Showing papers in "International Journal of Digital Earth in 2013"

Global, 30-m resolution continuous fields of tree cover: Landsat-based rescaling of MODIS vegetation continuous fields with lidar-based estimates of error

Abstract: We developed a global, 30-m resolution dataset of percent tree cover by rescaling the 250-m MOderate-resolution Imaging Spectroradiometer (MODIS) Vegetation Continuous Fields (VCF) Tree Cover layer using circa- 2000 and 2005 Landsat images, incorporating the MODIS Cropland Layer to improve accuracy in agricultural areas Resulting Landsat-based estimates maintained consistency with the MODIS VCF in both epochs (RMSE =86% in 2000 and 119% in 2005), but showed improved accuracy in agricultural areas and increased discrimination of small forest patches Against lidar measurements, the Landsat-based estimates exhibited accuracy slightly less than that of the MODIS VCF (RMSE=168% for MODIS-based vs 174% for Landsat-based estimates), but RMSE of Landsat estimates was 33 percentage points lower than that of the MODIS data in an agricultural region The Landsat data retained the saturation artifact of the MODIS VCF at greater than or equal to 80% tree cover but showed greater potential for removal

A long-term Global LAnd Surface Satellite (GLASS) data-set for environmental studies

Abstract: Recently, five Global LAnd Surface Satellite (GLASS) products have been released: leaf area index (LAI), shortwave broadband albedo, longwave broadband emissivity, incident short radiation, and pho...

Preliminary evaluation of the long-term GLASS albedo product

Abstract: Land surface albedo is an important parameter to describe the radiant forcing in the climate system. A long-time series of global albedo products is needed to understand the mechanism of climate ch...

FROM-GC: 30 m global cropland extent derived through multisource data integration

Abstract: We report on a global cropland extent product at 30-m spatial resolution developed with two 30-m global land cover maps (i.e. FROM-GLC, Finer Resolution Observation and Monitoring, Global Land Cover; FROM-GLC-agg) and a 250-m cropland probability map. A common land cover validation sample database was used to determine optimal thresholds of cropland probability in different parts of the world to generate a cropland/noncropland mask according to the classification accuracies for cropland samples. A decision tree was then applied to combine two 250-m cropland masks: one existing mask from the literature and the other produced in this study, with the 30-m global land cover map FROM-GLC-agg. For the smallest difference with country-level cropland area in Food and Agriculture Organization Corporate Statistical (FAOSTAT) database, a final global cropland extent map was composited from the FROM-GLC, FROM-GLC-agg, and two masked cropland layers. From this map FROM-GC (Global Cropland), we estimated the global cro...

SAR polarimetric change detection for flooded vegetation

Abstract: Due to spatial and temporal variability an effective monitoring system for water resources must consider the use of remote sensing to provide information. Synthetic Aperture Radar (SAR) is useful due to timely data acquisition and sensitivity to surface water and flooded vegetation. The ability to map flooded vegetation is attributed to the double bounce scattering mechanism, often dominant for this target. Dong Ting Lake in China is an ideal site for evaluating SAR data for this application due to annual flooding caused by mountain snow melt causing extensive changes in flooded vegetation. A curvelet-based approach for change detection in SAR imagery works well as it highlights the change and suppresses the speckle noise. This paper addresses the extension of this change detection technique to polarimetric SAR data for monitoring surface water and flooded vegetation. RADARSAT-2 images of Dong Ting Lake demonstrate this curvelet-based change detection technique applied to wetlands although it is ...

Redefining the possibility of digital Earth and geosciences with spatial cloud computing

Abstract: Global challenges (such as economy and natural hazards) and technology advancements have triggered international leaders and organizations to rethink geosciences and Digital Earth in the new decade. The next generation visions pose grand challenges for infrastructure, especially computing infrastructure. The gradual establishment of cloud computing as a primary infrastructure provides new capabilities to meet the challenges. This paper reviews research conducted using cloud computing to address geoscience and Digital Earth needs within the context of an integrated Earth system. We also introduce the five papers selected through a rigorous review process as exemplar research in using cloud capabilities to address the challenges. The literature and research demonstrate that spatial cloud computing provides unprecedented new capabilities to enable Digital Earth and geosciences in the twenty-first century in several aspects: (1) virtually unlimited computing power for addressing big data storage, sha...

