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Remote Sens., Volume 5, Issue 12 (December 2013) – 39 articles , Pages 6159-7016

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7942 KiB  
Article
The Temporal-Spatial Distribution of Shule River Alluvial Fan Units in China Based on SAR Data and OSL Dating
by Lu Zhang and Huadong Guo
Remote Sens. 2013, 5(12), 6997-7016; https://doi.org/10.3390/rs5126997 - 16 Dec 2013
Cited by 5 | Viewed by 7223
Abstract
Alluvial fans in arid and semi-arid regions can provide important evidence of geomorphic and climatic changes, which reveal the evolution of the regional tectonic activity and environment. Synthetic aperture radar (SAR) remote sensing technology, which is sensitive to geomorphic features, plays an important [...] Read more.
Alluvial fans in arid and semi-arid regions can provide important evidence of geomorphic and climatic changes, which reveal the evolution of the regional tectonic activity and environment. Synthetic aperture radar (SAR) remote sensing technology, which is sensitive to geomorphic features, plays an important role in quickly mapping alluvial fan units of different ages. In this paper, RADARSAT-2 (Canada’s C-band new-generation radar satellite) and ALOS-PALSAR (Japan’s advanced land observing satellite, phased array type L-band SAR sensor) data, acquired over the Shule River Alluvial Fan (SRAF), are used to extract backscattering coefficients, scattering mechanism-related information, and polarimetric characteristic parameters. The correlation between these SAR characteristic parameters and fan units of the SRAF of different ages was studied, and the spatial distribution of fan units, since the Late Pleistocene, was extracted based on the Maximum Likelihood classification method. The results prove that (1) some C-band SAR parameters can describe the geomorphic characteristics of alluvial fan units of different ages in the SRAF; (2) SAR data can be used to map the SRAF’s surface between the Late Pleistocene and the Holocene and to extract the spatial distribution of fan units; and (3) the time-spatial distribution of the SRAF can provide valuable information for tectonic and paleoenvironmental research of the study area. Full article
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2376 KiB  
Article
Distribution of Actual Evapotranspiration over Qaidam Basin, an Arid Area in China
by Xiaomei Jin, Renhong Guo and Wei Xia
Remote Sens. 2013, 5(12), 6976-6996; https://doi.org/10.3390/rs5126976 - 13 Dec 2013
Cited by 38 | Viewed by 6978
Abstract
Evapotranspiration is a major loss flux of the water balance in arid and semi-arid areas. The estimation of actual evapotranspiration has significance for hydrological and environmental purposes. The Surface Energy Balance System (SEBS) algorithm was applied to estimate actual evapotranspiration in the Qaidam [...] Read more.
Evapotranspiration is a major loss flux of the water balance in arid and semi-arid areas. The estimation of actual evapotranspiration has significance for hydrological and environmental purposes. The Surface Energy Balance System (SEBS) algorithm was applied to estimate actual evapotranspiration in the Qaidam Basin and its eight hydrological sub-regions, Northwest China. There were 3,036 cloud-free and atmospherically corrected MODIS satellite images from 2001 to 2011 used in the SEBS algorithm to determine the actual evapotranspiration. The result indicated that the estimated annual actual evapotranspiration of the basin increased with time and the value varied from 72.7 to 182.3 mm. SEBS estimates were 7.5% and 14.1% of observed pan evaporation over the western and eastern areas, respectively. The variation of SEBS actual evapotranspiration is influenced by climate factors, vegetation, net radiation, land cover type and water table depth. The analysis of the evaporative behavior of different land cover types in the basin presented that water bodies, marsh, and farmland had relatively higher mean actual evapotranspiration though these land cover types make up less than 3.5% of the total basin. Bare soil has very low evapotranspiration and covered almost 60% of the study area. The actual evapotranspiration was observed to be decreased with an increase of water table depth. Overall, the SEBS algorithm proved to be useful and has potential for estimating spatial actual evapotranspiration on a regional scale. Full article
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637 KiB  
Article
The Application of Deep Convective Clouds in the Calibration and Response Monitoring of the Reflective Solar Bands of FY-3A/MERSI (Medium Resolution Spectral Imager)
by Lin Chen, Xiuqing Hu, Na Xu and Peng Zhang
Remote Sens. 2013, 5(12), 6958-6975; https://doi.org/10.3390/rs5126958 - 12 Dec 2013
Cited by 46 | Viewed by 6884
Abstract
Based on simulated reflectance, deep convective clouds (DCC) can be used as an invariant target to monitor the radiometric response degradation of the FY-3A/MERSI (Medium Resolution Spectral Imager) reflective solar bands (RSBs). The long-term response of the MERSI RSBs can easily be predicted [...] Read more.
Based on simulated reflectance, deep convective clouds (DCC) can be used as an invariant target to monitor the radiometric response degradation of the FY-3A/MERSI (Medium Resolution Spectral Imager) reflective solar bands (RSBs). The long-term response of the MERSI RSBs can easily be predicted using a quadratic fit of the monthly DCC mean reflectance, except for bands 6 and 7, which suffer from instrument anomalies. DCC-based degradations show that the blue bands (λ < 500 nm) and water-vapor bands have degraded significantly, whereas for near-infrared bands, the total degradations in four years are within 3% (excluding bands 3 and 20). For most bands, the degradation rates are greatest during the first year in orbit and decrease over time. The FY-3A/MERSI degradation results derived from DCC are consistent within 2.5%, except for bands, 11, 18 and 19, when compared with Aqua/MODIS(Moderate Resolution Imaging Sepetroradiometer) inter-calibration, multi-site invariant earth target calibration and the CRCS(Chinese Radiometric Calibration Site) Dunhuang desert vicarious calibration methods. Overall, the 2σ/mean degradation uncertainty for most MERSI bands was within 3%, validating the temporal stability of the DCC monthly mean reflectances. The DCC method has reduced the degradation uncertainties for MERSI water vapor bands over other methods. This is a significant advantage of the DCC calibration method. The saturation of some MERSI bands may hinder the effectiveness of the DCC calibration approach. Full article
(This article belongs to the Special Issue Calibration and Verification of Remote Sensing Instruments and Observations)
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1723 KiB  
Article
Long-Term Satellite Detection of Post-Fire Vegetation Trends in Boreal Forests of China
by Kunpeng Yi, Hiroshi Tani, Jiquan Zhang, Meng Guo, Xiufeng Wang and Guosheng Zhong
Remote Sens. 2013, 5(12), 6938-6957; https://doi.org/10.3390/rs5126938 - 12 Dec 2013
Cited by 23 | Viewed by 7908
Abstract
This paper describes the long-term effects on vegetation following the catastrophic fire in 1987 on the northern Great Xing’an Mountain by analyzing the AVHRR GIMMS 15-day composite normalized difference vegetation index (NDVI) dataset. Both temporal and spatial characteristics were analyzed for natural regeneration [...] Read more.
