Thermal Emission Model Research Articles

Identifying terraces in the hilly and gully regions of the Loess Plateau in China

AbstractTerrace identification is the basis for understanding quantity, quality, and land covers of terraces and their effects on agriculture production and various surface processes, for example, hydrological and ecological processes. However, there are some drawbacks and limitations in the automatic extraction of terraces, such as difficulty of outlining the overall boundary for individual terrace and the limitation of applying methods and parameters. In this study, we used machine learning methods on the basis of Geographic Object‐Based Image Analysis using K‐nearest neighbours and spectral angle mapper algorithms to extract terraces in the hilly and gully regions on the Loess Plateau, China. This study relied on medium‐resolution image Landsat‐8 combined with Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model to extract the overall boundary of terraces and relies on high‐resolution images GaoFen‐1 to extract the terraced edges of terraces. It used the methods of principal component analysis and Laplacian convolution filter to enhance and extract terraced edges inside of the boundary of terraces. Our estimates are with overall accuracy of 62.2% in K‐nearest neighbours and 74.8% in spectral angle mapper methods, indicating the advantages of the proposed method despite the use of much lower resolution data than previous studies that used both high‐resolution terrain and remote sensing imageries data. This study highlights the importance of using appropriate methods plus reasonable spatial resolution of remote sensing data for outlining the overall boundary of terraces in the hilly and gully regions.

Assessment of active tectonics from geomorphic indices and morphometric parameters in part of Ganga basin

Ganga river basins exposed to active erosional and deformational processes. The recurrence of landslides, floods, and seismic activities makes it more susceptible to deformational activities. The tectonic analysis using geomorphic indices and morphometric parameters will help in determining the hazard-prone area of the river basin. Geomorphic indices and morphometric parameters are calculated to investigate the role of neotectonic activities, as it acts as a controlling factor in the development of landforms in the tectonically active terrains. Neotectonic activities influence the terrain topography, which significantly affects the drainage system and geomorphological setup of the area. In this study, the assessment of active tectonics of study area was determined using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) based on Geomorphic Indices (Stream Length Gradient index, Hypsometric integral, Asymmetry factor, Basin shape, Valley floor width to Valley height ratio, Mountain front sinuosity index) cumulatively with Linear, Areal and Relief morphometric parameters on 27 delineated basins of the study area. The combined classification of Relative Tectonic Activity Index (Iat) and morphometric parameters of 27 basins categorized all the zones into four different classes: Class 1 - Very High ( 2.21; 299 km2). The basins with tectonic activities have a consistent relationship with structural disturbances, basin geometry, and field studies. The tectonically active zonation of a part of Ganga basin using geomorphic indices and morphometric parameters suggest that it has significant influence of neotectonic activities in a part of Ganga basin.

Evaluation of the Accuracy of Digital Elevation Model Produced from Different Open Source Data

This study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, the Geographic Information System (GIS) was utilized to analyze, imagine and interpolate data in this study. The result of the statistical analysis revealed that RMSE of DEM related to the differences between the reference points and Google Earth, SRTM DEM and ASTER GDEM are 6.9, 5.5 and 4.8, respectively. What is more, a finding of this study shows convergence the level of accuracy for all open sources used in this study.

An unusual transient following the short GRB 071227

ABSTRACT We present X-ray and optical observations of the short duration gamma-ray burst GRB 071227 and its host at z = 0.381, obtained using Swift, Gemini South, and the Very Large Telescope. We identify a short-lived and moderately bright optical transient, with flux significantly in excess of that expected from a simple extrapolation of the X-ray spectrum at 0.2–0.3 d after burst. We fit the SED with afterglow models allowing for high extinction and thermal emission models that approximate a kilonova to assess the excess’ origins. While some kilonova contribution is plausible, it is not favoured due to the low temperature and high luminosity required, implying superluminal expansion and a large ejecta mass of ∼0.1 M$\odot$. We find, instead, that the transient is broadly consistent with power-law spectra with additional dust extinction of E(B − V) ∼ 0.4 mag, although a possibly thermal excess remains in the z band. We investigate the host, a spiral galaxy with an edge-on orientation, resolving its spectrum along its major axis to construct the galaxy rotation curve and analyse the star formation and chemical properties. The integrated host emission shows evidence for high extinction, consistent with the afterglow findings. The metallicity and extinction are consistent with previous studies of this host and indicate the galaxy is a typical, but dusty, late-type SGRB host.

