THE DYNAMICS OF LAND-COVER CHANGE IN WESTERN HONDURAS: SPATIAL AUTOCORRELATION AND TEMPORAL VARIATION

This paper presents an econometric analysis of land-cover change in western Honduras. Ground-truthed satellite image analysis indicates that between 1987 and 1996, net reforestation occurred in the 1,015.12 km2 study region. While some reforestation can be attributed to a 1987 ban on logging, the area of reforestation greatly exceeds that of previously clear-cut areas. Further, new area was also deforested between 1987-1996. Thus, the observed land-cover changes most likely represent a complex mosaic of changing land-use patterns across time and space. We estimate a random-effects probit model to capture drivers of land-cover change that are spatial, temporal or both. We employ two techniques to correct for spatial error dependence in econometric analysis suitable to qualitative dependent variables. Lastly, we simulate the impact of anticipated changes in transportation costs on land cover. We find that market accessibility, increase in national coffee prices, and agricultural suitability are the most important determinants of recent land-cover change.Land Economics/Use,

Mapping Time-Space Brickfield Development Dynamics in Peri-Urban Area of Dhaka, Bangladesh

Due to the high demand for cheap construction materials, clay-made brick manufacturing has become a thriving industry in Bangladesh, with manufacturing kilns heavily concentrated in the peripheries of larger cities and towns. These manufacturing sites, known as brickfields, operate using centuries-old technologies which expel dust, ash, black smoke and other pollutants into the atmosphere. This in turn impacts the air quality of cities and their surroundings and may also have broader impacts on health, the environment, and potentially contribute to global climate change. Using remotely sensed Landsat imagery, this study identifies brickfield locations and areal expansion between 1990 and 2015 in Dhaka, and employs spatial statistics methods including quadrat analysis and Ripley’s K-function to analyze the spatial variation of brickfield locations. Finally, using nearest neighbor distance as density functions, the distance between brickfield locations and six major geographical features (i.e., urban, rural settlement, wetland, river, highway, and local road) were estimated to investigate the threat posed by the presence of such polluting brickfields nearby urban, infrastructures and other natural areas. Results show significant expansion of brickfields both in number and clusters between 1990 and 2015 with brickfields increasing in number from 247 to 917 (total growth rate 271%) across the Dhaka urban center. The results also reveal that brickfield locations are spatially clustered: 78% of brickfields are located on major riverbanks and 40% of the total are located in ecologically sensitive wetlands surrounding Dhaka. Additionally, the average distance from the brick manufacturing plant to the nearest urban area decreased from 1500 m to 500 m over the study period. This research highlights the increasing threats to the environment, human health, and the sustainability of the megacity Dhaka from brickfield expansion in the immediate peripheral areas of its urban center. Findings and methods presented in this study can facilitate data-driven decision making by government officials and city planners to formulate strategies for improved brick production technologies and decreased environmental impacts for this urban region in Bangladesh

Parks, people and pixels: evaluating landscape effects of an East African national park on its surroundings

Landscapes surrounding protected areas, while still containing considerable biodiversity, have rapidly growing human populations and associated agricultural development in most of the developing world that tend to isolate them, potentially reducing their conservation value. Using field studies and multi-temporal Landsat imagery, we examine a forest park, Kibale National Park in western Uganda, its changes over time, and related land cover change in the surrounding landscape. We find Kibale has successfully defended its borders and prevents within-park deforestation and other land incursions, and has maintained tree cover throughout the time period of the study. Outside the park there was a significant increase in tea plantations and continued forest fragmentation and wetland loss. The question of whether the park is a conservation success because of the network of forest fragments and wetlands or in spite of them remains unanswered

A spatiotemporal natural-human database to evaluate road development impacts in an Amazon trinational frontier

Road construction and paving bring socio-economic benefits to receiving regions but can also be drivers of deforestation and land cover change. Road infrastructure often increases migration and illegal economic activities, which in turn affect local hydrology, wildlife, vegetation structure and dynamics, and biodiversity. To evaluate the full breadth of impacts from a coupled natural-human systems perspective, information is needed over a sufficient timespan to include pre- and post-road paving conditions. In addition, the spatial scale should be appropriate to link local human activities and biophysical system components, while also allowing for upscaling to the regional scale. A database was developed for the tri-national frontier in the Southwestern Amazon, where the Inter-Oceanic Highway was constructed through an area of high biological value and cultural diversity. Extensive socio-economic surveys and botanical field work are combined with remote sensing and reanalysis data to provide a rich and unique database, suitable for coupled natural-human systems research

Beyond precipitation: physiographic gradients dictate the relative importance of environmental drivers on savanna vegetation

