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PubMed2004

[Accuracy analysis of vegetation mapping for Meili Snow Mountain area, northwest Yunnan, China].

The Meili Snow Mountain (28 degrees 20'-28 degrees 33'N, 98 degrees 30'-8 degrees 52'E) is a very famous mountain in Northwest Yunnan of China by its rich and well protected biodiversity and Tibetan cultural diversity. By applying 3S (RS-Remote Sensing, GIS-Geography Information System, GPS-Global Position System) technology, the 1:50000 vegetation map of Meili Snow Mountain area (total about 332 km2) was drawn out. The vegetation in this area was classified into 18 vegetation types except for stone, glacier and river system. The vegetation map was rectified by applying the GPS points got from the fields. The numbers of GPS points were calculated by the formula of numbers of samples in statistics. 313 GPS points were used to rectify the vegetation map. The numbers were fit for the formula of numbers of samples in Statistics. The accuracy and verify of vegetation types distribution in the map was analyzed by building a Probability Error Matrix (PEM) and through the variance analysis. The results indicated that the overall accuracy (OA) of the vegetation map was 84.7%. The accuracy of vegetation map finished by 3S technology was lied on the area of the region and the grade of vegetation class first, but the grade of vegetation class classified by remote sensing technology disaccord with the traditional vegetation class system. The other factos deciding the accuracy of vegetation were the distinguish ability of Remote Sensing image, the accuracy of distinguish, and the numbers of the samples, including vegetation class experts knowledge.

Abies↗

PubMed2003

Cluster analysis of structural stage classes to map wildland fuels in a Madrean ecosystem.

Geospatial information technology is changing the nature of fire mapping science and management. Geographic information systems (GIS) and global positioning system technology coupled with remotely sensed data provide powerful tools for mapping, assessing, and understanding the complex spatial phenomena of wildland fuels and fire hazard. The effectiveness of these technologies for fire management still depends on good baseline fuels data since techniques have yet to be developed to directly interrogate understory fuels with remotely sensed data. We couple field data collections with GIS, remote sensing, and hierarchical clustering to characterize and map the variability of wildland fuels within and across vegetation types. One hundred fifty six fuel plots were sampled in eight vegetation types ranging in elevation from 1150 to 2600 m surrounding a Madrean 'sky island' mountain range in the southwestern US. Fuel plots within individual vegetation types were divided into classes representing various stages of structural development with unique fuel load characteristics using a hierarchical clustering method. Two Landsat satellite images were then classified into vegetation/fuel classes using a hybrid unsupervised/supervised approach. A back-classification accuracy assessment, which uses the same pixels to test as used to train the classifier, produced an overall Kappa of 50% for the vegetation/fuels map. The map with fuel classes within vegetation type collapsed into single classes was verified with an independent dataset, yielding an overall Kappa of 80%.

Cluster Analysis↗

PubMed2001

Remote sensing of landscape-level coastal environmental indicators.

Advances in technology and decreases in cost are making remote sensing (RS) and geographic information systems (GIS) practical and attractive for use in coastal resource management. They are also allowing researchers and managers to take a broader view of ecological patterns and processes. Landscape-level environmental indicators that can be detected by Landsat Thematic Mapper (TM) and other remote sensors are available to provide quantitative estimates of coastal and estuarine habitat conditions and trends. Such indicators include watershed land cover, riparian buffers, shoreline and wetland changes, among others. With the launch of Landsat 7, the cost of TM imagery has dropped by nearly a factor of 10, decreasing the cost of monitoring large coastal areas and estuaries. New satellites, carrying sensors with much finer spatial (1-5 m) and spectral (200 narrow bands) resolutions are being launched, providing a capability to more accurately detect changes in coastal habitat and wetland health. Advances in the application of GIS help incorporate ancillary data layers to improve the accuracy of satellite land-cover classification. When these techniques for generating, organizing, storing, and analyzing spatial information are combined with mathematical models, coastal planners and managers have a means for assessing the impacts of alternative management practices.

Conservation of Natural Resources↗

PubMed1992

Optical remote measurement of toxic gases.

