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Remote Sens., Volume 1, Issue 4 (December 2009) – 39 articles , Pages 620-1394

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1170 KiB  
Article
Leaf Area Index (LAI) Estimation of Boreal Forest Using Wide Optics Airborne Winter Photos
by Terhikki Manninen, Lauri Korhonen, Pekka Voipio, Panu Lahtinen and Pauline Stenberg
Remote Sens. 2009, 1(4), 1380-1394; https://doi.org/10.3390/rs1041380 - 22 Dec 2009
Cited by 26 | Viewed by 14051
Abstract
A new simple airborne method based on wide optics camera is developed for leaf area index (LAI) estimation in coniferous forests. The measurements are carried out in winter, when the forest floor is completely snow covered and thus acts as a light background [...] Read more.
A new simple airborne method based on wide optics camera is developed for leaf area index (LAI) estimation in coniferous forests. The measurements are carried out in winter, when the forest floor is completely snow covered and thus acts as a light background for the hemispherical analysis of the images. The photos are taken automatically and stored on a laptop during the flights. The R2 value of the linear regression of the airborne and ground based LAI measurements was 0.89. Full article
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1249 KiB  
Article
Using Urban Landscape Trajectories to Develop a Multi-Temporal Land Cover Database to Support Ecological Modeling
by Jeffrey Hepinstall-Cymerman, Stefan Coe and Marina Alberti
Remote Sens. 2009, 1(4), 1353-1379; https://doi.org/10.3390/rs1041353 - 22 Dec 2009
Cited by 12 | Viewed by 14535
Abstract
Urbanization and the resulting changes in land cover have myriad impacts on ecological systems. Monitoring these changes across large spatial extents and long time spans requires synoptic remotely sensed data with an appropriate temporal sequence. We developed a multi-temporal land cover dataset for [...] Read more.
Urbanization and the resulting changes in land cover have myriad impacts on ecological systems. Monitoring these changes across large spatial extents and long time spans requires synoptic remotely sensed data with an appropriate temporal sequence. We developed a multi-temporal land cover dataset for a six-county area surrounding the Seattle, Washington State, USA, metropolitan region. Land cover maps for 1986, 1991, 1995, 1999, and 2002 were developed from Landsat TM images through a combination of spectral unmixing, image segmentation, multi-season imagery, and supervised classification approaches to differentiate an initial nine land cover classes. We then used ancillary GIS layers and temporal information to define trajectories of land cover change through multiple updating and backdating rules and refined our land cover classification for each date into 14 classes. We compared the accuracy of the initial approach with the landscape trajectory modifications and determined that the use of landscape trajectory rules increased our ability to differentiate several classes including bare soil (separated into cleared for development, agriculture, and clearcut forest) and three intensities of urban. Using the temporal dataset, we found that between 1986 and 2002, urban land cover increased from 8 to 18% of our study area, while lowland deciduous and mixed forests decreased from 21 to 14%, and grass and agriculture decreased from 11 to 8%. The intensity of urban land cover increased with 252 km2 in Heavy Urban in 1986 increasing to 629 km2 by 2002. The ecological systems that are present in this region were likely significantly altered by these changes in land cover. Our results suggest that multi-temporal (i.e., multiple years and multiple seasons within years) Landsat data are an economical means to quantify land cover and land cover change across large and highly heterogeneous urbanizing landscapes. Our data, and similar temporal land cover change products, have been used in ecological modeling of past, present, and likely future changes in ecological systems (e.g., avian biodiversity, water quality). Such data are important inputs for ecological modelers, policy makers, and urban planners to manage and plan for future landscape change. Full article
(This article belongs to the Special Issue Ecological Status and Change by Remote Sensing)
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386 KiB  
Article
“Group Inversion Approach” for Detection of Soil Moisture Temporal-Invariant Locations
by Claudia Notarnicola
Remote Sens. 2009, 1(4), 1338-1352; https://doi.org/10.3390/rs1041338 - 21 Dec 2009
Viewed by 10861
Abstract
This paper presents an approach denominated Group Inversion Approach (GIA) which aims at detecting soil moisture temporal invariants, i.e., the stable temporal soil moisture locations, by using mainly remotely sensed data. The soil moisture temporal invariants are those locations where [...] Read more.
This paper presents an approach denominated Group Inversion Approach (GIA) which aims at detecting soil moisture temporal invariants, i.e., the stable temporal soil moisture locations, by using mainly remotely sensed data. The soil moisture temporal invariants are those locations where independently of the absolute value changes, the relative spatial distribution of soil moisture remains almost constant. In this procedure, the soil moisture values estimated from different inversion approaches and sensor configurations are compared among themselves and with the ground data. The procedure has been tested in a watershed of around 7,000 km2 with data collected during the SMEX’02 experiment in Iowa (USA). The results indicate that fields with inversion errors lower than five times the soil moisture variability detected with ground measurements represent well the mean watershed soil moisture values. The GIA technique has been also found in good agreement with the classical technique used to detect the stable soil moisture features, based exclusively on ground measurements. Full article
(This article belongs to the Special Issue Microwave Remote Sensing)
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739 KiB  
Article
Direct Georeferencing of Stationary LiDAR
by Ahmed Mohamed and Benjamin Wilkinson
Remote Sens. 2009, 1(4), 1321-1337; https://doi.org/10.3390/rs1041321 - 17 Dec 2009
Cited by 17 | Viewed by 16414
Abstract
Unlike mobile survey systems, stationary survey systems are given very little direct georeferencing attention. Direct Georeferencing is currently being used in several mobile applications, especially in terrestrial and airborne LiDAR systems. Georeferencing of stationary terrestrial LiDAR scanning data, however, is currently performed indirectly [...] Read more.
