Integration of remotely sensed indices for land cover changes caused by the 2009 Victorian bushfires using Landsat TM imagery

In order to minimise the bushfires negative impacts on society, an efficient andreliable bushfire detection system was proposed to assess the devastated effects of the2009 Victorian bushfires.It is possible to utilise the repetitive capability of satellite remotesensing imagery to identify the location of change to the Earth's surface and integrate thedifferent remotely sensed indices.The results confirm that the procedure can offer essentialspatial information for bushfire assessment.

Changes in the Shoreline Position Caused by Natural Processes for Coastline of Marsa Alam – Hamata, Red Sea, Egypt

The probability of storms and ice-drift events and their impact on coasts is expected to increase as result of climate change. Multi-years shoreline mapping is considered a valuable task for coastal monitoring and assessment. This paper presents shoreline maps illustrating the shoreline erosion accretion pattern in the coastal area between Marsa Alam – Hamata of Red Sea coastline by using different sources of remote sensing data. In the present study, Landsat MSS (1972), Landsat TM (1990), Landsat ETM+ (1998, 2000) and Terra Aster (2007) satellite images were used. In this study, two techniques were used to estimate rate of shoreline retreat. The first technique is corresponding to the formation of automated shoreline positions and the second one is for estimating rate of shoreline change based on data of remote sensing applying Digital Shoreline Analysis System (DSAS) software. In this study, the End Point Rate (EPR) was calculated by dividing the distance of shoreline movement by the time elapsed between the earliest and latest measurements at each transect. Alongshore rate changes shows that there are changes of erosion and accretion pattern due to coastal processes and climate changes.

An Investigation of the Dimensional Changes of Polymer Mixture Tablets Containing a Soluble Drug, Using an Image Analysis Method. Influence of These Characteristics on Drug Release and Its Mechanism

The properties and characteristics of the polymer used for the preparation of matrix drug delivery systems considerably influence their performance and the extent of drug release and its mechanism. The objective of this research was to examine the dimensional changes, and gel evolution of polymer matrices consisting of three different polymers Polyox, sodium alginate (hydrophilic) and Ethocel (hydrophobic), using an image analysis method. Furthermore to explore how these changes influence the release rate of a soluble drug namely, venlafaxine. All tablets displayed marked dimensional expansion and gel growth particularly those consisting of two hydrophilic polymers Polyox/sodium alginate (POL/SA/V) compared to those consisting of the hydrophilic/hydrophobic Polyox/Ethocel (POL/ET/V). Similarly the thickness of the gel layer in POL/SA/V matrices increased considerably with time up to 8 hours. In general our findings show that the POL/SA/V matrices, due to their thicker gel layer produced a more effective barrier which results in a more pronounced sustained release delivery. This accounts for the slower and smaller overall drug release observed with the POL/SA/V matrices compared to those containing POL/ET/V and indicates that the formation of a thick and durable gel barrier is a characteristic necessary for the preparation of sustained drug release systems. Moreover the solubility of venlafaxine in combination with the polymer’s properties appears to play an important role on the extent of drug release and the release mechanism. Overall the polymer mixtures examined comprise a useful and promising combination of materials for the development and manufacture of sustained release preparations based on these polymers.

Integrating cross-sensor high spatial resolution satellite images to detect subtle forest vegetation change in the Purple Mountains,a national scenic spot in Nanjing,China