Enactment of the Clean Air Act Amendments (CAAA) of 1990 has resulted in increased ambient air monitoring needs for industry, some of which may be met efficiently using open-path optical remote sensing techniques. These techniques include Fourier transform spectroscopy, differential optical absorption spectroscopy, laser long-path absorption, differential absorption lidar, and gas cell correlation spectroscopy. With this regulatory impetus, it is an opportune time to consider applying these technologies to the remote and/or path-averaged measurement and monitoring of toxic gases covered by the CAAA. This article reviews the optical remote sensing technology and literature for that application.

Air Pollutants↗

PubMed2004

Remote sensing as a tool for mapping mosquito breeding habitats and associated health risk to assist control efforts and development plans: a case study in Wadi El Natroun, Egypt.

Limited mosquito ground surveys were combined with remote sensing and GIS technologies to identify mosquito breeding habitats in Natroun lakes area and to delineate associated health risks. Mosquito larval surveys were carried out in a small area to characterize positive breeding habitats and determine their geographic coordinates. Mosquitoes (Anopheles multicolor, Culex antennatus and Cx. theileri) were found breeding in water-flooded habitats with dense vegetation cover spatially associated to existing lakes. Chemical analysis indicated that mosquito breeding water was found to be polluted by several sources including agriculture, industrial and domestic sources. This information served as a training set to characterize the spectral signature of mosquitogenic (mosquito-producing) habitats using reflectance data of the Thematic Mapper (TM) sensor aboard Landsat 5 satellite. Following characterization of the spectral signature, satellite data were used to predict, potential mosquito breeding patches over the whole study area. Field surveys were then carried out to assess the accuracy of predicted habitats and those surveys have indicated that all checked sites were positive for mosquito larvae demonstrating an accuracy of 100%. Based on an average adult mosquito flight range of 2 km, GIS was used to create buffer zones around breeding habitats describing areas at risk from mosquito nuisance and disease transmission. The obtained results could thus provide a new basis for directing the control of mosquito vectors as they provide health authorities with precise maps of mosquito breeding habitats in a timely manner. Moreover, the generated map delineating risk areas could be used by project developers to either re-site the project or invest in mosquito control activities in order to avoid health risks and ensure sustainability of their development. The approach adopted in this investigation demonstrated the practical and successful application of remote sensing and GIS in assisting health and development decision making.

Animals↗

PubMed1999

Alignment of adjacent picture frames captured by a CLSM.

Mosaicking a picture from its adjacent parts (called picture frames or tiles) is encountered in different fields of research and technology, e.g., photogrammetry, remote sensing, microscopy, etc. It is applied whenever the object of investigation is too large for the field of view of the sensor, e.g. a microscope. We describe mosaicking with a confocal laser-scanning microscope (CLSM) Bio-Rad, MRC 600 (U.K.). Aligning neighboring picture tiles was accomplished by registering the overlapped border areas of these tiles. Such registration procedures are constrained by: 1) the limited size of the registered samples (windows); 2) anisotropy of the form of the windows (usually narrow rectangles); and 3) the content of the windows, including changes of their intensity scale. Focusing on the latter problem, methods of registration were discussed and the robustness of the following three similarity based methods was studied with regard to the distortions of the intensity scales of the tiles to be registered: 1) the sum of absolute valued differences (SAVD); 2) normalized correlation coefficient (NCC); and 3) the mutual information function (MIF). Pilot experiments were extended to three-dimensional (3-D) stacks of pictures encountered in the framework of 3-D object rendering and visualization. MIF was found in most cases to be the most robust; however, it also demanded the most computational power. It is discussed how to choose a cost-effective method of the registration with regard to the content (texture, contrast, intensity scale distortion) of the tiles.

Microscopy, Confocal↗

PubMed2004

A multidisciplinary decision support system for forest fire crisis management.