Unlike mobile survey systems, stationary survey systems are given very little direct georeferencing attention. Direct Georeferencing is currently being used in several mobile applications, especially in terrestrial and airborne LiDAR systems. Georeferencing of stationary terrestrial LiDAR scanning data, however, is currently performed indirectly through using control points in the scanning site. The indirect georeferencing procedure is often troublesome; the availability of control stations within the scanning range is not always possible. Also, field procedure can be laborious and involve extra equipment and target setups. In addition, the conventional method allows for possible human error due to target information bookkeeping. Additionally, the accuracy of this procedure varies according to the quality of the control used. By adding a dual GPS antenna apparatus to the scanner setup, thereby supplanting the use of multiple ground control points scattered throughout the scanning site, we mitigate not only the problems associated with indirect georeferencing but also induce a more efficient set up procedure while maintaining sufficient precision. In this paper, we describe a new method for determining the 3D absolute orientation of LiDAR point cloud using GPS measurements from two antennae firmly mounted on the optical head of a stationary LiDAR system. In this paper, the general case is derived where the orientation angles are not small; this case completes the theory of stationary LiDAR direct georeferencing. Simulation and real world field experimentation of the prototype implementation suggest a precision of about 0.05 degrees (~1 milli-radian) for the three orientation angles. Full article
(This article belongs to the Special Issue LiDAR)
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827 KiB  
Article
Measurement of Crown Cover and Leaf Area Index Using Digital Cover Photography and Its Application to Remote Sensing
by Burak Pekin and Craig Macfarlane
Remote Sens. 2009, 1(4), 1298-1320; https://doi.org/10.3390/rs1041298 - 15 Dec 2009
Cited by 74 | Viewed by 18200
Abstract
Digital cover photography (DCP) is a high resolution, vertical field-of-view method for ground-based estimation of forest metrics, and has advantages over fisheye sensors owing to its ease of application and high accuracy. We conducted the first thorough technical appraisal of DCP using both [...] Read more.
Digital cover photography (DCP) is a high resolution, vertical field-of-view method for ground-based estimation of forest metrics, and has advantages over fisheye sensors owing to its ease of application and high accuracy. We conducted the first thorough technical appraisal of DCP using both single-lens-reflex (DSLR) and point-and-shoot cameras and concluded that differences result primarily from the better quality optics available for the DSLR camera. File compression, image size and ISO equivalence had little or no effect on estimates of forest metrics. We discuss the application of DCP for ground truthing of remotely sensed canopy metrics, and highlight its strengths over fisheye photography for testing and calibration of vertical field-of-view remote sensing. Full article
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452 KiB  
Article
An Empirical Algorithm for Estimating Agricultural and Riparian Evapotranspiration Using MODIS Enhanced Vegetation Index and Ground Measurements of ET. I. Description of Method
by Pamela L. Nagler, Kiyomi Morino, R. Scott Murray, John Osterberg and Edward P. Glenn
Remote Sens. 2009, 1(4), 1273-1297; https://doi.org/10.3390/rs1041273 - 10 Dec 2009
Cited by 67 | Viewed by 13335
Abstract
We used the Enhanced Vegetation Index (EVI) from MODIS to scale evapotranspiration (ETactual) over agricultural and riparian areas along the Lower Colorado River in the southwestern US. Ground measurements of ETactual by alfalfa, saltcedar, cottonwood and arrowweed were expressed as [...] Read more.
We used the Enhanced Vegetation Index (EVI) from MODIS to scale evapotranspiration (ETactual) over agricultural and riparian areas along the Lower Colorado River in the southwestern US. Ground measurements of ETactual by alfalfa, saltcedar, cottonwood and arrowweed were expressed as fraction of potential (reference crop) ETo (EToF) then regressed against EVI scaled between bare soil (0) and full vegetation cover (1.0) (EVI*). EVI* values were calculated based on maximum and minimum EVI values from a large set of riparian values in a previous study. A satisfactory relationship was found between crop and riparian plant EToF and EVI*, with an error or uncertainty of about 20% in the mean estimate (mean ETactual = 6.2 mm d−1, RMSE = 1.2 mm d−1). The equation for ETactual was: ETactual = 1.22 × ETo-BC × EVI*, where ETo-BC is the Blaney Criddle formula for ETo. This single algorithm applies to all the vegetation types in the study, and offers an alternative to ETactual estimates that use crop coefficients set by expert opinion, by using an algorithm based on the actual state of the canopy as determined by time-series satellite images. Full article
(This article belongs to the Special Issue Global Croplands)
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593 KiB  
Article
Improving Landsat and IRS Image Classification: Evaluation of Unsupervised and Supervised Classification through Band Ratios and DEM in a Mountainous Landscape in Nepal
by Krishna Bahadur K.C.
Remote Sens. 2009, 1(4), 1257-1272; https://doi.org/10.3390/rs1041257 - 8 Dec 2009
Cited by 61 | Viewed by 18335
Abstract
Modification of the original bands and integration of ancillary data in digital image classification has been shown to improve land use land cover classification accuracy. There are not many studies demonstrating such techniques in the context of the mountains of Nepal. The objective [...] Read more.
Modification of the original bands and integration of ancillary data in digital image classification has been shown to improve land use land cover classification accuracy. There are not many studies demonstrating such techniques in the context of the mountains of Nepal. The objective of this study was to explore and evaluate the use of modified band and ancillary data in Landsat and IRS image classification, and to produce a land use land cover map of the Galaudu watershed of Nepal. Classification of land uses were explored using supervised and unsupervised classification for 12 feature sets containing the LandsatMSS, TM and IRS original bands, ratios, normalized difference vegetation index, principal components and a digital elevation model. Overall, the supervised classification method produced higher accuracy than the unsupervised approach. The result from the combination of bands ration 4/3, 5/4 and 5/7 ranked the highest in terms of accuracy (82.86%), while the combination of bands 2, 3 and 4 ranked the lowest (45.29%). Inclusion of DEM as a component band shows promising results. Full article
(This article belongs to the Special Issue Ecological Status and Change by Remote Sensing)
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833 KiB  
Article
Upliftment Estimation of the Zagros Transverse Fault in Iran Using Geoinformatics Technology
by Hojjat Ollah Safari, Saeid Pirasteh and Biswajeet Pradhan
Remote Sens. 2009, 1(4), 1240-1256; https://doi.org/10.3390/rs1041240 - 8 Dec 2009
Cited by 16 | Viewed by 13271
Abstract
The Izeh fault zone is a transverse fault zone with dextral strike slip (and some reverse component) in the Zagros Mountains (Iran). It causes some structural deformations. This fault zone is acting as eastern boundary of Dezful Embayment and forms subsidence of the [...] Read more.
