Remote Sensing

9191 KiB

Open AccessArticle

Detection and Monitoring of Surface Motions in Active Open Pit Iron Mine in the Amazon Region, Using Persistent Scatterer Interferometry with TerraSAR-X Satellite Data

by Marcos E. Hartwig, Waldir R. Paradella and José C. Mura

Remote Sens. 2013, 5(9), 4719-4734; https://doi.org/10.3390/rs5094719 - 18 Sep 2013

Cited by 34 | Viewed by 9133

Abstract

Persistent Scatterer interferometry (PSI) represents a powerful tool for the detection and monitoring of tiny surface deformations in vast areas, allowing a better understanding of its triggering mechanisms, planning of mitigation measures, as well as to find better solutions for social and environmental [...] Read more.

Persistent Scatterer interferometry (PSI) represents a powerful tool for the detection and monitoring of tiny surface deformations in vast areas, allowing a better understanding of its triggering mechanisms, planning of mitigation measures, as well as to find better solutions for social and environmental issues. However, there is no record hitherto of its use in active open pit mine in tropical rainforest environment. In this paper we evaluate the use of the PSI technique for the detection and monitoring of mine slope deformations in the N4W iron mine and its surroundings, Pará State, Northern Brazil. The PSI processing was performed with 18 ascending SAR scenes of the TerraSAR-X satellite acquired in the dry season of 2012. The results showed a significant number of widely distributed persistent scatterers. It was observed that most of the study area was stable during the time span. Nevertheless, high deformation rates (312 mm/year) were mapped over the mine waste piles, but do not offer any hazard, since they are expected displacements of meters in magnitude for these manmade land structures. Additionally, it was mapped tiny deformation rates in both the east and west flanks of pits 1 and 2. The main underlying reasons can be assigned to the accommodation phenomena of very poor rock masses, to the local geometric variations of the slope cuts, to the geological contact between ironstones and the country rocks, to the exploitation activities, as well as to the major geological structures. This study showed the applicability of the PSI technique using TerraSAR-X scenes in active open pit mines in tropical moist environment. However, the PSI technique is not capable in providing real-time warnings, and faces limitations due to SAR viewing geometry. In this sense, we strongly recommend the use of radar scenes acquired in both ascending and descending orbits, which would also provide a more complete understanding of the deformation patterns. Full article

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1138 KiB

Open AccessArticle

A Satellite-Based Surface Radiation Climatology Derived by Combining Climate Data Records and Near-Real-Time Data

by Stefan Krähenmann, Andre Obregon, Richard Müller, Jörg Trentmann and Bodo Ahrens

Remote Sens. 2013, 5(9), 4693-4718; https://doi.org/10.3390/rs5094693 - 18 Sep 2013

Cited by 13 | Viewed by 7436

Abstract

This study presents a method for adjusting long-term climate data records (CDRs) for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS). Recently, a 23-year long (1983–2005) continuous SIS CDR has been generated based on the visible [...] Read more.

This study presents a method for adjusting long-term climate data records (CDRs) for the integrated use with near-real-time data using the example of surface incoming solar irradiance (SIS). Recently, a 23-year long (1983–2005) continuous SIS CDR has been generated based on the visible channel (0.45–1 μm) of the MVIRI radiometers onboard the geostationary Meteosat First Generation Platform. The CDR is available from the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). Here, it is assessed whether a homogeneous extension of the SIS CDR to the present is possible with operationally generated surface radiation data provided by CM SAF using the SEVIRI and GERB instruments onboard the Meteosat Second Generation satellites. Three extended CM SAF SIS CDR versions consisting of MVIRI-derived SIS (1983–2005) and three different SIS products derived from the SEVIRI and GERB instruments onboard the MSG satellites (2006 onwards) were tested. A procedure to detect shift inhomogeneities in the extended data record (1983–present) was applied that combines the Standard Normal Homogeneity Test (SNHT) and a penalized maximal T-test with visual inspection. Shift detection was done by comparing the SIS time series with the ground stations mean, in accordance with statistical significance. Several stations of the Baseline Surface Radiation Network (BSRN) and about 50 stations of the Global Energy Balance Archive (GEBA) over Europe were used as the ground-based reference. The analysis indicates several breaks in the data record between 1987 and 1994 probably due to artefacts in the raw data and instrument failures. After 2005 the MVIRI radiometer was replaced by the narrow-band SEVIRI and the broadband GERB radiometers and a new retrieval algorithm was applied. This induces significant challenges for the homogenisation across the satellite generations. Homogenisation is performed by applying a mean-shift correction depending on the shift size of any segment between two break points to the last segment (2006–present). Corrections are applied to the most significant breaks that can be related to satellite changes. This study focuses on the European region, but the methods can be generalized to other regions. To account for seasonal dependence of the mean-shifts the correction was performed independently for each calendar month. In comparison to the ground-based reference the homogenised data record shows an improvement over the original data record in terms of anomaly correlation and bias. In general the method can also be applied for the adjustment of satellite datasets addressing other variables to bridge the gap between CDRs and near-real-time data. Full article

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6243 KiB

Open AccessReview

Synthesis of Transportation Applications of Mobile LIDAR

by Keith Williams, Michael J. Olsen, Gene V. Roe and Craig Glennie

Remote Sens. 2013, 5(9), 4652-4692; https://doi.org/10.3390/rs5094652 - 18 Sep 2013

Cited by 156 | Viewed by 18832

Abstract

A thorough review of available literature was conducted to inform of advancements in mobile LIDAR technology, techniques, and current and emerging applications in transportation. The literature review touches briefly on the basics of LIDAR technology followed by a more in depth description of [...] Read more.

