A series of adventures in the course of a voyage up the Red-Sea: on the coasts of Arabia and Egypt; and of a route through the desarts of Thebais, in the year 1777. With a supplement of a voyage from Venice to Latichea; and of a route through the desarts of Arabia, by Aleppo, Bagdad, and the Tygris to Busrah, in the years 1780 and 1781. In letters to a lady.

Mode of access: Internet.

Narrative of the operations and recent discoveries within the pyramids, temples, tombs, and excavations in Egypt and Nubia; and of a journey to the coast of the Red Sea in search of the ancient Berenice, and another to the oasis of Jupiter Ammon /

"Mrs. Belzoni's trifling account of the women of Egypt, Nubia, and Syria": p. 441-483.

Narrative of the operations and recent discoveries within the pyramids, temples, tombs, and excavations, in Egypt and Nubia : and of a journey to the coast of the Red Sea, in search of the ancient Berenice, and another to the oasis of Jupiter Ammon /

"Short account of the women of Egypt, Nubia, and Syria; by Mrs. Belzoni": v. 2, p. [241]-327.

Letters from the Red Sea, Egypt, and the continent.

Mode of access: Internet.

Application of remote sensing and GIS in mineral resource mapping - An overview

Remote sensing, as a direct adjunct to field, lithologic and structural mapping, and more recently, GIS have played an important role in the study of mineralized areas. A review on the application of remote sensing in mineral resource mapping is attempted here. It involves understanding the application of remote sensing in lithologic, structural and alteration mapping. Remote sensing becomes an important tool for locating mineral deposits, in its own right, when the primary and secondary processes of mineralization result in the formation of spectral anomalies. Reconnaissance lithologic mapping is usually the first step of mineral resource mapping. This is complimented with structural mapping, as mineral deposits usually occur along or adjacent to geologic structures, and alteration mapping, as mineral deposits are commonly associated with hydrothermal alteration of the surrounding rocks. In addition to these, understanding the use of hyperspectral remote sensing is crucial as hyperspectral data can help identify and thematically map regions of exploration interest by using the distinct absorption features of most minerals. Finally coming to the exploration stage, GIS forms the perfect tool in integrating and analyzing various georeferenced geoscience data in selecting the best sites of mineral deposits or rather good candidates for further exploration.

Visualisation of quality information for geospatial and remote sensing data:providing the GIS community with the decision support tools for geospatial dataset quality evaluation

The evaluation of geospatial data quality and trustworthiness presents a major challenge to geospatial data users when making a dataset selection decision. The research presented here therefore focused on defining and developing a GEO label – a decision support mechanism to assist data users in efficient and effective geospatial dataset selection on the basis of quality, trustworthiness and fitness for use. This thesis thus presents six phases of research and development conducted to: (a) identify the informational aspects upon which users rely when assessing geospatial dataset quality and trustworthiness; (2) elicit initial user views on the GEO label role in supporting dataset comparison and selection; (3) evaluate prototype label visualisations; (4) develop a Web service to support GEO label generation; (5) develop a prototype GEO label-based dataset discovery and intercomparison decision support tool; and (6) evaluate the prototype tool in a controlled human-subject study. The results of the studies revealed, and subsequently confirmed, eight geospatial data informational aspects that were considered important by users when evaluating geospatial dataset quality and trustworthiness, namely: producer information, producer comments, lineage information, compliance with standards, quantitative quality information, user feedback, expert reviews, and citations information. Following an iterative user-centred design (UCD) approach, it was established that the GEO label should visually summarise availability and allow interrogation of these key informational aspects. A Web service was developed to support generation of dynamic GEO label representations and integrated into a number of real-world GIS applications. The service was also utilised in the development of the GEO LINC tool – a GEO label-based dataset discovery and intercomparison decision support tool. The results of the final evaluation study indicated that (a) the GEO label effectively communicates the availability of dataset quality and trustworthiness information and (b) GEO LINC successfully facilitates ‘at a glance’ dataset intercomparison and fitness for purpose-based dataset selection.