The Izeh fault zone is a transverse fault zone with dextral strike slip (and some reverse component) in the Zagros Mountains (Iran). It causes some structural deformations. This fault zone is acting as eastern boundary of Dezful Embayment and forms subsidence of the embayment. The fault has been recognized using remote sensing techniques in conjunction with surface and subsurface analyses. The stratigraphic columns have been prepared in 3D form using Geographical Information System (GIS) tools on the basis of structural styles and thickness of lithologic units. Height differences for erosion levels have been calculated in stratigraphic columns with respect to the subsidence in the Dezful Embayment, which is related to Izeh zone. These height differences have been estimated to be 5,430 m in the central part (and 5,844 m in the northern part) from the Eocene to recent times. This study shows that comparison of the same erosion levels in Asmari-Pabdeh formation boundaries for interior and eastern block of the Izeh fault zone with the absolute uplifting due to the fault activity which is about 533 m per million years in the Izeh zone. The present study reveals that subtracting the absolute uplifting from total subsidence; the real subsidence of Dezful embayment from Eocene to Recent is 0.13 mm/year. The mean rate of uplifting along the Izeh fault zone is 0.015 mm/year. Full article
(This article belongs to the Special Issue Remote Sensing in Seismology)
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2645 KiB  
Review
Antarctic Ice Sheet and Radar Altimetry: A Review
by Frédérique Rémy and Soazig Parouty
Remote Sens. 2009, 1(4), 1212-1239; https://doi.org/10.3390/rs1041212 - 7 Dec 2009
Cited by 80 | Viewed by 16826
Abstract
Altimetry is probably one of the most powerful tools for ice sheet observation. Our vision of the Antarctic ice sheet has been deeply transformed since the launch of the ERS1 satellite in 1991. With the launch of ERS2 and Envisat, the series of [...] Read more.
Altimetry is probably one of the most powerful tools for ice sheet observation. Our vision of the Antarctic ice sheet has been deeply transformed since the launch of the ERS1 satellite in 1991. With the launch of ERS2 and Envisat, the series of altimetric observations now provides 19 years of continuous and homogeneous observations that allow monitoring of the shape and volume of ice sheets. The topography deduced from altimetry is one of the relevant parameters revealing the processes acting on ice sheet. Moreover, altimeter also provides other parameters such as backscatter and waveform shape that give information on the surface roughness or snow pack characteristics. Full article
(This article belongs to the Special Issue Microwave Remote Sensing)
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872 KiB  
Article
HF Radar Bistatic Measurement of Surface Current Velocities: Drifter Comparisons and Radar Consistency Checks
by Belinda Lipa, Chad Whelan, Bill Rector and Bruce Nyden
Remote Sens. 2009, 1(4), 1190-1211; https://doi.org/10.3390/rs1041190 - 1 Dec 2009
Cited by 28 | Viewed by 12844
Abstract
We describe the operation of a bistatic HF radar network and outline analysis methods for the derivation of the elliptical velocity components from the radar echo spectra. Bistatic operation is illustrated by application to a bistatic pair: Both remote systems receive backscattered echo, [...] Read more.
We describe the operation of a bistatic HF radar network and outline analysis methods for the derivation of the elliptical velocity components from the radar echo spectra. Bistatic operation is illustrated by application to a bistatic pair: Both remote systems receive backscattered echo, with one remote system in addition receiving bistatic echoes transmitted by the other. The pair produces elliptical velocity components in addition to two sets of radials. Results are compared with drifter measurements and checks performed on internal consistency in the radar results. We show that differences in drifter/radar current velocities are consistent with calculated radar data uncertainties. Elliptical and radial velocity components are demonstrated to be consistent within the data uncertainties. Inclusion of bistatic operation in radar networks can be expected to increase accuracy in derived current velocities and extend the coverage area. Full article
(This article belongs to the Special Issue Ocean Remote Sensing)
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857 KiB  
Article
A Class-Oriented Strategy for Features Extraction from Multidate ASTER Imagery
by Nicola Crocetto and Eufemia Tarantino
Remote Sens. 2009, 1(4), 1171-1189; https://doi.org/10.3390/rs1041171 - 30 Nov 2009
Cited by 28 | Viewed by 11702
Abstract
In this paper we propose a hybrid classification method, adopting the best features extraction strategy for each land cover class on multidate ASTER data. To enable an effective comparison among images, Multivariate Alteration Detection (MAD) transformation was applied in the pre-processing phase, because [...] Read more.
In this paper we propose a hybrid classification method, adopting the best features extraction strategy for each land cover class on multidate ASTER data. To enable an effective comparison among images, Multivariate Alteration Detection (MAD) transformation was applied in the pre-processing phase, because of its high level of automation and reliability in the enhancement of change information among different images. Consequently, different features identification procedures, both spectral and object-based, were implemented to overcome problems of misclassification among classes with similar spectral response. Lastly, a post-classification comparison was performed on multidate ASTER-derived land cover (LC) maps to evaluate the effects of change in the study area. Full article
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1422 KiB  
Article
Enhanced Automated Canopy Characterization from Hyperspectral Data by a Novel Two Step Radiative Transfer Model Inversion Approach
by Wouter Dorigo, Rudolf Richter, Frédéric Baret, Richard Bamler and Wolfgang Wagner
Remote Sens. 2009, 1(4), 1139-1170; https://doi.org/10.3390/rs1041139 - 27 Nov 2009
Cited by 57 | Viewed by 17816
Abstract
Automated, image based methods for the retrieval of vegetation biophysical and biochemical variables are often hampered by the lack of a priori knowledge about land cover and phenology, which makes the retrieval a highly underdetermined problem. This study addresses this problem by presenting [...] Read more.