Accurate information on the location and magnitude of vegetation change in scenic areas can guide the configuration of tourism facilities and the formulation of vegetation protection measures.High spatial resolution remote sensing images can be used to detect subtle vegetation changes.The major objective of this study was to map and quantify forest vegetation changes in a national scenic location,the Purple Mountains of Nanjing,China,using multi-temporal cross-sensor high spatial resolution satellite images to identify the main drivers of the vegetation changes and provide a reference for sustainable management.We used Quickbird images acquired in 2004,IKONOS images acquired in 2009,and WorldView2 images acquired in 2015.Four pixel-based direct change detection methods including the normalized difference vegetation index difference method,multi-index integrated change analysis(MIICA),principal component analysis,and spectral gradient difference analysis were compared in terms of their change detection performances.Subsequently,the best pixel-based detection method in conjunction with object-oriented image analysis was used to extract subtle forest vegetation changes.An accuracy assessment using the stratified random sampling points was conducted to evaluate the performance of the change detection results.The results showed that the MIICA method was the best pixel-based change detection method.And the object-oriented MIICA with an overall accuracy of 0.907 and a kappa coefficient of 0.846 was superior to the pixel-based MIICA.From 2004 to 2009,areas of vegetation gain mainly occurred around the periphery of the study area,while areas of vegetation loss were observed in the interior and along the boundary of the study area due to construction activities,which contributed to 79%of the total area of vegetation loss.During 2009–2015,the greening initiatives around the construction areas increased the forest vegetation coverage,accounting for 84%of the total area of vegetation gain.In spite of this,vegetation loss occurred in the interior of the Purple Mountains due to infrastructure development that caused conversion from vegetation to impervious areas.We recommend that:(1)a local multi-agency team inspect and assess law enforcement regarding natural resource utilization;and(2)strengthen environmental awareness education.

Study of Forest Cover Change Dynamics between 2000 and 2015 in the Ikongo District of Madagascar Using Multi-Temporal Landsat Satellite Images

Satellite images are considered reliable data that preserve land cover information. In the field of remote sensing, these images allow relevant analyses of changes in space over time through the use of computer tools. In this study, we have applied the “discriminant” change detection algorithm. In this, we have verified its effectiveness in multi-temporal studies. Also, we have determined the change in forest dynamics in the Ikongo district of Madagascar between 2000 and 2015. During the treatments, we have used the Landsat TM satellite images for the years 2000, 2005 and 2010 as well as ETM+ for 2015. Thus, analyses carried out have allowed us to note that between 2000-2005, 1.4% of natural forest disappeared. And, between 2005-2010, forests degradation was 1.8%. Also, between 2010-2015, about 0.5% of the natural forest conserved in 2010 disappeared. Furthermore, we have found that the discriminant algorithm is considerably efficient in terms of monitoring the dynamics of forest cover change.

Smart Photogrammetric and Remote Sensing Image Processing for Very High Resolution Optical Images——Examples from the CRC-AGIP Lab at UNB

This paper introduces some of the image processing techniques developed in the Canada Research Chair in Advanced Geomatics Image Processing Laboratory (CRC-AGIP Lab) and in the Department of Geodesy and Geomatics Engineering (GGE) at the University of New Brunswick (UNB), Canada. The techniques were developed by innovatively/“smartly” utilizing the characteristics of the available very high resolution optical remote sensing images to solve important problems or create new applications in photogrammetry and remote sensing. The techniques to be introduced are: automated image fusion (UNB-PanSharp), satellite image online mapping, street view technology, moving vehicle detection using single set satellite imagery, supervised image segmentation, image matching in smooth areas, and change detection using images from different viewing angles. Because of their broad application potential, some of the techniques have made a global impact, and some have demonstrated the potential for a global impact.

Delineating suspended sediment concentration patterns in surface waters of the Changjiang Estuary by remote sensing analysis

Three Landsat TM imageries （taken on 18 May 1987,4 August 1998 and 28 July 2007） were used as the data source to identify the spatial and temporal variations of the suspended sediment concentration （SSC） in surface waters of the Changjiang Estuary.Atmospheric correction was carried out to determine the water-leaving reflectance using the FLAASH module.A regression equation between surveyed SSC and suspended sediment index was chosen to retrieve the SSC from the Landsat TM images.In addition,tidal harmonic analysis was performed to calculate tidal conditions corresponding to the acquisition time of satellite images.The results show that the SSC spatial patterns are similar to the in situ observation results,which show the highest SSC in the region of turbidity maximum zone in the Changjiang Estuary.For the period of 1987 to 2007,the SSC pattern is controlled mainly by tidal dynamic conditions and wind speeds,rather than sediment discharges from the river.