Generation of high spatial and temporal resolution NDVI and its application in crop biomass estimation

Abstract: While data like HJ-1 CCD images have advantageous spatial characteristics for describing crop properties, the temporal resolution of the data is rather low, which can be easily made worse by cloud contamination. In contrast, although Moderate Resolution Imaging Spectroradiometer (MODIS) can only achieve a spatial resolution of 250 m in its normalised difference vegetation index (NDVI) product, it has a high temporal resolution, covering the Earth up to multiple times per day. To combine the high spatial resolution and high temporal resolution of different data sources, a new method (Spatial and Temporal Adaptive Vegetation index Fusion Model [STAVFM]) for blending NDVI of different spatial and temporal resolutions to produce high spatial–temporal resolution NDVI datasets was developed based on Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). STAVFM defines a time window according to the temporal variation of crops, takes crop phenophase into consideration and improves the temporal...

Lake variations in response to climate change in the Tibetan Plateau in the past 40 years

Abstract: The Qinghai-Tibetan Plateau plays an important role in global climate and environmental change and holds the largest lake area in China, with a total surface area of 36,900 km2. The expansion and shrinkage of these lakes are critical to the water cycle and ecological and environmental systems across the plateau. In this paper, surface areas of major lakes within the plateau were extracted based on a topographic map from 1970, and Landsat MSS, TM and ETM+ satellite images from the 1970s to 2008. Then, a multivariate correlation analysis was conducted to examine the relationship between the changes in lake surface areas and the changes in climatic variables including temperature, precipitation, evaporation, and sunshine duration. Initial results suggest that the variations in lake surface areas within the plateau are closely related to the warming, humidified climate transition in recent years such as the rise of air temperature and the increase in precipitation. In particular, the rising temperature accele...

A RESTful proxy and data model for linked sensor data

Abstract: The vision of a Digital Earth calls for more dynamic information systems, new sources of information, and stronger capabilities for their integration. Sensor networks have been identified as a major information source for the Digital Earth, while Semantic Web technologies have been proposed to facilitate integration. So far, sensor data are stored and published using the Observations & Measurements standard of the Open Geospatial Consortium (OGC) as data model. With the advent of Volunteered Geographic Information and the Semantic Sensor Web, work on an ontological model gained importance within Sensor Web Enablement (SWE). In contrast to data models, an ontological approach abstracts from implementation details by focusing on modeling the physical world from the perspective of a particular domain. Ontologies restrict the interpretation of vocabularies toward their intended meaning. The ongoing paradigm shift to Linked Sensor Data complements this attempt. Two questions have to be addressed: (1) ...

Geoprocessing in Cloud Computing platforms – a comparative analysis

Abstract: The emergence of Cloud Computing technologies brings a new information infrastructure to users. Providing geoprocessing functions in Cloud Computing platforms can bring scalable, on-demand, and cost–effective geoprocessing services to geospatial users. This paper provides a comparative analysis of geoprocessing in Cloud Computing platforms – Microsoft Windows Azure and Google App Engine. The analysis compares differences in the data storage, architecture model, and development environment based on the experience to develop geoprocessing services in the two Cloud Computing platforms; emphasizes the importance of virtualization; recommends applications of hybrid geoprocessing Clouds, and suggests an interoperable solution on geoprocessing Cloud services. The comparison allows one to selectively utilize Cloud Computing platforms or hybrid Cloud pattern, once it is understood that the current development of geoprocessing Cloud services is restricted to specific Cloud Computing platforms with certain ...

Determining oil slick thickness using hyperspectral remote sensing in the Bohai Sea of China

Abstract: Determining oil slick thickness plays an important role in assessing oil spill volume and its environmental impacts on the ocean. In this study, we used a Hyperion image of an oil spill accident area and seawater and fresh crude oil samples collected in the Bohai Sea of China. A well-controlled laboratory experiment was designed to simulate spectral responses to different oil slick thicknesses. Spectral resampling and normalization methods were used to reduce the differences in spectral reflectances between the experimental background seawater sample and real background seawater. Fitting the analysis with laboratory experimental data results showed a linear relationship between normalized oil slick reflectance and normalized oil slick thickness [20th band (R 2=0.92938, n=49, p<0.01), 26th band (R 2=0.93806, n=49, p<0.01), 29th band (R 2=0.93288, n=49, p<0.01)]. By using these statistical models, we successfully determined the normalized oil slick thickness with the Hyperion image. Our results ind...