This paper describes the long-term effects on vegetation following the catastrophic fire in 1987 on the northern Great Xing’an Mountain by analyzing the AVHRR GIMMS 15-day composite normalized difference vegetation index (NDVI) dataset. Both temporal and spatial characteristics were analyzed for natural regeneration and tree planting scenarios from 1984 to 2006. Regressing post-fire NDVI values on the pre-fire values helped identify the NDVI for burnt pixels in vegetation stands. Stand differences in fire damage were classified into five levels: Very High (VH), High (H), Moderate (M), Low (L) and Slight (S). Furthermore, intra-annual and inter-annual post-fire vegetation recovery trajectories were analyzed by deriving a time series of NDVI and relative regrowth index (RRI) values for the entire burned area. Finally, spatial pattern and trend analyses were conducted using the pixel-based post-fire annual stands regrowth index (SRI) with a nonparametric Mann-Kendall (MK) statistics method. The results show that October was a better period compared to other months for distinguishing the post- and pre-fire vegetation conditions using the NDVI signals in boreal forests of China because colored leaves on grasses and shrubs fall down, while the leaves on healthy trees remain green in October. The MK statistics method is robustly capable of detecting vegetation trends in a relatively long time series. Because tree planting primarily occurred in the severely burned area (approximately equal to the Medium, High and Very High fire damage areas) following the Daxing’anling fire in 1987, the severely burned area exhibited a better recovery trend than the lightly burned regions. Reasonable tree planting can substantially quicken the recovery and shorten the restoration time of the target species. More detailed satellite analyses and field data will be required in the future for a more convincing validation of the results. Full article
(This article belongs to the Special Issue Quantifying the Environmental Impact of Forest Fires)
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1659 KiB  
Article
Block-to-Point Fine Registration in Terrestrial Laser Scanning
by Jin Wang
Remote Sens. 2013, 5(12), 6921-6937; https://doi.org/10.3390/rs5126921 - 11 Dec 2013
Cited by 13 | Viewed by 7532
Abstract
Fine registration of point clouds plays an important role in data analysis in Terrestrial Laser Scanning (TLS). This work proposes a block-to-point fine registration approach to correct the errors of point clouds from TLS and of geodetic networks observed using total stations. Based [...] Read more.
Fine registration of point clouds plays an important role in data analysis in Terrestrial Laser Scanning (TLS). This work proposes a block-to-point fine registration approach to correct the errors of point clouds from TLS and of geodetic networks observed using total stations. Based on a reference coordinate system, the block-to-point estimation is performed to obtain representative points. Then, fine registration with a six-parameter transformation is performed with the help of an Iterative Closest Point (ICP) method. For comparisons, fine registration with a seven-parameter transformation is introduced by applying a Singular Value Decomposition (SVD) algorithm. The proposed method not only corrects the registration errors between a geodetic network and the scans, but also considers the errors among the scans. The proposed method was tested on real TLS data of a dam surface, and the results showed that distance discrepancies of estimated representative points between scans were reduced by approximately 60%. Full article
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3473 KiB  
Article
Ship Discrimination Using Polarimetric SAR Data and Coherent Time-Frequency Analysis
by Canbin Hu, Laurent Ferro-Famil and Gangyao Kuang
Remote Sens. 2013, 5(12), 6899-6920; https://doi.org/10.3390/rs5126899 - 11 Dec 2013
Cited by 27 | Viewed by 6425
Abstract
This paper presents a new approach for the discrimination of ship responses using polarimetric SAR (PolSAR) data. The PolSAR multidimensional information is analyzed using a linear Time-Frequency (TF) decomposition approach, which permits to describe the polarimetric behavior of a ship and its background [...] Read more.
This paper presents a new approach for the discrimination of ship responses using polarimetric SAR (PolSAR) data. The PolSAR multidimensional information is analyzed using a linear Time-Frequency (TF) decomposition approach, which permits to describe the polarimetric behavior of a ship and its background area for different azimuthal angles of observation and frequencies of illumination. This paper proposes to discriminate ships from their background by using characteristics of their polarimetric TF responses, which may be associated with the intrinsic nature of the observed natural or artificial scattering structures. A statistical descriptor related to polarimetric coherence of the signal in the TF domain is proposed for detecting ships in different complex backgrounds, including SAR azimuth ambiguities, artifacts, and small natural islands, which may induce numerous false alarms. Choices of the TF analysis direction, i.e., along separate azimuth or range axis, or simultaneously in both directions, are investigated and evaluated. TF decomposition modes including range direction perform better in terms of discriminating ships from range focusing artifacts. In comparison with original full-resolution polarimetric indicators, the proposed TF polarimetric coherence descriptor is shown to qualitatively enhance the ship/background contrast and improve discrimination capabilities. Using polarimetric RADARSAT-2 data acquired over complex scenes, experimental results demonstrate the efficiency of this approach in terms of ship location retrieval and response characterization. Full article
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7327 KiB  
Article
Using Unmanned Aerial Vehicles (UAV) for High-Resolution Reconstruction of Topography: The Structure from Motion Approach on Coastal Environments
by Francesco Mancini, Marco Dubbini, Mario Gattelli, Francesco Stecchi, Stefano Fabbri and Giovanni Gabbianelli
Remote Sens. 2013, 5(12), 6880-6898; https://doi.org/10.3390/rs5126880 - 09 Dec 2013
Cited by 625 | Viewed by 41143
Abstract
The availability of high-resolution Digital Surface Models of coastal environments is of increasing interest for scientists involved in the study of the coastal system processes. Among the range of terrestrial and aerial methods available to produce such a dataset, this study tests the [...] Read more.
The availability of high-resolution Digital Surface Models of coastal environments is of increasing interest for scientists involved in the study of the coastal system processes. Among the range of terrestrial and aerial methods available to produce such a dataset, this study tests the utility of the Structure from Motion (SfM) approach to low-altitude aerial imageries collected by Unmanned Aerial Vehicle (UAV). The SfM image-based approach was selected whilst searching for a rapid, inexpensive, and highly automated method, able to produce 3D information from unstructured aerial images. In particular, it was used to generate a dense point cloud and successively a high-resolution Digital Surface Models (DSM) of a beach dune system in Marina di Ravenna (Italy). The quality of the elevation dataset produced by the UAV-SfM was initially evaluated by comparison with point cloud generated by a Terrestrial Laser Scanning (TLS) surveys. Such a comparison served to highlight an average difference in the vertical values of 0.05 m (RMS = 0.19 m). However, although the points cloud comparison is the best approach to investigate the absolute or relative correspondence between UAV and TLS methods, the assessment of geomorphic features is usually based on multi-temporal surfaces analysis, where an interpolation process is required. DSMs were therefore generated from UAV and TLS points clouds and vertical absolute accuracies assessed by comparison with a Global Navigation Satellite System (GNSS) survey. The vertical comparison of UAV and TLS DSMs with respect to GNSS measurements pointed out an average distance at cm-level (RMS = 0.011 m). The successive point by point direct comparison between UAV and TLS elevations show a very small average distance, 0.015 m, with RMS = 0.220 m. Larger values are encountered in areas where sudden changes in topography are present. The UAV-based approach was demonstrated to be a straightforward one and accuracy of the vertical dataset was comparable with results obtained by TLS technology. Full article
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526 KiB  
Article
Integrating Solar Induced Fluorescence and the Photochemical Reflectance Index for Estimating Gross Primary Production in a Cornfield
by Yen-Ben Cheng, Elizabeth M. Middleton, Qingyuan Zhang, Karl F. Huemmrich, Petya K. E. Campbell, Lawrence A. Corp, Bruce D. Cook, William P. Kustas and Craig S. Daughtry
Remote Sens. 2013, 5(12), 6857-6879; https://doi.org/10.3390/rs5126857 - 09 Dec 2013
Cited by 85 | Viewed by 9952
Abstract
The utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four growing seasons. [...] Read more.