Geographic Object-Based Image Analysis of Changes in Land Cover in the Coastal Zones of the Red River Delta (Vietnam)

The majority of the population and economic activity of the northern half of Vietnam is clustered in the Red River Delta and about half of the country’s rice production takes place here. There are significant problems associated with its geographical position and the intensive exploitation of resources by an overabundant population (population density of 962 inhabitants/km2). Some thirty years after the economic liberalization and the opening of the country to international markets, agricultural land use patterns in the Red River Delta, particularly in the coastal area, have undergone many changes. Remote sensing is a particularly powerful tool in processing and providing spatial information for monitoring land use changes. The main methodological objective is to find a solution to process the many heterogeneous coastal land use parameters, so as to describe it in all its complexity, specifically by making use of the latest European satellite data (Sentinel-2). This complexity is due to local variations in ecological conditions, but also to anthropogenic factors that directly and indirectly influence land use dynamics. The methodological objective was to develop a new Geographic Object-based Image Analysis (GEOBIA) approach for mapping coastal areas using Sentinel-2 data and Landsat 8. By developing a new segmentation, accuracy measure, in this study was determined that segmentation accuracies decrease with increasing segmentation scales and that the negative impact of under-segmentation errors significantly increases at a large scale. An Estimation of Scale Parameter (ESP) tool was then used to determine the optimal segmentation parameter values. A popular machine learning algorithms (Random Forests-RFs) is used. For all classifications algorithm, an increase in overall accuracy was observed with the full synergistic combination of available data sets.

A Comparative Study of Image Classification Algorithms for Landscape Assessment of the Niger Delta Region

A critical problem associated with the southern part of Nigeria is the rapid alteration of the landscape as a result of logging, agricultural practices, human migration and expansion, oil exploration, exploitation and production activities. These processes have had both positive and negative effects on the economic and socio-political development of the country in general. The negative impacts have led not only to the degradation of the ecosystem but also posing hazards to human health and polluting surface and ground water resources. This has created the need for the development of a rapid, cost effective and efficient land use/land cover (LULC) classification technique to monitor the biophysical dynamics in the region. Due to the complex land cover patterns existing in the study area and the occasionally indistinguishable relationship between land cover and spectral signals, this paper introduces a combined use of unsupervised and supervised image classification for detecting land use/land cover (LULC) classes. With the continuous conflict over the impact of oil activities in the area, this work provides a procedure for detecting LULC change, which is an important factor to consider in the design of an environmental decision-making framework. Results from the use of this technique on Landsat TM and ETM+ of 1987 and 2002 are discussed. The results reveal the pros and cons of the two methods and the effects of their overall accuracy on post-classification change detection.

Normal tension glaucoma: from the brain to the eye or the inverse?

Glaucoma is a chronic, progressive optic neuropathy characterized by the loss of peripheral vision first and then central vision. Clinically, normal tension glaucoma is considered a special subtype of glaucoma, in which the patient’s intraocular pressure is within the normal range, but the patient experiences typical glaucomatous changes. However, increasing evidence has challenged the traditional pathophysiological view of normal tension glaucoma, which is based only on intraocular pressure, and breakthroughs in central nervous system imaging may now greatly increase our knowledge about the mechanisms underlying normal tension glaucoma. In this article, we review the latest progress in understanding the pathogenesis of normal tension glaucoma and in developing imaging techniques to detect it, to strengthen the appreciation for the connection between normal tension glaucoma and the brain.

Responses of Alpine Wetlands to Climate Changes on the Qinghai-Tibetan Plateau Based on Remote Sensing

The alpine wetlands in QTP(Qinghai-Tibetan Plateau)have been profoundly impacted along with global climate changes.We employ satellite datasets and climate data to explore the relationships between alpine wetlands and climate changes based on remote sensing data.Results show that:1)the wetland NDVI(Normalized Difference Vegetation Index)and GPP(Gross Primary Production)were more sensitive to air temperature than to precipitation rate.The wetland ET(evapotranspiration)across alpine wetlands was greatly correlated with precipitation rate.2)Alpine wetlands responses to climate changes varied spatially and temporally due to different geographic environments,variety of wetland formation and human disturbances.3)The vegetation responses of the Zoige wetland was the most noticeable and related to the temperature,while the GPP and NDVI of the Qiangtang Plateau and Gyaring-Ngoring Lake were significantly correlated with both temperature and precipitation.4)ET in the Zoige wetland showed a significantly positive trend,while ET in Maidika wetland and the Qiangtang plateau showed a negative trend,implying wetland degradation in those two wetland regions.The complexities of the impacts of climate changes on alpine wetlands indicate the necessity of further study to understand and conserve alpine wetland ecosystems.