A wildland fire is a serious threat for forest ecosystems in Southern Europe affecting severely and irreversibly regions of significant ecological value as well as human communities. To support decision makers during large-scale forest fire incidents, a multidisciplinary system has been developed that provides rational and quantitative information based on the site-specific circumstances and the possible consequences. The system's architecture consists of several distinct supplementary modules of near real-time satellite monitoring and fire forecast using an integrated framework of satellite Remote Sensing, GIS, and RDBMS technologies equipped with interactive communication capabilities. The system may handle multiple fire ignitions and support decisions regarding dispatching of utilities, equipment, and personnel that would appropriately attack the fire front. The operational system was developed for the region of Penteli Mountain in Attika, Greece, one of the mountain areas in the country most hit by fires. Starting from a real fire incident in August 2000, a scenario is presented to illustrate the effectiveness of the proposed approach.

Communication↗

PubMed2006

Advanced imaging of multiple mRNAs in brain tissue using a custom hyperspectral imager and multivariate curve resolution.

Simultaneous imaging of multiple cellular components is of tremendous importance in the study of complex biological systems, but the inability to use probes with similar emission spectra and the time consuming nature of collecting images on a confocal microscope are prohibitive. Hyperspectral imaging technology, originally developed for remote sensing applications, has been adapted to measure multiple genes in complex biological tissues. A spectral imaging microscope was used to acquire overlapping fluorescence emissions from specific mRNAs in brain tissue by scanning the samples using a single fluorescence excitation wavelength. The underlying component spectra obtained from the samples are then separated into their respective spectral signatures using multivariate analyses, enabling the simultaneous quantitative measurement of multiple genes either at regional or cellular levels.

Animals↗

PubMed2005

An information value based analysis of physical and climatic factors affecting dengue fever and dengue haemorrhagic fever incidence.

BACKGROUND: Vector-borne diseases are the most dreaded worldwide health problems. Although many campaigns against it have been conducted, Dengue Fever (DF) and Dengue Haemorrhagic Fever (DHF) are still the major health problems of Thailand. The reported number of dengue incidences in 1998 for the Thailand was 129,954, of which Sukhothai province alone reported alarming number of 682. It was the second largest epidemic outbreak of dengue after 1987. Government arranges the remedial facilities as and when dengue is reported. But, the best way to control is to prevent it from happening. This will be possible only when knowledge about the relationship of DF/DHF with climatic and physio-environmental agents is discovered. This paper explores empirical relationship of climatic factors rainfall, temperature and humidity with the DF/DHF incidences using multivariate regression analysis. Also, a GIS based methodology is proposed in this paper to explore the influence of physio-environmental factors on dengue incidences. Remotely sensed data provided important data about physical environment and have been used for many vector borne diseases. Information Values (IV) method was utilised to derive influence of various factors in the quantitative terms. Researchers have not applied this type of analysis for dengue earlier. Sukhothai province was selected for the case study as it had high number of dengue cases in 1998 and also due to its diverse physical setting with variety of land use/land cover types. RESULTS: Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF/DHF. A composite analysis of these three factors with dengue incidences was carried out using multivariate regression analysis. Three empirical models ER-1, ER-2 and ER-3 were evaluated. It was found that these three factors have significant relation with DF/DHF incidences and can be related to the forecast expected number of dengue cases. The results have shown significantly high coefficient of determination if applied only for the rainy season using empirical relation-2 (ER-2). These results have shown further improvement once a concept of time lag of one month was applied using the ER-3 empirical relation. ER-3 model is most suitable for the Sukhothai province in predicting possible dengue incidence with 0.81 coefficient of determination. The spatial statistical relationship of various land use/land cover classes with dengue-affected areas was quantified in the form of information value received from GIS analysis. The highest information value was obtained for the Built-up area. This indicated that Built-up area has the maximum influence on the incidence of dengue. The other classes showing negative values indicate lesser influence on dengue epidemics. Agricultural areas have yielded moderate risk areas based on their medium high information values. Water bodies have shown significant information value for DF/DHF only in one district. Interestingly, forest had shown no influence on DF/DHF. CONCLUSION: This paper explores the potential of remotely sensed data and GIS technology to analyze the spatial factors affecting DF/DHF epidemic. Three empirical models were evaluated. It was found that Empirical Relatrion-3 (ER-3) has yielded very high coefficient of determination to forecast the number of DF/DHF incidence. An analysis of physio-environmental factors such as land use/land cover types with dengue incidence was carried out. Influence of these factors was obtained in quantitative terms using Information Value method in the GIS environment. It was found that built-up areas have highest influence and constitute the highest risk zones. Forest areas have no influence on DF/DHF epidemic. Agricultural areas have moderate risk in DF/DHF incidences. Finally the dengue risk map of the Sukhothai province was developed using Information Value method. Dengue risk map can be used by the Public Health Department as a base map for applying preventive measures to control the dengue outbreak. Public Health Department can initiate their effort once the ER-3 predicts a possibility of significant high dengue incidence. This will help in focussing the preventive measures being applied on priority in very high and high-risk zones and help in saving time and money.

