The use of remote sensing imagery for monitoring recovery in the aftermath of a natural disaster: the Hurricane Katrina Case

Although Recovery is often defined as the less studied and documented phase of the Emergency Management Cycle, a wide literature is available for describing characteristics and sub-phases of this process. Previous works do not allow to gain an overall perspective because of a lack of systematic consistent monitoring of recovery utilizing advanced technologies such as remote sensing and GIS technologies. Taking into consideration the key role of Remote Sensing in Response and Damage Assessment, this thesis is aimed to verify the appropriateness of such advanced monitoring techniques to detect recovery advancements over time, with close attention to the main characteristics of the study event: Hurricane Katrina storm surge. Based on multi-source, multi-sensor and multi-temporal data, the post-Katrina recovery was analysed using both a qualitative and a quantitative approach. The first phase was dedicated to the investigation of the relation between urban types, damage and recovery state, referring to geographical and technological parameters. Damage and recovery scales were proposed to review critical observations on remarkable surge- induced effects on various typologies of structures, analyzed at a per-building level. This wide-ranging investigation allowed a new understanding of the distinctive features of the recovery process. A quantitative analysis was employed to develop methodological procedures suited to recognize and monitor distribution, timing and characteristics of recovery activities in the study area. Promising results, gained by applying supervised classification algorithms to detect localization and distribution of blue tarp, have proved that this methodology may help the analyst in the detection and monitoring of recovery activities in areas that have been affected by medium damage. The study found that Mahalanobis Distance was the classifier which provided the most accurate results, in localising blue roofs with 93.7% of blue roof classified correctly and a producer accuracy of 70%. It was seen to be the classifier least sensitive to spectral signature alteration. The application of the dissimilarity textural classification to satellite imagery has demonstrated the suitability of this technique for the detection of debris distribution and for the monitoring of demolition and reconstruction activities in the study area. Linking these geographically extensive techniques with expert per-building interpretation of advanced-technology ground surveys provides a multi-faceted view of the physical recovery process. Remote sensing and GIS technologies combined to advanced ground survey approach provides extremely valuable capability in Recovery activities monitoring and may constitute a technical basis to lead aid organization and local government in the Recovery management.

The impact of ice crystals on radiative forcing and remote sensing of arctic boundary-layer mixed-phase clouds

This PhD thesis is embedded into the Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) and investigates the radiative transfer through Arctic boundary-layer mixed-phase (ABM) clouds. For this purpose airborne spectral solar radiation measurements and simulations of the solar and thermal infrared radiative transfer have been performed. This work reports on measurements with the Spectral Modular Airborne Radiation measurement sysTem (SMART-Albedometer) conducted in the framework of ASTAR in April 2007 close to Svalbard. For ASTAR the SMART-Albedometer was extended to measure spectral radiance. The development and calibration of the radiance measurements are described in this work. In combination with in situ measurements of cloud particle properties provided by the Laboratoire de M¶et¶eorologie Physique (LaMP) and simultaneous airborne lidar measurements by the Alfred Wegener Institute for Polar and Marine Research (AWI) ABM clouds were sampled. The SMART-Albedometer measurements were used to retrieve the cloud thermodynamic phase by three different approaches. A comparison of these results with the in situ and lidar measurements is presented in two case studies. Beside the dominating mixed-phase clouds pure ice clouds were found in cloud gaps and at the edge of a large cloud field. Furthermore the vertical distribution of ice crystals within ABM clouds was investigated. It was found that ice crystals at cloud top are necessary to describe the observed SMART-Albedometer measurements. The impact of ice crystals on the radiative forcing of ABM clouds is in vestigated by extensive radiative transfer simulations. The solar and net radiative forcing was found to depend on the ice crystal size, shape and the mixing ratio of ice crystals and liquid water droplets.

Applications of GIS and remote sensing techniques for studying the housing patterns in Cairo Governorate

