An examination of forest cover change at Angkor, Cambodia, using satellite imagery, interviews and interpretation of historical events

In the three decades since the mid-1970s through to the early 2000s forest cover at the Angkor World Heritage Site, Cambodia has not progressed linearly but in response to different historical events. This research uses multiple methods in comparing satellite image classification with key informant interviews and other forms of data at the landscape scale and at case studies to provide an historical perspective on forest cover change. The earliest date corresponds to the beginning of the civil war in Cambodia through to a time when a number of events had contributed to significant change in forest pattern and extent at Angkor. The change observed is a result of regulatory controls on land use, ongoing subsistence resource use activities and other events and processes, and more broadly reflects a country in transition and a history of conflict relating to resource governance. The research demonstrates that multiple methods combining medium resolution satellite imagery with interview data and processes detectable at specific time periods can be used to understand patterns of forest change and establish links to processes on the ground

Exploitation des images satellitaires Modis-Terra pour la caractérisation des états de surface : cas de la Tunisie

Bien que de nombreuses incertitudes demeurent sur la rapidité, l'amplitude et la répartition géographique du changement climatique, sa réalité fait aujourd'hui consensus au sein de la communauté scientifique, et l'occurrence des sécheresses et des dégradations du couvert végétal et des zones humides dans tous les continents soulignent l'importance de ce phénomène. Les pays de l'Afrique du nord, et la Tunisie en particulier, sont parmi les régions les plus vulnérables à cause de leurs situations géographiques particulières limitées par le Sahara au sud et la mer au nord. Dans ce contexte de changement global, le suivi spatio-temporel de l'état de surface en Tunisie permettra de comprendre l'étendue, l'amplitude et le déroulement de ce phénomène dans la région. Les images satellitaires hebdomadaires de MODIS-Terra épurées des effets atmosphériques, des nuages et de leur ombre et ayant de bonnes résolutions temporelle et radiométrique sont un bon outil pour le suivi temporel de l'état de surface. Ainsi, des méthodes de classification non supervisée (ISODATA) et supervisée (Maximum de vraisemblance et Fuzzy) sont utilisées pour les classifier. Elles aboutissent à des séries temporelles traduisant l'évolution des surfaces occupées par les sols secs, les sols humides, la végétation et les plans d'eau de 2000 à 2009 ainsi qu'à la détection de leur changement. L'analyse spectrale et le filtrage numérique ont servi pour montrer que l'évolution temporelle de ces quatre classes est à la base annuelle, et qu'elle est liée à la pluviométrie. Cependant, une variabilité à grande échelle, à l'ordre de 8-9 ans, peut être mise en question à cause de sa faible puissance dans les séries temporelles de 10 ans obtenues

Error and uncertainty in the accuracy assessment of land cover maps

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsTraditionally the accuracy assessment of land cover maps is performed through the comparison of these maps with a reference database, which is intended to represent the “real” land cover, being this comparison reported with the thematic accuracy measures through confusion matrixes. Although, these reference databases are also a representation of reality, containing errors due to the human uncertainty in the assignment of the land cover class that best characterizes a certain area, causing bias in the thematic accuracy measures that are reported to the end users of these maps. The main goal of this dissertation is to develop a methodology that allows the integration of human uncertainty present in reference databases in the accuracy assessment of land cover maps, and analyse the impacts that uncertainty may have in the thematic accuracy measures reported to the end users of land cover maps. The utility of the inclusion of human uncertainty in the accuracy assessment of land cover maps is investigated. Specifically we studied the utility of fuzzy sets theory, more precisely of fuzzy arithmetic, for a better understanding of human uncertainty associated to the elaboration of reference databases, and their impacts in the thematic accuracy measures that are derived from confusion matrixes. For this purpose linguistic values transformed in fuzzy intervals that address the uncertainty in the elaboration of reference databases were used to compute fuzzy confusion matrixes. The proposed methodology is illustrated using a case study in which the accuracy assessment of a land cover map for Continental Portugal derived from Medium Resolution Imaging Spectrometer (MERIS) is made. The obtained results demonstrate that the inclusion of human uncertainty in reference databases provides much more information about the quality of land cover maps, when compared with the traditional approach of accuracy assessment of land cover maps

Multi-Temporal Remote-Sensing-based Mapping and Characterization of Landscape Evolution of a Meandering River Floodplain