Journal Article↗

PubMed1994

Electronic endoscopy in perspective.

Electronic endoscopy, developed in 1983, enables the endoscopic image to be transmitted through electric signals that can be easily processed by computer. An electronic endoscope is composed of three vital parts, i.e., a charge-coupled device (CCD) that converts the image to electric signals, a video processor that converts analog electric signals to the digital and processes them to become video signals, and a television monitor. The introduction of electronic endoscopy has enabled computer management of endoscopic images, on one hand, and provided an opportunity for image processing and analysis, on the other. A digital image management system will further develop into a database of endoscopic images. Combined with the technologies of remote control and remote sensing, the introduction of CCD to endoscopy has made it possible to transform the endoscope, so that it could become a capsule. Future advances in the research of image processing and analysis will lead to the development of a system of automated endoscopic diagnosis.

Electronics, Medical↗

PubMedDate not supplied

Aneurysm sac pressure measurement with a pressure sensor in endovascular aortic aneurysm repair.

Aortic endograft surveillance is a necessity for the lifetime of a patient owing to the risk of endoleaks and device complications. The current standard of care for surveillance is radiologic imaging. The most commonly used modality is computed tomographic angiography. Magnetic resonance angiography and ultrasonography have also been used as surveillance tools. These imaging techniques have risks and limitations, and alternative surveillance tools are being investigated. Remote pressure sensing is a promising technology that can provide adjunctive support to the current imaging modalities. The technology is applicable to both abdominal and thoracic endograft implantation and surveillance. It has recently gained clearance from the US Food and Drug Administration for acute aneurysm exclusion during an abdominal endograft insertion. As more data are accumulated, it may be possible for remote pressure sensing to replace current imaging techniques as the sole modality for endograft surveillance.

Aortic Aneurysm, Abdominal↗

PubMed1996

An Introduction to Digital Methods in Remote Sensing of Forested Ecosystems: Focus on the Pacific Northwest, USA

Aerial photography has been routinely used for several decades by natural resource scientists and managers to map and monitor the condition of forested landscapes. Recently, along with the emergence of concepts in managing forests as ecosystems, has come a significant shift in emphasis from smaller to larger spatial scales and the widespread use of geographic information systems. These developments have precipitated an increasing need for vegetation information derived from other remote sensing imagery, especially digital data acquired from high-elevation aircraft and satellite platforms. This paper introduces fundamental concepts in digital remote sensing and describes numerous applications of the technology. The intent is to provide a balanced, nontechnical view, discussing the shortcomings, successes, and future potential for digital remote sensing of forested ecosystems.

Journal Article↗

PubMed2005

A geographic information and remote sensing based model for prediction of Oncomelania hupensis habitats in the Poyang Lake area, China.

A model was developed using remote sensing and geographic information system technologies for habitat identification of Oncomelania hupensis, the intermediate host snail of Schistosoma japonicum, in the Poyang Lake area, China. In a first step, two multi-temporal Landsat TM 5 satellite images, one from the wet and the second from the dry season, were visually classified into different land-use types. Next, the normalized difference vegetation index was extracted from the images and the tasseled-cap transformation was employed to derive the wetness feature. Our model predicted an estimated 709 km2 of the marshlands in Poyang Lake as potential habitats for O. hupensis. Near-ground temperature measurements in April and August yielded a range of 22.8-24.2 degrees C, and pH values of 6.0-8.5 were derived from existing records. Both climatic features represent suitable breeding conditions for the snails. Preliminary validation of the model at 10 sites around Poyang Lake revealed an excellent accuracy for predicting the presence of O. hupensis. We used the predicted snail habitats as centroids and established buffer zones around them. Villages with an overall prevalence of S. japonicum below 3% were located more than 1200m away from the centroids. Furthermore, a gradient of high-to-low prevalence was observed with increasing distance from the centroids. In conclusion, the model holds promise for identifying high risk areas of schistosomiasis japonica and may become an important tool for the ongoing national schistosomiasis control programme. The model is of particular relevance for schistosome-affected regions that lack accurate surveillance capabilities and are large enough to be detected at most commercially available remote sensing scales.