A thorough review of available literature was conducted to inform of advancements in mobile LIDAR technology, techniques, and current and emerging applications in transportation. The literature review touches briefly on the basics of LIDAR technology followed by a more in depth description of current mobile LIDAR trends, including system components and software. An overview of existing quality control procedures used to verify the accuracy of the collected data is presented. A collection of case studies provides a clear description of the advantages of mobile LIDAR, including an increase in safety and efficiency. The final sections of the review identify current challenges the industry is facing, the guidelines that currently exist, and what else is needed to streamline the adoption of mobile LIDAR by transportation agencies. Unfortunately, many of these guidelines do not cover the specific challenges and concerns of mobile LIDAR use as many have been developed for airborne LIDAR acquisition and processing. From this review, there is a lot of discussion on “what” is being done in practice, but not a lot on “how” and “how well” it is being done. A willingness to share information going forward will be important for the successful use of mobile LIDAR. Full article

(This article belongs to the Special Issue Advances in Mobile Laser Scanning and Mobile Mapping)

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2048 KiB

Open AccessArticle

Automatic Estimation of Excavation Volume from Laser Mobile Mapping Data for Mountain Road Widening

by Jinhu Wang, Higinio González-Jorge, Roderik Lindenbergh, Pedro Arias-Sánchez and Massimo Menenti

Remote Sens. 2013, 5(9), 4629-4651; https://doi.org/10.3390/rs5094629 - 17 Sep 2013

Cited by 19 | Viewed by 8789

Abstract

Roads play an indispensable role as part of the infrastructure of society. In recent years, society has witnessed the rapid development of laser mobile mapping systems (LMMS) which, at high measurement rates, acquire dense and accurate point cloud data. This paper presents a [...] Read more.

Roads play an indispensable role as part of the infrastructure of society. In recent years, society has witnessed the rapid development of laser mobile mapping systems (LMMS) which, at high measurement rates, acquire dense and accurate point cloud data. This paper presents a way to automatically estimate the required excavation volume when widening a road from point cloud data acquired by an LMMS. Firstly, the input point cloud is down-sampled to a uniform grid and outliers are removed. For each of the resulting grid points, both on and off the road, the local surface normal and 2D slope are estimated. Normals and slopes are consecutively used to separate road from off-road points which enables the estimation of the road centerline and road boundaries. In the final step, the left and right side of the road points are sliced in 1-m slices up to a distance of 4 m, perpendicular to the roadside. Determining and summing each sliced volume enables the estimation of the required excavation for a widening of the road on the left or on the right side. The procedure, including a quality analysis, is demonstrated on a stretch of a mountain road that is approximately 132 m long as sampled by a Lynx LMMS. The results in this particular case show that the required excavation volume on the left side is 8% more than that on the right side. In addition, the error in the results is assessed in two ways. First, by adding up estimated local errors, and second, by comparing results from two different datasets sampling the same piece of road both acquired by the Lynx LMMS. Results of both approaches indicate that the error in the estimated volume is below 4%. The proposed method is relatively easy to implement and runs smoothly on a desktop PC. The whole workflow of the LMMS data acquisition and subsequent volume computation can be completed in one or two days and provides road engineers with much more detail than traditional single-point surveying methods such as Total Station or GPS profiling. A drawback is that an LMMS system can only sample what is within the view of the system from the road. Full article

(This article belongs to the Special Issue Advances in Mobile Laser Scanning and Mobile Mapping)

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Open AccessArticle

Stereoscopic Height and Wind Retrievals for Aerosol Plumes with the MISR INteractive eXplorer (MINX)

by David L. Nelson, Michael J. Garay, Ralph A. Kahn and Ben A. Dunst

Remote Sens. 2013, 5(9), 4593-4628; https://doi.org/10.3390/rs5094593 - 17 Sep 2013

Cited by 99 | Viewed by 11107

Abstract

The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the Terra satellite acquires imagery at 275-m resolution at nine angles ranging from 0° (nadir) to 70° off-nadir. This multi-angle capability facilitates the stereoscopic retrieval of heights and motion vectors for clouds and aerosol plumes. MISR’s [...] Read more.

The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the Terra satellite acquires imagery at 275-m resolution at nine angles ranging from 0° (nadir) to 70° off-nadir. This multi-angle capability facilitates the stereoscopic retrieval of heights and motion vectors for clouds and aerosol plumes. MISR’s operational stereo product uses this capability to retrieve cloud heights and winds for every satellite orbit, yielding global coverage every nine days. The MISR INteractive eXplorer (MINX) visualization and analysis tool complements the operational stereo product by providing users the ability to retrieve heights and winds locally for detailed studies of smoke, dust and volcanic ash plumes, as well as clouds, at higher spatial resolution and with greater precision than is possible with the operational product or with other space-based, passive, remote sensing instruments. This ability to investigate plume geometry and dynamics is becoming increasingly important as climate and air quality studies require greater knowledge about the injection of aerosols and the location of clouds within the atmosphere. MINX incorporates features that allow users to customize their stereo retrievals for optimum results under varying aerosol and underlying surface conditions. This paper discusses the stereo retrieval algorithms and retrieval options in MINX, and provides appropriate examples to explain how the program can be used to achieve the best results. Full article

(This article belongs to the Special Issue Optical Remote Sensing of the Atmosphere)

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1320 KiB

Open AccessArticle

3D Modeling of Coarse Fluvial Sediments Based on Mobile Laser Scanning Data

by Yunsheng Wang, Xinlian Liang, Claude Flener, Antero Kukko, Harri Kaartinen, Matti Kurkela, Matti Vaaja, Hannu Hyyppä and Petteri Alho

Remote Sens. 2013, 5(9), 4571-4592; https://doi.org/10.3390/rs5094571 - 16 Sep 2013

Cited by 32 | Viewed by 9266

Abstract

High quality sedimentary measurements are required for studying fluvial geomorphology and hydrological processes e.g., flood and river dynamics. Mobile laser scanning (MLS) currently provides the opportunity to achieve high precision measurements of coarse fluvial sediments in a large survey area. Our study aims [...] Read more.