Large meandering river floodplains are critical components of the Earth ecosystems for their high biodiversity and productivity. However, it is challenging to study these regions because of their complex land-covers and dynamic surface processes. This study applies soft classification and change-detection analysis to five Landsat 5 Thematic Mapper (TM) satellite images to examine long-term surface-cover composition and configuration change of the Rio Beni floodplain in Bolivia from 1987 to 2006. One hard/crisp classification algorithm (i.e., ISODATA) and two soft classification algorithms (i.e., Bayes classification and fuzzy classification) were applied to the study-area satellite images to examine the performances of classifying and mapping meandering river-floodplain environments between hard and soft classification approaches. In all five scenes, three algorithms achieved ~90% classification accuracy via hard classification outputs. However, the two soft algorithms were of more utility in this study because their results were less affected by “salt-and-pepper” noise and provided extra land-cover probability/membership layers. A novel change-detection algorithm was proposed in this study, namely Modified Change Vector Analysis (MCVA). The MCVA operated in fuzzy-membership space, considered change uncertainty during the thresholding stage, and utilized change-vector directions to modify the determination of change/no-change status for each pixel. A fuzzy Markov Random Field (FMRF) model was applied to further refine the change maps by incorporating spatial change uncertainty. A second thresholding stage was also applied to separate a type of change referred to as “transitional change,” which preserved fuzzy membership information and provided a concise map output. Compared with three traditional change-detection algorithms, the MCVA achieved higher change-detection accuracy and provided more detailed change dynamics regarding the land-surface change. Dynamics of major floodplain cover types (i.e., oxbow lakes, river, sand, forest, non-forest vegetation, and dry and wet soil) were investigated via multi-temporal analysis. Over the observing period of 1987 to 2006, 74.4% of pixels remained the same land-cover, 20% experienced clear land-cover change and 5.6% experienced transitional land-cover change. The riparian area experienced more dramatic change than other parts of the Rio Beni floodplain during this period. Additional analysis of landscape metrics provided information regarding the spatial patterns of the land-cover, but future work would be needed to further examine its utility in understanding floodplain dynamics. This study provides information on remote-sensing-based mapping and quantitative characterization methods for meandering river floodplains. The spatiotemporal patterns of landscape on Rio Beni floodplain can be used in sustainable management and protection of floodplain ecosystems

Monitoring Large Conservation Areas with Imaging Spectroscopy

Monitoring of large conservation areas has to be accomplished to fulfil the reporting commitment of the European FFH Directive. Aim of this project was to develop a new monitoring approach for area-wide mapping on a stand level. This approach was based on the combination of numerical methods in vegetation ecology with imaging spectroscopy. The study took place in the FFH conservation area Murnauer Moos, Upper Bavaria. The imagery had been gathered using the imaging spectrometer HyMap™. In order to develop maps that include spatial information on vegetation types as well as on transitions, crisp field and image classifications were combined with fuzzy methods in field and image data analysis. With Non-metric Multidimensional Scaling (NMS) ordination technique for the pre-processing of vegetation data and Partial Least Squares (PLS) regression for extrapolation, we took account of occurring mixed stands and gradual vegetation transitions. In contrast, crisp supervised image classifications are suited to assign clear categories, which are also needed in management practice. Certain emphasis was given to the different possibilities of ground data classification and endmember selection. Different applications of endmember determination to Spectral Angle Mapper (SAM) classification and Multiple Endmember Spectral Mixture Analysis (MESMA) were compared. Synthesis maps for monitoring were produced that deliver two-fold information on pixel basis: vegetation type membership on the one side, stand position in the context of the continuous field of the vegetation on the other. Hence, ecotones can be monitored within habitats. This study shows that with the use of high spatial and spectral resolution of the imagery, this information is given in the same spatial detail for a large area, and the quality of the given details is measurable

Effects of Land Use Change on Juvenile Fishes, Blue Crab, and Brown Shrimp Abundance in the Estuarine Nursery Habitats of North Carolina

