Poverty and inequality in Vietnam: spatial patterns and geographic determinants

"This study uses a relatively new method called “small area estimation” to estimate various measures of poverty and inequality for provinces, districts, and communes of Vietnam. The method was applied by combining information from the 1997-98 Vietnam Living Standards Survey and the 1999 Population and Housing Census... Mapping the density of poverty reveals that, although the poverty rates are highest in the remote upland areas, these areas are sparsely populated so most of the poor live in the Red River Delta and the Mekong River Delta... This analysis confirms other studies indicating that the inequality in per capita expenditure is relatively low in Vietnam by international standards. Inequality is greatest in the large cities and (surprisingly) in parts of the upland areas. Inequality is lowest in the Red River Delta, followed by the Mekong Delta. Just one-third of the inequality is found between districts and two-thirds within them, suggesting that district-level targeting of anti-poverty programs may not be very effective... Finally, the study notes that the small area estimation method is not very useful for annual poverty mapping because it relies on census data, but it could be used to show detailed spatial patterns in other variables of interest to policymakers, such as income diversification, agricultural market surplus, and vulnerability. Furthermore, it can be used to estimate poverty rates among vulnerable populations too small to be studied with household survey data, such as the disabled, small ethnic minorities, or fishermen." from Authors' summarysouth east asia, East and Southeast Asia, Vietnam, Inequality, Poverty mapping,

Investigation of Spatial and Temporal Aspects of Airborne Gamma Spectrometry: Final Report

A study has been conducted which demonstrates the reproducibility of Airborne Gamma-ray Spectrometry (AGS) and the effects of changes in survey parameters, particularly line spacing. This has involved analysis of new data collected from estuarine salt marsh and upland areas in West Cumbria and SW Scotland during three phases of field work, in which over 150000 spectra were recorded with a 16 litre NaI(Tl) detector. The shapes and inventories of radiometric features have been examined. It has been shown that features with dimensions that are large relative to the survey line spacing are very well reproduced with all line spacings, whereas smaller features show more variability. The AGS technique has been applied to measuring changes in the radiation environment over a range of time scales from a few days to several years using data collected during this and previous surveys of the area. Changes due to sedimentation and erosion of salt marshes, and hydrological transportation of upland activity have been observed

Augmented Terrain-Based Navigation to Enable Persistent Autonomy for Underwater Vehicles in GPS-Denied Environments

Aquatic robots, such as Autonomous Underwater Vehicles (AUVs), play a major role in the study of ocean processes that require long-term sampling efforts and commonly perform navigation via dead-reckoning using an accelerometer, a magnetometer, a compass, an IMU and a depth sensor for feedback. However, these instruments are subjected to large drift, leading to unbounded uncertainty in location. Moreover, the spatio-temporal dynamics of the ocean environment, coupled with limited communication capabilities, make navigation and localization difficult, especially in coastal regions where the majority of interesting phenomena occur. To add to this, the interesting features are themselves spatio-temporally dynamic, and effective sampling requires a good understanding of vehicle localization relative to the sampled feature. Therefore, our work is motivated by the desire to enable intelligent data collection of complex dynamics and processes that occur in coastal ocean environments to further our understanding and prediction capabilities. The study originated from the need to localize and navigate aquatic robots in a GPS-denied environment and examine the role of the spatio-temporal dynamics of the ocean into the localization and navigation processes. The methods and techniques needed range from the data collection to the localization and navigation algorithms used on-board of the aquatic vehicles. The focus of this work is to develop algorithms for localization and navigation of AUVs in GPS-denied environments. We developed an Augmented terrain-based framework that incorporates physical science data, i.e., temperature, salinity, pH, etc., to enhance the topographic map that the vehicle uses to navigate. In this navigation scheme, the bathymetric data are combined with the physical science data to enrich the uniqueness of the underlying terrain map and increase the accuracy of underwater localization. Another technique developed in this work addresses the problem of tracking an underwater vehicle when the GPS signal suddenly becomes unavailable. The methods include the whitening of the data to reveal the true statistical distance between datapoints and also incorporates physical science data to enhance the topographic map. Simulations were performed at Lake Nighthorse, Colorado, USA, between April 25th and May 2nd 2018 and at Big Fisherman\u27s Cove, Santa Catalina Island, California, USA, on July 13th and July 14th 2016. Different missions were executed on different environments (snow, rain and the presence of plumes). Results showed that these two methodologies for localization and tracking work for reference maps that had been recorded within a week and the accuracy on the average error in localization can be compared to the errors found when using GPS if the time in which the observations were taken are the same period of the day (morning, afternoon or night). The whitening of the data had positive results when compared to localizing without whitening

