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

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Open AccessArticle Leaf Area Index (LAI) Estimation of Boreal Forest Using Wide Optics Airborne Winter Photos
Remote Sens. 2009, 1(4), 1380-1394; https://doi.org/10.3390/rs1041380
Received: 11 November 2009 / Revised: 10 December 2009 / Accepted: 14 December 2009 / Published: 22 December 2009
Cited by 15 | PDF Full-text (1170 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle Using Urban Landscape Trajectories to Develop a Multi-Temporal Land Cover Database to Support Ecological Modeling
Remote Sens. 2009, 1(4), 1353-1379; https://doi.org/10.3390/rs1041353
Received: 27 October 2009 / Revised: 14 December 2009 / Accepted: 14 December 2009 / Published: 22 December 2009
Cited by 8 | PDF Full-text (1249 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle “Group Inversion Approach” for Detection of Soil Moisture Temporal-Invariant Locations
Remote Sens. 2009, 1(4), 1338-1352; https://doi.org/10.3390/rs1041338
Received: 26 October 2009 / Revised: 9 December 2009 / Accepted: 14 December 2009 / Published: 21 December 2009
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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
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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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Open AccessArticle Direct Georeferencing of Stationary LiDAR
Remote Sens. 2009, 1(4), 1321-1337; https://doi.org/10.3390/rs1041321
Received: 18 October 2009 / Revised: 24 November 2009 / Accepted: 8 December 2009 / Published: 17 December 2009
Cited by 10 | PDF Full-text (739 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle Measurement of Crown Cover and Leaf Area Index Using Digital Cover Photography and Its Application to Remote Sensing
Remote Sens. 2009, 1(4), 1298-1320; https://doi.org/10.3390/rs1041298
Received: 14 October 2009 / Revised: 27 November 2009 / Accepted: 14 December 2009 / Published: 15 December 2009
Cited by 39 | PDF Full-text (827 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle An Empirical Algorithm for Estimating Agricultural and Riparian Evapotranspiration Using MODIS Enhanced Vegetation Index and Ground Measurements of ET. I. Description of Method
Remote Sens. 2009, 1(4), 1273-1297; https://doi.org/10.3390/rs1041273
Received: 13 October 2009 / Revised: 19 November 2009 / Accepted: 3 December 2009 / Published: 10 December 2009
Cited by 31 | PDF Full-text (452 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle Improving Landsat and IRS Image Classification: Evaluation of Unsupervised and Supervised Classification through Band Ratios and DEM in a Mountainous Landscape in Nepal
Remote Sens. 2009, 1(4), 1257-1272; https://doi.org/10.3390/rs1041257
Received: 21 October 2009 / Revised: 23 November 2009 / Accepted: 2 December 2009 / Published: 8 December 2009
Cited by 21 | PDF Full-text (593 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle Upliftment Estimation of the Zagros Transverse Fault in Iran Using Geoinformatics Technology
Remote Sens. 2009, 1(4), 1240-1256; https://doi.org/10.3390/rs1041240
Received: 22 October 2009 / Revised: 25 November 2009 / Accepted: 30 November 2009 / Published: 8 December 2009
Cited by 9 | PDF Full-text (833 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessReview Antarctic Ice Sheet and Radar Altimetry: A Review
Remote Sens. 2009, 1(4), 1212-1239; https://doi.org/10.3390/rs1041212
Received: 12 October 2009 / Revised: 13 November 2009 / Accepted: 28 November 2009 / Published: 7 December 2009
Cited by 32 | PDF Full-text (2645 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle HF Radar Bistatic Measurement of Surface Current Velocities: Drifter Comparisons and Radar Consistency Checks
Remote Sens. 2009, 1(4), 1190-1211; https://doi.org/10.3390/rs1041190
Received: 26 October 2009 / Revised: 5 November 2009 / Accepted: 27 November 2009 / Published: 1 December 2009
Cited by 14 | PDF Full-text (872 KB) | HTML Full-text | XML Full-text
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,
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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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Open AccessArticle A Class-Oriented Strategy for Features Extraction from Multidate ASTER Imagery
Remote Sens. 2009, 1(4), 1171-1189; https://doi.org/10.3390/rs1041171
Received: 23 October 2009 / Revised: 20 November 2009 / Accepted: 26 November 2009 / Published: 30 November 2009
Cited by 9 | PDF Full-text (857 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle Enhanced Automated Canopy Characterization from Hyperspectral Data by a Novel Two Step Radiative Transfer Model Inversion Approach
Remote Sens. 2009, 1(4), 1139-1170; https://doi.org/10.3390/rs1041139
Received: 10 September 2009 / Revised: 2 November 2009 / Accepted: 23 November 2009 / Published: 27 November 2009
Cited by 35 | PDF Full-text (1422 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle 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.
Remote Sens. 2009, 1(4), 1125-1138; https://doi.org/10.3390/rs1041125
Received: 3 September 2009 / Revised: 30 October 2009 / Accepted: 19 November 2009 / Published: 20 November 2009
Cited by 27 | PDF Full-text (470 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle Evaluating the Effects of Environmental Changes on the Gross Primary Production of Italian Forests
Remote Sens. 2009, 1(4), 1108-1124; https://doi.org/10.3390/rs1041108
Received: 15 October 2009 / Revised: 6 November 2009 / Accepted: 16 November 2009 / Published: 19 November 2009
Cited by 7 | PDF Full-text (324 KB) | HTML Full-text | XML Full-text
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
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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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Open AccessArticle 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
Remote Sens. 2009, 1(4), 1097-1107; https://doi.org/10.3390/rs1041097
Received: 16 September 2009 / Revised: 9 November 2009 / Accepted: 16 November 2009 / Published: 19 November 2009
Cited by 3 | PDF Full-text (213 KB) | HTML Full-text | XML Full-text
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
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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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