The U.S. coastal region is home to more than half of the American population. Also, the coastal counties' population is growing much faster than that of inland counties. With a high density and an increasing population, there are rapid changes in land-use and land-cover (LULC) types, characterized mostly by the increase in areal coverage of anthropogenic land uses (agriculture and developed), while "natural/unaltered" land uses (forest and wetland) are in decline. The human population growth and land-use and land-cover changes caused by humans generate nutrients and pollutants to coastal waters, which can affect water quality and aquatic life. Trends in the land-use and land-cover changes that might impact fish and invertebrate species abundance at 71 selected estuarine stations sampled by the North Carolina Division of Marine Fisheries (NCDMF) juvenile sampling program (Program 120) were analyzed. Land use categories of interest were forest, wetland, agriculture, and developed areas. The selected fish and invertebrate species were: Atlantic croaker (Micropogonias undulatus), Atlantic menhaden (Brevoortia tyrannus), pinfish (Lagodon rhomboides), southern flounder (Paralichthys lethostigma), spot (Leiostomus xanthurus), blue crab (Callinectes sapidus), and brown shrimp (Farfantepenaeus aztectus). Geographic information system (GIS) data, remotely sensed data and statistical techniques were used to quantify the LULC type changes between 1980 and 2000 within the immediate coastal watersheds of North Carolina. Forest has been the most affected, losing about 30.1% of its total area to the increase (~24.1%) of agriculture area. The wetland and developed land use varied depending on location, but their overall changes were small when the whole study area was considered. The long-term trends in abundance of juveniles of selected fish and invertebrate species indicated declines at certain sampling stations, and increases at others. In order to determine whether land use changes were correlated with changes in the selected species, and also to find which other factors might influence changes in their abundance, I analyzed seven predictor variables [(1) percent land use change within local catchments centered on the NCDMF sampling sites, (2) number of pollution point sources in large USDA Natural Resources Soil Conservation watersheds, (3) number of people in US Census tracts within watersheds, (4) water temperature, (5) water salinity, (6) station depth, and (7) distance to inlet (minimum distance by water to an ocean inlet) for each NCDMF juvenile fish and invertebrate trawl sampling program station] in a classification and regression tree statistical analysis to predict normalized change in trawl catch for the selected species in NCDMF Program 120 data between 1980 and 2004. Land use changes were found to be influential to the number of blue crab, southern founder and Atlantic croaker, and declines were observed at 47 stations when land use changes were greater than 13% (blue crab), at 30 stations when land use changes were greater than 21% (southern flounder), and 6 stations when land use changes were greater than 53% (Atlantic croaker). Water salinity was found to be more important than land use change for southern flounder catch, and increased catch was observed at stations with salinity 21 km and highest when salinity was > 14 ppt. Spot showed an increase in abundance when distance to inlet was greater than 42 km and the human population was > 883 people/census tract in the year 2000.  Land use change impacts were observed in the classification and regression tree analysis for blue crab at 66% of the NCDMF stations, 42% of stations for southern flounder, and 8% of stations for Atlantic croaker. These three species were ranked first, second, and fourth in commercial value in North Carolina fisheries, and were the only species of those selected for this study that were considered to be overfished in 2000 by the NCDMF. Thus, land use change had the greatest impact on species that were targets of intensive commercial fishing and had low adult spawning stock. This result suggests an interaction between commercial fisheries harvest and land development for agriculture along the coast. Recruitment of these species may have been low because of reduced spawning stock due to commercial harvests, and this reduced recruitment was most noticeable where land use changes were high. Species that were not intensively harvested (pinfish) or had stable adult stock sizes as determined by the NCDMF (brown shrimp, Atlantic menhaden, and spot) were able to produce many recruits, and this high recruitment may have allowed colonization of areas with marginal habitat due to land use changes. Few stations showed declines in abundance of the juvenile stages of these latter species, suggesting that land use change was not a significant factor between 1980 and 2004. However, post-recruitment mortality (survivorship after June throughout the summer and fall) was not monitored by NCDMF and should be studied in the future. The results of this study serve as an early warning to coastal managers regarding the potential impact of coastal land use changes. The abundance and growth of these valuable fishes and invertebrates in North Carolina estuarine nursery habitats could be reduced in the future, given the national trends in coastal development and fishery harvests.  Ph.D

Video content analysis for automated detection and tracking of humans in CCTV surveillance applications

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The problems of achieving high detection rate with low false alarm rate for human detection and tracking in video sequence, performance scalability, and improving response time are addressed in this thesis. The underlying causes are the effect of scene complexity, human-to-human interactions, scale changes, and scene background-human interactions. A two-stage processing solution, namely, human detection, and human tracking with two novel pattern classifiers is presented. Scale independent human detection is achieved by processing in the wavelet domain using square wavelet features. These features used to characterise human silhouettes at different scales are similar to rectangular features used in [Viola 2001]. At the detection stage two detectors are combined to improve detection rate. The first detector is based on shape-outline of humans extracted from the scene using a reduced complexity outline extraction algorithm. A Shape mismatch measure is used to differentiate between the human and the background class. The second detector uses rectangular features as primitives for silhouette description in the wavelet domain. The marginal distribution of features collocated at a particular position on a candidate human (a patch of the image) is used to describe statistically the silhouette. Two similarity measures are computed between a candidate human and the model histograms of human and non human classes. The similarity measure is used to discriminate between the human and the non human class. At the tracking stage, a tracker based on joint probabilistic data association filter (JPDAF) for data association, and motion correspondence is presented. Track clustering is used to reduce hypothesis enumeration complexity. Towards improving response time with increase in frame dimension, scene complexity, and number of channels; a scalable algorithmic architecture and operating accuracy prediction technique is presented. A scheduling strategy for improving the response time and throughput by parallel processing is also presented