High quality sedimentary measurements are required for studying fluvial geomorphology and hydrological processes e.g., flood and river dynamics. Mobile laser scanning (MLS) currently provides the opportunity to achieve high precision measurements of coarse fluvial sediments in a large survey area. Our study aims to investigate the capability of single-track MLS data for individual particle-based sediment modeling. Individual particles are firstly detected and delineated from a digital surface model (DSM) that is generated from the MLS data. 3D MLS points of each detected individual particle are then extracted from the point cloud. The grain size and the sphericity as well as the orientation of each individual particle are estimated based on the extracted MLS points. According to the evaluations conduced in the paper, it is possible to detect and to model sediment particles above 63 mm from a single-track MLS point cloud with a high reliability. The paper further discusses the strength and the challenges of individual particle-based approach for sedimentary measurement. Full article

(This article belongs to the Special Issue Advances in Mobile Laser Scanning and Mobile Mapping)

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Open AccessArticle

Detecting Zimbabwe’s Decadal Economic Decline Using Nighttime Light Imagery

by Xi Li, Linlin Ge and Xiaoling Chen

Remote Sens. 2013, 5(9), 4551-4570; https://doi.org/10.3390/rs5094551 - 16 Sep 2013

Cited by 64 | Viewed by 12848

Abstract

Zimbabwe’s economy declined between 2000 and 2009. This study detects the economic decline in different regions of Zimbabwe using nighttime light imagery from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). We found a good correlation (coefficient = 0.7361) between Zimbabwe’s total [...] Read more.

Zimbabwe’s economy declined between 2000 and 2009. This study detects the economic decline in different regions of Zimbabwe using nighttime light imagery from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS). We found a good correlation (coefficient = 0.7361) between Zimbabwe’s total nighttime light (TNL) and Gross Domestic Product (GDP) for the period 1992 to 2009. Therefore, TNL was used as an indicator of regional economic conditions in Zimbabwe. Nighttime light imagery from 2000 and 2008 was compared at both national and regional scales for four types of regions. At the national scale, we found that nighttime light in more than half of the lit area decreased between 2000 and 2008. Moreover, within the four region types (inland mining towns, inland agricultural towns, border towns and cities) we determined that the mining and agricultural sectors experienced the most severe economic decline. Some of these findings were validated by economic survey data, proving that the nighttime light data is a potential data source for detecting the economic decline in Zimbabwe. Full article

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2855 KiB

Open AccessArticle

A Study of Soil Line Simulation from Landsat Images in Mixed Grassland

by Dandan Xu and Xulin Guo

Remote Sens. 2013, 5(9), 4533-4550; https://doi.org/10.3390/rs5094533 - 12 Sep 2013

Cited by 29 | Viewed by 10723

Abstract

The mixed grassland in Canada is characterized by low to medium green vegetation cover, with a large amount of canopy background, such as non-photosynthetic vegetation residuals (litter), bare soil, and ground level biological crust. It is a challenge to extract the canopy information [...] Read more.

The mixed grassland in Canada is characterized by low to medium green vegetation cover, with a large amount of canopy background, such as non-photosynthetic vegetation residuals (litter), bare soil, and ground level biological crust. It is a challenge to extract the canopy information from satellite images because of the influence of canopy background. Therefore, this study aims to extract a soil line, a representation of bare soil with litter and soil crust in the surface, from Landsat images to reduce the background effect. Field work was conducted in the West Block of Grasslands National Park (GNP) in Canada, which represents the northern mixed grassland from late June to early July 2005. Six TM images with either no or only a small amount of cloud content were collected in 2005. In this study, soil lines were extracted directly from images by quantile regression and the (R, NIR_min) method. The results show that, (1) both cloud and cloud shadow have obvious influence on simulating soil line automatically from images; (2) green up and late senescence seasons are relatively better for soil line simulation; (3) the (R, NIR_min) method is better for soil line simulation than quantile regression to extract green biomass or green cover information. Full article

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2176 KiB

Open AccessArticle

Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data

by Maurizio Santoro, Oliver Cartus, Johan E.S. Fransson, Anatoly Shvidenko, Ian McCallum, Ronald J. Hall, André Beaudoin, Christian Beer and Christiane Schmullius

Remote Sens. 2013, 5(9), 4503-4532; https://doi.org/10.3390/rs5094503 - 12 Sep 2013

Cited by 37 | Viewed by 10317

Abstract

A study was undertaken to assess Envisat Advanced Synthetic Aperture Radar (ASAR) ScanSAR data for quantifying forest growing stock volume (GSV) across three boreal regions with varying forest types, composition, and structure (Sweden, Central Siberia, and Québec). Estimates of GSV were obtained using [...] Read more.

A study was undertaken to assess Envisat Advanced Synthetic Aperture Radar (ASAR) ScanSAR data for quantifying forest growing stock volume (GSV) across three boreal regions with varying forest types, composition, and structure (Sweden, Central Siberia, and Québec). Estimates of GSV were obtained using hyper-temporal observations of the radar backscatter acquired by Envisat ASAR with the BIOMASAR algorithm. In total, 5.3×10⁶ km²were mapped with a 0.01° pixel size to obtain estimates representative for the year of 2005. Comparing the SAR-based estimates to spatially explicit datasets of GSV, generated from forest field inventory and/or Earth Observation data, revealed similar spatial distributions of GSV. Nonetheless, the weak sensitivity of C-band backscatter to forest structural parameters introduced significant uncertainty to the estimated GSV at full resolution. Further discrepancies were observed in the case of different scales of the ASAR and the reference GSV and in areas of fragmented landscapes. Aggregation to 0.1° and 0.5° was then undertaken to generate coarse scale estimates of GSV. The agreement between ASAR and the reference GSV datasets improved; the relative difference at 0.5° was consistently within a magnitude of 20–30%. The results indicate an improvement of the characterization of forest GSV in the boreal zone with respect to currently available information. Full article

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1619 KiB

Open AccessArticle

Geo-Correction of High-Resolution Imagery Using Fast Template Matching on a GPU in Emergency Mapping Contexts

by Guido Lemoine and Martina Giovalli

Remote Sens. 2013, 5(9), 4488-4502; https://doi.org/10.3390/rs5094488 - 12 Sep 2013

Cited by 10 | Viewed by 9228

Abstract

The increasing availability of satellite imagery acquired by existing and new sensors allows a wide variety of new applications that depend on the use of diverse spectral and spatial resolution data sets. One of the pre-conditions for the use of hybrid image data [...] Read more.