The main objective of this study is to reveal the housing patterns in Cairo as one of the most rapidly urbanizing city in the developing world. The study outlines the evolution of the housing problem and its influencing factors in Egypt generally and in Cairo specifically. The study takes into account the political transition from the national state economy to the open door policy, the neo-liberal period and finally to the housing situation after the January 2011 Revolution. The resulting housing patterns in Cairo Governorate were identified as (1) squatter settlements, (2) semi-informal settlements, (3) deteriorated inner pockets, and (4) formal settlements. rnThe study concluded that the housing patterns in Cairo are reflecting a multifaceted problem resulting in: (1) the imbalance between the high demand for affordable housing units for low-income families and the oversupply of upper-income housing, (2) the vast expansion of informal areas both on agricultural and desert lands, (3) the deterioration of the old parts of Cairo without upgrading or appropriate replacement of the housing structure, and (4) the high vacancy rate of newly constructed apartmentsrnThe evolution and development of the current housing problem were attributed to a number of factors. These factors are demographic factors represented in the rapid growth of the population associated with urbanization under the dictates of poverty, and the progressive increase of the prices of both buildable land and building materials. The study underlined that the current pattern of population density in Cairo Governorate is a direct result of the current housing problems. Around the depopulation core of the city, a ring of relatively stable areas in terms of population density has developed. Population densification, at the expense of the depopulation core, is characterizing the peripheries of the city. The population density in relation to the built-up area was examined using Landsat-7 ETM+ image (176/039). The image was acquired on 24 August 2006 and considered as an ideal source for land cover classification in Cairo since it is compatible with the population census 2006.rnConsidering that the socio-economic setting is a driving force of change of housing demand and that it is an outcome of the accumulated housing problems, the socio-economic deprivations of the inhabitants of Cairo Governorate are analyzed. Small administrative units in Cairo are categorized into four classes based on the Socio-Economic Opportunity Index (SEOI). This index is developed by using multiple domains focusing on the economic, educational and health situation of the residential population. The results show four levels of deprivation which are consistent with the existing housing patterns. Informal areas on state owned land are included in the first category, namely, the “severely deprived” level. Ex-formal areas or deteriorated inner pockets are characterized as “deprived” urban quarters. Semi-informal areas on agricultural land concentrate in the third category of “medium deprived” settlements. Formal or planned areas are included mostly in the fourth category of the “less deprived” parts of Cairo Governorate. rnFor a better understanding of the differences and similarities among the various housing patterns, four areas based on the smallest administrative units of shiakhat were selected for a detailed study. These areas are: (1) El-Ma’desa is representing a severely deprived squatter settlement, (2) Ain el-Sira is an example for an ex-formal deprived area, (3) El-Marg el-Qibliya was selected as a typical semi-informal and medium deprived settlement, and (4) El-Nozha is representing a formal and less deprived area.rnThe analysis at shiakhat level reveals how the socio-economic characteristics and the unregulated urban growth are greatly reflected in the morphological characteristics of the housing patterns in terms of street network and types of residential buildings as well as types of housing tenure. It is also reflected in the functional characteristics in terms of land use mix and its degree of compatibility. It is concluded that the provision and accessibility to public services represents a performance measure of the dysfunctional structure dominating squatter and semi-informal settlements on one hand and ample public services and accessibility in formal areas on the other hand.rn

An automated method for mapping physical soil and water conservation structures on cultivated land using GIS and remote sensing techniques

An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS, ERDAS IMAGINE, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.

Radiance, irradiance, and remote sensing reflectance during the North Sea Coast Harmful Algal Bloom (NORCOHAB II) HEINCKE cruise HE302

In this study four data quality flags are presented for automated and unmanned above-water hyperspectral optical measurements collected underway in the North Sea, The Minch, Irish Sea and Celtic Sea in April/May 2009. Coincident to these optical measurements a DualDome D12 (Mobotix, Germany) camera system was used to capture sea surface and sky images. The first three flags are based on meteorological conditions, to select erroneous incoming solar irradiance (ES) taken during dusk, dawn, before significant incoming solar radiation could be detected or under rainfall. Furthermore, the relative azimuthal angle of the optical sensors to the sun is used to identify possible sunglint free sea surface zones. A total of 629 spectra remained after applying the meteorological masks (first three flags). Based on this dataset, a fourth flag for sunglint was generated by analysing and evaluating water leaving radiance (LW) and remote sensing reflectance (RRS) spectral behaviour in the presence and absence of sunglint salient in the simultaneously available sea surface images. Spectra conditions satisfying "mean LW (700-950 nm) < 2 mW/m**2/nm/Sr" or alternatively "minimum RRS (700-950 nm) < 0.010/Sr", mask the most measurements affected by sunglint, providing efficient flagging of sunglint in automated quality control. It is confirmed that valid optical measurements can be performed 0° <= theta <= 360° although 90° <= theta <= 135° is recommended.

Gas monitoring methodology and application to CCS projects as defined by atmospheric and remote sensing survey in the natural analogue of Campo de Calatrava

CO2 capture and storage (CCS) projects are presently developed to reduce the emission of anthropogenic CO2 into the atmosphere. CCS technologies are expected to account for the 20% of the CO2 reduction by 2050. Geophysical, ground deformation and geochemical monitoring have been carried out to detect potential leakage, and, in the event that this occurs, identify and quantify it. This monitoring needs to be developed prior, during and after the injection stage. For a correct interpretation and quantification of the leakage, it is essential to establish a pre-injection characterization (baseline) of the area affected by the CO2 storage at reservoir level as well as at shallow depth, surface and atmosphere, via soil gas measurements. Therefore, the methodological approach is important because it can affect the spatial and temporal variability of this flux and even jeopardize the total value of CO2 in a given area. In this sense, measurements of CO2 flux were done using portable infrared analyzers (i.e., accumulation chambers) adapted to monitoring the geological storage of CO2, and other measurements of trace gases, e.g. radon isotopes and remote sensing imagery were tested in the natural analogue of Campo de Calatrava (Ciudad Real, Spain) with the aim to apply in CO2 leakage detection; thus, observing a high correlation between CO2 and radon (r=0,858) and detecting some vegetation indices that may be successfully applied for the leakage detection.