Combining remote sensing change detection and qualitative data to examine landscape change in the context of world heritage

Following inscription of Angkor on the World Heritage List in 1992, restrictions on forest use have been imposed on the local communities residing within the Angkor area. The result has been reduced access to forest resources by local villagers living within the WHS management zones, and with it reduced vegetation cover. Boundaries associated with World Heritage inscription, as defined by administrative lines, are often ambiguous where local boundary demarcation has evolved over time. This ambiguity has contributed to differing levels of constraints on access to resources being placed on communities. This research examines vegetation response to changing use levels enforced through forest management policy across the broader Angkor area. Mixed methods (Jiang, 2003; Creswell and Plano-Clark, 2007) are used to examine the influence of World Heritage zoning on subsistence use of forest resources, and to evaluate different approaches for quantifying and monitoring vegetation change. The effectiveness of site management, in the context of World Heritage obligations, for achieving conservation and development objectives is explored, with an emphasis on combining quantitative remote sensing and qualitative methods. Spatio-temporal patterns of vegetation change and forest resource constraints imposed on villagers are compared at locations both within and outside the WHS management zones. Multiple study sites were established in the north-east of the Angkor plain and the higher slopes and plateau of Phnom Kulen National Park. Research methods included semi-structured interviews with local villagers and key informants (including senior representatives of the Authority for the Protection and Management of Angkor and the Region of Siem Reap (APSARA)), field-based vegetation surveys, and analysis of management policies and historical vegetation and relevant management reports. Field-based studies engaged representatives from local communities in semi-structured interviews across 17 villages to understand how restrictions on forest access at the local level have influenced vegetation change. Vegetation change analysis using field-based vegetation surveys and classified high resolution multi-spectral satellite imagery, as well as informal interviews at spatial locations in close correspondence with areas identified from the remote sensing change V detection, further augmented this process by relating levels of subsistence use to different patterns of vegetation change that have occurred at both the local and landscape scale. Bi-temporal Multivariate Alteration Detection (MAD; Canty, 2007; Canty and Nielsen, 2008) was used to identify landscape change as it does not require the identification of discrete unvegetated areas of sufficient size required to use as calibration targets for image normalisation. MAD outputs show different aspects of change in land cover such as vegetation changing to soil or to rice paddy, vegetation growth, vegetation removal or change in vegetation type between the two dates. The Normalised Difference Vegetation Index (NDVI; Rouse et al., 1973) was used to generate vegetation change maps and quantify change at case studies. The issues surrounding management of the Angkor WHS, including access and availability of forest resources for local residents, are evident in the spatio-temporal correspondence between signature patterns observed in remotely sensed imagery and events as described in field interviews. Several findings emerged from this research. Firstly, interpretation of remote sensing change analysis and data collected during community-based interviews suggests that controls imposed by management is targeted at locals yet unregulated activity by outsiders and those able to circumvent the existing zoning regulations, appears to have created significant change. Secondly, while villagers located within the WHS core management Zones 1 and 2, the two zones with the strictest controls, appear to share similar constraints on use of forest resources for subsistence purposes, the restrictions associated with the management across these zones differ. This is most evident at villages located in close proximity to each other but within different management zones, supporting the argument that controls associated with each of the management boundaries have little relevance to the activities occurring on-the-ground. Thirdly, to sufficiently understand the change identified from the remote sensing analysis both social and cultural processes must be examined. Lastly, understanding the implications of landscape change, both within and across borders, is important for heritage management, and Geographic Information Systems (GIS) and remote sensing based mixed methods can contribute to quantifying such change. This research acknowledges the need to incorporate the broader cultural landscapes of Angkor into management, and argues that the regulations imposed on local communities by the inscription of the site have had unintended consequences, particularly in those zones of management where regulations have proved difficult to enforce. Additionally, it recognises the VI importance of understanding links between differing constraints on the subsistence use of forest resources imposed by heritage listing, and observed rates of vegetation change. The value of management approaches that extend WHS boundaries is also demonstrated, including the contribution of both remotely sensed based monitoring techniques and community-based interviews in establishing connectivity between these spatio-temporal trends and the processes underlying observed change