The increasing availability of satellite imagery acquired by existing and new sensors allows a wide variety of new applications that depend on the use of diverse spectral and spatial resolution data sets. One of the pre-conditions for the use of hybrid image data sets is a consistent geo-correction capacity. We demonstrate how a novel fast template matching approach implemented on a graphics processing unit (GPU) allows us to accurately and rapidly geo-correct imagery in an automated way. The key difference with existing geo-correction approaches, which do not use a GPU, is the possibility to match large source image segments (8,192 by 8,192 pixels) with relatively large templates (512 by 512 pixels) significantly faster. Our approach is sufficiently robust to allow for the use of various reference data sources. The need for accelerated processing is relevant in our application context, which relates to mapping activities in the European Copernicus emergency management service. Our new method is demonstrated over an area northwest of Valencia (Spain) for a large forest fire event in July 2012. We use the Disaster Monitoring Constellation’s (DMC) DEIMOS-1 and RapidEye imagery for the delineation of burnt scar extent. Automated geo-correction of each full resolution image set takes approximately one minute. The reference templates are taken from the TerraColor data set and the Spanish national ortho-imagery database, through the use of dedicated web map services. Geo-correction results are compared to the vector sets derived in the Copernicus emergency service activation request. Full article

(This article belongs to the Special Issue High Performance Computing in Remote Sensing)

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3658 KiB

Open AccessArticle

Extraction of Coastline in Aquaculture Coast from Multispectral Remote Sensing Images: Object-Based Region Growing Integrating Edge Detection

by Tao Zhang, Xiaomei Yang, Shanshan Hu and Fenzhen Su

Remote Sens. 2013, 5(9), 4470-4487; https://doi.org/10.3390/rs5094470 - 12 Sep 2013

Cited by 109 | Viewed by 12426

Abstract

Aquaculture coasts have become widely distributed in coastal zones as human activities are intensified. Due to the complexity in this type of coast, it is difficult to extract the coastline with traditional automated mapping approaches. In this paper, we present an automated method— [...] Read more.

Aquaculture coasts have become widely distributed in coastal zones as human activities are intensified. Due to the complexity in this type of coast, it is difficult to extract the coastline with traditional automated mapping approaches. In this paper, we present an automated method—object-based region growing integrating edge detection (OBRGIE) for the extraction of this type of coastline. In this method, a new object feature named OMI (object merging index) is proposed to separate land and sea. The OBRGIE method was applied to Landsat Thematic Mapper (TM) (pixel size 30m) and Satellite Pour l’Observation de la Terre (SPOT-5) (pixel size 10 m) images of two coastal segments with lengths of 272.7 km and 35.5 km respectively, and the accuracy of the extracted coastlines was assessed in comparison with the manually delineated coastlines. The mean and RMSE (root mean square error) are 16.0 m and 16.4 m respectively for the TM images, and 8.0 m and 8.6 m, respectively, for the SPOT-5 images, indicating that the proposed method derives coastlines with pixel accuracy. The OBRGIE method is also found to be robust to the segmentation scale parameter, and the OMI feature is much more effective than the spectral attribute in separating land and sea in aquaculture coasts. This method may provide an inexpensive means of fast coastline mapping from remotely sensed imagery with relatively fine-to-moderate spatial resolution in coastal sectors with intense human interference. Full article

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1477 KiB

Open AccessArticle

Evaluating the Effects of Shadow Detection on QuickBird Image Classification and Spectroradiometric Restoration

by Jindong Wu and Marvin E. Bauer

Remote Sens. 2013, 5(9), 4450-4469; https://doi.org/10.3390/rs5094450 - 11 Sep 2013

Cited by 20 | Viewed by 7443

Abstract

Shadows in high resolution imagery create significant problems for urban land cover classification and environmental application. We first investigated whether shadows were intrinsically different and hypothetically possible to separate from each other with ground spectral measurements. Both pixel-based and object-oriented methods were used [...] Read more.

Shadows in high resolution imagery create significant problems for urban land cover classification and environmental application. We first investigated whether shadows were intrinsically different and hypothetically possible to separate from each other with ground spectral measurements. Both pixel-based and object-oriented methods were used to evaluate the effects of shadow detection on QuickBird image classification and spectroradiometric restoration. In each method, shadows were detected and separated either with or without histogram thresholding, and subsequently corrected with a k-nearest neighbor algorithm and a linear correlation correction. The results showed that shadows had distinct spectroradiometric characteristics, thus, could be detected with an optimal brightness threshold and further differentiated with a scene-based near infrared ratio. The pixel-based methods generally recognized more shadow areas and with statistically higher accuracy than the object-oriented methods. The effects of the prior shadow thresholding were not statistically significant. The accuracy of the final land cover classification, after accounting for the shadow detection and separation, was significantly higher for the pixel-based methods than for the object-oriented methods, although both achieved similar accuracy for the non-shadow classes. Both radiometric restoration algorithms significantly reduced shadow areas in the original satellite images. Full article

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1448 KiB

Open AccessArticle

VIIRS Nightfire: Satellite Pyrometry at Night

by Christopher D. Elvidge, Mikhail Zhizhin, Feng-Chi Hsu and Kimberly E. Baugh

Remote Sens. 2013, 5(9), 4423-4449; https://doi.org/10.3390/rs5094423 - 11 Sep 2013

Cited by 238 | Viewed by 23863

Abstract

The Nightfire algorithm detects and characterizes sub-pixel hot sources using multispectral data collected globally, each night, by the Suomi National Polar Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS). The spectral bands utilized span visible, near-infrared (NIR), short-wave infrared (SWIR), and mid-wave infrared [...] Read more.

The Nightfire algorithm detects and characterizes sub-pixel hot sources using multispectral data collected globally, each night, by the Suomi National Polar Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS). The spectral bands utilized span visible, near-infrared (NIR), short-wave infrared (SWIR), and mid-wave infrared (MWIR). The primary detection band is in the SWIR, centered at 1.6 μm. Without solar input, the SWIR spectral band records sensor noise, punctuated by high radiant emissions associated with gas flares, biomass burning, volcanoes, and industrial sites such as steel mills. Planck curve fitting of the hot source radiances yields temperature (K) and emission scaling factor (ESF). Additional calculations are done to estimate source size (m²), radiant heat intensity (W/m²), and radiant heat (MW). Use of the sensor noise limited M7, M8, and M10 spectral bands at night reduce scene background effects, which are widely reported for fire algorithms based on MWIR and long-wave infrared. High atmospheric transmissivity in the M10 spectral band reduces atmospheric effects on temperature and radiant heat retrievals. Nightfire retrieved temperature estimates for sub-pixel hot sources ranging from 600 to 6,000 K. An intercomparison study of biomass burning in Sumatra from June 2013 found Nightfire radiant heat (MW) to be highly correlated to Moderate Resolution Imaging Spectrometer (MODIS) Fire Radiative Power (MW). Full article

