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Remote Sens., Volume 2, Issue 11 (November 2010) – 10 articles , Pages 2442-2642

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Research

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4421 KiB  
Article
Development and Evaluation of Phenological Change Indices Derived from Time Series of Image Data
by Keith R. McCloy
Remote Sens. 2010, 2(11), 2442-2473; https://doi.org/10.3390/rs2112442 - 04 Nov 2010
Cited by 24 | Viewed by 7588
Abstract
Changes in vegetation phenology are recognized as being possibly the most important early indicator of the impact of climate change on ecosystems. Time series of image data are accepted as being the best way to map these changes, if we can derive suitable [...] Read more.
Changes in vegetation phenology are recognized as being possibly the most important early indicator of the impact of climate change on ecosystems. Time series of image data are accepted as being the best way to map these changes, if we can derive suitable indices from the huge volumes of time series data that make the interpretation of these time series difficult. The problem is thus to derive a set of indices from the time series of image data that depict changes in vegetation phenology in a way that is easy to analyze and use. This problem has been solved by deriving a set of six Phenological Change Indices that measure the five ways that the phenological curve of vegetation can change over time. These indices were then tested using simulated data based on sample phenological profiles for a set of land covers and showed that four of the indices measured four of the ways that the phenological profile can change, and two of the indices gave similar results in measuring the last way that the phenological profiles can change. A time series of image data was then used to map the Phenological Change Indices for Eurasia and a sample of land covers was used to relate the changes in phenology to location for each land cover. This work showed that the detected changes in phenology are similar to those found in other papers. The benefit of these indices is that we can now analyze changes in phenology in a much more detailed and accurate way than has been possible until now. Full article
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439 KiB  
Article
Seven Years’ Observation of Mid-Upper Tropospheric Methane from Atmospheric Infrared Sounder
by Xiaozhen Xiong, Chris Barnet, Eric Maddy, Jennifer Wei, Xingpin Liu and Thomas S. Pagano
Remote Sens. 2010, 2(11), 2509-2530; https://doi.org/10.3390/rs2112509 - 09 Nov 2010
Cited by 35 | Viewed by 9996
Abstract
The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua platform provides a measurement of global methane (CH4) in the mid-upper troposphere since September, 2002. As a thermal infrared sounder, the most sensitivity of AIRS to atmospheric CH4 is in the mid-upper troposphere [...] Read more.
The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua platform provides a measurement of global methane (CH4) in the mid-upper troposphere since September, 2002. As a thermal infrared sounder, the most sensitivity of AIRS to atmospheric CH4 is in the mid-upper troposphere with the degree of freedom of ~1.0. Validation of AIRS CH4 product versus thousands of aircraft profiles (convolved using the AIRS averaging kernels) demonstrates that its RMS error (RMSE) is mostly less than 1.5%, and its quality is pretty stable from 2003 to 2009. For scientific analysis of the spatial and temporal variation of mid-upper tropospheric CH4 (MUT-CH4) in the High Northern Hemisphere (HNH), it is more valuable to use the AIRS retrieved CH4 in a layer of about 100 hPa below tropopause (“Representative Layer”) than in a fixed pressure layer. Further analysis of deseasonalized time-series of AIRS CH4 in both a fixed pressure layer and the “Representative Layer” of AIRS (only for the HNH) from 2003 to 2009 indicates that, similar to the CH4 in the marine boundary layer (MBL) that was found to increase in 2007–2008, MUT-CH4 was also observed to have a recent increase but the most significant increase occurred in 2008. MUT-CH4 continued to increase in 2009, especially in the HNH. Moreover, the trend of MUT-CH4 from 2006 to 2008 is lower than the trend of CH4 in the MBL by 30–40% in both the southern hemisphere and HNH. This delay for the MUT-CH4 increase of about one year than CH4 in the MBL as well as the smaller increase trend for MUT-CH4 suggest that surface emission is likely a major driver for the recent CH4 increase. It is also found that the seasonal cycle of MUT-CH4 is different from CH4 in the MBL due to the impact of transport, in addition to the surface emission and the photochemical loss. Full article
(This article belongs to the Special Issue Atmospheric Remote Sensing)
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538 KiB  
Article
Riding Quality Model for Asphalt Pavement Monitoring Using Phase Array Type L-band Synthetic Aperture Radar (PALSAR)
by Weerakaset Suanpaga and Kamiya Yoshikazu
Remote Sens. 2010, 2(11), 2531-2546; https://doi.org/10.3390/rs2112531 - 12 Nov 2010
Cited by 18 | Viewed by 8274
Abstract
There are difficulties associated with near-real time or frequent pavement monitoring, because it is time consuming and costly. This study aimed to develop a binary logit model for the evaluation of highway riding quality, which could be used to monitor pavement conditions. The [...] Read more.