Automated, image based methods for the retrieval of vegetation biophysical and biochemical variables are often hampered by the lack of a priori knowledge about land cover and phenology, which makes the retrieval a highly underdetermined problem. This study addresses this problem by presenting a novel approach, called CRASh, for the concurrent retrieval of leaf area index, leaf chlorophyll content, leaf water content and leaf dry matter content from high resolution solar reflective earth observation data. CRASh, which is based on the inversion of the combined PROSPECT+SAILh radiative transfer model (RTM), explores the benefits of combining semi-empirical and physically based approaches. The approach exploits novel ways to address the underdetermined problem in the context of an automated retrieval from mono-temporal high resolution data. To regularize the inverse problem in the variable domain, RTM inversion is coupled with an automated land cover classification. Model inversion is based on a two step lookup table (LUT) approach: First, a range of possible solutions is selected from a previously calculated LUT based on the analogy between measured and simulated reflectance. The final solution is determined from this subset by minimizing the difference between the variables used to simulate the spectra contained in the reduced LUT and a first guess of the solution. This first guess of the variables is derived from predictive semi-empirical relationships between classical vegetation indices and the single variables. Additional spectral regularization is obtained by the use of hyperspectral data. Results show that estimates obtained with CRASh are significantly more accurate than those obtained with a tested conventional RTM inversion and semi-empirical approach. Accuracies obtained in this study are comparable to the results obtained by various authors for better constrained inversions that assume more a priori information. The completely automated and image-based nature of the approach facilitates its use in operational chains for upcoming high resolution airborne and spaceborne imaging spectrometers. Full article
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470 KiB  
Article
An Empirical Algorithm for Estimating Agricultural and Riparian Evapotranspiration Using MODIS Enhanced Vegetation Index and Ground Measurements of ET. II. Application to the Lower Colorado River, U.S.
by R. Scott Murray, Pamela L. Nagler, Kiyomi Morino and Edward P. Glenn
Remote Sens. 2009, 1(4), 1125-1138; https://doi.org/10.3390/rs1041125 - 20 Nov 2009
Cited by 43 | Viewed by 13136
Abstract
Large quantities of water are consumed by irrigated crops and riparian vegetation in western U.S. irrigation districts. Remote sensing methods for estimating evaporative water losses by soil and vegetation (evapotranspiration, ET) over wide river stretches are needed to allocate water for agricultural and [...] Read more.
Large quantities of water are consumed by irrigated crops and riparian vegetation in western U.S. irrigation districts. Remote sensing methods for estimating evaporative water losses by soil and vegetation (evapotranspiration, ET) over wide river stretches are needed to allocate water for agricultural and environmental needs. We used the Enhanced Vegetation Index (EVI) from MODIS sensors on the Terra satellite to scale ET over agricultural and riparian areas along the Lower Colorado River in the southwestern U.S., using a linear regression equation between ET of riparian plants and alfalfa measured on the ground, and meteorological and remote sensing data, with an error or uncertainty of about 20%. The algorithm was applied to irrigation districts and riparian areas from Lake Mead to the U.S./Mexico border. The results for agricultural crops were similar to results produced by crop coefficients developed for the irrigation districts along the river. However, riparian ET was only half as great as crop coefficient estimates set by expert opinion, equal to about 40% of reference crop evapotranspiration. Based on reported acreages in 2007, agricultural crops (146,473 ha) consumed 2.2 × 109 m3 yr−1 of water. All riparian shrubs and trees (47,014 ha) consumed 3.8 × 108 m3 yr−1, of which saltcedar, the dominant riparian shrub (25,044 ha), consumed 1.8 × 108 m3 yr−1, about 1% of the annual flow of the river. This method could supplement existing protocols for estimating ET by providing an estimate based on the actual state of the canopy as determined by frequent-return satellite data. Full article
(This article belongs to the Special Issue Global Croplands)
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324 KiB  
Article
Evaluating the Effects of Environmental Changes on the Gross Primary Production of Italian Forests
by Fabio Maselli, Marco Moriondo, Marta Chiesi, Gherardo Chirici, Nicola Puletti, Anna Barbati and Piermaria Corona
Remote Sens. 2009, 1(4), 1108-1124; https://doi.org/10.3390/rs1041108 - 19 Nov 2009
Cited by 10 | Viewed by 14237
Abstract
A ten-year data-set descriptive of Italian forest gross primary production (GPP) has been recently constructed by the application of Modified C-Fix, a parametric model driven by remote sensing and ancillary data. That data-set is currently being used to develop multivariate regression models which [...] Read more.
A ten-year data-set descriptive of Italian forest gross primary production (GPP) has been recently constructed by the application of Modified C-Fix, a parametric model driven by remote sensing and ancillary data. That data-set is currently being used to develop multivariate regression models which link the inter-year GPP variations of five forest types (white fir, beech, chestnut, deciduous and evergreen oaks) to seasonal values of temperature and precipitation. The five models obtained, which explain from 52% to 88% of the inter-year GPP variability, are then applied to predict the effects of expected environmental changes (+2 °C and increased CO2 concentration). The results show a variable response of forest GPP to the simulated climate change, depending on the main ecosystem features. In contrast, the effects of increasing CO2 concentration are always positive and similar to those given by a combination of the two environmental factors. These findings are analyzed with reference to previous studies on the subject, particularly concerning Mediterranean environments. The analysis confirms the plausibility of the scenarios obtained, which can cast light on the important issue of forest carbon pool variations under expected global changes. Full article
(This article belongs to the Special Issue Ecological Status and Change by Remote Sensing)
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213 KiB  
Article
A Simple Method to Determine the Timing of Snow Melt by Remote Sensing with Application to the CO2 Balances of Northern Mire and Heath Ecosystems
by Janne Rinne, Mika Aurela and Terhikki Manninen
Remote Sens. 2009, 1(4), 1097-1107; https://doi.org/10.3390/rs1041097 - 19 Nov 2009
Cited by 8 | Viewed by 11389
Abstract
The timing of the disappearance of the snow cover in spring, or snow melt day (SMD), is a key parameter controlling the carbon dioxide balance between the northern mire and heath ecosystems and the atmosphere. We present a simple method for the determination [...] Read more.