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Open AccessArticle

Ultraviolet Fluorescence LiDAR (UFL) as a Measurement Tool for Water Quality Parameters in Turbid Lake Conditions

by Stephanie C.J. Palmer, Vadim V. Pelevin, Igor Goncharenko, Attila W. Kovács, András Zlinszky, Mátyás Présing, Hajnalka Horváth, Virginia Nicolás-Perea, Heiko Balzter and Viktor R. Tóth

Remote Sens. 2013, 5(9), 4405-4422; https://doi.org/10.3390/rs5094405 - 11 Sep 2013

Cited by 47 | Viewed by 10252

Abstract

Despite longstanding contributions to oceanography, similar use of fluorescence light detection and ranging (LiDAR) in lake settings is not routine. The potential for ship-mounted, multispectral Ultraviolet Fluorescence LiDAR (UFL) to provide rapid, high-resolution data in variably turbid and productive lake conditions are investigated [...] Read more.

Despite longstanding contributions to oceanography, similar use of fluorescence light detection and ranging (LiDAR) in lake settings is not routine. The potential for ship-mounted, multispectral Ultraviolet Fluorescence LiDAR (UFL) to provide rapid, high-resolution data in variably turbid and productive lake conditions are investigated here through a series of laboratory tank and field measurements carried out on Lake Balaton, Hungary. UFL data, calibrated empirically to a set of coinciding conventionally-analyzed samples, provide simultaneous estimates of three important parameters-chlorophyll a(chla), total suspended matter (TSM) and colored dissolved organic matter (CDOM). Successful UFL retrievals from both laboratory and field measurements were achieved for chla (0.01–378 mg∙m⁻³; R = 0.83–0.92), TSM (0.1–130 g∙m⁻³; R = 0.90–0.96) and CDOM (0.003–0.125 aCDOM(440); R = 0.80–0.97). Fluorescence emission at 685 nm is shown through tank measurements to display robust but distinct relationships with chla concentration for the two cultured algae species investigated (cyanobacteria, Cylindrospermopsis raciborskii, and chlorophyta, Scenedesmus armatus). The ratio between fluorescence emissions measured at 650 nm, related to the phycocyanin fluorescence maximum, to that at 685 nm is demonstrated to effectively distinguish these two species. Validation through both laboratory measurements and field measurements confirmed that site specific calibration is necessary. This study presents the first known assessment and application of ship-mounted fluorescence LiDAR in freshwater lake conditions and demonstrates the use of UFL in measuring important water quality parameters despite the more complicated hydro-optic conditions of inland waters. Full article

(This article belongs to the Special Issue Remote Sensing of Phytoplankton)

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Open AccessArticle

Characterizing the Absorption Properties for Remote Sensing of Three Small Optically-Diverse South African Reservoirs

by Mark William Matthews and Stewart Bernard

Remote Sens. 2013, 5(9), 4370-4404; https://doi.org/10.3390/rs5094370 - 9 Sep 2013

Cited by 46 | Viewed by 8619

Abstract

Characterizing the specific inherent optical properties (SIOPs) of water constituents is fundamental to remote sensing applications. Therefore, this paper presents the absorption properties of phytoplankton, gelbstoff and tripton for three small, optically-diverse South African inland waters. The three reservoirs, Hartbeespoort, Loskop and Theewaterskloof, [...] Read more.

Characterizing the specific inherent optical properties (SIOPs) of water constituents is fundamental to remote sensing applications. Therefore, this paper presents the absorption properties of phytoplankton, gelbstoff and tripton for three small, optically-diverse South African inland waters. The three reservoirs, Hartbeespoort, Loskop and Theewaterskloof, are challenging for remote sensing, due to differences in phytoplankton assemblage and the considerable range of constituent concentrations. Relationships between the absorption properties and biogeophysical parameters, chlorophyll-a (chl-a), TChl (chl-a plus phaeopigments), seston, minerals and tripton, are established. The value determined for the mass-specific tripton absorption coefficient at 442 nm, a∗ (442), ranges from 0.024 to 0.263 m2·g−1. The value of the TChl-specific phytoplankton absorption coefficient (a∗ ) was strongly influenced by phytoplankton species, size, accessory pigmentation and biomass. a∗ (440) ranged from 0.056 to 0.018 m2·mg−1 in oligotrophic to hypertrophic waters. The positive relationship between cell size and trophic state observed in open ocean waters was violated by significant small cyanobacterial populations. The phycocyanin-specific phytoplankton absorption at 620 nm, a∗ (620), was determined as 0.007 m2·g−1 in a M. aeruginosa bloom. Chl-a was a better indicator of phytoplankton biomass than phycocyanin (PC) in surface scums, due to reduced accessory pigment production. Absorption budgets demonstrate that monospecific blooms of M. aeruginosa and C. hirundinella may be treated as “cultures”, removing some complexities for remote sensing applications. These results contribute toward a better understanding of IOPs and remote sensing applications in hypertrophic inland waters. However, the majority of the water is optically complex, requiring the usage of all the SIOPs derived here for remote sensing applications. The SIOPs may be used for developing remote sensing algorithms for the detection of biogeophysical parameters, including chl-a, suspended matter, tripton and gelbstoff, and in advanced remote sensing studies for phytoplankton type detection. Full article

(This article belongs to the Special Issue Remote Sensing of Phytoplankton)

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Open AccessArticle

Assessing Regional Climate and Local Landcover Impacts on Vegetation with Remote Sensing

by Pei-Ling Lin and Nathaniel Brunsell

Remote Sens. 2013, 5(9), 4347-4369; https://doi.org/10.3390/rs5094347 - 9 Sep 2013

Cited by 4 | Viewed by 6173

Abstract

Landcover change alters not only the surface landscape but also regional carbon and water cycling. The objective of this study was to assess the potential impacts of landcover change across the Kansas River Basin (KRB) by comparing local microclimatic impacts and regional scale [...] Read more.

