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Remote Sens., Volume 3, Issue 2 (February 2011), Pages 203-415

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Open AccessArticle Environmental Drivers of NDVI-Based Vegetation Phenology in Central Asia
Remote Sens. 2011, 3(2), 203-246; doi:10.3390/rs3020203
Received: 16 November 2010 / Revised: 7 December 2010 / Accepted: 19 January 2011 / Published: 1 February 2011
Cited by 26 | PDF Full-text (3911 KB) | HTML Full-text | XML Full-text
Abstract
Through the application and use of geospatial data, this study aimed to detect and characterize some of the key environmental drivers contributing to landscape-scale vegetation response patterns in Central Asia. The objectives of the study were to identify the variables driving the [...] Read more.
Through the application and use of geospatial data, this study aimed to detect and characterize some of the key environmental drivers contributing to landscape-scale vegetation response patterns in Central Asia. The objectives of the study were to identify the variables driving the year-to-year vegetation dynamics in three regional landscapes (desert, steppe, and mountainous); and to determine if the identified environmental drivers can be used to explain the spatial-temporal variability of these spatio-temporal dynamics over time. It was posed that patterns of change in terrestrial phenology, derived from the 8 km bi-weekly time series of Normalized Difference Vegetation Index (NDVI) data acquired by the Advanced Very High Resolution Radiometer (AVHRR) satellites (1981–2008), can be explained through a multi-scale analysis of a suite of environmental drivers. Multiple linear stepwise regression analyses were used to test the hypotheses and address the objectives of the study. The annually computed phenological response variables or pheno-metricstime (season start, season length, and an NDVI-based productivity metric) were modeled as a function of ten environmental factors relating to soil, topography, and climate. Each of the three studied regional landscapes was shown to be governed by a distinctive suite of environmental drivers. The phenological responses of the steppe landscapes were affected by the year-to-year variation in temperature regimes. The phenology of the mountainous landscapes was influenced primarily by the elevation gradient. The phenological responses of desert landscapes were demonstrated to have the greatest variability over time and seemed to be affected by soil carbon content and year-to-year variation of both temperature regimes and winter precipitation patterns. Amounts and scales of observed phenological variability over time (measured through coefficient of variation for each pheno-metrictime) in each of the regional landscapes were interpreted in terms of their resistance and resilience capacities under existing and projected environmental settings. Full article
(This article belongs to the Special Issue Remote Sensing in Climate Monitoring and Analysis)
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Open AccessArticle An Assessment of the Accuracy of Volunteered Road Map Production in Western Kenya
Remote Sens. 2011, 3(2), 247-256; doi:10.3390/rs3020247
Received: 29 November 2010 / Revised: 31 January 2011 / Accepted: 2 February 2011 / Published: 9 February 2011
Cited by 13 | PDF Full-text (468 KB) | HTML Full-text | XML Full-text
Abstract
The introduction of web based mapping facilities that use satellite imagery, offers local people the possibility to map their environment. However, maps need to be accurate, which is the reason why map making is assigned to professionals. In this paper, we investigated [...] Read more.
The introduction of web based mapping facilities that use satellite imagery, offers local people the possibility to map their environment. However, maps need to be accurate, which is the reason why map making is assigned to professionals. In this paper, we investigated the classification accuracy of road infrastructure from high resolution satellite imagery of an urban area in western Kenya achieved by surveyors and non-surveyors alike, with and without local knowledge. Those with local knowledge classified roads with over 92% accuracy on average, irrespective of surveying background. Professional surveyors and laymen without local knowledge achieved lower accuracies of 67.7% and 42.9% respectively. We argue that local knowledge is also likely to improve the classification accuracy of many other attributes featured in topographic maps and thus conclude that there is reason to consider engaging local expertise in the production and updating of topographic maps. Full article
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Open AccessArticle Global Characterization of CO2 Column Retrievals from Shortwave-Infrared Satellite Observations of the Orbiting Carbon Observatory-2 Mission
Remote Sens. 2011, 3(2), 270-304; doi:10.3390/rs3020270
Received: 7 December 2010 / Revised: 8 February 2011 / Accepted: 9 February 2011 / Published: 14 February 2011
Cited by 69 | PDF Full-text (1753 KB) | HTML Full-text | XML Full-text
Abstract
The global characteristics of retrievals of the column-averaged CO2 dry air mole fraction, XCO2, from shortwave infrared observations has been studied using the expected measurement performance of the NASA Orbiting Carbon Observatory-2 (OCO-2) mission. This study focuses on X [...] Read more.