The timing of the disappearance of the snow cover in spring, or snow melt day (SMD), is a key parameter controlling the carbon dioxide balance between the northern mire and heath ecosystems and the atmosphere. We present a simple method for the determination of the SMD using a satellite-based surface albedo product (SAL). The method is based on the local change of albedo from higher wintertime values towards the lower summertime values. The satellite SMD timing correlates well with the SMD determined from snow depth measurements at Finnish weather stations (r = 0.86, slope 1.05). In 50% of the cases the error was 3.4 days or less and bias less than half a day. This would lead to a moderate uncertainty in the annual CO2 balance of mire and heath ecosystems, if the published SMD—CO2 balance relations are valid. However, due to the limited data sets available a systematic validation is left for the future. Full article
(This article belongs to the Special Issue Ecological Status and Change by Remote Sensing)
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12663 KiB  
Article
Remote Sensing of Channels and Riparian Zones with a Narrow-Beam Aquatic-Terrestrial LIDAR
by Jim McKean, Dave Nagel, Daniele Tonina, Philip Bailey, Charles Wayne Wright, Carolyn Bohn and Amar Nayegandhi
Remote Sens. 2009, 1(4), 1065-1096; https://doi.org/10.3390/rs1041065 - 19 Nov 2009
Cited by 169 | Viewed by 17168
Abstract
The high-resolution Experimental Advanced Airborne Research LIDAR (EAARL) is a new technology for cross-environment surveys of channels and floodplains. EAARL measurements of basic channel geometry, such as wetted cross-sectional area, are within a few percent of those from control field surveys. The largest [...] Read more.
The high-resolution Experimental Advanced Airborne Research LIDAR (EAARL) is a new technology for cross-environment surveys of channels and floodplains. EAARL measurements of basic channel geometry, such as wetted cross-sectional area, are within a few percent of those from control field surveys. The largest channel mapping errors are along stream banks. The LIDAR data adequately support 1D and 2D computational fluid dynamics models and frequency domain analyses by wavelet transforms. Further work is needed to establish the stream monitoring capability of the EAARL and the range of water quality conditions in which this sensor will accurately map river bathymetry. Full article
(This article belongs to the Special Issue LiDAR)
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1755 KiB  
Communication
Investigating the Impacts of Landuse-landcover (LULC) Change in the Pearl River Delta Region on Water Quality in the Pearl River Estuary and Hong Kong’s Coast
by Yuanzhi Zhang, Yufei Wang, Yunpeng Wang and Hongyan Xi
Remote Sens. 2009, 1(4), 1055-1064; https://doi.org/10.3390/rs1041055 - 17 Nov 2009
Cited by 24 | Viewed by 14358
Abstract
Water quality information in the coastal region of Hong Kong and the Pearl River Estuary (PRE) is of great concern to the local community. Due to great landuse-landcover (LULC) changes with rapid industrialization and urbanization in the Pearl River Delta (PRD) region, water [...] Read more.
Water quality information in the coastal region of Hong Kong and the Pearl River Estuary (PRE) is of great concern to the local community. Due to great landuse-landcover (LULC) changes with rapid industrialization and urbanization in the Pearl River Delta (PRD) region, water quality in the PRE has worsened during the last 20 years. Frequent red tide and harmful algal blooms have occurred in the estuary and its adjacent coastal waters since the 1980s and have caused important economic losses, also possibly threatening to the coastal environment, fishery, and public health in Hong Kong. In addition, recent literature shows that water nutrients in Victoria Harbor of Hong Kong have been proven to be strongly influenced by both the Pearl River and sewage effluent in the wet season (May to September), but it is still unclear how the PRE diluted water intrudes into Victoria Harbor. Due to the cloudy and rainy conditions in the wet season in Hong Kong, ASAR images will be used to monitor the PRE river plumes and track the intruding routes of PRE water nutrients. In this paper, we first review LULC change in the PRD and then show our preliminary results to analyze water quality spatial and temporal information from remote observations with different sensors in the coastal region and estuary. The study will also emphasizes on time series of analysis of LULC trends related to annual sediment yields and critical source areas of erosion for the PRD region since the 1980s. Full article
(This article belongs to the Special Issue Ecological Status and Change by Remote Sensing)
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871 KiB  
Article
MODIS Hotspot Validation over Thailand
by Veerachai Tanpipat, Kiyoshi Honda and Prayoonyong Nuchaiya
Remote Sens. 2009, 1(4), 1043-1054; https://doi.org/10.3390/rs1041043 - 17 Nov 2009
Cited by 29 | Viewed by 18645
Abstract
To ensure remote sensing MODIS hotspot (also known as active fire products or hotspots) quality and precision in forest fire control and management in Thailand, an increased level of confidence is needed. Accuracy assessment of MODIS hotspots utilizing field survey data validation is [...] Read more.
To ensure remote sensing MODIS hotspot (also known as active fire products or hotspots) quality and precision in forest fire control and management in Thailand, an increased level of confidence is needed. Accuracy assessment of MODIS hotspots utilizing field survey data validation is described. A quantitative evaluation of MODIS hotspot products has been carried out since the 2007 forest fire season. The carefully chosen hotspots were scattered throughout the country and within the protected areas of the National Parks and Wildlife Sanctuaries. Three areas were selected as test sites for validation guidelines. Both ground and aerial field surveys were also conducted in this study by the Forest Fire Control Division, National Park, Wildlife and Plant Conversation Department, Ministry of Natural Resources and Environment, Thailand. High accuracy of 91.84 %, 95.60% and 97.53% for the 2007, 2008 and 2009 fire seasons were observed, resulting in increased confidence in the use of MODIS hotspots for forest fire control and management in Thailand. Full article
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412 KiB  
Article
Detection of Cypress Canopies in the Florida Panhandle Using Subpixel Analysis and GIS
by Jialing Wang and Paul A. Lang
Remote Sens. 2009, 1(4), 1028-1042; https://doi.org/10.3390/rs1041028 - 17 Nov 2009
Cited by 6 | Viewed by 12756
Abstract
In this study, multitemporal subpixel analysis was used to identify cypress canopies from Landsat 7 ETM+ imagery. One spring and one fall image were selected for each of two sites, an eastern one centered on Tallahassee, FL and a western one centered on [...] Read more.