Using GIS and Remote Sensing Technologies to Identify Environmental Variables of Malaria Vector Breeding Sites in Western Kenya

This study used Landsat 8 satellite imagery to identify environmental variables of households with malaria vector breeding sites in a malaria endemic rural district in Western Kenya. Understanding the influence of environmental variables on the distribution of malaria has been critical in the strengthening of malaria control programs. Using remote sensing and GIS technologies, this study performed a land classification, NDVI, Tasseled Cap Wetness Index, and derived land surface temperature values of the study area and examined the significance of each variable in predicting the probability of a household with a mosquito breeding site with and without larvae. The findings of this study revealed that households with any potential breeding sites were characterized by higher moisture, higher vegetation density (NDVI) and in urban areas or roads. The results of this study also confirmed that land surface temperature was significant in explaining the presence of active mosquito breeding sites (P< 0.000). The present study showed that freely available Landsat 8 imagery has limited use in deriving environmental characteristics of malaria vector habitats at the scale of the Bungoma East District in Western Kenya.

CHARACTERIZING THE FIRST HISTORIC ERUPTION OF NABRO, ERITREA: INSIGHTS FROM THERMAL AND UV REMOTE SENSING

June 2011 saw the first historic eruption of Nabro volcano, one of an ongoing sequence of eruptions in the Afar-Red Sea region since 2005. It halted air travel in northern Africa, contaminated food and water sources, and displaced thousands from their homes. Due to its remote location, little was known about this event in terms of the quantity of erupted products and the timing and mechanisms of their emplacement. Geographic isolation, previous quiescence and regional civil unrest meant that this volcano was effectively unmonitored at the time of eruption, and opportunities for field study are limited. Using free, publicly available satellite data, I examined rates of lava effusion and SO2 emission in order to quantify the amount of erupted products and understand the temporal evolution of the eruption, as well as explore what information can be gleaned about eruption mechanisms using remote sensing data. These data revealed a bimodal eruption, beginning with explosive activity marked by high SO2 emission totalling 1824 - 2299 KT, and extensive ash fall of 270 - 440 km2. This gave way to a period of rapid effusion, producing a ~17 km long lava flow, and a volume of ~22.1 x 106 m3. Mass balance between the SO2 and lava flows reveals no sulfur 'excess', suggesting that nearly all of the degassed magma was extruded. The 2011 eruption of Nabro lasted nearly 6 weeks, and may be considered the second largest historic eruption in Africa. Work such as this highlights the importance of satellite remote sensing for studying and monitoring volcanoes, particularly those in remote regions that may be otherwise inaccessible.

APPLICATION OF REMOTE SENSING IN AQUATIC ECOSYSTEMS

I utilized state the art remote sensing and GIS (Geographical Information System) techniques to study large scale biological, physical and ecological processes of coastal, nearshore, and offshore waters of Lake Michigan and Lake Superior. These processes ranged from chlorophyll a and primary production time series analysies in Lake Michigan to coastal stamp sand threats on Buffalo Reef in Lake Superior. I used SeaWiFS (Sea-viewing Wide Field-of-view Sensor) satellite imagery to trace various biological, chemical and optical water properties of Lake Michigan during the past decade and to investigate the collapse of early spring primary production. Using spatial analysis techniques, I was able to connect these changes to some important biological processes of the lake (quagga mussels filtration). In a separate study on Lake Superior, using LiDAR (Light Detection and Ranging) and aerial photos, we examined natural coastal erosion in Grand Traverse Bay, Michigan, and discussed a variety of geological features that influence general sediment accumulation patterns and interactions with migrating tailings from legacy mining. These sediments are moving southwesterly towards Buffalo Reef, creating a threat to the lake trout and lake whitefish breeding ground.