Development of a large-scale remote sensing ecological index in arid areas and its application in the Aral Sea Basin

The Aral Sea Basin in Central Asia is an important geographical environment unit in the center of Eurasia.It is of great significance to the ecological protection and sustainable development of Central Asia to carry out dynamic monitoring and effective evaluation of the eco-environmental quality of the Aral Sea Basin.In this study,the arid remote sensing ecological index(ARSEI)for large-scale arid areas was developed,which coupled the information of the greenness index,the salinity index,the humidity index,the heat index,and the land degradation index of arid areas.The ARSEI was used to monitor and evaluate the eco-environmental quality of the Aral Sea Basin from 2000 to 2019.The results show that the greenness index,the humidity index and the land degradation index had a positive impact on the quality of the ecological environment in the Aral Sea Basin,while the salinity index and the heat index exerted a negative impact on the quality of the ecological environment.The eco-environmental quality of the Aral Sea Basin demonstrated a trend of initial improvement,followed by deterioration,and finally further improvement.The spatial variation of these changes was significant.From 2000 to 2019,grassland and wasteland(saline alkali land and sandy land)in the central and western parts of the basin had the worst ecological environment quality.The areas with poor ecological environment quality are mainly distributed in rivers,wetlands,and cultivated land around lakes.During the period from 2000 to 2019,except for the surrounding areas of the Aral Sea,the ecological environment quality in other areas of the Aral Sea Basin has been improved in general.The correlation coefficients between the change in the eco-environmental quality and the heat index and between the change in the eco-environmental quality and the humidity index were–0.593 and 0.524,respectively.Climate conditions and human activities have led to different combinations of heat and humidity changes in the eco-environmental quality of the Aral Sea Basin.However,human activities had a greater impact.The ARSEI can quantitatively and intuitively reflect the scale and causes of large-scale and long-time period changes of the eco-environmental quality in arid areas;it is very suitable for the study of the eco-environmental quality in arid areas.

Land Use and Land Cover Change Detection in the Saudi Arabian Desert Cities of Makkah and Al-Taif Using Satellite Data

Land use/land cover (LULC) changes have become a central issue in current global change and sustainability research. Saudi Arabia has undergone significant change in land use and land cover since the government embarked on a course of intense national development 30 years ago, as a result of huge national oil revenues. This study evaluates LULC change in Makkah and Al-Taif, Saudi Arabia from 1986 to 2013 using Landsat images. Maximum likelihood and object-oriented classification were used to develop LULC maps. The change detection was executed using post-classification comparison and GIS. The results indicated that urban areas have increased over the period by approximately 174% in Makkah and 113% in Al-Taif. Analysis of vegetation cover over the study area showed a variable distribution from year to year due to changing average precipitation in this environment. Object-based classification provided slightly greater accuracy than maximum likelihood classification. Information provided by satellite remote sensing can play an important role in quantifying and understanding the relationship between population growth and LULC changes, which can assist future planning and potential environmental impacts of expanding urban areas.

Land Use and Land Cover Changes in Arid Region: The Case New Urbanized Zone, Northeast Cairo, Egypt