Exploring natural and anthropogenic risk for cultural heritage in Cyprus using remote sensing and GIS

Abstract: On site observation is the most common way of monitoring cultural heritage sites and monuments in Cyprus. However, this procedure that includes data collection, periodical observations, and multivariate risk assessment analysis is difficult to accomplish with the traditional practices and methods since it is time consuming and expensive. Furthermore, many archaeological sites and monuments are located at inaccessible areas, far away from the main road network and urban areas. Satellite remote sensing and Geographical Information Systems (GIS) can successfully confront this problem by providing the scientists with integrated monitoring of the study areas and the unique advantage to store and manipulate a large amount of spatial and attribute data simultaneously. Actually the monitoring and identification of several natural and anthropogenic hazards in the vicinity of the cultural heritage sites in Cyprus, seems to be one of the main priorities of its governmental and municipal authorities. This st...

Utilize cloud computing to support dust storm forecasting

Abstract: The simulations and potential forecasting of dust storms are of significant interest to public health and environment sciences. Dust storms have interannual variabilities and are typical disruptive events. The computing platform for a dust storm forecasting operational system should support a disruptive fashion by scaling up to enable high-resolution forecasting and massive public access when dust storms come and scaling down when no dust storm events occur to save energy and costs. With the capability of providing a large, elastic, and virtualized pool of computational resources, cloud computing becomes a new and advantageous computing paradigm to resolve scientific problems traditionally requiring a large-scale and high-performance cluster. This paper examines the viability for cloud computing to support dust storm forecasting. Through a holistic study by systematically comparing cloud computing using Amazon EC2 to traditional high performance computing (HPC) cluster, we find that cloud computi...

A cloud detection method based on a time series of MODIS surface reflectance images

Abstract: The Moderate Resolution Imaging Spectroradiometer (MODIS)-Terra surface reflectance product (MOD09A1), with bands 1 to 7, is a gridded, eight-day composite product derived from the MODIS-Terra top ...

Land-surface temperature retrieval at high spatial and temporal resolutions based on multi-sensor fusion

Abstract: Land-surface temperature (LST) is of great significance for the estimation of radiation and energy budgets associated with land-surface processes. However, the available satellite LST products have...

Prototyping an open environment for sharing geographical analysis models on cloud computing platform

Abstract: The sharing of geographical analysis models is of crucial importance for simulating geographic processes and phenomena in the current geographical information systems (e.g. Digital Earth), but there remain some issues that have not been completely resolved. The challenges include, eliminating model heterogeneity and searching for suitable infrastructures to support the open sharing and effective execution of models. Taking advantage of cloud computing, this article aims to address the above issues and develop an open environment for geographical analysis model sharing. On the basis of the analysis of the applicability of cloud computing, the architecture of the open environment is proposed. More importantly, key strategies designed for heterogeneous model description, model encapsulating as well as model deploying and transparent accessing in the cloud are discussed in detail to establish such an environment. Finally, the prototype environment is implemented, and experiments were conducted to ver...

Transferring Google Earth observations to GIS-software: example from gully erosion study

Abstract: High-resolution images available on Google Earth are increasingly being consulted in geographic studies. However, most studies limit themselves to visualizations or on-screen measurements. Google Earth allows users to create points, lines, and polygons on-screen, which can be saved as Keyhole Markup Language (KML) files. Here, the use of R statistics freeware is proposed to easily convert these files to the shapefile format [or ‘.shp file format’], which can be loaded into Geographic Information System (GIS) software (ESRI ArcGIS 9 in our example). The geospatial data integration in GIS strongly increases the analysis possibilities.

A tree counting algorithm for precision agriculture tasks

Abstract: This study proposes an automatic procedure for individual fruit tree identification using GeoEye-1 sensor data. Depending on site-specific pruning practices, the morphologic characteristics of tree crowns may generate one or more brightness peaks (tree top) on the imagery. To optimize tree counting and to minimize typical background noises from orchards (i.e. bare soil, weeds, and man-made objects), a four-step algorithm was implemented with spatial transforms and functions suitable for spaced stands (asymmetrical smoothing filter, local minimum filter, mask layer, and spatial aggregation operator). System performance was evaluated through objective criteria, showing consistent results in fast capturing tree position for precision agriculture tasks.

Improving a Penman–Monteith evapotranspiration model by incorporating soil moisture control on soil evaporation in semiarid areas

Abstract: Penman–Monteith (PM) theory has been successfully applied to calculate land surface evapotranspiration (ET) for regional and global scales. However, soil surface resistance, related to soil moisture, is always difficult to determine over a large region, especially in arid or semiarid areas. In this study, we developed an ET estimation algorithm by incorporating soil moisture control, a soil moisture index (SMI) derived from the surface temperature and vegetation index space. We denoted this ET algorithm as the PM-SMI. The PM-SMI algorithm was compared with several other algorithms that calculated soil evaporation using relative humidity, and validated with Bowen ratio measurements at seven sites in the Southern Great Plain (SGP) that were covered by grassland and cropland with low vegetation cover, as well as at three eddy covariance sites from AmeriFlux covered by forest with high vegetation cover. The results show that in comparison with the other methods examined, the PM-SMI algorithm significantly imp...

