Assessing the dynamic of structural changes in Cerrado vegetation of protected and non-protected areas using NDVI

The structure of Brazilian savannah, named locally as “cerrado”, tends to change if the human pressures, such as pasture and intensive fire, are suppressed showing a densification of the physiognomies throughout the time. Vegetation Index acquired from remotely sensed data has been a proper way to study and monitoring large areas, and the Normalized Difference Vegetation Index (NDVI) is one of the most used for this purpose. The aim of this study was to assess the dynamic of structural changes in protected and non-protected areas of cerrado vegetation using NDVI. For this purpose, three cerrado fragments in the state of São Paulo, Brazil, were evaluated for a 26 year time span from 1985 and 2011, being two of them protected against anthropogenic interference. Landsat 5 –Thematic Mapper images were used and processed in ArcGIS. In the protected areas NDVI indicated that the vegetation followed the expected trend of changes for cerrado, with more open physiognomies tending to be denser throughout this period of 26 years, whereas in the non-protected fragment the NDVI evidences human pressure, showing lower phytomass in 2011. NDVI showed to be efficient in detecting and monitoring changes in cerrado vegetation structure, and can be useful to study both, the natural dynamics of cerrado vegetation and the anthropogenic interference in protected areas.

Multitemporal assessment of the geomorphologic evolution of the Restinga of Marambaia, Rio de Janeiro, Brazil

The Restinga of Marambaia is an emerged sand bar located between the Sepetiba Bay and the South Atlantic Ocean, on the south-east coast of Brazil. The objective of this study was to observe the geomorphologic evolution of the coastal zone of the Restinga of Marambaia using multitemporal satellite images acquired by multisensors from 1975 to 2004. The images were digitally segmented by a region growth algorithm and submitted to an unsupervised classification procedure (ISOSEG) followed by a raster edit based on visual interpretation. The image time-series showed a general trend of decrease in the total sand bar area with values varying from 80.61km(2) in 1975 to 78.15km(2) in 2004. The total area calculation based on the 1975 and 1978 Landsat MSS data was shown to be super-estimated in relation to the Landsat TM, Landsat ETM+, and CBERS-2 CCD data. These differences can also be associated to the relatively poorer spatial resolution of the MSS data, nominally 79m, against the 20m of the CCD data and 30m of the TM and ETM+ data. For the estimates of the width in the central portion of the sand bar the variation was from 158m (1975) to 100m (2004). The formation of a spit in the northern region of the study area was visually observed. The area of the spit was estimated, with values varying from 0.82km(2) (1975) to 0.55km(2) (2004).

Soil carbon balance in a tropical grassland: Estimation of soil respiration and its partitioning using a semi-empirical model

In savannah and tropical grasslands, which account for 60% of grasslands worldwide, a large share of ecosystem carbon is located below ground due to high root:shoot ratios. Temporal variations in soil CO2 efflux (R-S) were investigated in a grassland of coastal Congo over two years. The objectives were (1) to identify the main factors controlling seasonal variations in R-S and (2) to develop a semi-empirical model describing R-S and including a heterotrophic component (R-H) and an autotrophic component (R-A). Plant above-ground activity was found to exert strong control over soil respiration since 71% of seasonal R-S variability was explained by the quantity of photosynthetically active radiation absorbed (APAR) by the grass canopy. We tested an additive model including a parameter enabling R-S partitioning into R-A and R-H. Assumptions underlying this model were that R-A mainly depended on the amount of photosynthates allocated below ground and that microbial and root activity was mostly controlled by soil temperature and soil moisture. The model provided a reasonably good prediction of seasonal variations in R-S (R-2 = 0.85) which varied between 5.4 mu mol m(-2) s(-1) in the wet season and 0.9 mu mol m(-2) s(-1) at the end of the dry season. The model was subsequently used to obtain annual estimates of R-S, R-A and R-H. In accordance with results reported for other tropical grasslands, we estimated that R-H accounted for 44% of R-S, which represented a flux similar to the amount of carbon brought annually to the soil from below-ground litter production. Overall, this study opens up prospects for simulating the carbon budget of tropical grasslands on a large scale using remotely sensed data. (C) 2012 Elsevier B.V. All rights reserved.

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.

Applications of LiDAR remote sensing of forest structure in the Upper Great Lakes region, USA

We used active remote sensing technology to characterize forest structure in a northern temperate forest on a landscape- and local-level in the Upper Peninsula of Michigan. Specifically, we used a form of active remote sensing called light detection and ranging (e.g., LiDAR) to aid in the depiction of current forest structural stages and total canopy gap area estimation. On a landscape-level, LiDAR data are shown not only to be a useful tool in characterizing forest structure, in both coniferous and deciduous forest cover types, but also as an effective basis for data-driven surrogates for classification of forest structure. On a local-level, LiDAR data are shown to be a benchmark reference point to evaluate field-based canopy gap area estimations, due to the highly accurate nature of such remotely sensed data. The application of LiDAR remote sensed data can help facilitate current and future sustainable forest management.