The spatial characteristics of land cover are useful for understanding the various impacts of human activity on the overall ecological conditions of the urban environment. The multi-temporal Landsat images (TM) between the years of 1990 and 2003 were used together with the Geographic Information System (GIS) techniques to evaluate the environmental changes in the area around Gabal El Hamza and the surrounding urban expansion in the new urban cities at the northeast side of the Greater Cairo by using the post classification change detection technique and field investigation. Five major units were determined including: urban, cultivated land, Holocene sand dunes, Oligocene basalt and Miocene–Pleistocene sediments. The cultivated cover changed from 89.6 to 150.4 km2 for the years of 1990 and 2003 respectively. The urban area increased from 49.5 to 120.9 km2 with a great value of change reached 71.3 km2 . The basaltic exposures changed from 3 to 3.75 km2 . The sandy cover decreased from 68.9 to 60.1 km2 and the exposures of the rock units changed from 904.8 to 780.8 km2 with removing 124 km2 in 13 years. The total accuracy of the Landsat-derived land cover data was 95 and 92% for the years 1990 and 2003 respectively. Landsat TM thermal infrared data indicated that the surface temperature was strongly affected by the land cover changes.

Magnetic Particle Imaging for Magnetic Hyperthermia Treatment: Visualization and Quantification of the Intratumoral Distribution and Temporal Change of Magnetic Nanoparticles in Vivo

Purpose: Magnetic hyperthermia treatment (MHT) is a strategy for cancer therapy using the tem-perature rise of magnetic nanoparticles (MNPs) under an alternating magnetic field (AMF). Re-cently, a new imaging method called magnetic particle imaging (MPI) has been introduced. MPI allows imaging of the spatial distribution of MNPs. The purpose of this study was to investigate the feasibility of visualizing and quantifying the intratumoral distribution and temporal change of MNPs and predicting the therapeutic effect of MHT using MPI. Materials and Methods: Colon-26 cells (1 × 106 cells) were implanted into the backs of eight-week-old male BALB/c mice. When the tumor volume reached approximately 100 mm3, mice were divided into untreated (n = 10) and treated groups (n = 27). The tumors in the treated group were directly injected with MNPs (Resovist?) with iron concentrations of 500 mM (A, n = 9), 400 mM (B, n = 8), and 250 mM (C, n = 10), respectively, and MHT was performed using an AMF with a frequency of 600 kHz and a peak amplitude of 3.5 kA/m. The mice in the treated group were scanned using our MPI scanner immediately before, immediately after, 7 days, and 14 days after MHT. We drew a region of interest (ROI) on the tumor in the MPI image and calculated the average, maximum, and total MPI values and the number of pixels by taking the threshold value for extracting the contour as 40% of the maximum MPI value (pixel value) within the ROI. These parameters in the untreated group were taken as zero. We also measured the relative tumor volume growth (RTVG) defined by (V-V0)/V0, where V0 and V are the tumor volumes immediately before and after MHT, respectively. Results: The average, maximum, and total MPI values decreased up to 7 days after MHT and remained almost constant thereafter in all groups, whereas the number of pixels tended to increase with time. The RTVG values in Groups A and B were significantly lower than those in the control group 3 days or more and 5 days or more after MHT, respectively. The above four parameters were significantly inversely correlated with the RTVG values 5, 7, and 14 days after MHT. Conclusion: MPI can visualize and quantify the intratumoral distribution and temporal change of MNPs before and after MHT. Our results suggest that MPI will be useful for predicting the therapeutic effect of MHT and for the treatment planning of MHT.

Landscape Changes from 1974 to 1995 in the Upper Minjiang River Basin, China

Landscape changes were traced over the 20 years from 1974 to 1995 in the upper Minjiang River basin, one of the most important forest regions in China, based on satellite image interpretation to provide basic data for local decision-making as well as sustainable landscape use and management. Results revealed that landscape from 1974 to 1995 changed at the regional scale as the area of forestland decreased, while cropland, shrubland, economic forest, grassland, and built-up land increased. Landscape changes mainly occurred in forestland, shrubland, grassland, economic forest, and built-up land. Moreover, the changes among forestland, shrubland, and grassland were the largest, influencing the whole characteristics of the changes in the basin. Analysis of the changes between 1974 and 1995 in the study area indicated that landscape heterogeneity and fragmentation increased, whereas landscape connectivity decreased. There were multiple reasons for landscape changes. A principal component analysis (PCA) was used to quantitatively study driving forces of landscape changes. The PCA results showed that economic and population factors were the principal driving forces of landscape changes from 1974 to 1995 in the upper Minjiang River basin, and that PCA was a suitable method for investigating driving forces of landscape changes.