Full polarimetric PALSAR-based land cover monitoring in Cambodia for implementation of REDD policies

Abstract: Forest cover monitoring plays an important role in the implementation of climate change mitigation policies such as Kyoto protocol and Reducing Emissions from Deforestation and Forest Degradation (REDD). In this study, we have monitored land cover using the PALSAR (Phased Array type L-band Synthetic Aperture Radar) full polarimetric data based on incoherent target decomposition. Supervised classification technique has been applied on Cloude–Pottier decomposition, Freeman–Durden three component, and Yamaguchi four component decomposition for accurate mapping of different types of land cover classes. Based on confusion matrix derived from the predicted and defined pixels, the evergreen and sparsely deciduous forests have shown high producer's accuracy by Freeman–Durden three component and Yamaguchi four component classifications. The overall accuracy of Maximum Likelihood Classification by Yamaguchi four component is 94.1% with 0.93 kappa coefficient as compared to the 90.3% with 0.88 kappa coeffic...

Cloud computing for integrated stochastic groundwater uncertainty analysis

Abstract: One of the major scientific challenges and societal concerns is to make informed decisions to ensure sustainable groundwater availability when facing deep uncertainties. A major computational requirement associated with this is on-demand computing for risk analysis to support timely decision. This paper presents a scientific modeling service called ‘ModflowOnAzure’ which enables large-scale ensemble runs of groundwater flow models to be easily executed in parallel in the Windows Azure cloud. Several technical issues were addressed, including the conjunctive use of desktop tools in MATLAB to avoid license issues in the cloud, integration of Dropbox with Azure for improved usability and ‘Drop-and-Compute,’ and automated file exchanges between desktop and the cloud. Two scientific use cases are presented in this paper using this service with significant computational speedup. One case is from Arizona, where six plausible alternative conceptual models and a streamflow stochastic model are used to eva...

Construction of a virtual lunar environment platform

Abstract: Many of the world's powerful and wealthy nations, including China, have devoted both large amounts of funding and considerable promotion to lunar research and exploration. The launch of Chinese Chang'e-1 satellite and the construction of the scientific observation data platform created a favourable opportunity for research into the lunar geometrical, physical and chemical environment. Based on this background, a Wide Area Network (WAN) based virtual lunar environment was constructed for observation data sharing and further exploration. The systematic architecture and framework were introduced and then strategies of mass data (e.g. lunar digital elevation model, lunar digital orthophoto map and typical thematic lunar data) organisation, integration, management and scheduling were then set up to achieve the 3D visualisation of typical lunar geomorphic features. Furthermore, the integration method of 3D lunar data and the process model of impact craters were studied; thus, the whole lunar and celest...

Estimating global land surface broadband thermal-infrared emissivity using advanced very high resolution radiometer optical data

Abstract: An algorithm for retrieving global eight-day 5 km broadband emissivity (BBE) from advanced very high resolution radiometer (AVHRR) visible and near-infrared data from 1981 through 1999 was presente...

Using remote sensing to assess impacts of land management policies in the Ordos rangelands in China

Abstract: Implementation of land management policies influences land use and hence causes environmental change. Taking the Ordos rangelands in China as a case study, this paper explores the potential of remote sensing to assess in dryland areas the impacts of policies on the environment. Thirteen Landsat images of the period 1978–2010 were acquired and those corresponding to the starting dates of implementation of different policies were selected for land-cover change analysis; others were used to check the detected change and track the normalized difference vegetation index (NDVI) trajectory matched with time series of meteorological data for calibration of natural response of rangelands to rainfall. The results indicate that policy impacts are complex and include both positive and negative aspects depending on the locality in space. On one hand, policies have aroused the enthusiasm of people in agricultural production and sand-control leading to the recovery of about 2618 km2 of desertified rangeland and sandy la...