The utilization of remotely sensed observations for light use efficiency (LUE) and tower-based gross primary production (GPP) estimates was studied in a USDA cornfield. Nadir hyperspectral reflectance measurements were acquired at canopy level during a collaborative field campaign conducted in four growing seasons. The Photochemical Reflectance Index (PRI) and solar induced chlorophyll fluorescence (SIF), were derived. SIF retrievals were accomplished in the two telluric atmospheric oxygen absorption features centered at 688 nm (O2-B) and 760 nm (O2-A). The PRI and SIF were examined in conjunction with GPP and LUE determined by flux tower-based measurements. All of these fluxes, environmental variables, and the PRI and SIF exhibited diurnal as well as day-to-day dynamics across the four growing seasons. Consistent with previous studies, the PRI was shown to be related to LUE (r2 = 0.54 with a logarithm fit), but the relationship varied each year. By combining the PRI and SIF in a linear regression model, stronger performances for GPP estimation were obtained. The strongest relationship (r2 = 0.80, RMSE = 0.186 mg CO2/m2/s) was achieved when using the PRI and SIF retrievals at 688 nm. Cross-validation approaches were utilized to demonstrate the robustness and consistency of the performance. This study highlights a GPP retrieval method based entirely on hyperspectral remote sensing observations. Full article
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1040 KiB  
Article
Application of a Land Surface Model Using Remote Sensing Data for High Resolution Simulations of Terrestrial Processes
by Hyun Il Choi
Remote Sens. 2013, 5(12), 6838-6856; https://doi.org/10.3390/rs5126838 - 09 Dec 2013
Cited by 8 | Viewed by 8188
Abstract
Most current land surface models (LSMs) coupled to regional climate models (RCMs) have been implemented at the several tens of kilometer spatial scales. Modeling land surface processes in LSMs at a finer resolution is necessary for improvements in terrestrial water and energy predictions [...] Read more.
Most current land surface models (LSMs) coupled to regional climate models (RCMs) have been implemented at the several tens of kilometer spatial scales. Modeling land surface processes in LSMs at a finer resolution is necessary for improvements in terrestrial water and energy predictions especially for small catchments. This study has therefore assessed the applicability of high-resolution simulations for terrestrial processes to a small study basin from the Common Land Model (CoLM) using 1-km surface boundary conditions (SBCs) based on remote sensing products. The performance of the CoLM simulations at finer (1-km) and coarser (30-km) resolutions are evaluated for daily runoff and land surface temperature results which have a significant influence on the terrestrial water and energy cycles. The daily stream water temperature is also estimated by a linear regression function of the 1-km daily land surface temperature prediction. The daily stream runoff and temperature results are compared with observations from a stream gauge station, and the daily land surface temperature prediction is compared with the 1-km remote sensing product. It is observed that the high-resolution CoLM results can reasonably capture seasonal variations in both daily runoff and temperatures crucial to the terrestrial water and energy budget. Full article
(This article belongs to the Special Issue Remote Sensing in Geomorphology)
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1917 KiB  
Article
Future Retrievals of Water Column Bio-Optical Properties using the Hyperspectral Infrared Imager (HyspIRI)
by Emmanuel Devred, Kevin R. Turpie, Wesley Moses, Victor V. Klemas, Tiffany Moisan, Marcel Babin, Gerardo Toro-Farmer, Marie-Hélène Forget and Young-Heon Jo
Remote Sens. 2013, 5(12), 6812-6837; https://doi.org/10.3390/rs5126812 - 06 Dec 2013
Cited by 58 | Viewed by 10686
Abstract
Interpretation of remote sensing reflectance from coastal waters at different wavelengths of light yields valuable information about water column constituents, which in turn, gives information on a variety of processes occurring in coastal waters, such as primary production, biogeochemical cycles, sediment transport, coastal [...] Read more.
Interpretation of remote sensing reflectance from coastal waters at different wavelengths of light yields valuable information about water column constituents, which in turn, gives information on a variety of processes occurring in coastal waters, such as primary production, biogeochemical cycles, sediment transport, coastal erosion, and harmful algal blooms. The Hyperspectral Infrared Imager (HyspIRI) is well suited to produce global, seasonal maps and specialized observations of coastal ecosystems and to improve our understanding of how phytoplankton communities are spatially distributed and structured, and how they function in coastal and inland waters. This paper draws from previously published studies on high-resolution, hyperspectral remote sensing of coastal and inland waters and provides an overview of how the HyspIRI mission could enable the retrieval of new aquatic biophysical products or improve the retrieval accuracy of existing satellite-derived products (e.g., inherent optical properties, phytoplankton functional types, pigment composition, chlorophyll-a concentration, etc.). The intent of this paper is to introduce the development of the HyspIRI mission to the coastal and inland remote sensing community and to provide information regarding several potential data products that were not originally part of the HyspIRI mission objectives but could be applicable to research related to coastal and inland waters. Further work toward quantitatively determining the extent and quality of these products, given the instrument and mission characteristics, is recommended. Full article
(This article belongs to the Special Issue Remote Sensing of Phytoplankton)
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957 KiB  
Article
A Downscaling Method for Improving the Spatial Resolution of AMSR-E Derived Soil Moisture Product Based on MSG-SEVIRI Data
by Wei Zhao and Ainong Li
Remote Sens. 2013, 5(12), 6790-6811; https://doi.org/10.3390/rs5126790 - 06 Dec 2013
Cited by 67 | Viewed by 9632
Abstract
Soil moisture is a vital parameter in various land surface processes, and microwave remote sensing is widely used to estimate regional soil moisture. However, the application of the retrieved soil moisture data is restricted by its coarse spatial resolution. To overcome this weakness, [...] Read more.