Age-related changes of lateral ventricular width and periventricular white matter in the human brain: a diffusion tensor imaging study

Introduction Aging is the accumulation of multidimensional deterioration of process- ing of biological, psychological, and social changes with expansion over time （Bowen and Atwood, 2004; Grady, 2012）. Aging-related changes are typically accompanied by decline in cognitive function, urinary control, sensory-motor function, and gait ability （Bradley et al., 1991; Bowen and Atwood, 2004; Hedden and Gabrieli, 2004; Grady, 2012; Moran et al., 2012）. In addition, a number of studies have suggested changes in brain structure with normal aging, such as decrease in cortical thickness or increase in ventricular width （Blatter et al., 1995; Tang et al., 1997; Uylings and de Brabander, 2002; Preul et al., 2006; Apostolova et al., 2012）. In particular, ventricular enlargement has been suggested as a structural biomarker for normal aging and progression of some illnesses, such as Alzheimer＇s disease （Blatter et al., 1995; Tang et al.,

Spatial assessment of forest cover and land-use changes in the Hindu-Kush mountain ranges of northern Pakistan

Anthropogenic activities and natural processes are continuously altering the mountainous environment through deforestation, forest degradation and other land-use changes. It is highly important to assess, monitor and forecast forest cover and other land-use changes for the protection and conservation of mountainous environment. The present study deals with the assessment of forest cover and other land-use changes in the mountain ranges of Dir Kohistan in northern Pakistan, using high resolution multi-temporal SPOT-5 satellite images. The SPOT-5 satellite images of years 2004, 2007, 2010 and 2013 were acquired and classified into land-cover units. In addition, forest cover and land-use change detection map was developed using the classified maps of 2004 and 2013. The classified maps were verified through random field samples and Google Earth imagery(Quick birds and SPOT-5). The results showed that during the period 2004 to 2013 the area of forest land decreased by 6.4%, however, area of range land and agriculture land have increased by 22.1% and 2.9%, respectively. Similarly, barren land increased by 1.1%, whereas, area of snow cover/glacier is significantly decreased by 21.3%. The findings from the study will be useful for forestry and landscape planning and can be utilized by the local, provincial and national forest departments; and REDD+ policy makers in Pakistan.

Glacier Extent and Volume Change(1966～2000) on the Su-lo Mountain in Northeastern Tibetan Plateau,China

The topographic maps of 1:50,000 scales,aerial photographs taken in 1966,one Landsat image taken in 1999,and SRTM data from 2000 were used to quantify the losses in area and volume of the glaciers on the Su-lo Mountain,in the northeastern Tibetan Plateau,China in the past 30 years.The total glacier area decreased from 492.9km2 in 1966 to 458.2km2 in 1999.The volume loss of the studied glaciers reached 1.4 km3 from 1966 to 2000.This agrees with documented changes in other mountain glaciers of the whole Tibetan Plateau.

Variations of Laohugou Glacier No.12 in the western Qilian Mountains, China, from 1957 to 2015

Glaciers were solid reservoirs and important water resources in western China,but they were retreating significantly in context of global warming.Laohugou Glacier No.12 was the largest valley glacier in Qilian Mountains.In this study,realtime kinematic(RTK)data,topographic map and World View-2 satellite imagery were used to measure changes in terminus,extent and volume of Laohugou Glacier No.12.Results showed that Laohugou Glacier No.12 was shrinking significantly since 1957.From1960 to 2015,the terminus reduction of Laohugou Glacier No.12 was 402.96 m(3.99%)in total,and glacier length decreased to 9.7 km from 10.1 km.Reduction of glacier area and volume were the most obvious.From 1957 to 2015,glacier area and volume decreased by 1.54 km^2(7.03%)and 0.1816 km^3,respectively.Reduction trend of terminus and area was slowing in 1950-1980s,even stable for a period in the mid-1980s,and then accelerated.Ice core analysis result and nearly meteorological station data shown an increasing trend of temperature in 1957-2015,it was a main reason of continuous retreating of Laohugou Glacier No.12.