Analysing urban dynamics using multi-temporal satellite images in the case of a mountain area,Sinaia (Romania)

The purpose of this study is to produce an analysis of the urban expansion in the case of a mountain resort in the Romanian Carpathians through the integration of different cartographic and ancillary material in the remote sensing imagery processing. The spatial pattern analysis of the changes underwent by the urban landscape was based on multi-temporal information sources, covering 28 years, which highlighted the major turning points in landscape evolution, meaning industrial development under the communist production planning and residential expansion in recent years. To fully exploit the combination of satellite image processing in IDRISI, the manual image classification and database interrogation in ArcGis, we used a uniform grid, representing a set of vector data for each year available from the Landsat image archive. The image comparison was completed by using appropriate quantitative techniques. In conclusion the urban landscape evolution was linked to the socio-economic context. At a historic scale the main phenomenon identified is the concentration of mass tourism facilities, located in contiguity to a protected area, a situation reflected in the constant fragmentation of surfaces covered with vegetation at the urban fringe. In the digital earth science, the interplay between mountain ecosystems and human activities encompasses a key role in the management of viable mountain landscapes.     

Mapping and analyzing the local climate zones in China's 32 major cities using Landsat imagery based on a novel convolutional neural network

The Local Climate Zone (LCZ) scheme provides researchers with a standard method to monitor the Urban Heat Island (UHI) effect and conduct temperature studies. H...     

A study of a matching pixel by pixel (MPP) algorithm to establish an empirical model of water quality mapping,as based on unmanned aerial vehicle (UAV) images

Linear regression models are a popular choice for the relationships between water quality parameters and bands (or band ratios) of remote sensing data. However, this research regards the phenomena of mixed pixels, specular reflection, and water fluidity as the challenges to establish a robust regression model. Based on the data of measurements in situ and remote sensing data, this study presents an enumeration-based algorithm, called matching pixel by pixel (MPP), and tests its performance in an empirical model of water quality mapping. Four small reservoirs, which cover a mere several hundred-thousand m², in Kinmen, Taiwan, are selected as the study sites. The multispectral sensors, carried on an unmanned aerial vehicle (UAV), are adopted to acquire remote sensing data regarding water quality parameters, including chlorophyll-a (Chl-a), Secchi disk depth (SDD), and turbidity in the reservoirs. The experimental results indicate that, while MPP can reduce the influence of specular reflection on regression model establishment, specular reflection does hamper the correction of thematic map production. Due to water fluidity, sampling in situ should be followed by UAV imaging as soon as possible. Excluding turbidity, the obtained estimation accuracy can satisfy the national standard.     

Developing a semi-analytical algorithm to estimate particulate organic carbon (POC) levels in inland eutrophic turbid water based on MERIS images: A case study of Lake Taihu

Particulate organic carbon (POC) plays an important role in the carbon cycle in water due to its biological pump process. In the open ocean, algorithms can accurately estimate the surface POC concentration. However, no suitable POC-estimation algorithm based on MERIS bands is available for inland turbid eutrophic water. A total of 228 field samples were collected from Lake Taihu in different seasons between 2013 and 2015. At each site, the optical parameters and water quality were analyzed. Using in situ data, it was found that POC-estimation algorithms developed for the open ocean and coastal waters using remote sensing reflectance were not suitable for inland turbid eutrophic water. The organic suspended matter (OSM) concentration was found to be the best indicator of the POC concentration, and POC has an exponential relationship with the OSM concentration. Through an analysis of the POC concentration and optical parameters, it was found that the absorption peak of total suspended matter (TSM) at 665 nm was the optimum parameter to estimate POC. As a result, MERIS band 7, MERIS band 10 and MERIS band 12 were used to derive the absorption coefficient of TSM at 665 nm, and then, a semi-analytical algorithm was used to estimate the POC concentration for inland turbid eutrophic water. An accuracy assessment showed that the developed semi-analytical algorithm could be successfully applied with a MAPE of 31.82% and RMSE of 2.68 mg/L. The developed algorithm was successfully applied to a MERIS image, and two full-resolution MERIS images, acquired on August 13, 2010, and December 7, 2010, were used to map the POC spatial distribution in Lake Taihu in summer and winter.     

Application of the Fisher's “Horizon Viewshed” to a proposed power transmission line in Nozzano (Italy)

Visibility algorithms have progressed very little since early GIS software, and today the typical approach is still based on the simple binary logic (visible – not visible). Specialized packages, such as Esri's 3DAnalyst, provide tools able only to identify the cells from which an observer can see the evaluated target object. This technical note presents an experimental approach to combining different Esri tools into a model in order to return the visibility analysis based on the Fisher's “horizon viewshed” approach (Fisher, 1996 ). The latter consists in evaluating whether an object in the landscape rises above the skyline or remains below it. The model has been applied to study the visual impact of an High Voltage Power line in the area of Nozzano Castle, Lucca (Italy).     