In this study, multitemporal subpixel analysis was used to identify cypress canopies from Landsat 7 ETM+ imagery. One spring and one fall image were selected for each of two sites, an eastern one centered on Tallahassee, FL and a western one centered on Panama City, FL. Signatures derived from the two eastern images were applied on the two western images that served as the control images for accuracy assessment. Results indicated that multitemporal subpixel analysis greatly improved the classification accuracy and signatures developed from one scene could be used to the subpixel classification of another scene with caution. Full article
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814 KiB  
Article
Assessing the Impact of Canopy Structure Simplification in Common Multilayer Models on Irradiance Absorption Estimates of Measured and Virtually Created Fagus sylvatica (L.) Stands
by Dimitrios Biliouris, Dimitry Van der Zande, Willem W. Verstraeten, Bart Muys and Pol Coppin
Remote Sens. 2009, 1(4), 1009-1027; https://doi.org/10.3390/rs1041009 - 16 Nov 2009
Cited by 7 | Viewed by 12829
Abstract
Multilayer canopy representations are the most common structural stand representations due to their simplicity. Implementation of recent advances in technology has allowed scientists to simulate geometrically explicit forest canopies. The effect of simplified representations of tree architecture (i.e., multilayer representations) of [...] Read more.
Multilayer canopy representations are the most common structural stand representations due to their simplicity. Implementation of recent advances in technology has allowed scientists to simulate geometrically explicit forest canopies. The effect of simplified representations of tree architecture (i.e., multilayer representations) of four Fagus sylvatica (L.) stands, each with different LAI, on the light absorption estimates was assessed in comparison with explicit 3D geometrical stands. The absorbed photosynthetic radiation at stand level was calculated. Subsequently, each geometrically explicit 3D stand was compared with three multilayer models representing horizontal, uniform, and planophile leaf angle distributions. The 3D stands were created either by in situ measured trees or by modelled trees generated with the AMAP plant growth software. The Physically Based Ray Tracer (PBRT) algorithm was used to simulate the irradiance absorbance of the detailed 3D architecture stands, while for the three multilayer representations, the probability of light interception was simulated by applying the Beer-Lambert’s law. The irradiance inside the canopies was characterized as direct, diffuse and scattered irradiance. The irradiance absorbance of the stands was computed during eight angular sun configurations ranging from 10° (near nadir) up to 80° sun zenith angles. Furthermore, a leaf stratification (the number and angular distribution of leaves per LAI layer inside a canopy) analysis between the 3D stands and the multilayer representations was performed, indicating the amount of irradiance each leaf is absorbing along with the percentage of sunny and shadow leaves inside the canopy. The results reveal that a multilayer representation of a stand, using a multilayer modelling approach, greatly overestimated the absorbed irradiance in an open canopy, while it provided a better approximation in the case of a closed canopy. Moreover, the actual stratification of leaves differed significantly between a multilayer representation and a 3D architecture canopy of the same LAI. The deviations in irradiance absorbance were caused by canopy structure, clumping and positioning of leaves. Although it was found that the use of canopy simplifications for modelling purposes in closed canopies is demonstrated as a valid option, special care should be taken when considering forest stands irradiance simulation for sparse canopies and particularly on higher sun zenith angles where the surrounding trees strongly affect the absorbed irradiance and results can highly deviate from the multilayer assumptions. Full article
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1231 KiB  
Article
Estimating Flow Resistance of Wetlands Using SAR Images and Interaction Models
by Mercedes Salvia, Mariano Franco, Francisco Grings, Pablo Perna, Roman Martino, Haydee Karszenbaum and Paolo Ferrazzoli
Remote Sens. 2009, 1(4), 992-1008; https://doi.org/10.3390/rs1040992 - 13 Nov 2009
Cited by 13 | Viewed by 12395
Abstract
The inability to monitor wetland drag coefficients at a regional scale is rooted in the difficulty to determine vegetation structure from remote sensing data. Based on the fact that the backscattering coefficient is sensitive to marsh vegetation structure, this paper presents a methodology [...] Read more.
The inability to monitor wetland drag coefficients at a regional scale is rooted in the difficulty to determine vegetation structure from remote sensing data. Based on the fact that the backscattering coefficient is sensitive to marsh vegetation structure, this paper presents a methodology to estimate the drag coefficient from a combination of SAR images, interaction models and ancillary data. We use as test case a severe fire event occurred in the Paraná River Delta (Argentina) at the beginning of 2008, when 10% of the herbaceous vegetation was burned up. A map of the reduction of the wetland drag coefficient is presented. Full article
(This article belongs to the Special Issue Microwave Remote Sensing)
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1349 KiB  
Article
An Improved ASTER Index for Remote Sensing of Crop Residue
by Guy Serbin, E. Raymond Hunt, Jr., Craig S. T. Daughtry, Gregory W. McCarty and Paul C. Doraiswamy
Remote Sens. 2009, 1(4), 971-991; https://doi.org/10.3390/rs1040971 - 11 Nov 2009
Cited by 103 | Viewed by 16429
Abstract
Unlike traditional ground-based methodology, remote sensing allows for the rapid estimation of crop residue cover (fR). While the Cellulose Absorption Index (CAI) is ideal for fR estimation, a new index, the Shortwave Infrared Normalized Difference Residue Index (SINDRI), utilizing [...] Read more.
Unlike traditional ground-based methodology, remote sensing allows for the rapid estimation of crop residue cover (fR). While the Cellulose Absorption Index (CAI) is ideal for fR estimation, a new index, the Shortwave Infrared Normalized Difference Residue Index (SINDRI), utilizing ASTER bands 6 and 7, is proposed for future multispectral sensors and would be less costly to implement. SINDRI performed almost as well as CAI and better than other indices at five locations in the USA on multiple dates. A minimal upgrade from one broad band to two narrow bands would provide fR data for carbon cycle modeling and tillage verification. Full article
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1218 KiB  
Article
Analysis of Land Use/Cover Changes and Animal Population Dynamics in a Wildlife Sanctuary in East Africa
by Charles Ndegwa Mundia and Yuji Murayama
Remote Sens. 2009, 1(4), 952-970; https://doi.org/10.3390/rs1040952 - 11 Nov 2009
Cited by 33 | Viewed by 19275
Abstract
Changes in wildlife conservation areas have serious implications for ecological systems and the distribution of wildlife species. Using the Masai Mara ecosystem as an example, we analyzed long-term land use/cover changes and wildlife population dynamics. Multitemporal satellite images, together with physical and social [...] Read more.