Soil moisture is a vital parameter in various land surface processes, and microwave remote sensing is widely used to estimate regional soil moisture. However, the application of the retrieved soil moisture data is restricted by its coarse spatial resolution. To overcome this weakness, many methods were proposed to downscale microwave soil moisture data. The traditional method is the microwave-optical/IR synergistic approach, in which land surface temperature (LST), vegetation index and surface albedo are key parameters. However, due to the uncertainty in absolute LST estimation, this approach is partly dependent on the accuracy of LST estimation. To eliminate the impacts of LST estimation, an improved downscaling method is proposed in this study to downscale Advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR-E) Land Parameter Retrieval Model (LPRM) soil moisture product with visible and thermal data of Meteosat Second Generation (MSG)—Spinning Enhanced Visible and Infrared Imager (SEVIRI). Two temperature temporal variation parameters related to soil moisture, including mid-morning rising rate and daily maximum temperature time, are introduced in the proposed method to replace LST. The proposed method and the traditional method are both applied to the Iberian Peninsula area for July and August 2007. Comparison of the two results shows that the coefficient of determination (R-squared) has an average improvement of 0.08 and the root mean square error has a systematic decrease. The downscaled soil moisture by the proposed method was validated by REMEDHUS soil moisture network in the study area, and site specific validation gets poor correlation between the two datasets because of the low spatial representativeness of site measurement for one MSG-SEVIRI pixel. Although the comparisons at 15 km and network scale show an improvement over the site specific comparison, it is found that the downscaling method systematically degrades the accuracy in soil moisture data, with a R-squared of 0–0.4 and 0.218 for the downscaled data set against 0.7–0.8 and 0.571 for AMSR-E data at 15 km scale and the network scale respectively. Full article
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1474 KiB  
Article
Evaluation of Different Topographic Corrections for Landsat TM Data by Prediction of Foliage Projective Cover (FPC) in Topographically Complex Landscapes
by Sisira Ediriweera, Sumith Pathirana, Tim Danaher, Doland Nichols and Trevor Moffiet
Remote Sens. 2013, 5(12), 6767-6789; https://doi.org/10.3390/rs5126767 - 06 Dec 2013
Cited by 24 | Viewed by 8039
Abstract
The reflected radiance in topographically complex areas is severely affected by variations in topography; thus, topographic correction is considered a necessary pre-processing step when retrieving biophysical variables from these images. We assessed the performance of five topographic corrections: (i) C correction (C), (ii) [...] Read more.
The reflected radiance in topographically complex areas is severely affected by variations in topography; thus, topographic correction is considered a necessary pre-processing step when retrieving biophysical variables from these images. We assessed the performance of five topographic corrections: (i) C correction (C), (ii) Minnaert, (iii) Sun Canopy Sensor (SCS), (iv) SCS + C and (v) the Processing Scheme for Standardised Surface Reflectance (PSSSR) on the Landsat-5 Thematic Mapper (TM) reflectance in the context of prediction of Foliage Projective Cover (FPC) in hilly landscapes in north-eastern Australia. The performance of topographic corrections on the TM reflectance was assessed by (i) visual comparison and (ii) statistically comparing TM predicted FPC with ground measured FPC and LiDAR (Light Detection and Ranging)-derived FPC estimates. In the majority of cases, the PSSSR method performed best in terms of eliminating topographic effects, providing the best relationship and lowest residual error when comparing ground measured FPC and LiDAR FPC with TM predicted FPC. The Minnaert, C and SCS + C showed the poorest performance. Finally, the use of TM surface reflectance, which includes atmospheric correction and broad Bidirectional Reflectance Distribution Function (BRDF) effects, seemed to account for most topographic variation when predicting biophysical variables, such as FPC. Full article
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14034 KiB  
Article
Illuminating the Capabilities of the Suomi National Polar-Orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band
by Steven D. Miller, William Straka III, Stephen P. Mills, Christopher D. Elvidge, Thomas F. Lee, Jeremy Solbrig, Andi Walther, Andrew K. Heidinger and Stephanie C. Weiss
Remote Sens. 2013, 5(12), 6717-6766; https://doi.org/10.3390/rs5126717 - 06 Dec 2013
Cited by 266 | Viewed by 22880
Abstract
Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information [...] Read more.
Daytime measurements of reflected sunlight in the visible spectrum have been a staple of Earth-viewing radiometers since the advent of the environmental satellite platform. At night, these same optical-spectrum sensors have traditionally been limited to thermal infrared emission, which contains relatively poor information content for many important weather and climate parameters. These deficiencies have limited our ability to characterize the full diurnal behavior and processes of parameters relevant to improved monitoring, understanding and modeling of weather and climate processes. Visible-spectrum light information does exist during the nighttime hours, originating from a wide variety of sources, but its detection requires specialized technology. Such measurements have existed, in a limited way, on USA Department of Defense satellites, but the Suomi National Polar-orbiting Partnership (NPP) satellite, which carries a new Day/Night Band (DNB) radiometer, offers the first quantitative measurements of nocturnal visible and near-infrared light. Here, we demonstrate the expanded potential for nocturnal low-light visible applications enabled by the DNB. Via a combination of terrestrial and extraterrestrial light sources, such observations are always available—expanding many current existing applications while enabling entirely new capabilities. These novel low-light measurements open doors to a wealth of new interdisciplinary research topics while lighting a pathway toward the optimized design of follow-on satellite based low light visible sensors. Full article
(This article belongs to the Special Issue Optical Remote Sensing of the Atmosphere)
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6200 KiB  
Article
Dynamic Hydrological Modeling in Drylands with TRMM Based Rainfall
by Elena Tarnavsky, Mark Mulligan, Mohamed Ouessar, Abdoulaye Faye and Emily Black
Remote Sens. 2013, 5(12), 6691-6716; https://doi.org/10.3390/rs5126691 - 04 Dec 2013
Cited by 17 | Viewed by 9649
Abstract
This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to [...] Read more.
This paper introduces and evaluates DryMOD, a dynamic water balance model of the key hydrological process in drylands that is based on free, public-domain datasets. The rainfall model of DryMOD makes optimal use of spatially disaggregated Tropical Rainfall Measuring Mission (TRMM) datasets to simulate hourly rainfall intensities at a spatial resolution of 1-km. Regional-scale applications of the model in seasonal catchments in Tunisia and Senegal characterize runoff and soil moisture distribution and dynamics in response to varying rainfall data inputs and soil properties. The results highlight the need for hourly-based rainfall simulation and for correcting TRMM 3B42 rainfall intensities for the fractional cover of rainfall (FCR). Without FCR correction and disaggregation to 1 km, TRMM 3B42 based rainfall intensities are too low to generate surface runoff and to induce substantial changes to soil moisture storage. The outcomes from the sensitivity analysis show that topsoil porosity is the most important soil property for simulation of runoff and soil moisture. Thus, we demonstrate the benefit of hydrological investigations at a scale, for which reliable information on soil profile characteristics exists and which is sufficiently fine to account for the heterogeneities of these. Where such information is available, application of DryMOD can assist in the spatial and temporal planning of water harvesting according to runoff-generating areas and the runoff ratio, as well as in the optimization of agricultural activities based on realistic representation of soil moisture conditions. Full article
(This article belongs to the Special Issue Hydrological Remote Sensing)
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3961 KiB  
Article
Hierarchical Bayesian Data Analysis in Radiometric SAR System Calibration: A Case Study on Transponder Calibration with RADARSAT-2 Data
by Björn J. Döring, Kersten Schmidt, Matthias Jirousek, Daniel Rudolf, Jens Reimann, Sebastian Raab, John Walter Antony and Marco Schwerdt
Remote Sens. 2013, 5(12), 6667-6690; https://doi.org/10.3390/rs5126667 - 04 Dec 2013
Cited by 19 | Viewed by 8806
Abstract
A synthetic aperture radar (SAR) system requires external absolute calibration so that radiometric measurements can be exploited in numerous scientific and commercial applications. Besides estimating a calibration factor, metrological standards also demand the derivation of a respective calibration uncertainty. This uncertainty is currently [...] Read more.