There are difficulties associated with near-real time or frequent pavement monitoring, because it is time consuming and costly. This study aimed to develop a binary logit model for the evaluation of highway riding quality, which could be used to monitor pavement conditions. The model was applied to investigate the influence of backscattering values of Phase Array type L-band Synthetic Aperture Radar (PALSAR). Training data obtained during 3–7 May 2007 was used in the development process, together with actual international roughness index (IRI) values collected along a highway in Ayutthaya province, Thailand. The analysis showed that an increase in the backscattering value in the HH or the VV polarization indicated the poor condition of the pavement surface and, of the two, the HH polarization is more suitable for developing riding quality evaluation. The model developed was applied to analyze highway number 3467, to demonstrate its capability. It was found that the assessment accuracy of the prediction of the highway level of service was 97.00%. This is a preliminary study of the proposed technique and more intensive investigation must be carried out using ALOS/PALSAR images in various seasons. Full article
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1429 KiB  
Article
Remote Sensing of Environmental Change in the Antirio Deltaic Fan Region, Western Greece
by Emmanuel Vassilakis
Remote Sens. 2010, 2(11), 2547-2560; https://doi.org/10.3390/rs2112547 - 16 Nov 2010
Cited by 6 | Viewed by 7827
Abstract
In the westernmost region of the rapidly widening Corinth rift, Greece, extensive development of roads, bridges and other human infrastructure has caused continuous environmental change over the past twenty years. River networks, the land surface and the coastal environment, have been altered, especially [...] Read more.
In the westernmost region of the rapidly widening Corinth rift, Greece, extensive development of roads, bridges and other human infrastructure has caused continuous environmental change over the past twenty years. River networks, the land surface and the coastal environment, have been altered, especially in the areas corresponding to deltaic fans. In this paper we use earth observation systems that have captured these environmental changes, particularly medium (Landsat TM and ETM+) and high (Quickbird) resolution satellite images, to identify environmental changes between the periods 1992, 2000, 2002, and 2005. Six pseudo-color multi-temporal images in different spectral areas were created in order to detect changes to the terrestrial and coastal environment caused mainly by direct or indirect human impact. This methodology provided new data for quantifying significant alterations in the environment on different scales. In many cases this revealed their sequence during the time of observation. Full article
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752 KiB  
Article
Satellite Global and Hemispheric Lower Tropospheric Temperature Annual Temperature Cycle
by Benjamin M. Herman, Michael A. Brunke, Roger A. Pielke, Sr., John R. Christy and Richard T. McNider
Remote Sens. 2010, 2(11), 2561-2570; https://doi.org/10.3390/rs2112561 - 16 Nov 2010
Cited by 5 | Viewed by 9742
Abstract
Previous analyses of the Earth’s annual cycle and its trends have utilized surface temperature data sets. Here we introduce a new analysis of the global and hemispheric annual cycle using a satellite remote sensing derived data set during the period 1979–2009, as determined [...] Read more.
Previous analyses of the Earth’s annual cycle and its trends have utilized surface temperature data sets. Here we introduce a new analysis of the global and hemispheric annual cycle using a satellite remote sensing derived data set during the period 1979–2009, as determined from the lower tropospheric (LT) channel of the MSU satellite. While the surface annual cycle is tied directly to the heating and cooling of the land areas, the tropospheric annual cycle involves additionally the gain or loss of heat between the surface and atmosphere. The peak in the global tropospheric temperature in the 30 year period occurs on 10 July and the minimum on 9 February in response to the larger land mass in the Northern Hemisphere. The actual dates of the hemispheric maxima and minima are a complex function of many variables which can change from year to year thereby altering these dates.Here we examine the time of occurrence of the global and hemispheric maxima and minima lower tropospheric temperatures, the values of the annual maxima and minima, and the slopes and significance of the changes in these metrics. The statistically significant trends are all relatively small. The values of the global annual maximum and minimum showed a small, but significant trend. Northern and Southern Hemisphere maxima and minima show a slight trend toward occurring later in the year. Most recent analyses of trends in the global annual cycle using observed surface data have indicated a trend toward earlier maxima and minima. Full article
(This article belongs to the Special Issue Remote Sensing in Climate Monitoring and Analysis)
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4167 KiB  
Article
Long-Term Volcanic Activity at Shiveluch Volcano: Nine Years of ASTER Spaceborne Thermal Infrared Observations
by Adam Carter and Michael Ramsey
Remote Sens. 2010, 2(11), 2571-2583; https://doi.org/10.3390/rs2112571 - 17 Nov 2010
Cited by 23 | Viewed by 9901
Abstract
Shiveluch (Kamchatka, Russia) is the most active andesitic volcano of the Kuril-Kamchatka arc, typically exhibiting near-continual high-temperature fumarolic activity and periods of exogenous lava dome emplacement punctuated by discrete large explosive eruptions. These eruptions can produce large pyroclastic flow (PF) deposits, which are [...] Read more.