Changes in wildlife conservation areas have serious implications for ecological systems and the distribution of wildlife species. Using the Masai Mara ecosystem as an example, we analyzed long-term land use/cover changes and wildlife population dynamics. Multitemporal satellite images, together with physical and social economic data were employed in a post classification analysis with GIS to analyze outcomes of different land use practices and policies. The results show rapid land use/cover conversions and a drastic decline for a wide range of wildlife species. Integration of land use/cover monitoring data and wildlife resources data can allow for the analysis of changes, and can be used to project trends to provide knowledge about potential land use/cover change scenarios and ecological impacts. Full article
(This article belongs to the Special Issue Ecological Status and Change by Remote Sensing)
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131 KiB  
Review
LiDAR Utility for Natural Resource Managers
by Andrew Thomas Hudak, Jeffrey Scott Evans and Alistair Matthew Stuart Smith
Remote Sens. 2009, 1(4), 934-951; https://doi.org/10.3390/rs1040934 - 11 Nov 2009
Cited by 141 | Viewed by 18719
Abstract
Applications of LiDAR remote sensing are exploding, while moving from the research to the operational realm. Increasingly, natural resource managers are recognizing the tremendous utility of LiDAR-derived information to make improved decisions. This review provides a cross-section of studies, many recent, that demonstrate [...] Read more.
Applications of LiDAR remote sensing are exploding, while moving from the research to the operational realm. Increasingly, natural resource managers are recognizing the tremendous utility of LiDAR-derived information to make improved decisions. This review provides a cross-section of studies, many recent, that demonstrate the relevance of LiDAR across a suite of terrestrial natural resource disciplines including forestry, fire and fuels, ecology, wildlife, geology, geomorphology, and surface hydrology. We anticipate that interest in and reliance upon LiDAR for natural resource management, both alone and in concert with other remote sensing data, will continue to rapidly expand for the foreseeable future. Full article
(This article belongs to the Special Issue LiDAR)
802 KiB  
Article
Remote Sensing and Spectral Characteristics of Desert Sand from Qatar Peninsula, Arabian/Persian Gulf
by Abdulali Sadiq and Fares Howari
Remote Sens. 2009, 1(4), 915-933; https://doi.org/10.3390/rs1040915 - 11 Nov 2009
Cited by 18 | Viewed by 16675
Abstract
Remote sensing data can provide valuable information about the surface expression of regional geomorphologic and geological features of arid regions. In the present study, several processing techniques were applied to reveal such in the Qatar Peninsula. Those included preprocessing for radiometric and geometric [...] Read more.
Remote sensing data can provide valuable information about the surface expression of regional geomorphologic and geological features of arid regions. In the present study, several processing techniques were applied to reveal such in the Qatar Peninsula. Those included preprocessing for radiometric and geometric correction, various enhancement methods, classification, accuracy assessment, contrast stretching, color composition, and principal component analyses. Those were coupled with field groundtruthing and lab analyses. Field groundtruthing included one hundred and forty measurements of spectral reflectance for various sediment exposures representing main sand types in the four studied parts in Qatar. Lab investigations included grain size analysis, X-ray diffraction and laboratory measurements of spectral reflectance. During the course of this study three sand types have been identified: (i) sabkha-derived salt-rich, quartz sand, and (ii) beach-derived calcareous sand and (iii) aeolian dune quartz. Those areas are spectrally distinct in the VNIR, suggesting that VNIR spectral data can be used to discriminate them. The study found that the main limitation of the ground spectral reflectance study is the difficulty of covering large areas. The study also found that ground and laboratory spectral radiance are generally higher in reflectance than those of Landsat TM. This is due to several factors such as atmospheric conditions, the low altitude or different scales. Whereas for areas with huge size of dune sand, the Landsat TM spectral has higher reflectance than those from field and laboratory. The study observed that there is a good correspondence or correlation of the wavelengths maximum sensitivity between the three spectral measurements i.e lab, field and space-borne measurements. Full article
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970 KiB  
Article
Regional Assessment of Aspen Change and Spatial Variability on Decadal Time Scales
by Temuulen Tsagaan Sankey
Remote Sens. 2009, 1(4), 896-914; https://doi.org/10.3390/rs1040896 - 10 Nov 2009
Cited by 11 | Viewed by 11793
Abstract
Quaking aspen (Populus tremuloides) is commonly believed to be declining throughout western North America. Using a historical vegetation map and Landsat TM5 imagery, this study detects changes in regional aspen cover over two different time periods of 85 and 18 years [...] Read more.
Quaking aspen (Populus tremuloides) is commonly believed to be declining throughout western North America. Using a historical vegetation map and Landsat TM5 imagery, this study detects changes in regional aspen cover over two different time periods of 85 and 18 years and examines aspen change patterns with biophysical variables in the Targhee National Forest of eastern Idaho, USA. A subpixel classification approach was successfully used to classify aspen. The results indicate greater spatial variability in regional aspen change patterns than indicated by local-scale studies. The observed spatial variability appears to be an inherent pattern in regional aspen dynamics, which interacts with biophysical variables, but persists over time. Full article
(This article belongs to the Special Issue Ecological Status and Change by Remote Sensing)
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1570 KiB  
Article
Supervised Classification of Agricultural Land Cover Using a Modified k-NN Technique (MNN) and Landsat Remote Sensing Imagery
by Luis Samaniego and Karsten Schulz
Remote Sens. 2009, 1(4), 875-895; https://doi.org/10.3390/rs1040875 - 9 Nov 2009
Cited by 48 | Viewed by 16975
Abstract
Nearest neighbor techniques are commonly used in remote sensing, pattern recognition and statistics to classify objects into a predefined number of categories based on a given set of predictors. These techniques are especially useful for highly nonlinear relationship between the variables. In most [...] Read more.