A synthetic aperture radar (SAR) system requires external absolute calibration so that radiometric measurements can be exploited in numerous scientific and commercial applications. Besides estimating a calibration factor, metrological standards also demand the derivation of a respective calibration uncertainty. This uncertainty is currently not systematically determined. Here for the first time it is proposed to use hierarchical modeling and Bayesian statistics as a consistent method for handling and analyzing the hierarchical data typically acquired during external calibration campaigns. Through the use of Markov chain Monte Carlo simulations, a joint posterior probability can be conveniently derived from measurement data despite the necessary grouping of data samples. The applicability of the method is demonstrated through a case study: The radar reflectivity of DLR’s new C-band Kalibri transponder is derived through a series of RADARSAT-2 acquisitions and a comparison with reference point targets (corner reflectors). The systematic derivation of calibration uncertainties is seen as an important step toward traceable radiometric calibration of synthetic aperture radars. Full article
(This article belongs to the Special Issue Calibration and Verification of Remote Sensing Instruments and Observations)
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462 KiB  
Article
Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery
by Jonathan Van Beek, Laurent Tits, Ben Somers and Pol Coppin
Remote Sens. 2013, 5(12), 6647-6666; https://doi.org/10.3390/rs5126647 - 04 Dec 2013
Cited by 31 | Viewed by 7558 | Correction
Abstract
Remote sensing can provide good alternatives for traditional in situ water status measurements in orchard crops, such as stem water potential (Ψstem). However, the heterogeneity of these cropping systems causes significant differences with regards to remote sensing products within one orchard [...] Read more.
Remote sensing can provide good alternatives for traditional in situ water status measurements in orchard crops, such as stem water potential (Ψstem). However, the heterogeneity of these cropping systems causes significant differences with regards to remote sensing products within one orchard and between orchards. In this study, robust spectral indicators of Ψstem were sought after, independent of sensor viewing geometry, orchard architecture and management. To this end, Ψstem was monitored throughout three consecutive growing seasons in (deficit) irrigated and rainfed pear orchards and related to spectral observations of leaves, canopies and WorldView-2 imagery. On a leaf and canopy level, high correlations were observed between the shortwave infrared reflectance and in situ measured Ψstem. Additionally, for canopy measurements, visible and near-infrared wavelengths (R530/R600, R530/R700 and R720/R800) showed significant correlations. Therefore, the Red-edge Normalized Difference Vegetation Index (ReNDVI) was applied on fully sunlit satellite imagery and found strongly related with Ψstem (R2 = 0.47; RMSE = 0.36 MPa), undoubtedly showing the potential of WorldView-2 to monitor water stress in pear orchards. The relationship between ReNDVI and Ψstem was independent of management, irrigation setup, phenology and environmental conditions. In addition, results showed that this relation was also independent of off-nadir viewing angle and almost independent of viewing geometry, as the correlation decreased after the inclusion of fully shaded scenes. With further research focusing on issues related to viewing geometry and shadows, high spatial water status monitoring with space borne remote sensing is achievable. Full article
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8768 KiB  
Article
Indoor Localization Algorithms for an Ambulatory Human Operated 3D Mobile Mapping System
by Nicholas Corso and Avideh Zakhor
Remote Sens. 2013, 5(12), 6611-6646; https://doi.org/10.3390/rs5126611 - 03 Dec 2013
Cited by 45 | Viewed by 8252
Abstract
Indoor localization and mapping is an important problem with many applications such as emergency response, architectural modeling, and historical preservation. In this paper, we develop an automatic, off-line pipeline for metrically accurate, GPS-denied, indoor 3D mobile mapping using a human-mounted backpack system consisting [...] Read more.
Indoor localization and mapping is an important problem with many applications such as emergency response, architectural modeling, and historical preservation. In this paper, we develop an automatic, off-line pipeline for metrically accurate, GPS-denied, indoor 3D mobile mapping using a human-mounted backpack system consisting of a variety of sensors. There are three novel contributions in our proposed mapping approach. First, we present an algorithm which automatically detects loop closure constraints from an occupancy grid map. In doing so, we ensure that constraints are detected only in locations that are well conditioned for scan matching. Secondly, we address the problem of scan matching with poor initial condition by presenting an outlier-resistant, genetic scan matching algorithm that accurately matches scans despite a poor initial condition. Third, we present two metrics based on the amount and complexity of overlapping geometry in order to vet the estimated loop closure constraints. By doing so, we automatically prevent erroneous loop closures from degrading the accuracy of the reconstructed trajectory. The proposed algorithms are experimentally verified using both controlled and real-world data. The end-to-end system performance is evaluated using 100 surveyed control points in an office environment and obtains a mean accuracy of 10 cm. Experimental results are also shown on three additional datasets from real world environments including a 1500 meter trajectory in a warehouse sized retail shopping center. Full article
(This article belongs to the Special Issue Advances in Mobile Laser Scanning and Mobile Mapping)
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5643 KiB  
Article
Temporal and Seasonal Variations of the Hot Spring Basin Hydrothermal System, Yellowstone National Park, USA
by Cheryl Jaworowski, Henry Heasler, Christopher Neale, Sivarajan Saravanan and Ashish Masih
Remote Sens. 2013, 5(12), 6587-6610; https://doi.org/10.3390/rs5126587 - 03 Dec 2013
Cited by 7 | Viewed by 7410
Abstract
Monitoring Yellowstone National Park’s hydrothermal systems and establishing hydrothermal baselines are the main goals of an ongoing collaborative effort between Yellowstone National Park’s Geology program and Utah State University’s Remote Sensing Services Laboratory. During the first years of this research effort, improvements were [...] Read more.
Monitoring Yellowstone National Park’s hydrothermal systems and establishing hydrothermal baselines are the main goals of an ongoing collaborative effort between Yellowstone National Park’s Geology program and Utah State University’s Remote Sensing Services Laboratory. During the first years of this research effort, improvements were made in image acquisition, processing and calibration. In 2007, a broad-band, forward looking infrared (FLIR) camera (8–12 microns) provided reliable airborne images for a hydrothermal baseline of the Hot Spring Basin hydrothermal system. From 2008 to 2011, night-time, airborne thermal infrared image acquisitions during September yielded temperature maps that established the temporal variability of the hydrothermal system. A March 2012 airborne image acquisition provided an initial assessment of seasonal variability. The consistent, high-spatial resolution imagery (~1 m) demonstrates that the technique is robust and repeatable for generating corrected (atmosphere and emissivity) and calibrated temperature maps of the Hot Spring Basin hydrothermal system. Atmospheric conditions before and at flight-time determine the usefulness of the thermal infrared imagery for geohydrologic applications, such as hydrothermal monitoring. Although these ground-surface temperature maps are easily understood, quantification of radiative heat from the Hot Spring Basin hydrothermal system is an estimate of the system’s total energy output. Area is a key parameter for calculating the hydrothermal system’s heat output. Preliminary heat calculations suggest a radiative heat output of ~56 MW to 62 MW for the central Hot Spring Basin hydrothermal system. Challenges still remain in removing the latent solar component within the calibrated, atmospherically adjusted, and emissivity corrected night-time imagery. Full article
(This article belongs to the Special Issue Hydrological Remote Sensing)
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7694 KiB  
Article
Orthogonal Equations of Multi-Spectral Satellite Imagery for the Identification of Un-Excavated Archaeological Sites
by Athos Agapiou, Dimitrios D. Alexakis, Apostolos Sarris and Diofantos G. Hadjimitsis
Remote Sens. 2013, 5(12), 6560-6586; https://doi.org/10.3390/rs5126560 - 03 Dec 2013
Cited by 44 | Viewed by 9545
Abstract
This paper aims to introduce new linear orthogonal equations for different satellite data derived from QuickBird; IKONOS; WorldView-2; GeoEye-1, ASTER; Landsat 4 TM and Landsat 7 ETM+ sensors, in order to enhance the exposure of crop marks. The latest are of significant value [...] Read more.
