cover map. To make this process open and transparent, we have developed a new online tool called LACO-Wiki, which encapsulates this process into a set of four simple steps including uploading a land cover map, creating a sample from the map, interpreting the sample with very high resolution satellite imagery and generating a report with accuracy measures. The aim of this paper is to present the main features of this new tool followed by an example of how it can be used for accuracy assessment of a land cover map. For the purpose of illustration, we have chosen GlobeLand30 for Kenya. Two different samples were interpreted by three individuals: one sample was provided by the GlobeLand30 team as part of their international efforts in validating GlobeLand30 with GEO (Group on Earth Observation) member states while a second sample was generated using LACO-Wiki. Using satellite imagery from Google Maps, Bing and Google Earth, the results show overall accuracies between 53% to 61%, which is lower than the global accuracy assessment of GlobeLand30 but may be reasonable given the complex landscapes found in Kenya. Statistical models were then fit to the data to determine what factors affect the agreement between the three interpreters such as the land cover class, the presence of very high resolution satellite imagery and the age of the image in relation to the baseline year for GlobeLand30 (2010). The results showed that all factors had a significant effect on the agreement. Full article
(This article belongs to the Special Issue Validation on Global Land Cover Datasets)
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Open AccessArticle A Novel Method to Reconstruct Overhead High-Voltage Power Lines Using Cable Inspection Robot LiDAR Data
Remote Sens. 2017, 9(7), 753; https://doi.org/10.3390/rs9070753
Received: 24 June 2017 / Revised: 16 July 2017 / Accepted: 17 July 2017 / Published: 22 July 2017
Cited by 3 | PDF Full-text (12201 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Overhead high-voltage power lines are key components of power transmission and their monitoring has a very significant influence on security and reliability of power system. Advanced laser scanning techniques have been widely used to capture three-dimensional (3D) point clouds of power system scenes.
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Overhead high-voltage power lines are key components of power transmission and their monitoring has a very significant influence on security and reliability of power system. Advanced laser scanning techniques have been widely used to capture three-dimensional (3D) point clouds of power system scenes. Nevertheless, power line corridors are found in increasingly complex environments (e.g., mountains and forests), and the multi-loop structure on the same power line tower raises great challenges to process light detection and ranging (LiDAR) data. This paper addresses these challenges by constructing a new collection mode of LiDAR data for power lines using cable inspection robot (CIR). A novel method is proposed to extract and reconstruct power line using CIR LiDAR data, which has two advantages: (1) rapidly extracts power line point by position and orientation system (POS) extraction model; and (2) better solves pseudo-line during reconstruction of power line by structured partition. The proposed method mainly includes four steps: CIR LiDAR data generation, POS-based crude extraction, voxel-based accurate extraction and power line reconstruction. The feasibility and validity of the proposed method are verified by test site experiment and actual line experiment, demonstrating a fast and reliable solution to accurately reconstruct power line. Full article
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Open AccessFeature PaperArticle Minimizing the Residual Topography Effect on Interferograms to Improve DInSAR Results: Estimating Land Subsidence in Port-Said City, Egypt
Remote Sens. 2017, 9(7), 752; https://doi.org/10.3390/rs9070752
Received: 22 May 2017 / Revised: 15 July 2017 / Accepted: 18 July 2017 / Published: 21 July 2017
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Abstract
The accurate detection of land subsidence rates in urban areas is important to identify damage-prone areas and provide decision-makers with useful information. Meanwhile, no precise measurements of land subsidence have been undertaken within the coastal Port-Said City in Egypt to evaluate its hazard
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The accurate detection of land subsidence rates in urban areas is important to identify damage-prone areas and provide decision-makers with useful information. Meanwhile, no precise measurements of land subsidence have been undertaken within the coastal Port-Said City in Egypt to evaluate its hazard in relationship to sea-level rise. In order to address this shortcoming, this work introduces and evaluates a methodology that substantially improves small subsidence rate estimations in an urban setting. Eight ALOS/PALSAR-1 scenes were used to estimate the land subsidence rates in Port-Said City, using the Small BAse line Subset (SBAS) DInSAR technique. A stereo pair of ALOS/PRISM was used to generate an accurate DEM to minimize the residual topography effect on the generated interferograms. A total of 347 well distributed ground control points (GCP) were collected in Port-Said City using the leveling instrument to calibrate the generated DEM. Moreover, the eight PALSAR scenes were co-registered using 50 well-distributed GCPs and used to generate 22 interferogram pairs. These PALSAR interferograms were subsequently filtered and used together with the coherence data to calculate the phase unwrapping. The phase-unwrapped interferogram-pairs were then evaluated to discard four interferograms that were affected by phase jumps and phase ramps. Results confirmed that using an accurate DEM (ALOS/PRISM) was essential for accurately detecting small deformations. The vertical displacement rate during the investigated period (2007–2010) was estimated to be −28 mm. The results further indicate that the northern area of Port-Said City has been subjected to higher land subsidence rates compared to the southern area. Such land subsidence rates might induce significant environmental changes with respect to sea-level rise. Full article