The global characteristics of retrievals of the column-averaged CO2 dry air mole fraction, XCO2, from shortwave infrared observations has been studied using the expected measurement performance of the NASA Orbiting Carbon Observatory-2 (OCO-2) mission. This study focuses on XCO2 retrieval precision and averaging kernels and their sensitivity to key parameters such as solar zenith angle (SZA), surface pressure, surface type and aerosol optical depth (AOD), for both nadir and sunglint observing modes. Realistic simulations have been carried out and the single sounding retrieval errors for XCO2 have been derived from the formal retrieval error covariance matrix under the assumption that the retrieval has converged to the correct answer and that the forward model can adequately describe the measurement. Thus, the retrieval errors presented in this study represent an estimate of the retrieval precision. For nadir observations, we find single-sounding retrieval errors with values typically less than 1 part per million (ppm) over most land surfaces for SZAs less than 70° and up to 2.5 ppm for larger SZAs. Larger errors are found over snow/ice and ocean surfaces due to their low albedo in the spectral regions of the CO2 absorption bands and, for ocean, also in the O2 A band. For sunglint observations, errors over the ocean are significantly smaller than in nadir mode with values in the range of 0.3 to 0.6 ppm for small SZAs which can decrease to values as small as 0.15 for the largest SZAs. The vertical sensitivity of the retrieval that is represented by the column averaging kernel peaks near the surface and exhibits values near unity throughout most of the troposphere for most anticipated scenes. Nadir observations over dark ocean or snow/ice surfaces and observations with large AOD and large SZA show a decreased sensitivity to near-surface CO2. All simulations are carried out for a mid-latitude summer atmospheric profile, a given aerosol type and vertical distribution, a constant windspeed for ocean sunglint and by excluding the presence of thin cirrus clouds. The impact of these parameters on averaging kernels and XCO2 retrieval errors are studied with sensitivity studies. Systematic biases in retrieved XCO2, as can be introduced by uncertainties in the spectroscopic parameters, instrument calibration or deficiencies in the retrieval algorithm itself, are not included in this study. The presented error estimates will therefore only describe the true retrieval errors once systematic biases are eliminated. It is expected that it will be possible to retrieve XCO2 for cloud free observations and for low AOD (here less than 0.3 for the wavelength region of the O2 A band) with sufficient accuracy for improving CO2 surface flux estimates and we find that on average 18% to 21% of all observations are sufficiently cloud-free with only few areas suffering from the presence of persistent clouds or high AOD. This results typically in tens of useful observations per 16 day ground track repeat cycle at a 1° × 1° resolution. Averaging observations acquired along ~1° intervals for individual ground tracks will significantly reduce the random component of the errors of the XCO2 average product for ingestion into data assimilation/inverse models. If biases in the XCO2 retrieval of the order of a few tenth ppm can be successfully removed by validation or by bias-correction in the flux inversion, then it can be expected that OCO-2 XCO2 data can lead to tremendous improvements in estimates of CO2 surface-atmosphere fluxes. Full article
(This article belongs to the Special Issue Atmospheric Remote Sensing)
Open AccessArticle Spaceborne Differential SAR Interferometry: Data Analysis Tools for Deformation Measurement
Remote Sens. 2011, 3(2), 305-318; doi:10.3390/rs3020305
Received: 30 November 2010 / Revised: 13 January 2011 / Accepted: 10 February 2011 / Published: 15 February 2011
Cited by 22 | PDF Full-text (2146 KB) | HTML Full-text | XML Full-text
Abstract
This paper is focused on spaceborne Differential Interferometric SAR (DInSAR) for land deformation measurement and monitoring. In the last two decades several DInSAR data analysis procedures have been proposed. The objective of this paper is to describe the DInSAR data processing and [...] Read more.