Variation of mass accretion rate on to the white dwarf in the dwarf nova VW Hyi in quiescence

Abstract We have analysed a series of Suzaku data and one data set of XMM–Newton of the SU UMa type dwarf nova VW Hyi in optical quiescence. The observed spectra in the 0.2–10 keV band are moderately well represented by multitemperature thermal plasma emission models with a maximum temperature of 5–9 keV and bolometric luminosity of (2.4–5.2) × 1030 erg s−1. The mass accretion rate derived from the hard X-ray spectra does not show any clear trend as a function of time since the last superoutburst, in contradiction to theoretical predictions of the disc behaviour of an SU UMa type dwarf nova. The mass accretion rate, on the other hand, shows a clear declining trend with time since the last outburst (including the superoutburst). The rate of decline is of the same order as that evaluated from the hard X-ray light curves of the other two dwarf novae SS Cyg and SU UMa. The standard disc instability model, on the other hand, predicts that the mass accretion rate should increase throughout the optically quiescent phase. We need further observation and theoretical consideration to resolve this discrepancy.

Remote sensing signature analysis of ASTER imagery for geological mapping of Gasus area, central eastern desert, Egypt

The using of processed ASTER images and ASTER-GDEM (Advanced Spaceborne Thermal Emission and Reflection Radiometer-global digital elevation model) supplemented by extensive geological field work and spectral measurements of field samples enabled the creating of a new geological map of Gasus area. SVM (Support Vector Machine) method obtained 86% as overall accuracy of the classification and was verified by previous published maps and field verifications. Structure lineaments were automatically extracted and directional analysis of the automatically extracted lineament maps showing that the major trend of the lineaments are NW-SE and NNW-SSE, while NNE-SSW and NE-SW trends can also be recognized but in a less significant order. These trends are compatible and corresponding to the field verification.

Prediction of land surface temperatures for surface urban heat island assessment over Chandigarh city using support vector regression model

Rapid urbanization is one of the primary reasons for changing the local climate, and there is a high impact on the surrounding areas. Chandigarh is one of the fastest developing cities in India showing rapidly urbanizing agglomeration. Due to the rapid urbanization, natural land surfaces are being replaced by the anthropogenic materials which negatively impacts the ecosystem resulting in urban heat island (UHI) effect. Land surface temperature (LST) is the primary and vital step for the analysis of UHI effect. The present study has been conducted to predict the LSTs for the assessment of UHI effect of the area surrounding Chandigarh city. Remote sensing data from Moderate-Resolution Imaging Spectroradiometer (MODIS) sensor and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) have been used for the prediction of LST. In the study, support vector regression (SVR) model has been developed from LST values of previous three years along with enhanced vegetation index (EVI), road density (RD) and elevation as input parameters to predict LST. The results of the SVR model have been validated using the data of the year 2014. A comparison of the model estimated LST and measured LST indicates that the range of mean absolute error (MAE) and mean absolute percentage error (MAPE) varies between 0.521 K and 0.525 K and 0.181–0.187%, respectively. Hence, SVR model can be used as a significant tool to predict LST for the assessment of heat island effect at any location. From the sensitivity analysis, it is observed that LST was ultimately the most sensitive to the RD compared to EVI and elevation. The SVR model has been compared with artificial neural networks (ANN) model to estimate the skill score factor of the SVR model (Forecasted) with reference to the ANN (Referred) model. Skill scores calculated for the periods show positive values which clearly depicts the efficacy of SVR model compared to ANN model for better LST prediction.

Surface Foam and L-Band Microwave Radiometer Measurements in High Winds

The ocean surface roughness and foam coverage are the two important elements in the electromagnetic (EM) thermal emission computation. The foam contribution accounts for the air modifying the dielectric property of the water side interface layer. It can be modeled using a mixing rule of the air and water relative permittivities weighted by the air fraction and foam-free portion in the EM-influence volume, respectively. For high EM frequencies, the air fraction can be approximated by the whitecap fraction given as a function of wind speed empirically established with oceanographic observations. This simplification works very well for C band and higher frequencies but overestimates the foam effects for the L-band; the air fraction needs to be reduced compared to the whitecap fraction. Through the thermal emission analysis applied to several data sets of radiometer measurements in high winds, a function relating the air fraction and whitecap coverage is established. Incorporating the proposed function, the thermal emission model computations are in very good agreement with radiometer measurements at 1.4, 4.7, 6, 10, 18, 23, and 37 GHz with various incidence angles and both vertical and horizontal polarizations. Comparing the foam and roughness components contributing to the wind-induced thermal emission, the roughness contribution dominates over a broad wind speed range. Except for the vertical polarization near the 55° incidence angle, the roughness contribution is almost always greater than the foam contribution to well above 20 m/s wind speed, the crossover wind speed for the foam contribution to exceed roughness contribution is dependent on the frequency, incidence angle, and polarization.