TECHNOLOGICAL ADVANCEMENT IN REMOTE SENSING AND INNOVATIVE APPLICATION TO VOLCANOLOGY

The integration of remote monitoring techniques at different scales is of crucial importance for monitoring of volcanoes and assessment of the associated hazard. In this optic, technological advancement and collaboration between research groups also play a key role. Vhub is a community cyberinfrastructure platform designed for collaboration in volcanology research. Within the Vhub framework, this dissertation focuses on two research themes, both representing novel applications of remotely sensed data in volcanology: advancement in the acquisition of topographic data via active techniques and application of passive multi-spectral satellite data to monitoring of vegetated volcanoes. Measuring surface deformation is a critical issue in analogue modelling of Earth science phenomena. I present a novel application of the Microsoft Kinect sensor to measurement of vertical and horizontal displacements in analogue models. Specifically, I quantified vertical displacement in a scaled analogue model of Nisyros volcano, Greece, simulating magmatic deflation and inflation and related surface deformation, and included the horizontal component to reconstruct 3D models of pit crater formation. The detection of active faults around volcanoes is of importance for seismic and volcanic hazard assessment, but not a simple task to be achieved using analogue models. I present new evidence of neotectonic deformation along a north-south trending fault from the Mt Shasta debris avalanche deposit (DAD), northern California. The fault was identified on an airborne LiDAR campaign of part of the region interested by the DAD and then confirmed in the field. High resolution LiDAR can be utilized also for geomorphological assessment of DADs, and I describe a size-distance analysis to document geomorphological aspects of hummock in the Shasta DAD. Relating the remote observations of volcanic passive degassing to conditions and impacts on the ground provides an increased understanding of volcanic degassing and how satellite-based monitoring can be used to inform hazard management strategies in nearreal time. Combining a variety of satellite-based spectral time series I aim to perform the first space-based assessment of the impacts of sulfur dioxide emissions from Turrialba volcano, Costa Rica, on vegetation in the surrounding environment, and establish whether vegetation indices could be used more broadly to detect volcanic unrest.

Carbon storage versus albedo change: radiative forcing of forest expansion in temperate mountainous regions of Switzerland

In this study, we assess the climate mitigation potential from afforestation in a mountainous snow-rich region (Switzerland) with strongly varying environmental conditions. Using radiative forcing calculations, we quantify both the carbon sequestration potential and the effect of albedo change at high resolution. We calculate the albedo radiative forcing based on remotely sensed data sets of albedo, global radiation and snow cover. Carbon sequestration is estimated from changes in carbon stocks based on national inventories. We first estimate the spatial pattern of radiative forcing (RF) across Switzerland assuming homogeneous transitions from open land to forest. This highlights where forest expansion still exhibits climatic benefits when including the radiative forcing of albedo change. Second, given that forest expansion is currently the dominant land-use change process in the Swiss Alps, we calculate the radiative forcing that occurred between 1985 and 1997. Our results show that the net RF of forest expansion ranges from −24 W m−2 at low elevations of the northern Prealps to 2 W m−2 at high elevations of the Central Alps. The albedo RF increases with increasing altitude, which offsets the CO2 RF at high elevations with long snow-covered periods, high global radiation and low carbon sequestration. Albedo RF is particularly relevant during transitions from open land to open forest but not in later stages of forest development. Between 1985 and 1997, when overall forest expansion in Switzerland was approximately 4%, the albedo RF offset the CO2 RF by an average of 40%. We conclude that the albedo RF should be considered at an appropriately high resolution when estimating the climatic effect of forestation in temperate mountainous regions.

Climate and infectious disease: Use of remote sensing for detection of Vibrio cholerae by indirect measurement

It has long been known that cholera outbreaks can be initiated when Vibrio cholerae, the bacterium that causes cholera, is present in drinking water in sufficient numbers to constitute an infective dose, if ingested by humans. Outbreaks associated with drinking or bathing in unpurified river or brackish water may directly or indirectly depend on such conditions as water temperature, nutrient concentration, and plankton production that may be favorable for growth and reproduction of the bacterium. Although these environmental parameters have routinely been measured by using water samples collected aboard research ships, the available data sets are sparse and infrequent. Furthermore, shipboard data acquisition is both expensive and time-consuming. Interpolation to regional scales can also be problematic. Although the bacterium, V. cholerae, cannot be sensed directly, remotely sensed data can be used to infer its presence. In the study reported here, satellite data were used to monitor the timing and spread of cholera. Public domain remote sensing data for the Bay of Bengal were compared directly with cholera case data collected in Bangladesh from 1992–1995. The remote sensing data included sea surface temperature and sea surface height. It was discovered that sea surface temperature shows an annual cycle similar to the cholera case data. Sea surface height may be an indicator of incursion of plankton-laden water inland, e.g., tidal rivers, because it was also found to be correlated with cholera outbreaks. The extensive studies accomplished during the past 25 years, confirming the hypothesis that V. cholerae is autochthonous to the aquatic environment and is a commensal of zooplankton, i.e., copepods, when combined with the findings of the satellite data analyses, provide strong evidence that cholera epidemics are climate-linked.