This paper is focused on spaceborne Differential Interferometric SAR (DInSAR) for land deformation measurement and monitoring. In the last two decades several DInSAR data analysis procedures have been proposed. The objective of this paper is to describe the DInSAR data processing and analysis tools developed at the Institute of Geomatics in almost ten years of research activities. Four main DInSAR analysis procedures are described, which range from the standard DInSAR analysis based on a single interferogram to more advanced Persistent Scatterer Interferometry (PSI) approaches. These different procedures guarantee a sufficient flexibility in DInSAR data processing. In order to provide a technical insight into these analysis procedures, a whole section discusses their main data processing and analysis steps, especially those needed in PSI analyses. A specific section is devoted to the core of our PSI analysis tools: the so-called 2+1D phase unwrapping procedure, which couples a 2D phase unwrapping, performed interferogram-wise, with a kind of 1D phase unwrapping along time, performed pixel-wise. In the last part of the paper, some examples of DInSAR results are discussed, which were derived by standard DInSAR or PSI analyses. Most of these results were derived from X-band SAR data coming from the TerraSAR-X and CosmoSkyMed sensors. Full article
(This article belongs to the Special Issue 100 Years ISPRS - Advancing Remote Sensing Science)
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Open AccessArticle Object-Based Image Analysis for Detection of Japanese Knotweed s.l. taxa (Polygonaceae) in Wales (UK)
Remote Sens. 2011, 3(2), 319-342; doi:10.3390/rs3020319
Received: 23 December 2010 / Revised: 10 February 2011 / Accepted: 12 February 2011 / Published: 16 February 2011
Cited by 13 | PDF Full-text (2271 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
Japanese Knotweed s.l. taxa are amongst the most aggressive vascular plant Invasive Alien Species (IAS) in the world. These taxa form dense, suppressive monocultures and are persistent, pervasive invaders throughout the more economically developed countries (MEDCs) of the world. The current paper [...] Read more.
Japanese Knotweed s.l. taxa are amongst the most aggressive vascular plant Invasive Alien Species (IAS) in the world. These taxa form dense, suppressive monocultures and are persistent, pervasive invaders throughout the more economically developed countries (MEDCs) of the world. The current paper utilises the Object-Based Image Analysis (OBIA) approach of Definiens Imaging Developer software, in combination with very high spatial resolution (VHSR) colour infra-red (CIR) and visible‑band (RGB) aerial photography in order to detect Japanese Knotweed s.l. taxa in Wales (UK). An algorithm was created using Definiens in order to detect these taxa, using variables found to effectively distinguish them from landscape and vegetation features. The results of the detection algorithm were accurate, as confirmed by field validation and desk‑based studies. Further, these results may be incorporated into Geographical Information Systems (GIS) research as they are readily transferable as vector polygons (shapefiles). The successful detection results developed within the Definiens software should enable greater management and control efficacy. Further to this, the basic principles of the detection process could enable detection of these taxa worldwide, given the (relatively) limited technical requirements necessary to conduct further analyses. Full article
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Open AccessArticle The HelioClim Project: Surface Solar Irradiance Data for Climate Applications
Remote Sens. 2011, 3(2), 343-361; doi:10.3390/rs3020343
Received: 20 December 2010 / Revised: 9 February 2011 / Accepted: 10 February 2011 / Published: 17 February 2011
Cited by 41 | PDF Full-text (543 KB) | HTML Full-text | XML Full-text
Abstract
Meteosat satellite images are processed to yield values of the incoming surface solar irradiance (SSI), one of the Essential Climate Variables. Two HelioClim databases, HC-1 and HC-3, were constructed covering Europe, Africa and the Atlantic Ocean, and contain daily and monthly means [...] Read more.