This paper aims to introduce new linear orthogonal equations for different satellite data derived from QuickBird; IKONOS; WorldView-2; GeoEye-1, ASTER; Landsat 4 TM and Landsat 7 ETM+ sensors, in order to enhance the exposure of crop marks. The latest are of significant value for the detection of buried archaeological features using remote sensing techniques. The proposed transformations, re-projects the initial VNIR bands of the satellite image, into a new 3D coordinate system where the first component is the so called “crop mark”, the second component “vegetation” and the third component “soil”. For the purpose of this study, a large ground spectral signature database has been explored and analyzed separately for each different satellite image. The narrow band reflectance has been re-calculated using the Relative Spectral Response filters of each sensor, and then a PCA analysis was carried out. Subsequently, the first three PCA components were rotated in order to enhance the detection of crop marks. Finally, all proposed transformations have been successfully evaluated in different existing archaeological sites and some interesting crop marks have been exposed. Full article
(This article belongs to the Special Issue New Perspectives of Remote Sensing for Archaeology)
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5639 KiB  
Article
Spatial Quality Assessment of Pan-Sharpened High Resolution Satellite Imagery Based on an Automatically Estimated Edge Based Metric
by Farzaneh Dadras Javan, Farhad Samadzadegan and Peter Reinartz
Remote Sens. 2013, 5(12), 6539-6559; https://doi.org/10.3390/rs5126539 - 03 Dec 2013
Cited by 33 | Viewed by 7612
Abstract
Most of the existing pan-sharpening quality assessment methods consider only the spectral quality and there are just few investigations, which concentrate on spatial characteristics. Spatial quality of pan-sharpened images is vital in elaborating the capability of object extraction, identification, or reconstruction, especially regarding [...] Read more.
Most of the existing pan-sharpening quality assessment methods consider only the spectral quality and there are just few investigations, which concentrate on spatial characteristics. Spatial quality of pan-sharpened images is vital in elaborating the capability of object extraction, identification, or reconstruction, especially regarding man-made objects and their application for large scale mapping in urban areas. This paper presents an Edge based image Fusion Metric (EFM) for spatial quality evaluation of pan-sharpening in high resolution satellite imagery. Considering Modulation Transfer Function (MTF) as a precise measurement of edge response, MTFs of pan-sharpened images are assessed and compared to those obtained from the original multispectral or panchromatic images. Spatial quality assessment of pan-sharpening is done by comparison of MTF curves of the pan-sharpened and reference images. The capability of the proposed method is evaluated by quality assessment of two different residential and industrial urban areas of WorldView-2 pan-sharpened images. Obtained results clearly show the wide spatial discrepancy in quality of Pan-sharpened images, resulting from different fusion methods, and confirm the need for spatial quality assessment of fused products. The results also prove the capability of the proposed EFM as a powerful tool for evaluation and comparison of different image fusion techniques and products. Full article
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2080 KiB  
Article
Combined Spatial and Temporal Effects of Environmental Controls on Long-Term Monthly NDVI in the Southern Africa Savanna
by Miguel A. Campo-Bescós, Rafael Muñoz-Carpena, Jane Southworth, Likai Zhu, Peter R. Waylen and Erin Bunting
Remote Sens. 2013, 5(12), 6513-6538; https://doi.org/10.3390/rs5126513 - 03 Dec 2013
Cited by 49 | Viewed by 10514
Abstract
Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds [...] Read more.
Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time-series dimension reduction technique, was used to identify the most important physical drivers of regional vegetation change. We first evaluated the Advanced Very High Resolution Radiometer (AVHRR)- vs. the Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) datasets across their overlapping period (2001–2010). NDVI follows a general pattern of cyclic seasonal variation, with distinct spatio-temporal patterns across physio-geographic regions. Both NDVI products produced similar DFA models, although MODIS was simulated better. Soil moisture and precipitation controlled NDVI for mean annual precipitation (MAP) < 750 mm, and above this, evaporation and mean temperature dominated. A second DFA with the full AVHRR (1982–2010) data found that for MAP < 750 mm, soil moisture and actual evapotranspiration control NDVI dynamics, followed by mean and maximum temperatures. Above 950 mm, actual evapotranspiration and precipitation dominate. The quantification of the combined spatio-temporal environmental drivers of NDVI expands our ability to understand landscape level changes in vegetation evaluated through remote sensing and improves the basis for the management of vulnerable regions, like the southern Africa savannas. Full article
(This article belongs to the Special Issue Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011))
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3155 KiB  
Communication
Videographic Analysis of Eriophorum Vaginatum Spatial Coverage in an Ombotrophic Bog
by Margaret Kalacska, J. Pablo Arroyo-Mora, Julie De Gea, Eva Snirer, Carrie Herzog and Tim R. Moore
Remote Sens. 2013, 5(12), 6501-6512; https://doi.org/10.3390/rs5126501 - 02 Dec 2013
Cited by 25 | Viewed by 8493
Abstract
The use of Remotely Piloted Aircraft Systems (RPAS) as well as newer automated unmanned aerial vehicles is becoming a standard method in remote sensing studies requiring high spatial resolution (<1 m) and very precise temporal data to capture phenological events. In this study [...] Read more.
The use of Remotely Piloted Aircraft Systems (RPAS) as well as newer automated unmanned aerial vehicles is becoming a standard method in remote sensing studies requiring high spatial resolution (<1 m) and very precise temporal data to capture phenological events. In this study we use a low cost rotorcraft to map Eriophorum vaginatum at Mer Bleue, an ombrotrophic bog located east of Ottawa, ON, Canada. We focus on E. vaginatum because this sedge plays an important role in methane (CH4) gas exchange in peatlands. Using the remote controlled rotorcraft we were able to record, process, and mosaic 11.1 hectares of 4.5 cm spatial resolution imagery extracted from individual frames of video recordings (post georegistration RMSE 4.90 ± 4.95 cm). Our results, based on a supervised classification (96% accuracy) of the red, green, blue image planes, indicate a total tussock cover of 2,417 m2. Because the basal area of the plant is more relevant for calculating its contribution to the CH4 flux, the tussock area was related to the basal area from field data (R2 = 0.88, p < 0.0001). Our final results indicate a total basal area of 1,786 ± 62.8 m2. Based on temporal measurements of CH4 flux from the peatland as a whole that vary over the growing season, we estimate the E. vaginatum contribution to range from 3.0% to 17.3% of that total. Overall, our low cost approach was an effective non-destructive way to derive E. vaginatum coverage and estimate CH4 exchange over the growing season. Full article
(This article belongs to the Special Issue Remote Sensing of Peatlands I)
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11731 KiB  
Article
Seasonal Composite Landsat TM/ETM+ Images Using the Medoid (a Multi-Dimensional Median)
by Neil Flood
Remote Sens. 2013, 5(12), 6481-6500; https://doi.org/10.3390/rs5126481 - 02 Dec 2013
Cited by 184 | Viewed by 17302
Abstract
Multi-temporal satellite imagery can be composited over a season (or other time period) to produce imagery which is representative of that period, using techniques which will reduce contamination by cloud and other problems. For the purposes of vegetation monitoring, a commonly used technique [...] Read more.