Atmospheric and remote sensing surveys evaluated at the natural analogue "Campo de Calatrava" and its relation with isotopic Radon activity and CO2 flux as strategy for CCS projects

C0 capture and storage (CCS) projects are presently developed to reduce the emission of anthropogenic co2 into the atmosphere. CCS technologies are expected to account for the 20% of the C0 reduction by 2050.The results of this paper are referred to the OXYCFB300 Compostilla Project (European Energy Program for Recover). Since the detection and control of potential leakage from storage formation is mandatory in a project of capture and geological storage of C02 (CCS), geophysical , ground deformation and geochemical monitoring have been carried out to detect potentialleakage, and, in the event that this occurs, identify and quantify it. This monitoring needs to be developed prior, during and after the injection stage. For a correct interpretation and quantification of the leakage, it is essential to establish a pre-injection characterization (baseline)of the area affected by the C02 storage at reservoir level as well as at shallow depth, surface and atmosphere, via soil gas measurements.

Integrating spatial optimization and cellular automata for evaluating urban change

Urban growth and change presents numerous challenges for planners and policy makers. Effective and appropriate strategies for managing growth and change must address issues of social, environmental and economic sustainability. Doing so in practical terms is a difficult task given the uncertainty associated with likely growth trends not to mention the uncertainty associated with how social and environmental structures will respond to such change. An optimization based approach is developed for evaluating growth and change based upon spatial restrictions and impact thresholds. The spatial optimization model is integrated with a cellular automata growth simulation process. Application results are presented and discussed with respect to possible growth scenarios in south east Queensland, Australia.

Remotely sensed data for ecosystem analyses: Combining hierarchy and scene models

Remotely sensed data have been used extensively for environmental monitoring and modeling at a number of spatial scales; however, a limited range of satellite imaging systems often. constrained the scales of these analyses. A wider variety of data sets is now available, allowing image data to be selected to match the scale of environmental structure(s) or process(es) being examined. A framework is presented for use by environmental scientists and managers, enabling their spatial data collection needs to be linked to a suitable form of remotely sensed data. A six-step approach is used, combining image spatial analysis and scaling tools, within the context of hierarchy theory. The main steps involved are: (1) identification of information requirements for the monitoring or management problem; (2) development of ideal image dimensions (scene model), (3) exploratory analysis of existing remotely sensed data using scaling techniques, (4) selection and evaluation of suitable remotely sensed data based on the scene model, (5) selection of suitable spatial analytic techniques to meet information requirements, and (6) cost-benefit analysis. Results from a case study show that the framework provided an objective mechanism to identify relevant aspects of the monitoring problem and environmental characteristics for selecting remotely sensed data and analysis techniques.

Assessment of relationships between precipitation and satellite derived vegetation condition in South Australia

The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental-scale vegetation changes and interpreting the impact of short to long-term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite-derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green-up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra-Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro-radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra-Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre. [ABSTRACT FROM AUTHOR]

Ultra-wideband multistatic SAR for the detection and location of landmines

Techniques for improving the signal to clutter ratio of an. ultra-wideband SAR designed to detect small mine-like objects in the surface of the ground were investigated. In particular, images were collected using different bistatic antenna configurations in an attempt to decorrelate the clutter with respect to the targets. The images were converted to a reference depression angle, summed, and then converted to ground coordinates. The resulting target strengths were then compared with the amplitude distribution of the ground clutter to show the improvement obtained. While some improvement was demonstrated, this was for the relatively easy scenario of targets on the surface partially obscured by grass. Detection based on thresholding the raw RF signal (the bipolar response) rather than the envelope (baseband I-2 + Q(2)) was also considered to further enhance target-to-clutter ratios.

Correlations between the satellite-derived seasonal cycle of phytoplankton biomass and aerosol optical depth in the Southern Ocean: Evidence for the influence of sea ice

The relationship between the production of dimethylsulfide (DMS) in the upper ocean and atmospheric sulfate aerosols has been confirmed through local shipboard measurements, and global modeling studies alike. In order to examine whether such a connection may be recoverable in the satellite record, we have analyzed the correlation between mean surface chlorophyll (CHL) and aerosol optical depth (AOD) in the Southern Ocean, where the marine atmosphere is relatively remote from anthropogenic and continental influences. We carried out the analysis in 5-degree zonal bands between 50 degrees S and 70 degrees S, for the period ( 1997 - 2004), and in smaller meridional sectors in the Eastern Antarctic, Ross and Weddell seas. Seasonality is moderate to strong in both CHL and AOD signatures throughout the study regions. Coherence in the CHL and AOD time series is strong in the band between 50 degrees S and 60 degrees S, however this synchrony is absent in the sea-ice zone (SIZ) south of 60 degrees S. Marked interannual variability in CHL occurs south of 60 degrees S, presumably related to variability in sea-ice production during the previous winter. We find a clear latitudinal difference in the cross correlation between CHL and AOD, with the AOD peak preceding the CHL bloom by up to 6 weeks in the SIZ. This suggests that substantial trace gas emissions ( aerosol precursors) are being produced over the SIZ in spring ( October - December) as sea ice melts. This hypothesis is supported by field data that record extremely high levels of sulfur species in sea ice, surface seawater, and the overlying atmosphere during ice melt.