Meteosat satellite images are processed to yield values of the incoming surface solar irradiance (SSI), one of the Essential Climate Variables. Two HelioClim databases, HC-1 and HC-3, were constructed covering Europe, Africa and the Atlantic Ocean, and contain daily and monthly means of SSI. The HC-1 database spans from 1985 to 2005; HC‑3 began in 2004 and is updated daily. Their quality and limitations in retrieving monthly means of SSI have been studied by a comparison between eleven stations offering long time-series of measurements. A good agreement was observed for each site: bias was less than 10 W/m² in absolute value (5% in relative value) for HC-3. HC-1 offers a similar quality, though it underestimates the SSI for latitudes greater than 45° and less than −45°. Time-series running from 1985 to date can be created by concatenating the HC-1 and HC-3 values and could help in assessing SSI and its changes. Full article
(This article belongs to the Special Issue Remote Sensing in Climate Monitoring and Analysis)
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Open AccessArticle Field Spectroscopy for Assisting Water Quality Monitoring and Assessment in Water Treatment Reservoirs Using Atmospheric Corrected Satellite Remotely Sensed Imagery
Remote Sens. 2011, 3(2), 362-377; doi:10.3390/rs3020362
Received: 31 December 2010 / Revised: 27 January 2011 / Accepted: 12 February 2011 / Published: 21 February 2011
Cited by 10 | PDF Full-text (618 KB) | HTML Full-text | XML Full-text
Abstract
The overall objective of this study was to use field spectro-radiometers for finding possible spectral regions in which chlorophyll-a (Chl-a) and particulate organic carbon (POC) could be identified so as to assist the assessment and monitoring of water quality using satellite remote [...] Read more.
The overall objective of this study was to use field spectro-radiometers for finding possible spectral regions in which chlorophyll-a (Chl-a) and particulate organic carbon (POC) could be identified so as to assist the assessment and monitoring of water quality using satellite remote sensing technology. This paper presents the methodology adopted in this study which is based on the application of linear regression analysis between the mean reflectance values (measured with the GER1500 field spectro-radiometer) across the spectrum and the concentrations of chlorophyll-a (µg/L) and POC (µg/L) acquired simultaneously on the same day and time in the Lower Thames Valley in West London (U.K.) from old campaigns. Each regression model (512 in total) corresponded to a measured wavelength of the GER1500 field spectro-radiometer. The achieved correlations presented as r2 against wavelength, indicate the regions with high correlation values for both water quality variables. Based on the results from this study and by matching the spectral bands of the field spectro-radiometer with those of the Landsat TM satellite sensor (or any other sensor), it has been found that suitable spectral regions for monitoring water quality in water treatment reservoirs are the following: for chlorophyll-a, the spectral region of 0.45–0.52 μm (TM band 1), and for POC, the region 0.52–0.60 μm (TM bands 1 and 2). Then 12 atmospheric corrected Landsat TM/ETM+ band 1 images acquired from 2001 to 2010 were used for validation purposes to retrieve the Chl-a concentrations. Full article
Open AccessArticle Alaskan Permafrost Groundwater Storage Changes Derived from GRACE and Ground Measurements
Remote Sens. 2011, 3(2), 378-397; doi:10.3390/rs3020378
Received: 1 December 2010 / Revised: 20 February 2011 / Accepted: 21 February 2011 / Published: 22 February 2011
Cited by 15 | PDF Full-text (969 KB) | HTML Full-text | XML Full-text
Abstract
The Arctic is in transition from climate-driven thawing of permafrost. We investigate satellite-derived water equivalent mass changes, snow water equivalent with in situ measurements of runoff and ground-survey derived geoid models from 1999 through 2009. The Alaskan Arctic coastal plain groundwater storage (including [...] Read more.