Enabling Digital Earth simulation models using cloud computing or grid computing – two approaches supporting high-performance GIS simulation frameworks

Abstract: Geospatial simulation models can help us understand the dynamic aspects of Digital Earth. To implement high-performance simulation models for complex geospatial problems, grid computing and cloud computing are two promising computational frameworks. This research compares the benefits and drawbacks of both in Web-based frameworks by testing a parallel Geographic Information System (GIS) simulation model (Schelling's residential segregation model). The parallel GIS simulation model was tested on XSEDE (a representative grid computing platform) and Amazon EC2 (a representative cloud computing platform). The test results demonstrate that cloud computing platforms can provide almost the same parallel computing capability as high-end grid computing frameworks. However, cloud computing resources are more accessible to individual scientists, easier to request and set up, and have more scalable software architecture for on-demand and dedicated Web services. These advantages may attract more geospatial sc...

Assessment of different topographic correction methods in ALOS AVNIR-2 data over a forest area

Abstract: Because the removal of topographic effects is one the most important pre-processing steps when extracting information from satellite images in digital Earth applications, the problem of differential terrain illumination on satellite imagery has been investigated for at least 20 years. As there is no superior topographic correction method applicable to all areas and all images, a comparison of topographic normalization methods in different regions and images is necessary. In this study, common topographic correction methods were applied on an ALOS AVNIR-2 image of a rugged forest area, and the results were evaluated through different criteria. The results show that the simple correction methods [Cosine, Sun-Canopy-sensor (SCS), and Minnaert correction] are inefficient in exceptionally rough forests. Among the improved correction methods (SCS+C, modified Minnaert, and pixel-based Minnaert), the best result was achieved using a pixel-based Minnaert approach in which a separate correction factor in v...

Monitoring nitrogen concentration of oilseed rape from hyperspectral data using radial basis function

Abstract: Remote sensing technology is the important tool of digital earth, it can facilitate nutrient management in sustainable cropping systems. In the study, two types of radial basis function (RBF) neural network approaches, the standard radial basis function (SRBF) neural networks and the modified type of RBF, generalized regression neural networks (GRNN), were investigated in estimating the nitrogen concentrations of oilseed rape canopy using vegetation indices (VIs) and hyperspectral reflectance. Comparison analyses were performed to the spectral variables and the approaches. The Root Mean Square Error (RMSE) and determination coefficients (R2) were used to assess their predictability of nitrogen concentrations. For all spectral variables (VIs and hyperspectral reflectance), the GRNN method produced more accurate estimates of nitrogen concentrations than did the SRBF method at all ranges of nitrogen concentrations, and the better agreements between the measured and the predicted nitrogen concentration were o...

Field validation of the GLASS land surface broadband emissivity database using pseudo-invariant sand dune sites in northern China

Abstract: The land surface broadband emissivity (LSBE) is a key parameter for estimating surface radiation, and there have been many studies of the LSBE at global or local scales. However, few studies have v...

Effects of LIDAR DEM resolution in hydrodynamic modelling: model sensitivity for cross-sections

Abstract: With the development of science and technology the entire Earth, together with all of its phenomena, is gradually becoming an object of computer digitisation. For several years, this process has also affected water components, which are essential for the development of humans and economies on Earth. Therefore, monitoring of its resources and movement across the Earth's surface is the main object of investigation of several research institutions. In recent years, hydraulic modelling has experienced significant development that meets water and computer connection conditions. This study consequently dealt with hydraulic modelling and uncertainties in the data that may affect the resulting flood zone. We analysed the effect of cross-sections generated and the subsequent inundation areas in Digital Elevation Models of different resolutions. The basic DEM was constructed from data obtained by the LIDAR method. Hydraulic results were obtained using a one-dimensional (1-D) model, HEC-RAS, and its extensi...

Application of digital techniques to identify aquifer artificial recharge sites in GIS environment

Abstract: Because the groundwater is considered as the major source of 99% of all retrievable fresh water, optimization of its usage would be very crucial. Groundwater artificial recharge (GAR) using surface water is the recommended solution because that increases the aquifer storage. Detection of aquifer storage site is the first step in designing GAR projects. The main objective of this research is the identification of suitable GAR sites scattered in the Shahrekord plain, Chaharmahal-va-Bakhtiari province of Iran, using Boolean and Fuzzy logic. Data affecting GAR including ground surface slope, soil infiltration rate, vadoze zone thickness, electrical conductivity of the surface water, land-use, and stream network were collected. After provision of digital maps, they were classified, weighted, and integrated through Boolean and Fuzzy operators. The result revealed almost 4.25% of the whole plain area is appropriate for GAR based on Boolean. Also, 4.79 and 17.94% of the plain area are suitable and rather favorabl...