Nearest neighbor techniques are commonly used in remote sensing, pattern recognition and statistics to classify objects into a predefined number of categories based on a given set of predictors. These techniques are especially useful for highly nonlinear relationship between the variables. In most studies the distance measure is adopted a priori. In contrast we propose a general procedure to find an adaptive metric that combines a local variance reducing technique and a linear embedding of the observation space into an appropriate Euclidean space. To illustrate the application of this technique, two agricultural land cover classifications using mono-temporal and multi-temporal Landsat scenes are presented. The results of the study, compared with standard approaches used in remote sensing such as maximum likelihood (ML) or k-Nearest Neighbor (k-NN) indicate substantial improvement with regard to the overall accuracy and the cardinality of the calibration data set. Also, using MNN in a soft/fuzzy classification framework demonstrated to be a very useful tool in order to derive critical areas that need some further attention and investment concerning additional calibration data. Full article
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555 KiB  
Article
Hyperspectral Reflectance and Fluorescence Imaging to Detect Scab Induced Stress in Apple Leaves
by Stephanie Delalieux, Annemarie Auwerkerken, Willem W. Verstraeten, Ben Somers, Roland Valcke, Stefaan Lhermitte, Johan Keulemans and Pol Coppin
Remote Sens. 2009, 1(4), 858-874; https://doi.org/10.3390/rs1040858 - 6 Nov 2009
Cited by 64 | Viewed by 15372
Abstract
Apple scab causes significant losses in the production of this fruit. A timely and more site-specific monitoring and spraying of the disease could reduce the number of applications of fungicides in the fruit industry. The aim of this leaf-scale study therefore lies in [...] Read more.
Apple scab causes significant losses in the production of this fruit. A timely and more site-specific monitoring and spraying of the disease could reduce the number of applications of fungicides in the fruit industry. The aim of this leaf-scale study therefore lies in the early detection of apple scab infections in a non-invasive and non-destructive way. In order to attain this objective, fluorescence- and hyperspectral imaging techniques were used. An experiment was conducted under controlled environmental conditions, linking hyperspectral reflectance and fluorescence imaging measurements to scab infection symptoms in a susceptible apple cultivar (Malus x domestica Borkh. cv. Braeburn). Plant stress was induced by inoculation of the apple plants with scab spores. The quantum efficiency of Photosystem II (PSII) photochemistry was derived from fluorescence images of leaves under light adapted conditions. Leaves inoculated with scab spores were expected to have lower PSII quantum efficiency than control (mock) leaves. However, besides scab-induced, also immature leaves exhibited low PSII quantum efficiency. Therefore, this study recommends the simultaneous use of fluorescence imaging and hyperspectral techniques. A shortwave infrared narrow-waveband ratio index (R1480/R2135) is presented in this paper as a promising tool to identify scab stress before symptoms become visible to the naked eye. Low PSII quantum efficiency attended by low narrow waveband R1480/R2135 index values points out scab stress in an early stage. Apparent high PSII quantum efficiency together with high overall reflectance in VIS and SWIR spectral domains indicate a severe, well-developed scab infection. Full article
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207 KiB  
Article
Derivation of Soil Line Influence on Two-Band Vegetation Indices and Vegetation Isolines
by Hiroki Yoshioka, Tomoaki Miura, José A. M. Demattê, Karim Batchily and Alfredo R. Huete
Remote Sens. 2009, 1(4), 842-857; https://doi.org/10.3390/rs1040842 - 3 Nov 2009
Cited by 14 | Viewed by 12807
Abstract
This paper introduces derivations of soil line influences on two-band vegetation indices (VIs) and vegetation isolines in the red and near infra-red reflectance space. Soil line variations are described as changes in the soil line parameters (slope and offset) and the red reflectance [...] Read more.
This paper introduces derivations of soil line influences on two-band vegetation indices (VIs) and vegetation isolines in the red and near infra-red reflectance space. Soil line variations are described as changes in the soil line parameters (slope and offset) and the red reflectance of the soil surface. A general form of a VI model equation written as a ratio of two linear functions (e.g., NDVI and SAVI) was assumed. It was found that relative VI variations can be approximated by a linear combination of the three soil parameters. The derived expressions imply the possibility of estimating and correcting for soil-induced bias errors in VIs and their derived biophysical parameters, caused by the assumption of a general soil line, through the use of external data sources such as regional soil maps. Full article
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563 KiB  
Article
Photogrammetric Methodology for the Production of Geomorphologic Maps: Application to the Veleta Rock Glacier (Sierra Nevada, Granada, Spain)
by Javier De Matías, José Juan De Sanjosé, Gonzalo López-Nicolás, Carlos Sagüés and José Jesús Guerrero
Remote Sens. 2009, 1(4), 829-841; https://doi.org/10.3390/rs1040829 - 28 Oct 2009
Cited by 19 | Viewed by 13219
Abstract
In this paper we present a stereo feature-based method using SIFT (Scale-invariant feature transform) descriptors. We use automatic feature extractors, matching algorithms between images and techniques of robust estimation to produce a DTM (Digital Terrain Model) using convergent shots of a rock glacier.The [...] Read more.
In this paper we present a stereo feature-based method using SIFT (Scale-invariant feature transform) descriptors. We use automatic feature extractors, matching algorithms between images and techniques of robust estimation to produce a DTM (Digital Terrain Model) using convergent shots of a rock glacier.The geomorphologic structure observed in this study is the Veleta rock glacier (Sierra Nevada, Granada, Spain). This rock glacier is of high scientific interest because it is the southernmost active rock glacier in Europe and it has been analyzed every year since 2001. The research on the Veleta rock glacier is devoted to the study of its displacement and cartography through geodetic and photogrammetric techniques. Full article
(This article belongs to the Special Issue Geomorphological Processes and Natural Hazards)
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