Shiveluch (Kamchatka, Russia) is the most active andesitic volcano of the Kuril-Kamchatka arc, typically exhibiting near-continual high-temperature fumarolic activity and periods of exogenous lava dome emplacement punctuated by discrete large explosive eruptions. These eruptions can produce large pyroclastic flow (PF) deposits, which are common on the southern flank of the volcano. Since 2000, six explosive eruptions have occurred that generated ash fall and PF deposits. Over this same time period, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument has been acquiring image-based visible/near infrared (VNIR), short wave infrared (SWIR) and thermal infrared (TIR) data globally, with a particular emphasis on active volcanoes. Shiveluch was selected as an ASTER target of interest early in the mission because of its frequent activity and potential impact to northern Pacific air transportation. The north Pacific ASTER archive was queried for Shiveluch data and we present results from 2000 to 2009 that documents three large PF deposits emplaced on 19 May 2001, 9 May 2004, and 28 February 2005. The long-term archive of infrared data provides an excellent record on the changing activity and eruption state of the volcano. Full article
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6392 KiB  
Article
Geostatistics for Mapping Leaf Area Index over a Cropland Landscape: Efficiency Sampling Assessment
by Beatriz Martinez, Eduardo Cassiraga, Fernando Camacho and Javier Garcia-Haro
Remote Sens. 2010, 2(11), 2584-2606; https://doi.org/10.3390/rs2112584 - 23 Nov 2010
Cited by 14 | Viewed by 10039
Abstract
This paper evaluates the performance of spatial methods to estimate leaf area index (LAI) fields from ground-based measurements at high-spatial resolution over a cropland landscape. Three geostatistical model variants of the kriging technique, the ordinary kriging (OK), the collocated cokriging (CKC) and kriging [...] Read more.
This paper evaluates the performance of spatial methods to estimate leaf area index (LAI) fields from ground-based measurements at high-spatial resolution over a cropland landscape. Three geostatistical model variants of the kriging technique, the ordinary kriging (OK), the collocated cokriging (CKC) and kriging with an external drift (KED) are used. The study focused on the influence of the spatial sampling protocol, auxiliary information, and spatial resolution in the estimates. The main advantage of these models lies in the possibility of considering the spatial dependence of the data and, in the case of the KED and CKC, the auxiliary information for each location used for prediction purposes. A high-resolution NDVI image computed from SPOT TOA reflectance data is used as an auxiliary variable in LAI predictions. The CKC and KED predictions have proven the relevance of the auxiliary information to reproduce the spatial pattern at local scales, proving the KED model to be the best estimator when a non-stationary trend is observed. Advantages and limitations of the methods in LAI field predictions for two systematic and two stratified spatial samplings are discussed for high (20 m), medium (300 m) and coarse (1 km) spatial scales. The KED has exhibited the best observed local accuracy for all the spatial samplings. Meanwhile, the OK model provides comparable results when a well stratified sampling scheme is considered by land cover. Full article
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1570 KiB  
Article
Hydraulic Geometry, GIS and Remote Sensing, Techniques against Rainfall-Runoff Models for Estimating Flood Magnitude in Ephemeral Fluvial Systems
by Carmelo Conesa-Garcia, Vicente Caselles-Miralles, Juan M. Sanchez Tomas and Rafael Garcia-Lorenzo
Remote Sens. 2010, 2(11), 2607-2628; https://doi.org/10.3390/rs2112607 - 23 Nov 2010
Cited by 15 | Viewed by 9686
Abstract
This paper shows the combined use of remotely sensed data and hydraulic geometry methods as an alternative to rainfall-runoff models. Hydraulic geometric data and boolean images of water sheets obtained from satellite images after storm events were integrated in a Geographical Information System. [...] Read more.