GIS-based spatial prediction of landslide susceptibility using frequency ratio model of Lachung River basin, North Sikkim, India

Landslide causes damage to property and life in the Himalayan region as well as Sikkim Himalaya. Landslide susceptibility assessment is very important to mark out the landslide susceptibility area, and researchers take some plans for the future. Landslide susceptibility map has become essential to identify the landslide-prone zones and to find out the probable causes of a landslide in an area. The main objectives of this study are to produce landslide susceptibility mapping by frequency ratio method and to find out the dominant parameters which are responsible for the occurrences of frequent landslide in Lachung River basin, the main tributary of Teesta River in Sikkim Himalaya. The study utilized different types of data which include geological data, advanced spaceborne thermal emission and reflection radiometer-based digital elevation model, Sentinel-2A sensor data, published thematic map and precipitation data, and all data have been processed with the help of remote sensing and GIS tools. Ten influential causative factors of landslide occurrence are used for the susceptibility assessment, and they are slope angle, slope aspect, elevation, profile curvature, land use/land cover, normalized differences vegetation index, drainage density, road density, geology and rainfall. The GIS-based landslide susceptibility analysis has been discussed with ten dominant factors by using frequency ratio model. Finally, the landslide susceptibility map was classified into very high (0.591%), high (1.867%), moderately high (5.172%), moderate (19.682%), moderately low (25.685%), low (29.816%) and very low (17.187%). The map was compared with the validation of landslide location, and the model was verified by the receiver operating characteristic curve. The results revealed 88.9% prediction rate and 92.3% success rate, which means this model is validated with landslide susceptibility analysis in the study area.

The Devdoraki Glacier Catastrophes, Georgian Caucasus

This study analyses the Devdoraki Glacier surge type catastrophes since 1776, lead to human casualties, destruction of settlements and the international road in the Georgian Caucasus. According to archival data, at least six ice and ice-rock avalanches fell from the Devdoraki Glacier onto the Tergi (Terek) River valley during the period 1776–1876, the largest on June 18, 1776 and on August 13, 1832. The first blocked the Tergi River for three days and was breached catastrophically; the second was ~100 m high and ~2 km wide and its breach started after 8 hours. The most recent hazard occurred on May 17, 2014 killing nine people, and destroyed the Trans-Caucasus gas pipeline, Dariali Hydropower Plant (HPP) and international road. Using aerial and satellite imagery – Landsat, ASTER, SENTINEL along with the 30 m resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM; 17 November 2011) we have reconstructed this event. On the basis of subsequent detailed field observations, new geological and tectonic maps of the study region have been compiled. After that collapse we have registered ~180 m advance of the Devdoraki Glacier snout between 2014 and 2015, which was mostly caused by rock-ice avalanche deposits. This part of the glacier should be monitored continuously as it can raise debris flow activity in the future. We consider the main hypotheses behind these events, namely a) tectonic and seismic, b) permafrost, c) volcanic and d) morphological factors; interpret the data for mechanisms and velocities of the catastrophic movement and argue that the 2014 event should not be classified as a glacier surge, although the possibility of similar glacial surges can not be excluded. The Kazbegi-Jimara massif should be considered as a natural laboratory that enables the investigation of rock-ice avalanches and glacial mudflows.