Development of national extent terrain attributes (tanz), soil water balance surfaces (swatbal), and environmental surfaces, and their application for spatial modelling of pinus radiata productivity across new zealand

The most widely distributed and commercially important forestry crop in New Zealand is Pinus radiata D. Don. Until recently foresters have focussed on maintaining plantation management systems that are highly productive, while remaining sustainable. However, the new era of reduced carbon emissions and carbon trading means forestry systems are now viewed as potential sinks for the sequestration of carbon. Never before has the need to quantify the productive capacity of New Zealand's plantation forests at the national extent been so great. Furthermore, regions of relatively low productivity may become increasingly desirable because these sites require lower capital outlay. In this research, a series of spatial surfaces potentially useful in the modelling and mapping of forest productivity across the national extent of New Zealand have been developed. Modelled surfaces include 15 primary and four secondary terrain attributes; 13 shortwave radiation surfaces, topographically adjusted (one annual and 12 monthly surfaces); and 39 soil water balance model surfaces (one annual and 12 monthly surfaces for fraction of available root zone water storage, available root zone water storage, and drainage). Terrain attributes were developed using a 25-m floating point DEM and are unique and currently the best comprehensive surfaces for the following reasons. (1) Terrain attributes comprehensively encompass the entire country compared with previous piecemeal and site-specific surfaces. (2) Terrain attributes were modelled using a macro-catchment concept that divides the New Zealand landscape into large, naturally draining catchments to avoid the modelling problems associated with edge effects at catchment boundaries. (3) Upslope contributing areas were calculated by switching between an FD8 algorithm that modelled flow divergence in upland regions above defined stream channels and a D8 algorithm used in low-lying areas where modelling of flow convergence is appropriate. (4) Where appropriate, terrain attributes were corrected for undesirable spurious sinks inherent in the 25-m floating point DEM, while retaining naturally occurring sinks in karst environments, depressional lakes and wetlands. This correction provided a continuous surface that modelled flow either to a sink or continuously across the surface until reaching the sea. The soil water balance model, SWatBal, is a dynamic spatial model that can be updated over time as new and improved data become available. SWatbal calculates the fraction of available root-zone water content, available root-zone water content, and drainage for the P. radiata species at a 100-m resolution throughout New Zealand. SWatBal was applied in this study to derive monthly mean soil water balance values, but the model can easily be adjusted to calculate any spatial extent or period. A further advance of SWatBal is the development of reasoned and allocated virtual (RAV) rainfall data. RAV consist of 365 rainfall surfaces representing the normal rainfall distribution on a monthly basis. The advantage RAV data have over monthly mean rainfall is that rainfall distribution of an actual month is used, making the data realistic, rather than assuming constant rainfall across each day for a month. A shortwave-radiation model was developed for New Zealand at a 25-m cell-size resolution utilising a national extent DEM and a latitude surface. This shortwave radiation model encompassed slope and aspect adequately while simultaneously accounting for the influence of terrain shading. As a model it has simplicity, flexibility, and minimal computation time and storage requirements. A partial least squares (PLS) regression technique was used to develop the surfaces of (i) stem volume mean annual increment at age thirty years for a defined reference regime of 300 stems ha-1 (300 Index), and (ii) mean top height at age twenty (Site Index) using TANZ, SWatBal and other developed and existing New Zealand spatial datasets. Together, (i) and (ii) provided the basis for a spatial model of P. radiata productivity. Initially, the 300 Index and Site Index values were calculated for 1698 permanent sampling plot (PSP) locations. For cross validation purposes, 552 PSP sites were withheld from all modelling procedures. PLS regression was used to model and predict 300 Index and Site Index values using previously developed and some existing datasets including climate, landuse, terrain, and their environmental surfaces. Best models explained 58% and 67 % of the variance for 300 Index and Site Index, respectively. The PLS models were also used to develop quantitative productivity maps across the national extent of New Zealand. In addition, a regression kriging (RK) technique was used, where ordinary kriging (OK) of the PLS model residuals was undertaken to improve model outcomes by summing the PLS and OK surfaces. Cross validation showed that prediction precision increased for both the 300 Index and Site Index RK models. However, only Site Index predictions were considered less biased using the RK technique. Findings from the commonly used and relatively straight forward spatial interpolation technique, inverse distance weighting (IDW), were compared with those derived using the more complex RK, OK, and PLS techniques. Cross validation showed that all techniques performed better than their respective data means. OK, RK, and IDW techniques were similar in prediction precision with the IDW prediction precision best for the 300 Index, and RK best for the Site Index. However, OK predictions showed reduced prediction bias. Having stated that RK, OK, and IDW interpolation techniques provided overall better predictions than PLS, it is emphasised that cross validation locations only occur within currently forested landscapes. Beyond these forested regions PLS regression has an inordinate advantage over OK and IDW prediction techniques by utilising local environmental and landform information. Additionally, there is the potential of prediction improvement through the coupling of the PLS model with its kriged regression residuals. Indeed, the main purpose of producing the 300 Index and Site Index maps was to provide empirically based predictions of regions currently without forests as much as regions with forests through spatial interpolation of existing national extent observed PSP data. Possible drivers of P. radiata productivity across 14 broad LENZ-derived environmental regimes were also assessed. It was found that generally air temperature and water balance variables were the predominate drivers