Multi-temporal satellite imagery can be composited over a season (or other time period) to produce imagery which is representative of that period, using techniques which will reduce contamination by cloud and other problems. For the purposes of vegetation monitoring, a commonly used technique is the Maximum NDVI Composite, used in conjunction with variety of other constraints. The current paper proposes an alternative based on the medoid (in reflectance space) over the time period (the medoid is a multi-dimensional analogue of the median), which is robust against extreme values, and appears to be better at producing imagery which is representative of the time period. For each pixel, the medoid is always selected from the available dates, so the result is always a single observation for that pixel, thus preserving relationships between bands. The method is applied to Landsat TM/ETM+ imagery to create seasonal reflectance images (four per year), with the aim being a regular time series of reflectance values which captures the variability at seasonal time scales. Analysis of the seasonal reflectance values suggests that resulting temporal image composites are more representative of the time series than the maximum NDVI seasonal composite. Full article
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1992 KiB  
Article
Canopy Fuel Load Mapping of Mediterranean Pine Sites Based on Individual Tree-Crown Delineation
by Giorgos Mallinis, Ιoannis Mitsopoulos, Panagiota Stournara, Petros Patias and Alexandros Dimitrakopoulos
Remote Sens. 2013, 5(12), 6461-6480; https://doi.org/10.3390/rs5126461 - 02 Dec 2013
Cited by 13 | Viewed by 8344
Abstract
This study presents an individual tree-crown-based approach for canopy fuel load estimation and mapping in two Mediterranean pine stands. Based on destructive sampling, an allometric equation was developed for the estimation of crown fuel weight considering only pine crown width, a tree characteristic [...] Read more.
This study presents an individual tree-crown-based approach for canopy fuel load estimation and mapping in two Mediterranean pine stands. Based on destructive sampling, an allometric equation was developed for the estimation of crown fuel weight considering only pine crown width, a tree characteristic that can be estimated from passive imagery. Two high resolution images were used originally for discriminating Aleppo and Calabrian pines crown regions through a geographic object based image analysis approach. Subsequently, the crown region images were segmented using a watershed segmentation algorithm and crown width was extracted. The overall accuracy of the tree crown isolation expressed through a perfect match between the reference and the delineated crowns was 34.00% for the Kassandra site and 48.11% for the Thessaloniki site, while the coefficient of determination between the ground measured and the satellite extracted crown width was 0.5. Canopy fuel load values estimated in the current study presented mean values from 1.29 ± 0.6 to 1.65 ± 0.7 kg/m2 similar to other conifers worldwide. Despite the modest accuracies attained in this first study of individual tree crown fuel load mapping, the combination of the allometric equations with satellite-based extracted crown width information, can contribute to the spatially explicit mapping of canopy fuel load in Mediterranean areas. These maps can be used among others in fire behavior prediction, in fuel reduction treatments prioritization and during active fire suppression. Full article
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1770 KiB  
Article
Spatiotemporal Patterns of Urban Encroachment on Cropland and Its Impacts on Potential Agricultural Productivity in China
by Hongyan Cai, Xiaohuan Yang and Xinliang Xu
Remote Sens. 2013, 5(12), 6443-6460; https://doi.org/10.3390/rs5126443 - 29 Nov 2013
Cited by 17 | Viewed by 6733
Abstract
Rapid urbanization and population growth in China have raised great concerns regarding food security caused by the loss of limited cultivated land. In this study, we used remotely sensed data and an agricultural productivity estimation model to characterize the spatiotemporal patterns of the [...] Read more.
Rapid urbanization and population growth in China have raised great concerns regarding food security caused by the loss of limited cultivated land. In this study, we used remotely sensed data and an agricultural productivity estimation model to characterize the spatiotemporal patterns of the conversion of cropland into urban land and quantify its impacts on agricultural productivity potential during China’s rapid urbanization period, from 1990 to 2010. The results show that urban development has transformed approximately 4.18 Mha, or 2.26%, of the total cropland in China. From 1990 to 2000, approximately 1.50 Mha of cropland was developed, while roughly 1.8 times this amount (2.68 Mha) was converted over the period of 2000 to 2010. Most of the conversion is located in the central and eastern coastal provinces and is mainly concentrated on the periphery of the major urban areas. The transformation has, consequently, caused a 71.45 Tg, or 2.65%, loss of potential light-temperature agricultural productivity (PLTAP); losses were 24.33 Tg in the first decade of the study and 47.11 Tg in the second. At the provincial scale, the largest percentages of PLTAP loss are mainly concentrated in the developed provinces on the eastern coast, such as Shanghai, Beijing, Zhejiang, Tianjin, and Jiangsu. Considering that these areas can accommodate more people and produce higher economic output on unit area of built-up land and, yet, scarce land that can be reclaimed, this study suggests that the dynamic balance of total farmland policy in China should be varied provincially according to the major function of the province. The policy adjustment will help maximize the utilization efficiency of land. Full article
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1639 KiB  
Article
Openness as Visualization Technique for Interpretative Mapping of Airborne Lidar Derived Digital Terrain Models
by Michael Doneus
Remote Sens. 2013, 5(12), 6427-6442; https://doi.org/10.3390/rs5126427 - 28 Nov 2013
Cited by 153 | Viewed by 15258
Abstract
Openness is proposed as a visualization technique for the archaeological interpretation of digital terrain models derived from airborne laser scanning. In contrast to various shading techniques, openness is not subject to directional bias and relief features highlighted by openness do not contain any [...] Read more.