Flash flood susceptibility modelling using geomorphometric approach in the Ushairy Basin, eastern Hindu Kush

This study focuses on flash flood susceptibility modelling using geomorphometric ranking approach in the Ushairy Basin. In the study area, flash floods are highly unpredictable and the worst hydrometeorological disaster. An advanced spaceborne thermal emission and reflection radiometer global digital elevation model was used as input data in a geographic information system environment to delineate the target basin. A total of 17 sub-basins were delimited using a threshold of $$4 \hbox {km}^{2}$$ . The attribute information of each sub-basin was analysed to compute the geomorphometric parameters by applying Hortonian and Strahler geomorphological models. The results were analysed and categorised into five classes using statistical techniques, and the rank score was assigned to each class of all parameters depending on their relation with flash flood risk. In this study, 16 parameters were analysed to quantify the geomorphometric number of each sub-basin depicting the degree of flash flood susceptibility. The geomorphometric number of each sub-basin was linked to the geo-database for spatial visualisation. The analysis reveals that extremely high, very high, high and moderate sub-basins susceptible to flash floods were spread over an area of 55%, 8.5%, 23.7%, and 11.5%, respectively. It was found that out of total settlements, 53% are located in the extremely highly and very highly susceptible sub-basins. In the study area, the upper reaches are characterised by snow-covered peaks, steep slopes and high drainage densities ( $${>}1.7 \hbox { km/km}^{2})$$ . The analysis further indicated that the flash flood susceptibility increases with the increase in area, relief and relief ratio of the sub-basins. Model accuracy was assessed using primary data regarding past flood damages and human fatalities. Similarly, socio-demographic conditions of each sub-basin were also compared and linked to the extent of flash flood susceptibility. This study may assist the district government and district disaster management authority of Dir upper to initiate flood risk reduction strategies in highly susceptible zones of the Ushairy Basin.

Layered compressive sensing reconstruction for non-scanning three-dimensional laser imaging

ABSTRACTAs an active remote-sensing technique, three-dimensional (3D) laser radar enables accurate target detection and identification. However, the resolution of obtained image is limited by the integrated level of the sensor array. In this article, we propose a layered compressive sensing reconstruction method for high-resolution 3D laser imaging. The range profile is first reconstructed by applying a designed range observation matrix to the original sampling data. According to the distribution of range values in the reconstructed range profile, the original sampling data are divided into several layers and the corresponding intensity images are reconstructed by different algorithms. The global intensity image is generated by the reconstructed intensity images with different range compensation coefficients. In our simulations based on real data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model Version 2 (ASTER GDEM V2) and Landsat-8 Operational Land Imager (OLI), the proposed method realised 3D laser imaging for complex landforms with a pixel resolution of , and reached a satisfactory performance for reconstructions of the range profile (peak signal-to-noise ratio (PSNR) = 33.08 dB, feature similarity (FSIM) = 0.9450) and the intensity image (PSNR = 20.63 dB, FSIM = 0.8893) with a subrate of 0.25.

Geomorphic evolution and neotectonics of the Qianhe River Basin on the southwest margin of the Ordos Block, North China

The Qianhe River Basin is located at the convergence zone of the northeastern margin of the Tibetan Plateau (NETP), the Ordos Block and the Qinling Mountains. A tectonic geomorphology study of the Qianhe River is significant for providing a deeper understanding of the tectonic transition between the NETP and the Ordos Block and the dynamic relationship of these three tectonic units. Based on Advanced Spaceborne Thermal Emission and Reflection global digital elevation model (ASTER-GDEM) data and geographic information system (GIS) techniques, four tectonic geomorphic indices, the hypsometric integral (HI), stream length-gradient (SL), drainage basin asymmetry (AF), and drainage basin shape (BS), were calculated and analyzed. Geologic evidence from field surveys, deformation measurements, and fault slip rate estimates was also obtained to further discuss the tectonic activity and tectonic geomorphic evolution model. Through analytical comparisons, we proposed that the variations in the applied geomorphic index values were not significantly affected by climate and lithology but indicated variations in related tectonic activity. The geomorphic index value analysis suggested relatively strong tectonic activity in Liupanshan Mountain and Longshan Mountain and northwestward tectonic tilting of the southwest margin of the Ordos Block. The actual mechanisms responsible for the observed variations in the Qianhe River Basin are the rapid uplift and northeastward extrusion of the Qinghai-Tibetan Plateau and the local tilting uplift of the southwestern Ordos Block.

European Digital Elevation Model Validation against Extensive Global Navigation Satellite Systems Data and Comparison with SRTM DEM and ASTER GDEM in Central Macedonia (Greece)

Digital elevation models (DEMs) are a widely used form of topographic information, with some of the most popular being the Shuttle Radar Topography Mission (SRTM) DEM and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM). These two sources of topographical information are the main constituents of the European Union Digital Elevation Model (EU-DEM), which is a relatively new dataset of the EU’s Copernicus Land Monitoring Service. In this context, the purpose of this study was to validate EU-DEM for its vertical accuracy and to compare it with SRTM DEM and ASTER GDEM data. This was achieved in a Geographic Information System (GIS) environment, using extensive—in the order of tens of thousands of points—geodetic Global Navigation Satellite System (GNSS) measurements and appropriate pre-processing steps. The absolute elevation errors results had a Root Mean Square Error (RMSE) of 2.7 m at a 90% confidence level and characterize the performance of EU-DEM from local to regional scale, generally confirming that it is an enhanced source of elevation information when compared with its predecessors.