Landcover change alters not only the surface landscape but also regional carbon and water cycling. The objective of this study was to assess the potential impacts of landcover change across the Kansas River Basin (KRB) by comparing local microclimatic impacts and regional scale climate influences. This was done using a 25-year time series of Normalized Difference Vegetation Index (NDVI) and precipitation (PPT) data analyzed using multi-resolution information theory metrics. Results showed both entropy of PPT and NDVI varied along a pronounced PPT gradient. The scalewise relative entropy of NDVI was the most informative at the annual scale, while for PPT the scalewise relative entropy varied temporally and by landcover type. The relative entropy of NDVI and PPT as a function of landcover showed the most information at the 512-day scale for all landcover types, implying different landcover types had the same response across the entire KRB. This implies that land use decisions may dramatically alter the local time scales of responses to global climate change. Additionally, altering land cover (e.g., for biofuel production) may impact ecosystem functioning at local to regional scales and these impacts must be considered for accurately assessing future implications of climate change. Full article

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Open AccessArticle

Landslide Investigation with Remote Sensing and Sensor Network: From Susceptibility Mapping and Scaled-down Simulation towards in situ Sensor Network Design

by Gang Qiao, Ping Lu, Marco Scaioni, Shuying Xu, Xiaohua Tong, Tiantian Feng, Hangbin Wu, Wen Chen, Yixiang Tian, Weian Wang and Rongxing Li

Remote Sens. 2013, 5(9), 4319-4346; https://doi.org/10.3390/rs5094319 - 6 Sep 2013

Cited by 53 | Viewed by 11905

Abstract

This paper presents an integrated approach to landslide research based on remote sensing and sensor networks. This approach is composed of three important parts: (i) landslide susceptibility mapping using remote-sensing techniques for susceptible determination of landslide spots; (ii) scaled-down landslide simulation experiments for [...] Read more.

This paper presents an integrated approach to landslide research based on remote sensing and sensor networks. This approach is composed of three important parts: (i) landslide susceptibility mapping using remote-sensing techniques for susceptible determination of landslide spots; (ii) scaled-down landslide simulation experiments for validation of sensor network for landslide monitoring, and (iii) in situ sensor network deployment for intensified landslide monitoring. The study site is the Taziping landslide located in Hongkou Town (Sichuan, China). The landslide features generated by landslides triggered by the 2008 Wenchuan Earthquake were first extracted by means of object-oriented methods from the remote-sensing images before and after the landslides events. On the basis of correlations derived between spatial distribution of landslides and control factors, the landslide susceptibility mapping was carried out using the Artificial Neural Network (ANN) technique. Then the Taziping landslide, located in the above mentioned study area, was taken as an example to design and implement a scaled-down landslide simulation platform in Tongji University (Shanghai, China). The landslide monitoring sensors were carefully investigated and deployed for rainfall induced landslide simulation experiments. Finally, outcomes from the simulation experiments were adopted and employed to design the future in situ sensor network in Taziping landslide site where the sensor deployment is being implemented. Full article

(This article belongs to the Special Issue Remote Sensing for Landslides Investigation: From Research into Practice)

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1764 KiB

Open AccessArticle

Trends in the Start of the Growing Season in Fennoscandia 1982–2011

by Kjell Arild Høgda, Hans Tømmervik and Stein Rune Karlsen

Remote Sens. 2013, 5(9), 4304-4318; https://doi.org/10.3390/rs5094304 - 6 Sep 2013

Cited by 63 | Viewed by 10154

Abstract

Global temperature is increasing, and this is affecting the vegetation phenology in many parts of the world. In Fennoscandia, as well as Northern Europe, the advances of phenological events in spring have been recorded in recent decades. In this study, we analyzed the [...] Read more.

Global temperature is increasing, and this is affecting the vegetation phenology in many parts of the world. In Fennoscandia, as well as Northern Europe, the advances of phenological events in spring have been recorded in recent decades. In this study, we analyzed the start of the growing season within five different vegetation regions in Fennoscandia using the 30-year Global Inventory Modeling and Mapping Studies (GIMMS) NDVI3g dataset. We applied a previously developed pixel-specific Normalized Difference Vegetation Index (NDVI) threshold method, adjusted it to the NDVI3g data and analyzed trends within the different regions. Results show a warming trend with an earlier start of the growing season of 11.8 ± 2.0 days (p < 0.01) for the whole area. However, there are large regional differences, and the warming/trend towards an earlier start of the growing season is most significant in the southern regions (19.3 ± 4.7 days, p < 0.01 in the southern oceanic region), while the start was stable or modest earlier (two to four days; not significant) in the northern regions. To look for temporal variations in the trends, we divided the 30-year period into three separate decadal time periods. Results show significantly more change/trend towards an earlier start of the growing season in the first period compared to the two last. In the second and third period, the trend towards an earlier start of the growing season slowed down, and in two of the regions, the trend towards an earlier start of the growing season was even reversed during the last decade. Full article

(This article belongs to the Special Issue Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011))

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999 KiB

Open AccessArticle

Hub Height Ocean Winds over the North Sea Observed by the NORSEWInD Lidar Array: Measuring Techniques, Quality Control and Data Management

by Charlotte Bay Hasager, Detlef Stein, Michael Courtney, Alfredo Peña, Torben Mikkelsen, Matthew Stickland and Andrew Oldroyd

Remote Sens. 2013, 5(9), 4280-4303; https://doi.org/10.3390/rs5094280 - 5 Sep 2013

Cited by 46 | Viewed by 9814

Abstract

In the North Sea, an array of wind profiling wind lidars were deployed mainly on offshore platforms. The purpose was to observe free stream winds at hub height. Eight lidars were validated prior to offshore deployment with observations from cup anemometers at 60, [...] Read more.