Openness is proposed as a visualization technique for the archaeological interpretation of digital terrain models derived from airborne laser scanning. In contrast to various shading techniques, openness is not subject to directional bias and relief features highlighted by openness do not contain any horizontal displacement. Additionally, it offers a clear distinction between relief features and the surrounding topography, while it highlights both the highest and lowest parts of features. This makes openness an ideal tool for mapping and outlining of archaeological features. A comparison with sky-view factor and local relief model visualizations helps to evaluate advantages and limits of the technique. Full article
(This article belongs to the Special Issue New Perspectives of Remote Sensing for Archaeology)
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4565 KiB  
Article
Multi-Decadal Mangrove Forest Change Detection and Prediction in Honduras, Central America, with Landsat Imagery and a Markov Chain Model
by Chi-Farn Chen, Nguyen-Thanh Son, Ni-Bin Chang, Cheng-Ru Chen, Li-Yu Chang, Miguel Valdez, Gustavo Centeno, Carlos Alberto Thompson and Jorge Luis Aceituno
Remote Sens. 2013, 5(12), 6408-6426; https://doi.org/10.3390/rs5126408 - 27 Nov 2013
Cited by 103 | Viewed by 12197
Abstract
Mangrove forests play an important role in providing ecological and socioeconomic services for human society. Coastal development, which converts mangrove forests to other land uses, has often ignored the services that mangrove may provide, leading to irreversible environmental degradation. Monitoring the spatiotemporal distribution [...] Read more.
Mangrove forests play an important role in providing ecological and socioeconomic services for human society. Coastal development, which converts mangrove forests to other land uses, has often ignored the services that mangrove may provide, leading to irreversible environmental degradation. Monitoring the spatiotemporal distribution of mangrove forests is thus critical for natural resources management of mangrove ecosystems. This study investigates spatiotemporal changes in Honduran mangrove forests using Landsat imagery during the periods 1985–1996, 1996–2002, and 2002–2013. The future trend of mangrove forest changes was projected by a Markov chain model to support decision-making for coastal management. The remote sensing data were processed through three main steps: (1) data pre-processing to correct geometric errors between the Landsat imageries and to perform reflectance normalization; (2) image classification with the unsupervised Otsu’s method and change detection; and (3) mangrove change projection using a Markov chain model. Validation of the unsupervised Otsu’s method was made by comparing the classification results with the ground reference data in 2002, which yielded satisfactory agreement with an overall accuracy of 91.1% and Kappa coefficient of 0.82. When examining mangrove changes from 1985 to 2013, approximately 11.9% of the mangrove forests were transformed to other land uses, especially shrimp farming, while little effort (3.9%) was applied for mangrove rehabilitation during this 28-year period. Changes in the extent of mangrove forests were further projected until 2020, indicating that the area of mangrove forests could be continuously reduced by 1,200 ha from 2013 (approximately 36,700 ha) to 2020 (approximately 35,500 ha). Institutional interventions should be taken for sustainable management of mangrove ecosystems in this coastal region. Full article
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4230 KiB  
Article
Seamless Mapping of River Channels at High Resolution Using Mobile LiDAR and UAV-Photography
by Claude Flener, Matti Vaaja, Anttoni Jaakkola, Anssi Krooks, Harri Kaartinen, Antero Kukko, Elina Kasvi, Hannu Hyyppä, Juha Hyyppä and Petteri Alho
Remote Sens. 2013, 5(12), 6382-6407; https://doi.org/10.3390/rs5126382 - 27 Nov 2013
Cited by 176 | Viewed by 21889
Abstract
Accurate terrain models are a crucial component of studies of river channel evolution. In this paper we describe a new methodology for creating high-resolution seamless digital terrain models (DTM) of river channels and their floodplains. We combine mobile laser scanning and low-altitude unmanned [...] Read more.
Accurate terrain models are a crucial component of studies of river channel evolution. In this paper we describe a new methodology for creating high-resolution seamless digital terrain models (DTM) of river channels and their floodplains. We combine mobile laser scanning and low-altitude unmanned aerial vehicle (UAV) photography-based methods for creating both a digital bathymetric model of the inundated river channel and a DTM of a point bar of a meandering sub-arctic river. We evaluate mobile laser scanning and UAV-based photogrammetry point clouds against terrestrial laser scanning and combine these data with an optical bathymetric model to create a seamless DTM of two different measurement periods. Using this multi-temporal seamless data, we calculate a DTM of difference that allows a change detection of the meander bend over a one-year period. Full article
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Graphical abstract

6716 KiB  
Article
Airborne Thermal Data Identifies Groundwater Discharge at the North-Western Coast of the Dead Sea
by Ulf Mallast, Friedhelm Schwonke, Richard Gloaguen, Stefan Geyer, Martin Sauter and Christian Siebert
Remote Sens. 2013, 5(12), 6361-6381; https://doi.org/10.3390/rs5126361 - 26 Nov 2013
Cited by 14 | Viewed by 9381
Abstract
A qualitative and quantitative monitoring of groundwater discharge was conducted based on an airborne thermal campaign undertaken along the north-western coast of the Dead Sea in January 2011 to contribute to the relatively scarce information on groundwater discharge to date in the region. [...] Read more.
A qualitative and quantitative monitoring of groundwater discharge was conducted based on an airborne thermal campaign undertaken along the north-western coast of the Dead Sea in January 2011 to contribute to the relatively scarce information on groundwater discharge to date in the region. The application of airborne thermal data exploits thermal contrasts that exist between discharging groundwater and background sea surface temperatures of the Dead Sea. Using these contrasts, 72 discharge sites were identified from which only 42 were known from previous in situ measurements undertaken at terrestrial springs by the Israel Hydrological Service. Six of these sites represent submarine springs and at a further 24 locations groundwater appears to seep through the sediment. Although the abundance of groundwater seepage sites suggests a significant, but so far unknown groundwater source, the main contribution appears to originate from terrestrial springs. In an attempt to provide a quantitative approach for terrestrial springs, a linear bootstrap regression model between in situ spring discharge and respective thermal discharge plumes (r2 = 0.87 p < 0.001) is developed and presented here. While the results appear promising and could potentially be applied to derive discharge values at unmonitored sites, several influence factors need to be clarified before a robust and reliable model to efficiently derive a complete quantitative picture of groundwater discharge can be proposed. Full article
(This article belongs to the Special Issue Hydrological Remote Sensing)
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1355 KiB  
Article
An Improved Image Fusion Approach Based on Enhanced Spatial and Temporal the Adaptive Reflectance Fusion Model
by Dongjie Fu, Baozhang Chen, Juan Wang, Xiaolin Zhu and Thomas Hilker
Remote Sens. 2013, 5(12), 6346-6360; https://doi.org/10.3390/rs5126346 - 26 Nov 2013
Cited by 83 | Viewed by 9222
Abstract
High spatiotemporal resolution satellite imagery is useful for natural resource management and monitoring for land-use and land-cover change and ecosystem dynamics. However, acquisitions from a single satellite can be limited, due to trade-offs in either spatial or temporal resolution. The spatial and temporal [...] Read more.
High spatiotemporal resolution satellite imagery is useful for natural resource management and monitoring for land-use and land-cover change and ecosystem dynamics. However, acquisitions from a single satellite can be limited, due to trade-offs in either spatial or temporal resolution. The spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM (ESTARFM) were developed to produce new images with high spatial and high temporal resolution using images from multiple sources. Nonetheless, there were some shortcomings in these models, especially for the procedure of searching spectrally similar neighbor pixels in the models. In order to improve these models’ capacity and accuracy, we developed a modified version of ESTARFM (mESTARFM) and tested the performance of two approaches (ESTARFM and mESTARFM) in three study areas located in Canada and China at different time intervals. The results show that mESTARFM improved the accuracy of the simulated reflectance at fine resolution to some extent. Full article
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