Spatial distribution of benthic microalgae on coral reefs determined by remote sensing

Understanding the ecological role of benthic microalgae, a highly productive component of coral reef ecosystems, requires information on their spatial distribution. The spatial extent of benthic microalgae on Heron Reef (southern Great Barrier Reef, Australia) was mapped using data from the Landsat 5 Thematic Mapper sensor. integrated with field measurements of sediment chlorophyll concentration and reflectance. Field-measured sediment chlorophyll concentrations. 2 ranging from 23-1.153 mg chl a m(2), were classified into low, medium, and high concentration classes (1-170, 171-290, and > 291 mg chl a m(-2)) using a K-means clustering algorithm. The mapping process assumed that areas in the Thematic Mapper image exhibiting similar reflectance levels in red and blue bands would correspond to areas of similar chlorophyll a levels. Regions of homogenous reflectance values corresponding to low, medium, and high chlorophyll levels were identified over the reef sediment zone by applying a standard image classification algorithm to the Thematic Mapper image. The resulting distribution map revealed large-scale ( > 1 km 2) patterns in chlorophyll a levels throughout the sediment zone of Heron Reef. Reef-wide estimates of chlorophyll a distribution indicate that benthic Microalgae may constitute up to 20% of the total benthic chlorophyll a at Heron Reef. and thus contribute significantly to total primary productivity on the reef.

Land cover mapping analysis and urban growth modeling using remote sensing techniques

The rapid growth of big cities has been noticed since 1950s when the majority of world population turned to live in urban areas rather than villages, seeking better job opportunities and higher quality of services and lifestyle circumstances. This demographic transition from rural to urban is expected to have a continuous increase. Governments, especially in less developed countries, are going to face more challenges in different sectors, raising the essence of understanding the spatial pattern of the growth for an effective urban planning. The study aimed to detect, analyse and model the urban growth in Greater Cairo Region (GCR) as one of the fast growing mega cities in the world using remote sensing data. Knowing the current and estimated urbanization situation in GCR will help decision makers in Egypt to adjust their plans and develop new ones. These plans should focus on resources reallocation to overcome the problems arising in the future and to achieve a sustainable development of urban areas, especially after the high percentage of illegal settlements which took place in the last decades. The study focused on a period of 30 years; from 1984 to 2014, and the major transitions to urban were modelled to predict the future scenarios in 2025. Three satellite images of different time stamps (1984, 2003 and 2014) were classified using Support Vector Machines (SVM) classifier, then the land cover changes were detected by applying a high level mapping technique. Later the results were analyzed for higher accurate estimations of the urban growth in the future in 2025 using Land Change Modeler (LCM) embedded in IDRISI software. Moreover, the spatial and temporal urban growth patterns were analyzed using statistical metrics developed in FRAGSTATS software. The study resulted in an overall classification accuracy of 96%, 97.3% and 96.3% for 1984, 2003 and 2014’s map, respectively. Between 1984 and 2003, 19 179 hectares of vegetation and 21 417 hectares of desert changed to urban, while from 2003 to 2014, the transitions to urban from both land cover classes were found to be 16 486 and 31 045 hectares, respectively. The model results indicated that 14% of the vegetation and 4% of the desert in 2014 will turn into urban in 2025, representing 16 512 and 24 687 hectares, respectively.