Animals↗

PubMed2006

Risk assessment and prediction of Ixodes ricinus tick questing activity and human tick-borne encephalitis infection in space and time in the Czech Republic.

Present risk assessment and prediction of future risk of humans exposed to Ixodes (I.) ricinus tick attacks and, consequently, to tick-borne encephalitis (TBE) virus infection as one of the basic preconditions for successful TBE prevention has been intensively studied in the Czech Republic. An atlas of TBE in the Czech Republic containing predictive maps of I. ricinus high-incidence habitats and TBE risk sites identified by satellite data (Landsat 5 TM with spatial resolution 30 m) at a scale of 1:200,000 over a territory of 52,000 km(2) and maps of human TBE case distribution (1971-2000) has been prepared using remote sensing and geographical information systems technologies. The influence of climate changes on a forest ecosystem inhabited by I. ricinus has been studied in the southern region of the Czech Republic. The analysis of long-term series (1931-2000) of climatologic and phenological characteristics has been carried out. The results are compared with the long-term series of TBE incidence. The influence of weather condition on day-to-day changes of I. ricinus host-seeking activities was studied in 2001-2004. Field observations were realized in the south-eastern periphery of Prague where the experimental plots for tick monitoring were established in a relevant type of forest growth (Querceto-carpinetum). I. ricinus activities were investigated by the flagging method on three plots (200 m(2) each) in weekly intervals (March to November) during 2001-2004. The instruments for micrometeorological observations were installed between the experimental plots. Macrometeorological data were used from the nearby Czech Hydrometeorological Institute first class meteorological observatory. Simple and multiple linear regression and quadratic regression were used to test the relation between weather modification and I. ricinus host-seeking activity. Two preliminary most suitable 'models' are demonstrated.

Animals↗

PubMedDate not supplied

Information technology and public health management of disasters--a model for South Asian countries.

This paper highlights the use of information technology (IT) in disaster management and public health management of disasters. Effective health response to disasters will depend on three important lines of action: (1) disaster preparedness; (2) emergency relief; and (3) management of disasters. This is facilitated by the presence of modern communication and space technology, especially the Internet and remote sensing satellites. This has made the use of databases, knowledge bases, geographic information systems (GIS), management information systems (MIS), information transfer, and online connectivity possible in the area of disaster management and medicine. This paper suggests a conceptual model called, "The Model for Public Health Management of Disasters for South Asia". This Model visualizes the use of IT in the public health management of disasters by setting up the Health and Disaster Information Network and Internet Community Centers, which will facilitate cooperation among all those in the areas of disaster management and emergency medicine. The suggested infrastructure would benefit the governments, non-government organizations, and institutions working in the areas of disaster and emergency medicine, professionals, the community, and all others associated with disaster management and emergency medicine. The creation of such an infrastructure will enable the rapid transfer of information, data, knowledge, and online connectivity from top officials to the grassroots organizations, and also among these countries regionally. This Model may be debated, modified, and tested further in the field to suit the national and local conditions. It is hoped that this exercise will result in a viable and practical model for use in public health management of disasters by South Asian countries.

Artificial Intelligence↗

PubMed2001

Characterization of enzootic foci of Venezuelan equine encephalitis virus in western Venezuela.