In the North Sea, an array of wind profiling wind lidars were deployed mainly on offshore platforms. The purpose was to observe free stream winds at hub height. Eight lidars were validated prior to offshore deployment with observations from cup anemometers at 60, 80, 100 and 116 m on an onshore met mast situated in flat terrain. The so-called “NORSEWInD standard” for comparing lidar and mast wind data includes the criteria that the slope of the linear regression should lie within 0.98 and 1.01 and the linear correlation coefficient higher than 0.98 for the wind speed range 4–16 m∙s⁻¹. Five lidars performed excellently, two slightly failed the first criterion and one failed both. The lidars were operated offshore from six months to more than two years and observed in total 107 months of 10-min mean wind profile observations. Four lidars were re-evaluated post deployment with excellent results. The flow distortion around platforms was examined using wind tunnel experiments and computational fluid dynamics and it was found that at 100 m height wind observations by the lidars were not significantly influenced by flow distortion. Observations of the vertical wind profile shear exponent at hub height are presented. Full article

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Open AccessArticle

Mapping and Evaluation of NDVI Trends from Synthetic Time Series Obtained by Blending Landsat and MODIS Data around a Coalfield on the Loess Plateau

by Feng Tian, Yunjia Wang, Rasmus Fensholt, Kun Wang, Li Zhang and Yi Huang

Remote Sens. 2013, 5(9), 4255-4279; https://doi.org/10.3390/rs5094255 - 2 Sep 2013

Cited by 83 | Viewed by 11320

Abstract

The increasingly intensive and extensive coal mining activities on the Loess Plateau pose a threat to the fragile local ecosystems. Quantifying the effects of coal mining activities on environmental conditions is of great interest for restoring and managing the local ecosystems and resources. [...] Read more.

The increasingly intensive and extensive coal mining activities on the Loess Plateau pose a threat to the fragile local ecosystems. Quantifying the effects of coal mining activities on environmental conditions is of great interest for restoring and managing the local ecosystems and resources. This paper generates dense NDVI (Normalized Difference Vegetation Index) time series between 2000 and 2011 at a spatial resolution of 30 m by blending Landsat and MODIS (Moderate Resolution Imaging Spectroradiometer) data using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and further evaluates its capability for mapping vegetation trends around a typical coalfield on the Loss Plateau. Synthetic NDVI images were generated using (1) STARFM-generated NIR (near infrared) and red band reflectance data (scheme 1) and (2) Landsat and MODIS NDVI images directly as inputs for STARFM (scheme 2). By comparing the synthetic NDVI images with the corresponding Landsat NDVI, we found that scheme 2 consistently generated better results (0.70 < R² < 0.76) than scheme 1 (0.56 < R² < 0.70) in this study area. Trend analysis was then performed with the synthetic dense NDVI time series and the annual maximum NDVI (NDVI_max) time series. The accuracy of these trends was evaluated by comparing to those from the corresponding MODIS time series, and it was concluded that both the trends from synthetic/MODIS NDVI dense time series and synthetic/MODIS NDVI_max time series (2000–2011) were highly consistent. Compared to trends from MODIS time series, trends from synthetic time series are better able to capture fine scale vegetation changes. STARFM-generated synthetic NDVI time series could be used to quantify the effects of mining activities on vegetation, but the test areas should be selected with caution, as the trends derived from synthetic and MODIS time series may be significantly different in some areas. Full article

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Open AccessArticle

Recent Declines in Warming and Vegetation Greening Trends over Pan-Arctic Tundra

by Uma S. Bhatt, Donald A. Walker, Martha K. Raynolds, Peter A. Bieniek, Howard E. Epstein, Josefino C. Comiso, Jorge E. Pinzon, Compton J. Tucker and Igor V. Polyakov

Remote Sens. 2013, 5(9), 4229-4254; https://doi.org/10.3390/rs5094229 - 29 Aug 2013

Cited by 177 | Viewed by 15600

Abstract

Vegetation productivity trends for the Arctic tundra are updated for the 1982–2011 period and examined in the context of land surface temperatures and coastal sea ice. Understanding mechanistic links between vegetation and climate parameters contributes to model advancements that are necessary for improving [...] Read more.

Vegetation productivity trends for the Arctic tundra are updated for the 1982–2011 period and examined in the context of land surface temperatures and coastal sea ice. Understanding mechanistic links between vegetation and climate parameters contributes to model advancements that are necessary for improving climate projections. This study employs remote sensing data: Global Inventory Modeling and Mapping Studies (GIMMS) Maximum Normalized Difference Vegetation Index (MaxNDVI), Special Sensor Microwave Imager (SSM/I) sea-ice concentrations, and Advanced Very High Resolution Radiometer (AVHRR) radiometric surface temperatures. Spring sea ice is declining everywhere except in the Bering Sea, while summer open water area is increasing throughout the Arctic. Summer Warmth Index (SWI—sum of degree months above freezing) trends from 1982 to 2011 are positive around Beringia but are negative over Eurasia from the Barents to the Laptev Seas and in parts of northern Canada. Eastern North America continues to show increased summer warmth and a corresponding steady increase in MaxNDVI. Positive MaxNDVI trends from 1982 to 2011 are generally weaker compared to trends from 1982–2008. So to better understand the changing trends, break points in the time series were quantified using the Breakfit algorithm. The most notable break points identify declines in SWI since 2003 in Eurasia and 1998 in Western North America. The Time Integrated NDVI (TI-NDVI, sum of the biweekly growing season values of MaxNDVI) has declined since 2005 in Eurasia, consistent with SWI declines. Summer (June–August) sea level pressure (slp) averages from 1999–2011 were compared to those from 1982–1998 to reveal higher slp over Greenland and the western Arctic and generally lower pressure over the continental Arctic in the recent period. This suggests that the large-scale circulation is likely a key contributor to the cooler temperatures over Eurasia through increased summer cloud cover and warming in Eastern North America from more cloud-free skies. Full article

(This article belongs to the Special Issue Monitoring Global Vegetation with AVHRR NDVI3g Data (1981-2011))

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5095 KiB

Open AccessArticle

Transferability of Object-Oriented Image Analysis Methods for Slum Identification

by Divyani Kohli, Pankaj Warwadekar, Norman Kerle, Richard Sliuzas and Alfred Stein

Remote Sens. 2013, 5(9), 4209-4228; https://doi.org/10.3390/rs5094209 - 29 Aug 2013

Cited by 81 | Viewed by 10725

Abstract

Updated spatial information on the dynamics of slums can be helpful to measure and evaluate progress of policies. Earlier studies have shown that semi-automatic detection of slums using remote sensing can be challenging considering the large variability in definition and appearance. In this [...] Read more.