Estimation of soil moisture in the root-zone from remote sensing data

Field-based soil moisture measurements are cumbersome. Thus, remote sensing techniques are needed because allows field and landscape-scale mapping of soil moisture depth-averaged through the root zone of existing vegetation. The objective of the study was to evaluate the accuracy of an empirical relationship to calculate soil moisture from remote sensing data of irrigated soils of the Apodi Plateau, in the Brazilian semiarid region. The empirical relationship had previously been tested for irrigated soils in Mexico, Egypt, and Pakistan, with promising results. In this study, the relationship was evaluated from experimental data collected from a cotton field. The experiment was carried out in an area of 5 ha with irrigated cotton. The energy balance and evaporative fraction (Λ) were measured by the Bowen ratio method. Soil moisture (θ) data were collected using a PR2 - Profile Probe (Delta-T Devices Ltd). The empirical relationship was tested using experimentally collected Λ and θ values and was applied using the Λ values obtained from the Surface Energy Balance Algorithm for Land (SEBAL) and three TM - Landsat 5 images. There was a close correlation between measured and estimated θ values (p<0.05, R² = 0.84) and there were no significant differences according to the Student t-test (p<0.01). The statistical analyses showed that the empirical relationship can be applied to estimate the root-zone soil moisture of irrigated soils, i.e. when the evaporative fraction is greater than 0.45.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Remote sensing of intertidal morphological change in Morecambe Bay, U.K., between 1991 and 2007

Tidal Flats are important examples of extensive areas of natural environment that remain relatively unaffected by man. Monitoring of tidal flats is required for a variety of purposes. Remote sensing has become an established technique for the measurement of topography over tidal flats. A further requirement is to measure topographic changes in order to measure sediment budgets. To date there have been few attempts to make quantitative estimates of morphological change over tidal flat areas. This paper illustrates the use of remote sensing to measure quantitative and qualitative changes in the tidal flats of Morecambe Bay during the relatively long period 1991–2007. An understanding of the patterns of sediment transport within the Bay is of considerable interest for coastal management and defence purposes. Tidal asymmetry is considered to be the dominant cause of morphological change in the Bay, with the higher currents associated with the flood tide being the main agency moulding the channel system. Quantitative changes were measured by comparing a Digital Elevation Model (DEM) of the intertidal zone formed using the waterline technique applied to satellite Synthetic Aperture Radar (SAR) images from 1991–1994, to a second DEM constructed from airborne laser altimetry data acquired in 2005. Qualitative changes were studied using additional SAR images acquired since 2003. A significant movement of sediment from below Mean Sea Level (MSL) to above MSL was detected by comparing the two Digital Elevation Models, though the proportion of this change that could be ascribed to seasonal effects was not clear. Between 1991 and 2004 there was a migration of the Ulverston channel of the river Leven north-east by about 5 km, followed by the development of a straighter channel to the west, leaving the previous channel decoupled from the river. This is thought to be due to independent tidal and fluvial forcing mechanisms acting on the channel. The results demonstrate the effectiveness of remote sensing for measurement of long-term morphological change in tidal flat areas. An alternative use of waterlines as partial bathymetry for assimilation into a morphodynamic model of the coastal zone is also discussed.

Remote sensing of cloud properties using ground-based measurements of zenith radiance

We have conducted the first extensive field test of two new methods to retrieve optical properties for overhead clouds that range from patchy to overcast. The methods use measurements of zenith radiance at 673 and 870 nm wavelengths and require the presence of green vegetation in the surrounding area. The test was conducted at the Atmospheric Radiation Measurement Program Oklahoma site during September–November 2004. These methods work because at 673 nm (red) and 870 nm (near infrared (NIR)), clouds have nearly identical optical properties, while vegetated surfaces reflect quite differently. The first method, dubbed REDvsNIR, retrieves not only cloud optical depth τ but also radiative cloud fraction. Because of the 1-s time resolution of our radiance measurements, we are able for the first time to capture changes in cloud optical properties at the natural timescale of cloud evolution. We compared values of τ retrieved by REDvsNIR to those retrieved from downward shortwave fluxes and from microwave brightness temperatures. The flux method generally underestimates τ relative to the REDvsNIR method. Even for overcast but inhomogeneous clouds, differences between REDvsNIR and the flux method can be as large as 50%. In addition, REDvsNIR agreed to better than 15% with the microwave method for both overcast and broken clouds. The second method, dubbed COUPLED, retrieves τ by combining zenith radiances with fluxes. While extra information from fluxes was expected to improve retrievals, this is not always the case. In general, however, the COUPLED and REDvsNIR methods retrieve τ to within 15% of each other.