This paper shows the combined use of remotely sensed data and hydraulic geometry methods as an alternative to rainfall-runoff models. Hydraulic geometric data and boolean images of water sheets obtained from satellite images after storm events were integrated in a Geographical Information System. Channel cross-sections were extracted from a high resolution Digital Terrain Model (DTM) and superimposed on the image cover to estimate the peak flow using HEC-RAS. The proposed methodology has been tested in ephemeral channels (ramblas) on the coastal zone in south-eastern Spain. These fluvial systems constitute an important natural hazard due to their high discharges and sediment loads. In particular, different areas affected by floods during the period 1997 to 2009 were delimited through HEC-GeoRAs from hydraulic geometry data and Landsat images of these floods (Landsat‑TM5 and Landsat-ETM+7). Such an approach has been validated against rainfall-surface runoff models (SCS Dimensionless Unit Hydrograph, SCSD, Témez gamma HU Tγ and the Modified Rational method, MRM) comparing their results with flood hydrographs of the Automatic Hydrologic Information System (AHIS) in several ephemeral channels in the Murcia Region. The results obtained from the method providing a better fit were used to calculate different hydraulic geometry parameters, especially in residual flood areas. Full article
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640 KiB  
Article
DEM Development from Ground-Based LiDAR Data: A Method to Remove Non-Surface Objects
by Maneesh Sharma, Ginger B. Paige and Scott N. Miller
Remote Sens. 2010, 2(11), 2629-2642; https://doi.org/10.3390/rs2112629 - 23 Nov 2010
Cited by 28 | Viewed by 9442
Abstract
Topography and land cover characteristics can have significant effects on infiltration, runoff, and erosion processes on watersheds. The ability to model the timing and routing of surface water and erosion is affected by the resolution of the digital elevation model (DEM). High resolution [...] Read more.
Topography and land cover characteristics can have significant effects on infiltration, runoff, and erosion processes on watersheds. The ability to model the timing and routing of surface water and erosion is affected by the resolution of the digital elevation model (DEM). High resolution ground-based Light Detecting and Ranging (LiDAR) technology can be used to collect detailed topographic and land cover characteristic data. In this study, a method was developed to remove vegetation from ground-based LiDAR data to create high resolution DEMs. Research was conducted on intensively studied rainfall–runoff plots on the USDA-ARS Walnut Gulch Experimental Watershed in Southeast Arizona. LiDAR data were used to generate 1 cm resolution digital surface models (DSM) for 5 plots. DSMs created directly from LiDAR data contain non-surface objects such as vegetation cover. A vegetation removal method was developed which used a slope threshold and a focal mean filter method to remove vegetation and create bare earth DEMs. The method was validated on a synthetic plot, where rocks and vegetation were added incrementally. Results of the validation showed a vertical error of ±7.5 mm in the final DEM. Full article
(This article belongs to the Special Issue LiDAR)
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Review

Jump to: Research

2655 KiB  
Review
Visible and Infrared Remote Imaging of Hazardous Waste: A Review
by Terrence Slonecker, Gary B. Fisher, Danielle P. Aiello and Barry Haack
Remote Sens. 2010, 2(11), 2474-2508; https://doi.org/10.3390/rs2112474 - 05 Nov 2010
Cited by 83 | Viewed by 16571
Abstract
One of the critical global environmental problems is human and ecological exposure to hazardous wastes from agricultural, industrial, military and mining activities. These wastes often include heavy metals, hydrocarbons and other organic chemicals. Traditional field and laboratory detection and monitoring of these wastes [...] Read more.
One of the critical global environmental problems is human and ecological exposure to hazardous wastes from agricultural, industrial, military and mining activities. These wastes often include heavy metals, hydrocarbons and other organic chemicals. Traditional field and laboratory detection and monitoring of these wastes are generally expensive and time consuming. The synoptic perspective of overhead remote imaging can be very useful for the detection and remediation of hazardous wastes. Aerial photography has a long and effective record in waste site evaluations. Aerial photographic archives allow temporal evaluation and change detection by visual interpretation. Multispectral aircraft and satellite systems have been successfully employed in both spectral and morphological analysis of hazardous wastes on the landscape and emerging hyperspectral sensors have permitted determination of the specific contaminants by processing strategies using the tens or hundreds of acquired wavelengths in the solar reflected and/or thermal infrared parts of the electromagnetic spectrum. This paper reviews the literature of remote sensing and overhead imaging in the context of hazardous waste and discusses future monitoring needs and emerging scientific research areas. Full article
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