Bathymetrical influences on spatial and temporal characteristics of chlorophyll-a concentrations in the Southern Ocean from 2002 to 2012 (October to March) using MODIS

Phytoplankton blooms, particularly in the Southern Ocean, can have significant impact on global biogeochemistry cycling. To investigate the accuracy of chlorophyll-a distribution, and to better understand the spatial and temporal dynamics of phytoplankton biomass, we examine chlorophyll-a estimates (October–March from 2002 to 2012) derived from Moderate Resolution Imaging Spectrometer (MODIS) data following the ocean chlorophyll-a 3 model (OC3M) algorithm. Noticeable seasonality occurs in the temporal distribution of chlorophyll-a concentrations, which shows the highest value in December and January and an increasing tendency during the 2002–2012 period. The spatial distribution of chlorophyll-a varies greatly with latitude, as higher latitudes experience more phytoplankton blooms (chlorophyll-a concentration larger than 1 mg/m³) and marginal seas (Ross Sea and Amundsen Sea) show different bloom anomalies caused by two dominant algae species. Areas at higher latitudes and shallow water (<500 m) experience the shorter ice-free periods with greater seasonality. A noticeable bathymetry gradient exists at 2500-m isobaths, while water at the 500–2500-m depth experiences quite long ice-free periods with a stable water environment. Blooms generally occur near topographic features where currents have strong interactions when the water depth is more than 2500 m. Based on these findings, we can classify the Southern Ocean into two bloom subregions, 0–500 m as an enhanced bloom zone (EBZ), and 500–2500 m as a moderate bloom zone (MBZ). The EBZ has a quite high-bloom probability of about 30%, while the MBZ has only 10%.     

Coseismic fault rupture detection and slip measurement by ASAR precise correlation using coherence maximization: application to a north-south blind fault in the vicinity of Bam (Iran)

Using the phase differences between satellite radar images recorded before and after an earthquake, interferometry allows mapping the projection along the line of sight (LOS) of the ground displacement. Acquisitions along multiple LOS theoretically allow deriving the complete deformation vector; however, due to the orbit inclination of current radar satellites, precision is poor in the north-south direction. Moreover, large deformation gradients (e.g., fault ruptures) prevent phase identification and unwrapping and cannot be measured directly by interferometry. Subpixel correlation techniques using the amplitude of the radar images allow measuring such gradients, both in slant-range and in azimuth. In this letter, we use a correlation technique based on the maximization of coherence for a radar pair in interferometric conditions, using the complex nature of the data. In the case of highly coherent areas, this technique allows estimating the relative distortion between images. Applied to ASAR images acquired before and after the December 26, 2003 Bam earthquake (Iran), we show that the near-field information retrieved by this technique is useful to constrain geophysical models. In particular, we confirm that the major gradients of ground displacement do not occur across the known fault scarp but approximately 3 km west of it, and we also estimate directly the amplitude of right lateral slip, while retrieving this value from interferometry requires passing through the use of a model for the earthquake fault and slip.     

Use of geomorphological units to improve drainage network extraction from a DEM : Comparison between automated extraction and photointerpretation methods in the Carraixet catchment (Valencia, Spain)

Drainage networks are one of the main elements characterizing basins, and network topology and geometry form the basis of many hydrological and geomorphological models (eg Geomorphological Unitary Hydrograph). The identification and manual delineation of channel networks from maps or aerial photographs requires much time and effort. In the last two decades, algorithms and procedures for automated extraction of drainage networks from digital elevation data have been developed and implemented in many specialized software applications. Nevertheless, automatically delineated channel networks do not always show close agreement with manually delineated networks. This paper describes a comparative analysis between a drainage network automatically extracted from a gridded digital elevation model, and the drainage network delineated manually from stereographic pairs of aerial photographs. The analysis showed that the automatic extraction technique may be adequate for catchment headwaters, but is inappropriate in the middle and lower basins, especially for alluvial fans and calcareous platforms. The paper suggests improving the automatic extraction technique by adapting it to operate with different parameters for each of the geomorphological units within the catchment.     

An improved dark object method to retrieve 500 m-resolution AOT (Aerosol Optical Thickness) image from MODIS data: A case study in the Pearl River Delta area,China

This paper presents an improved Dark Dense Vegetation (DDV) method for retrieving 500 m-resolution aerosol optical depth (AOT) based on MOD04-C005 arithmetic with the Moderate Resolution Imaging Spectroradiometer (MODIS) from the National Aeronautics and Space Administration (NASA). The improvements include change of the movement pattern of retrieval window, selection of a more suitable aerosol type, and storage of the look-up table. The method is then applied to obtain the AOT over the Pearl River Delta region (PRD). By comparing the results with the co-temporal ground sunphotometer observations in 2010, the correlation coefficient is found to be 0.794 with RMSE 0.139 and their variations remain consistent. Contrasts between model values in 2008 and MODIS AOT products in the same date also reveal a high accuracy of the improved DDV method. We also performed sensitivity tests to analyze the impacts of several parameters on apparent reflectance at different bands, and the results show that apparent reflectance is much more sensitive to surface reflectance and AOT than to elevation.