Evaluasi Tingkat Akurasi Digital Elevation Model (DEM) SRTM dan ASTER GDEM dalam Pemodelan Daerah Aliran Sungai (DAS) Ciliwung

Availability of Digital Elevation Model (DEM) dataset and Geographic Information System (GIS), makes the watershed properties can be extracted automatically. There are two DEM providers which are freely accessible for research purposes and commonly use that is the Shuttle Radar Topographic Mission (SRTM) - DEM (30m) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM V2). Based on the result of modeling conducted at Ciliwung River Basin with Qgis application, area generated from SRTM data is 5% smaller than Ciliwung River Basin which obtained from BPDAS Ciliwung-Citarum as a reference, while the result of ASTER-GDEM data is 87% larger than reference. Linear Regression Test and t-Test performed on three segments of the watershed shows that the upstream of both samples gives a good accuracy result that is R2 = 0,999; P = 0,499 (SRTM) and R2 = 0,999; P = 0,481 (ASTER-GDEM), while in the middle and downstream segments respectively for both samples are SRTM with R2 = 0,993; P = 0,413 and R2 = 0,734; P = 0,088; and then ASTER-GDEM with R2 = 0,784; P = 0,00038 and R2 = 0,376; P = 1,27209 x10-22.

A regional ASTER GDEM error model for the Chinese Loess Plateau

ABSTRACTAccuracy of the global ASTER GDEM (Advanced Space-borne Thermal Emission and Reflection Radiometer Global Digital Elevation Model) version 2 (v2) elevation data product is highly variable regionally, as are its empirical correlations with landscape variables. This paper investigates GDEM error along a 49-site geomorphologic gradient within the core region of the Chinese Loess Plateau, notable for its heterogeneous terrain. The error is modelled using its associations with MODIS (Moderate Resolution Imaging Spectroradiometer) composite forest cover percentage, GlobeLand30 land cover, and key elevation derivatives, including two indices, terrain roughness index (TRI) and topographic position index (TPI), not previously evaluated in GDEM accuracy studies. Overall root mean squared error (RMSE) is 20.33 m, in excess of the GDEM v2 accuracy specifications, while RMSE at each site varies substantially, from 10.67 m for a low relief area to 21.84 m for the most rugged site. Strong associations between covariates, especially slope, aspect, TRI, and forest cover are identified. A regression model using these variables is developed to formally characterize and predict GDEM error. External validation with independent checkpoints across all sites demonstrates that this model can reduce mean error by about 4 m.

Flood hazard assessment of upper Jhelum basin using morphometric parameters

Morphometric parameters can be useful tools to provide general understanding of physical characteristics of drainage basin with respect to floods. To evaluate the flood influencing factors in the upper Jhelum basin, we delineate the upper Jhelum basin into ten sub-basins, followed by extraction of drainage network and morphometric parameters using Advanced Spaceborne Thermal Emission and Reflection Radiometer digital elevation model and topographic maps in Geographic Information System. The overall flood potential was determined on the basis of compound value obtained for all morphometric parameters of each sub-basin. The analysis reveals that, in general, the northeastern segment of the upper Jhelum basin reveals comparative higher flood potential than the southwestern segment. The tributaries, such as Lidder, Veshav, Arapal, Arapat, and Bring, exhibit greater potential to produce peak flows during rainfall events, while the tributaries like Dudhganga, Rambiara, Sandran, Romushi, and Sasara express moderate-to-low flood potential, respectively. The results of this study are likely to be very useful for effective flood hazard mitigation in upper Jhelum floodplain.