The synthesis of estuarine bathymetry from sparse sounding data

The two aims of the project involved: 1. Devising a system for prediction o f areas of bathymetric change within the Fal estuary 2. Formulating and evaluating a method for interpolating single beam acoustic bathymetry to avoid artefacts o f interpolation. In order to address these aims, sources of bathymetric data for the Fal estuary were identified as Truro Harbour Office, Cornwall County Council and the Environment Agency. The data collected from these sources included red wavelength Lidar, aerial photography and single beam acoustic bathymetry from a number of different years. These data were input into a Geographic Information System (GIS) and assessed for suitability for the purposes o f data comparison and hence assessment of temporal trends in bathymetry within the estuary Problems encountered during mterpolation of the acoustic bathymetry resulted in the later aim of the project, to formulate an interpolation system suitable for interpolation of the single beam, bathymetric data in a realistic way, avoiding serious artefacts of interpolation. This aim was met, successfully, through the following processes: 1. An interpolation system was developed, using polygonal zones, bounded by channels and coastlines, to prevent interpolation across these boundaries. This system, based on Inverse Distance Weighting (IDW) interpolation, was referred to as Zoned Inverse Distance Weighting (ZIDW). 2. ZIDW was found, by visual inspection, to eliminate the interpolation artefacts described above. 3. The processes of identification of sounding lines and charmels, and the allocation of soundings and output grid cells to polygons, were successfully automated to allow ZIDW to be applied to large and multiple data sets. Manual intervention was maintained for processes performed most successfully by the human brain to optimise the results o f ZIDW. 4. To formalise the theory of ZIDW it was applied to a range of idealised, mathematically defined chaimels. For simple straight and regular curved, mathematical channels interpolation by the standard TIN method was found to perform as well as ZIDW. 5. Investigation of sinusoidal channels within a rectangular estuary, however, revealed that the TIN method begins to produce serious interpolation artefacts where sounding lines are not parallel to the centre lines o f channels and ridges. Hence, overall ZIDW was determined mathematically to represent the optimum method o f interpolation for single beam, bathymelric data. 6. Finally, ZIDW was refined, using data from the Humber and Gironde estuaries, to achieve universal applicability for interpolation of single beam, echo soimding data from any estuary. 7. The refinements involved allowance for non-continuous, flood and ebb type charmels; consideration of the effects of the scale of the estuary; smoothing of the channels using cubic splines; interpolation using a 'smart' ellipse and the option to reconstruct sounding lines from data that had previously been re-ordered

Patterns and Pathways of Wetland Sedimentation and Landscape Change in Coastal Louisiana

Coastal Louisiana wetlands exist in a dynamic physical environment and retracted dramatically in the last century. Here I examine the spatial and temporal variability of this landscape with an emphasis on the interactions between anthropogenic landscape modifications and geological processes. The Mississippi River watershed underwent drastic changes during the past 200 years, beginning with widespread land clearing and, later, large-scale reservoir construction. These modifications caused increases in suspended sediment concentrations, then sharp decreases, and have remained relatively stable since 1960. I show how changes in land area of the Mississippi River birdfoot delta reflect these fluctuations, and that they are distinct from the timing of land losses elsewhere along the coast. The deposition of inorganic sediments elsewhere along the coast is driven primarily by marine processes. I quantified the total amount and spatial distribution of mineral sediment following recent hurricanes and found that Hurricanes Katrina, Rita, and Gustav deposited an estimated 68, 48, and 21 million metric tons (MMT), respectively. I used the observed sediment deposition patterns away from the coast and storm track to estimate a long-term tropical cyclone sedimentation rate (5.6 MMT/yr) for coastal Louisiana wetlands, which accounts for the majority of inorganic sediments in soils of the abandoned delta lobes and chenier plain. I applied geographically weighted regression as a supplement to a traditional regression of geological and anthropogenic factors to further explore patterns of landscape variability. I found that the patterns of interior wetland loss are strongly related to the density of dredged canals, and that this relationship varies spatially. Canals closer to the coast, for example, are more strongly correlated to land loss than those found further inland. The research presented here raises new questions about how physical, chemical, and biological systems interact and regulate coastal systems, and how these driving factors can vary considerably over relatively short distances. The success of coastal restoration in Louisiana and elsewhere will be greatly aided if this spatial variability and remaining scientific uncertainties are included in planning and implementation schemes