Updated spatial information on the dynamics of slums can be helpful to measure and evaluate progress of policies. Earlier studies have shown that semi-automatic detection of slums using remote sensing can be challenging considering the large variability in definition and appearance. In this study, we explored the potential of an object-oriented image analysis (OOA) method to detect slums, using very high resolution (VHR) imagery. This method integrated expert knowledge in the form of a local slum ontology. A set of image-based parameters was identified that was used for differentiating slums from non-slum areas in an OOA environment. The method was implemented on three subsets of the city of Ahmedabad, India. Results show that textural features such as entropy and contrast derived from a grey level co-occurrence matrix (GLCM) and the size of image segments are stable parameters for classification of built-up areas and the identification of slums. Relation with classified slum objects, in terms of enclosed by slums and relative border with slums was used to refine classification. The analysis on three different subsets showed final accuracies ranging from 47% to 68%. We conclude that our method produces useful results as it allows including location specific adaptation, whereas generically applicable rulesets for slums are still to be developed. Full article

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Open AccessArticle

Assessing the Sensitivity of the OMI-NO₂ Product to Emission Changes across Europe

by Martijn Schaap, Richard Kranenburg, Lyana Curier, Magdalena Jozwicka, Enrico Dammers and Renske Timmermans

Remote Sens. 2013, 5(9), 4187-4208; https://doi.org/10.3390/rs5094187 - 27 Aug 2013

Cited by 27 | Viewed by 8403

Abstract

The advent of satellite data has provided a source of independent information to monitor trends in tropospheric nitrogen dioxide levels. To interpret these trends, one needs to know the sensitivity of the satellite retrieved NO₂ column to anthropogenic emissions. We have applied [...] Read more.

The advent of satellite data has provided a source of independent information to monitor trends in tropospheric nitrogen dioxide levels. To interpret these trends, one needs to know the sensitivity of the satellite retrieved NO₂ column to anthropogenic emissions. We have applied a chemistry transport model to investigate the sensitivity of the modeled NO₂ column, sampled at the OMI (Ozone Monitoring Instrument) overpass time and location and weighted by the OMI averaging kernel, to emission sources across Europe. The most important contribution (~35%) in Western Europe is made by road transport. Off-road transport and industrial combustion each contribute 10%–15% across continental Europe. In Eastern Europe, power plant contributions are of comparable magnitude as those of road transport. To answer the question if the OMI-NO₂ trends can be translated directly into emission changes, we assessed the anticipated changes in OMI-NO₂ between 2005 and 2020. Although the results indicated that for many countries, it is indeed possible, for medium- and small-sized coastal countries, the contribution of the increasing shipping emissions in adjacent sea areas may mask a significant part of national emission reductions. This study highlights the need for a combined use of models, a priori emission estimates and satellite data to verify emission trends. Full article

(This article belongs to the Special Issue Optical Remote Sensing of the Atmosphere)

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3993 KiB

Open AccessArticle

Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches

by Marek K. Jakubowski, Wenkai Li, Qinghua Guo and Maggi Kelly

Remote Sens. 2013, 5(9), 4163-4186; https://doi.org/10.3390/rs5094163 - 26 Aug 2013

Cited by 176 | Viewed by 18555

Abstract

Light detection and ranging (lidar) data is increasingly being used for ecosystem monitoring across geographic scales. This work concentrates on delineating individual trees in topographically-complex, mixed conifer forest across the California’s Sierra Nevada. We delineated individual trees using vector data and a 3D [...] Read more.

Light detection and ranging (lidar) data is increasingly being used for ecosystem monitoring across geographic scales. This work concentrates on delineating individual trees in topographically-complex, mixed conifer forest across the California’s Sierra Nevada. We delineated individual trees using vector data and a 3D lidar point cloud segmentation algorithm, and using raster data with an object-based image analysis (OBIA) of a canopy height model (CHM). The two approaches are compared to each other and to ground reference data. We used high density (9 pulses/m²), discreet lidar data and WorldView-2 imagery to delineate individual trees, and to classify them by species or species types. We also identified a new method to correct artifacts in a high-resolution CHM. Our main focus was to determine the difference between the two types of approaches and to identify the one that produces more realistic results. We compared the delineations via tree detection, tree heights, and the shape of the generated polygons. The tree height agreement was high between the two approaches and the ground data (r²: 0.93–0.96). Tree detection rates increased for more dominant trees (8–100 percent). The two approaches delineated tree boundaries that differed in shape: the lidar-approach produced fewer, more complex, and larger polygons that more closely resembled real forest structure. Full article

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380 KiB

Open AccessArticle

River Discharge Estimation by Using Altimetry Data and Simplified Flood Routing Modeling

by Angelica Tarpanelli, Silvia Barbetta, Luca Brocca and Tommaso Moramarco

Remote Sens. 2013, 5(9), 4145-4162; https://doi.org/10.3390/rs5094145 - 22 Aug 2013

Cited by 121 | Viewed by 13073

Abstract

A methodology to estimate the discharge along rivers, even poorly gauged ones, taking advantage of water level measurements derived from satellite altimetry is proposed. The procedure is based on the application of the Rating Curve Model (RCM), a simple method allowing for the [...] Read more.

A methodology to estimate the discharge along rivers, even poorly gauged ones, taking advantage of water level measurements derived from satellite altimetry is proposed. The procedure is based on the application of the Rating Curve Model (RCM), a simple method allowing for the estimation of the flow conditions in a river section using only water levels recorded at that site and the discharges observed at another upstream section. The European Remote-Sensing Satellite 2, ERS-2, and the Environmental Satellite, ENVISAT, altimetry data are used to provide time series of water levels needed for the application of RCM. In order to evaluate the usefulness of the approach, the results are compared with the ones obtained by applying an empirical formula that allows discharge estimation from remotely sensed hydraulic information. To test the proposed procedure, the 236 km-reach of the Po River is investigated, for which five in situ stations and four satellite tracks are available. Results show that RCM is able to appropriately represent the discharge, and its performance is better than the empirical formula, although this latter does not require upstream hydrometric data. Given its simple formal structure, the proposed approach can be conveniently utilized in ungauged sites where only the survey of the cross-section is needed. Full article

(This article belongs to the Special Issue Hydrological Remote Sensing)

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Remote Sens., Volume 5, Issue 9 (September 2013) – 25 articles , Pages 4145-4734

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