The Arctic is in transition from climate-driven thawing of permafrost. We investigate satellite-derived water equivalent mass changes, snow water equivalent with in situ measurements of runoff and ground-survey derived geoid models from 1999 through 2009. The Alaskan Arctic coastal plain groundwater storage (including wetland bog, thaw pond and lake) is increasing by 1.15 ± 0.65 km3/a (area-average 1.10 ± 0.62 cm/a), and Yukon River watershed groundwater storage is decreasing by 7.44 ± 3.76 km3/a (area‑average 0.79 ± 0.40 cm/a). Geoid changes show increases within the Arctic coastal region and decreases within the Yukon River watershed. We hypothesize these changes are linked to the development of new predominately closed- and possibly open-talik in the continuous permafrost zone under large thaw lakes with increases of lakes and new predominately open-talik and reduction of permafrost extent in the discontinuous and sporadic zones with decreases of thaw lakes. Full article
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Open AccessArticle Sky-View Factor as a Relief Visualization Technique
Remote Sens. 2011, 3(2), 398-415; doi:10.3390/rs3020398
Received: 4 January 2011 / Revised: 10 February 2011 / Accepted: 14 February 2011 / Published: 23 February 2011
Cited by 38 | PDF Full-text (8712 KB) | HTML Full-text | XML Full-text
Abstract
Remote sensing has become the most important data source for the digital elevation model (DEM) generation. DEM analyses can be applied in various fields and many of them require appropriate DEM visualization support. Analytical hill-shading is the most frequently used relief visualization [...] Read more.
Remote sensing has become the most important data source for the digital elevation model (DEM) generation. DEM analyses can be applied in various fields and many of them require appropriate DEM visualization support. Analytical hill-shading is the most frequently used relief visualization technique. Although widely accepted, this method has two major drawbacks: identifying details in deep shades and inability to properly represent linear features lying parallel to the light beam. Several authors have tried to overcome these limitations by changing the position of the light source or by filtering. This paper proposes a new relief visualization technique based on diffuse, rather than direct, illumination. It utilizes the sky-view factor—a parameter corresponding to the portion of visible sky limited by relief. Sky-view factor can be used as a general relief visualization technique to show relief characteristics. In particular, we show that this visualization is a very useful tool in archaeology as it improves the recognition of small scale features from high resolution DEMs. Full article
(This article belongs to the Special Issue Remote Sensing in Natural and Cultural Heritage)
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Open AccessLetter Nearshore Water Quality Estimation Using Atmospherically Corrected AVIRIS Data
Remote Sens. 2011, 3(2), 257-269; doi:10.3390/rs3020257
Received: 11 January 2011 / Revised: 8 February 2011 / Accepted: 9 February 2011 / Published: 11 February 2011
Cited by 4 | PDF Full-text (441 KB) | HTML Full-text | XML Full-text
Abstract
The objective of the research is to characterize the surface spectral reflectance of the nearshore waters using atmospheric correction code—Tafkaa for retrieval of the marine water constituent concentrations from hyperspectral data. The study area is the nearshore waters of New York/New Jersey [...] Read more.
The objective of the research is to characterize the surface spectral reflectance of the nearshore waters using atmospheric correction code—Tafkaa for retrieval of the marine water constituent concentrations from hyperspectral data. The study area is the nearshore waters of New York/New Jersey considered as a valued ecological, economic and recreational resource within the New York metropolitan area. Comparison of the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) measured radiance and in situ reflectance measurement shows the effect of the solar source and atmosphere in the total upwelling spectral radiance measured by AVIRIS. Radiative transfer code, Tafkaa was applied to remove the effects of the atmosphere and to generate accurate reflectance (R(0)) from the AVIRIS radiance for retrieving water quality parameters (i.e., total chlorophyll). Chlorophyll estimation as index of phytoplankton abundance was optimized using AVIRIS band ratio at 675 nm and 702 nm resulting in a coefficient of determination of R2 = 0.98. Use of the radiative transfer code in conjunction with bio optical model is the main tool for using ocean color remote sensing as an operational tool for monitoring of the key nearshore ecological communities of phytoplankton important in global change studies. Full article
(This article belongs to the Special Issue Remote Sensing in Coastal Ecosystem)

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