Utilizing remote sensing of thematic mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

The land-water interface of coastal marshes may influence the production of estuarine-dependent fisheries more than the area of these marshes. To test this hypothesis, a spatial model was created to explore the dynamic relationship between marshland-water interface and level of disintegration in the decaying coastal marshes of Louisiana's Barataria, Terrebonne, and Timbalier basins. Calibrating the model with Landsat Thematic Mapper satellite imagery, a parabolic relationship was found between land-water interface and marsh disintegration. Aggregated simulation data suggest that interface in the study area will soon reach its maximum and then decline. A statistically significant positive linear relationship was found between brown shrimp catch and total interface length over the past 28 years. This relationship suggests that shrimp yields will decline when interface declines, possibly beginning about 1995

Data analysis

The authors present to the Working Group on Ecosystem Monitoring and Management (WG EMM) the scientific background and justification for the development of a marine protected area (MPA) in the Weddell Sea planning area. In accordance with the recommendations by WG-EMM-14 (SC-CAMLR-XXIII, Annex 6), this was done in three separate documents (Part A-C). WG-EMM-16/01 (Part A) sets out the general context of the establishment of CCAMLR-MPAs and provides the background information on the Weddell Sea MPA (WSMPA) planning area; WG-EMM-16/02 (Part B) informs on the data retrieval process and WG-EMM-16/03 (Part C) describes the methods and the results of the scientific analyses as well as the development of the objectives and finally of the borders for the WSMPA. Earlier versions of Parts A-C were already presented at the meetings of EMM and SC-CAMLR in 2015. The Scientific Committee did recognise that the body of science of the background documents (SC-CAMLR-XXXIV/BG/15, BG/16, BG/17) provides the necessary foundation for developing a WSMPA proposal (SC-CAMLR-XXXIV, § 5.11). Here, the authors present the final version of Part C to WG EMM. Part C has been further revised in the light of comments received at the above mentioned meetings and in the 2015/16 intersessional period. The text has also undergone final editorial corrections. Chapter 1 shows a revision of the data analysis including, for example, newly analysed data layers on seabirds and demersal fish. Chapter 2 provides an update of the newly conducted MPA scenario development incorporating a cost layer analysis

GeoAI-enhanced Techniques to Support Geographical Knowledge Discovery from Big Geospatial Data

abstract: Big data that contain geo-referenced attributes have significantly reformed the way that I process and analyze geospatial data. Compared with the expected benefits received in the data-rich environment, more data have not always contributed to more accurate analysis. “Big but valueless” has becoming a critical concern to the community of GIScience and data-driven geography. As a highly-utilized function of GeoAI technique, deep learning models designed for processing geospatial data integrate powerful computing hardware and deep neural networks into various dimensions of geography to effectively discover the representation of data. However, limitations of these deep learning models have also been reported when People may have to spend much time on preparing training data for implementing a deep learning model. The objective of this dissertation research is to promote state-of-the-art deep learning models in discovering the representation, value and hidden knowledge of GIS and remote sensing data, through three research approaches. The first methodological framework aims to unify varied shadow into limited number of patterns, with the convolutional neural network (CNNs)-powered shape classification, multifarious shadow shapes with a limited number of representative shadow patterns for efficient shadow-based building height estimation. The second research focus integrates semantic analysis into a framework of various state-of-the-art CNNs to support human-level understanding of map content. The final research approach of this dissertation focuses on normalizing geospatial domain knowledge to promote the transferability of a CNN’s model to land-use/land-cover classification. This research reports a method designed to discover detailed land-use/land-cover types that might be challenging for a state-of-the-art CNN’s model that previously performed well on land-cover classification only.Dissertation/ThesisDoctoral Dissertation Geography 201