(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)
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Open AccessArticle Influence of Ecological Factors on Estimation of Impervious Surface Area Using Landsat 8 Imagery
Remote Sens. 2017, 9(7), 751; https://doi.org/10.3390/rs9070751
Received: 25 May 2017 / Revised: 16 July 2017 / Accepted: 18 July 2017 / Published: 21 July 2017
Cited by 3 | PDF Full-text (5097 KB) | HTML Full-text | XML Full-text
Abstract
Estimation of impervious surface area is important to the study of urban environments and social development, but surface characteristics, as well as the temporal, spectral, and spatial resolutions of remote sensing images, influence the estimation accuracy. To investigate the effects of regional environmental
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Estimation of impervious surface area is important to the study of urban environments and social development, but surface characteristics, as well as the temporal, spectral, and spatial resolutions of remote sensing images, influence the estimation accuracy. To investigate the effects of regional environmental characteristics on the estimation of impervious surface area, we divided China into seven sub-regions based on climate, soil type, feature complexity, and vegetation phenology: arid and semi-arid areas, Huang-Huai-Hai winter wheat production areas, typical temperate regions, the Pearl River Delta, the middle and lower reaches of the Yangtze River, typical tropical and subtropical regions, and the Qinghai Tibet Plateau. Impervious surface area was estimated from Landsat 8 images of five typical cities, including Yinchuan, Shijiazhuang, Shenyang, Ningbo, and Kunming. Using the linear spectral unmixing method, impervious and permeable surface areas were determined at the pixel-scale based on end-member proportions. We calculated the producer’s accuracy, user’s accuracy, and overall accuracy to assess the estimation accuracy, and compared the accuracies among images acquired from different seasons and locations. In tropical and subtropical regions, vegetation canopies can confound the identification of impervious surfaces and, thus, images acquired in winter, early spring, and autumn are most suitable; estimations in the Pearl River Delta, the middle and lower reaches of the Yangtze River are influenced by soil, vegetation phenology, vegetation canopy, and water, and images acquired in spring, summer, and autumn provide the best results; in typical temperate areas, images acquired from spring to autumn are most effective for estimations; in winter wheat-growing areas, images acquired throughout the year are suitable; and in arid and semi-arid areas, summer and early autumn, during which vegetation is abundant, are the optimal seasons for estimations. Knowledge of optimal time frames, multi-source data, and intelligent algorithms should be integrated to reduce spectral confusion and improve the estimation of impervious surface area from Landsat 8 OLI imagery. Full article
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
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Open AccessArticle Bathymetry of the Coral Reefs of Weizhou Island Based on Multispectral Satellite Images
Remote Sens. 2017, 9(7), 750; https://doi.org/10.3390/rs9070750
Received: 26 May 2017 / Revised: 13 July 2017 / Accepted: 18 July 2017 / Published: 21 July 2017
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Abstract
Shallow water depth measurements using multispectral images are crucial for marine surveying and mapping. At present, relevant studies either depend on the use of other auxiliary data (such as field water depths or water column data) or contain too many unknown variables, thus
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Shallow water depth measurements using multispectral images are crucial for marine surveying and mapping. At present, relevant studies either depend on the use of other auxiliary data (such as field water depths or water column data) or contain too many unknown variables, thus making these studies suitable only for images that contain enough visible wavebands. To solve this problem, a Quasi-Analytical Algorithm (QAA) approach is proposed in this paper for estimating the water depths around Weizhou Island by developing a QAA to estimate the diffuse attenuation coefficients and simplifying the parameterization of the bathymetric model. The approach contains an initialization sub-approach and a novel global adjustment sub-approach. It is not only independent of other auxiliary data but also greatly reduces the number of unknowns. Experimental results finally demonstrated that the Root Mean Square Errors (RMSEs) were 1.01 m and 0.77 m for the ZY-3 image and the WorldView-3 (WV-3) image, respectively, so the approach is competitive to other QAA bathymetric methods. Besides, the global adjustment sub-approach was also seen to be superior to common smoothing filters: if the Signal-to-Noise Ratio (SNR) is as low as 42, i.e., ZY-3, it can smooth the water depths and improve the accuracies, otherwise can avoid the over-smoothing of water depths. Full article