Conservation of freshwater thermal habitats for Pacific salmon in a changing climate

Thesis (Ph.D.)--University of Washington, 2016-06

Measuring and incorporating vulnerability into conservation planning

Conservation planning is the process of locating and designing conservation areas to promote the persistence of biodiversity in situ. To do this, conservation areas must be able to mitigate at least some of the proximate threats to biodiversity. Information on threatening processes and the relative vulnerability of areas and natural features to these processes is therefore crucial for effective conservation planning. However, measuring and incorporating vulnerability into conservation planning have been problematic. We develop a conceptual framework of the role of vulnerability assessments in conservation planning and propose a definition of vulnerability that incorporates three dimensions: exposure, intensity, and impact. We review and categorize methods for assessing the vulnerability of areas and the features they contain and identify the relative strengths and weaknesses of each broad approach, Our review highlights the need for further development and evaluation of approaches to assess vulnerability and for comparisons of their relative effectiveness.

Mapping and characterising subtropical estuarine landscapes using aerial photography and GIS for potential application in wildlife conservation and management

Coarse-resolution thematic maps derived from remotely sensed data and implemented in GIS play an important role in coastal and marine conservation, research and management. Here, we describe an approach for fine-resolution mapping of land-cover types using aerial photography and ancillary GIs and ground data in a large (100 x 35 km) subtropical estuarine system (Moreton Bay, Queensland, Australia). We have developed and implemented a classification scheme representing 24 coastal (subtidal, intertidal. mangrove, supratidal and terrestrial) cover types relevant to the ecology of estuarine animals, nekton and shorebirds. The accuracy of classifications of the intertidal and subtidal cover types, as indicated by the agreement between the mapped (predicted) and reference (ground) data, was 77-88%, depending on the zone and level of generalization required. The variability and spatial distribution of habitat mosaics (landscape types) across the mapped environment were assessed using K-means clustering and validated with Classification and Regression Tree models. Seven broad landscape types could be distinguished and ways of incorporating the information on landscape composition into site-specific conservation and field research are discussed. This research illustrates the importance and potential applications of fine-resolution mapping for conservation and management of estuarine habitats and their terrestrial and aquatic wildlife. (c) 2005 Elsevier Ltd. All rights reserved.

The application of remote sensing to water resources

Techniques are developed for the visual interpretation of drainage features from satellite imagery. The process of interpretation is formalised by the introduction of objective criteria. Problems of assessing the accuracy of maps are recognized, and a method is developed for quantifying the correctness of an interpretation, in which the more important features are given an appropriate weight. A study was made of imagery from a variety of landscapes in Britain and overseas, from which maps of drainage networks were drawn. The accuracy of the mapping was assessed in absolute terms, and also in relation to the geomorphic parameters used in hydrologic models. Results are presented relating the accuracy of interpretation to image quality, subjectivity and the effects of topography. It is concluded that the visual interpretation of satellite imagery gives maps of sufficient accuracy for the preliminary assessment of water resources, and for the estimation of geomorphic parameters. An examination is made of the use of remotely sensed data in hydrologic models. It is proposed that the spectral properties of a scene are holistic, and are therefore more efficient than conventional catchment characteristics. Key hydrologic parameters were identified, and were estimated from streamflow records. The correlation between hydrologic variables and spectral characteristics was examined, and regression models for streamflow were developed, based solely on spectral data. Regression models were also developed using conventional catchment characteristics, whose values were estimated using satellite imagery. It was concluded that models based primarily on variables derived from remotely sensed data give results which are as good as, or better than, models using conventional map data. The holistic properties of remotely sensed data are realised only in undeveloped areas. In developed areas an assessment of current land-use is a more useful indication of hydrologic response.

Radiative forcing of natural forest disturbances

Forest disturbances are major sources of carbon dioxide to the atmosphere, and therefore impact global climate. Biogeophysical attributes, such as surface albedo (reflectivity), further control the climate-regulating properties of forests. Using both tower-based and remotely sensed data sets, we show that natural disturbances from wildfire, beetle outbreaks, and hurricane wind throw can significantly alter surface albedo, and the associated radiative forcing either offsets or enhances the CO2 forcing caused by reducing ecosystem carbon sequestration over multiple years. In the examined cases, the radiative forcing from albedo change is on the same order of magnitude as the CO2 forcing. The net radiative forcing resulting from these two factors leads to a local heating effect in a hurricane-damaged mangrove forest in the subtropics, and a cooling effect following wildfire and mountain pine beetle attack in boreal forests with winter snow. Although natural forest disturbances currently represent less than half of gross forest cover loss, that area will probably increase in the future under climate change, making it imperative to represent these processes accurately in global climate models.

Detecting Calcareous Periphyton Mats in the Greater Everglades Using Passive Remote Sensing Methods

Use of remotely sensed data for environmental and ecological assessment has recently become more widespread in wetland research and management and advantages and limitations of this approach have been addresses (Ozesmi and Bauer 2002). Applications of remote sensing (RS) methods vary in spatial and temporal extent and resolution, in the types of data acquired, and in digital processing and pattern recognition algorithms used.