The distribution of the sylvatic subtype ID Venezuelan equine encephalitis (VEE) viruses in the lowland tropical forests of western Venezuela was investigated using remote sensing and geographic information system technologies. Landsat 5 Thematic Mapper satellite imagery was used to study the reflectance patterns of VEE endemic foci and to identify other locations with similar reflectance patterns. Enzootic VEE virus variants isolated during this study are the closest genetic relatives of the epizootic viruses that emerged in western Venezuela during 1992-1993. VEE virus surveillance was conducted by exposing sentinel hamsters to mosquito bites and trapping wild vertebrates in seven forests identified and located by means of the satellite image. We isolated VEE viruses from 48 of a total of 1,363 sentinel hamsters in two of the forests on six occasions, in both dry and wet seasons. None of the 12 small vertebrates captured in 8,190 trap-nights showed signs of previous VEE virus infection. The satellite image was classified into 13 validated classes of land use/vegetation using unsupervised and supervised techniques. Data derived from the image consisted of the raw digital values of near- and mid-infrared bands 4, 5, and 7, derived Tasseled Cap indices of wetness, greenness, and brightness, and the Normalized Difference Vegetation Index. Digitized maps provided ancillary data of elevation and soil geomorphology. Image enhancement was applied using Principal Component Analysis. A digital layer of roads together with georeferenced images was used to locate the study sites. A cluster analysis using the above data revealed two main groups of dense forests separated by spectral properties, altitude, and soil geomorphology. Virus was isolated more frequently from the forest type identified on flat flood plains of main rivers rather than the forest type found on the rolling hills of the study area. The spatial analysis suggests that mosquitoes carrying the enzootic viruses would reach 82-97% of the total land area by flying only 1-3 km from forests. We hypothesize that humans within that area are at risk of severe disease caused by enzootic ID VEE viruses. By contrast, equines could actually become naturally vaccinated, thus preventing the local emergence of epizootic IC VEE virus strains and protecting humans indirectly.

Animals↗

PubMed2002

Spatial analysis of West Nile virus: rapid risk assessment of an introduced vector-borne zoonosis.

The distribution of human risk for West Nile virus was determined by spatial analysis of the initial case distribution for the New York City area in 1999 using remote sensing and geographic information system technologies. Cluster analysis revealed the presence of a statistically significant grouping of cases, which also indicates the area of probable virus introduction. Within the cluster, habitat suitability for potentially infective adult mosquitoes was measured by the amount of vegetation cover using satellite imagery. Logistic regression analysis revealed satellite-derived vegetation abundance to be significantly and positively associated with the presence of human cases. The logistic model was used to estimate the spatial distribution of human risk for West Nile virus throughout New York City. Accuracy of the resulting risk map was cross-validated using virus-positive mosquito sample sites. These new epidemiological methods aid in rapid entry point identification and spatial prediction of human risk of infection for introduced vector-borne pathogens.

Animals↗

PubMed2005

Prospects for monitoring freshwater ecosystems towards the 2010 targets.

Human activities have severely affected the condition of freshwater ecosystems worldwide. Physical alteration, habitat loss, water withdrawal, pollution, overexploitation and the introduction of non-native species all contribute to the decline in freshwater species. Today, freshwater species are, in general, at higher risk of extinction than those in forests, grasslands and coastal ecosystems. For North America alone, the projected extinction rate for freshwater fauna is five times greater than that for terrestrial fauna--a rate comparable to the species loss in tropical rainforest. Because many of these extinctions go unseen, the level of assessment and knowledge of the status and trends of freshwater species are still very poor, with species going extinct before they are even taxonomically classified. Increasing human population growth and achieving the sustainable development targets set forth in 2002 will place even higher demands on the already stressed freshwater ecosystems, unless an integrated approach to managing water for people and ecosystems is implemented by a broad constituency. To inform and implement policies that support an integrated approach to water management, as well as to measure progress in halting the rapid decline in freshwater species, basin-level indicators describing the condition and threats to freshwater ecosystems and species are required. This paper discusses the extent and quality of data available on the number and size of populations of freshwater species, as well as the change in the extent and condition of natural freshwater habitats. The paper presents indicators that can be applied at multiple scales, highlighting the usefulness of using remote sensing and geographical information systems technologies to fill some of the existing information gaps. Finally, the paper includes an analysis of major data gaps and information needs with respect to freshwater species to measure progress towards the 2010 biodiversity targets.

Conservation of Natural Resources↗