Background: Understanding the drivers of large-scale vegetation change is critical to managing landscapes and key to predicting how projected climate and land use changes will affect regional vegetation patterns. This study aimed to improve our understanding of the role, magnitude and spatial distribution of the key environmental factors driving vegetation change in southern African savanna, and how they vary across physiographic gradients. Methodology/Principal Findings: We applied Dynamic Factor Analysis (DFA), a multivariate times series dimension reduction technique to ten years of monthly remote sensing data (MODIS-derived normalized difference vegetation index, NDVI) and a suite of environmental covariates: precipitation, mean and maximum temperature, soil moisture, relative humidity, fire and potential evapotranspiration. Monthly NDVI was described by cyclic seasonal variation with distinct spatiotemporal patterns in different physiographic regions. Results support existing work emphasizing the importance of precipitation, soil moisture and fire on NDVI, but also reveal overlooked effects of temperature and evapotranspiration, particularly in regions with higher mean annual precipitation. Critically, spatial distributions of the weights of environmental covariates point to a transition in the importance of precipitation and soil moisture (strongest in grass-dominated regions with precipitation,750 mm) to fire, potential evapotranspiration, and temperature (strongest in tree-dominated regions with precipitation.950 mm). Conclusions/Significance: We quantified the combined spatiotemporal effects of an available suite of environmental drivers on NDVI across a large and diverse savanna region. The analysis supports known drivers of savanna vegetation but also uncovers important roles of temperature and evapotranspiration. Results highlight the utility of applying the DFA approach to remote sensing products for regional analyses of landscape change in the context of global environmental change. With the dramatic increase in global change research, this methodology augurs well for further development and application of spatially explicit time series modeling to studies at the intersection of ecology and remote sensing.This study was funded by National Aeronautics and Space Administration Land-Cover/Land-Use Change Program (NASA LCLUC) Project # NNX09AI25G, titled ‘‘The Role of Socioeconomic Institutions in Mitigating Impacts of Climate Variability and Climate Change in Southern Africa’’, and National Science Foundation Integrative Graduate Education and Research Traineeship (NSF-IGERT) 0504422 Adaptive Management of Water, Wetlands and Watershed

Use of acoustic emission to identify novel candidate biomarkers for knee osteoarthritis (OA)

Our objective was to determine the efficacy and feasibility of a new approach for identifying candidate biomarkers for knee osteoarthritis (OA), based on selecting promising candidates from a range of high-frequency acoustic emission (AE) measurements generated during weight-bearing knee movement. Candidate AE biomarkers identified by this approach could then be validated in larger studies for use in future clinical trials and stratified medicine applications for this common health condition. A population cohort of participants with knee pain and a Kellgren-Lawrence (KL) score between 1-4 were recruited from local NHS primary and secondary care sites. Focusing on participants’ self-identified worse knee, and using our established movement protocol, sources of variation in AE measurement and associations of AE markers with other markers were explored. Using this approach we identified 4 initial candidate AE biomarkers, of which “number of hits” showed the best reproducibility, in terms of within-session, day to day, week to week, between-practitioner, and between-machine variation, at 2 different machine upper frequency settings. “Number of hits” was higher in knees with KL scores of 2 than in KL1, and also showed significant associations with pain in the contralateral knee, and with body weight. “Hits” occurred predominantly in 2 of 4 defined movement quadrants. The protocol was feasible and acceptable to all participants and professionals involved. This study demonstrates how AE measurement during simple sit-stand-sit movements can be used to generate novel candidate knee OA biomarkers. AE measurements probably reflect a composite of structural changes and joint loading factors. Refinement of the method and increasing understanding of factors contributing to AE will enable this approach to be used to generate further candidate biomarkers for validation and potential use in clinical trials

Remote Sensing-Based Fractal Analysis and Scale Dependence Associated with Forest Fragmentation in an Amazon Tri-National Frontier

Abstract: In the Amazon, the development and paving of roads connects regions and peoples, and over time can form dense and recursive networks, which often serve as nodes for continued development. These developed areas exhibit robust fractal structures that could potentially link their spatial patterns with deforestation processes. Fractal dimension is commonly used to describe the growth trajectory of such fractal structures and their spatial-filling capacities. Focusing on a tri-national frontier region, we applied a box-counting method to calculate the fractal dimension of the developed areas in the Peruvian state of Madre de Dios, Acre in Brazil, and the department of Pando in Bolivia, from 1986 through 2010. The results indicate that development has expanded in all three regions with declining forest cover over time, but with different patterns and rates in each country. Such differences were summarized within a proposed framework to indicate deforestation progress/level, which can be used to understand and regulate deforestation and its evolution in time. In addition, the role and influence of scale was also assessed, and we found local fractal dimensions are not invariant at different spatial scales and thus concluded such scale-dependent features of fragmentation patterns are here mainly shaped by the road paving