(This article belongs to the Section Ocean Remote Sensing)
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Open AccessFeature PaperArticle Mapping of Aedes albopictus Abundance at a Local Scale in Italy
Remote Sens. 2017, 9(7), 749; https://doi.org/10.3390/rs9070749
Received: 7 May 2017 / Revised: 11 July 2017 / Accepted: 17 July 2017 / Published: 21 July 2017
Cited by 1 | PDF Full-text (5369 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Given the growing risk of arbovirus outbreaks in Europe, there is a clear need to better describe the distribution of invasive mosquito species such as Aedes albopictus. Current challenges consist in simulating Ae. albopictus abundance, rather than its presence, and mapping its
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Given the growing risk of arbovirus outbreaks in Europe, there is a clear need to better describe the distribution of invasive mosquito species such as Aedes albopictus. Current challenges consist in simulating Ae. albopictus abundance, rather than its presence, and mapping its simulated abundance at a local scale to better assess the transmission risk of mosquito-borne pathogens and optimize mosquito control strategy. During 2014–2015, we sampled adult mosquitoes using 72 BG-Sentinel traps per year in the provinces of Belluno and Trento, Italy. We found that the sum of Ae. albopictus females collected during eight trap nights from June to September was positively related to the mean temperature of the warmest quarter and the percentage of artificial areas in a 250 m buffer around the sampling locations. Maps of Ae. albopictus abundance simulated from the most parsimonious model in the study area showed the largest populations in highly artificial areas with the highest summer temperatures, but with a high uncertainty due to the variability of the trapping collections. Vector abundance maps at a local scale should be promoted to support stakeholders and policy-makers in optimizing vector surveillance and control. Full article
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Open AccessArticle Criteria Comparison for Classifying Peatland Vegetation Types Using In Situ Hyperspectral Measurements
Remote Sens. 2017, 9(7), 748; https://doi.org/10.3390/rs9070748
Received: 24 May 2017 / Revised: 26 June 2017 / Accepted: 9 July 2017 / Published: 20 July 2017
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Abstract
This study aims to evaluate three classes of methods to discriminate between 13 peatland vegetation types using reflectance data. These vegetation types were empirically defined according to their composition, strata and biodiversity richness. On one hand, it is assumed that the same vegetation
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This study aims to evaluate three classes of methods to discriminate between 13 peatland vegetation types using reflectance data. These vegetation types were empirically defined according to their composition, strata and biodiversity richness. On one hand, it is assumed that the same vegetation type spectral signatures have similarities. Consequently, they can be compared to a reference spectral database. To catch those similarities, several similarities criteria (related to distances (Euclidean distance, Manhattan distance, Canberra distance) or spectral shapes (Spectral Angle Mapper) or probabilistic behaviour (Spectral Information Divergence)) and several mathematical transformations of spectral signatures enhancing absorption features (such as the first derivative or the second derivative, the normalized spectral signature, the continuum removal, the continuum removal derivative reflectance, the log transformation) were investigated. Furthermore, those similarity measures were applied on spectral ranges which characterize specific biophysical properties. On the other hand, we suppose that specific biophysical properties/components may help to discriminate between vegetation types applying supervised classification such as Random Forest (RF), Support Vector Machines (SVM), Regularized Logistic Regression (RLR), Partial Least Squares-Discriminant Analysis (PLS-DA). Biophysical components can be used in a local way considering vegetation spectral indices or in a global way considering spectral ranges and transformed spectral signatures, as explained above. RLR classifier applied on spectral vegetation indices (training size = 25%) was able to achieve 77.21% overall accuracy in discriminating peatland vegetation types. It was also able to discriminate between 83.95% vegetation types considering specific spectral range [[range-phrase = –]3501350 n m ], first derivative of spectral signatures and training size = 25%. Conversely, similarity criterion was able to achieve 81.70% overall accuracy using the Canberra distance computed on the full spectral range [[range-phrase = –]3502500 n m ]. The results of this study suggest that RLR classifier and similarity criteria are promising to map the different vegetation types with high ecological values despite vegetation heterogeneity and mixture. Full article
(This article belongs to the Special Issue Hyperspectral Imaging and Applications)
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