Flash flood susceptibility modeling using geo-morphometric and hydrological approaches in Panjkora Basin, Eastern Hindu Kush, Pakistan

This main objective of this study is flash flood susceptibility modeling using geo-morphometric and hydrological approaches in Panjkora Basin, Eastern Hindu Kush, Pakistan. In the study region, flash flood is one of the horrific and recurrent hydro-meteorological disasters causing damages to human life, their properties, and infrastructure. Watershed modeling approach is implemented to delineate Panjkora Basin, its sub-basins, and extract drainage network by utilizing Advance Space borne Thermal Emission and Reflection Radiometer Global Digital Elevation Model as an input data in geographic information system environment. A total of 30 sub-basins were delineated using threshold of 25 km2. The geo-morphometric parameters of each sub-basin were computed by applying Hortonian, Schumm, and Strahler Geo-morphological laws. The value of each parameter was normalized and aggregated into geo-morphometric ranking number depicting the degree of flash flood susceptibility. Surface run-off depth of each sub-basin is estimated by applying Natural Resource Conservation Service Curve Number hydrological model. Both models outputs were integrated by implementing weighted overlay analysis technique and susceptibility map is obtained. The resultant map was analyzed and zonated into very high, high, moderate, low, and very low flash flood susceptibility zones. These zones were spread over an area of 1441 km2 (27%), 1950 km2 (36.5%), 1252 km2 (23.4%), 604 km2 (11.3%), and 98 km2 (1.8%), respectively. Spatially, the very high susceptible zone is located in the upstream areas, characterized by snow covered peaks, steep gradient (> 30°), and high drainage density (> 1.7 km/km2), and geologically dominated by igneous and metamorphic lithological units. Analysis indicated that flash flood susceptibility is directly increases with increasing surface run-off and geo-morphometric ranking number. A new model is developed to geo-visualize the spatial pattern of flash flood susceptibility. Accuracy of the model is assessed using global positioning system-based primary data regarding past-flood damages and flood marks. The study results can facilitate Disaster Management Authorities and flood dealing line agencies to initiate location-specific flood-risk reduction strategies in highly susceptible areas of Panjkora Basin. Similarly, this methodological approach can be adapted for any highland river system.

Evaluation of detection ability of regional radar network in complex terrain based on digital elevation model: a sample study of Fujian province in China

Many countries employ weather radar networks to provide data for weather forecasting offices and research institutes, but most of the stations are located in mountainous regions, where terrain obstacles cause beam blockage. The authors propose a method for evaluating the detection ability of weather radars by combining radar range charts with iso-beam heights and maps of beam exposure intensity. First, methods of drawing radar range charts with iso-beam heights and maps of beam exposure intensity are introduced. Subsequently, the detection ability of the regional weather radar network in Fujian Province, China is evaluated by selecting data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM). During the evaluation, the radar coverage ratio, height–area index, and beam power loss ratio are chosen as indicators. These three parameters describe the radar coverage of Fujian Province from many aspects in detail. The main conclusions of this study are that radar range charts with iso-beam heights, and maps of beam exposure intensity can accurately indicate the detection ability of weather radars and that echo reflectivity needs to be corrected according to the beam exposure intensity rather than the degree of beam blockage caused by terrain obstacles.

Evaluating Glacier Volume Changes since the Little Ice Age Maximum and Consequences for Stream Flow by Integrating Models of Glacier Flow and Hydrology in the Cordillera Blanca, Peruvian Andes

Evaluating the historical contribution of the volume loss of ice to stream flow based on reconstructed volume changes through the Little Ice Age (LIA) can be directly related to the understanding of glacier-hydrology in the current epoch of rapid glacier loss that has disquieting implications for a water resource in the Cordillera Blanca in the Peruvian Andes. However, the accurate prediction of the future glacial meltwater availability for the developing regional Andean society needs more extensive quantitative estimation from long-term glacial meltwater of reconstructed glacial volume. Modeling the LIA paleoglaciers through the mid-19th century (with the most extensive recent period of mountain glacier expansion having occurred around 1850 AD) in different catchments of the Cordillera Blanca allows us to reconstruct glacier volume and its change from likely combinations of climatic control variables and time. We computed the rate and magnitude of centennial-scale glacier volume changes for glacier surfaces between the LIA and the modern era, as defined by 2011 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM V2) and 2008 Light Detection and Range (LiDAR) data. The model simulation showed good agreement with the observed geomorphic data and the volume and surface area (V-S) scaling remained within the 25% error range in the reconstructed simulation. Also, we employed a recently demonstrated approach (Baraër, M. et al.) to calculate meltwater contribution to glacierized catchment runoff. The results revealed multiple peaks of both mean annual and dry season discharge that have never been shown in previous research on the same mountain range.