Associating the spatial properties of a watershed with downstream Chl-a concentration using spatial analysis and generalized additive models

2019 ◽  
Vol 154 ◽  
pp. 387-401 ◽  
Author(s):  
Jin Hwi Kim ◽  
Dong Hoon Lee ◽  
Joo-Hyon Kang
Keyword(s):  
Spatial Analysis ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Chl A ◽  
Spatial Properties

scholarly journals Spatial analysis of learning and developmental disorders in upper Cape Cod, Massachusetts using generalized additive models

2010 ◽  
Vol 9 (1) ◽  
pp. 7 ◽  
Author(s):  
Kate Hoffman ◽  
Thomas F Webster ◽  
Janice M Weinberg ◽  
Ann Aschengrau ◽  
Patricia A Janulewicz ◽  
...  
Keyword(s):  
Spatial Analysis ◽  
Developmental Disorders ◽  
Generalized Additive Models ◽  
Additive Models ◽  
Cape Cod

scholarly journals Krill space: a comparative assessment of mesoscale structuring in polar and temperate marine ecosystems

2012 ◽  
Vol 69 (7) ◽  
pp. 1317-1327 ◽  
Author(s):  
Jarrod A. Santora ◽  
William J. Sydeman ◽  
Isaac D. Schroeder ◽  
Christian S. Reiss ◽  
Brian K. Wells ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Generalized Additive Models ◽  
Marine Ecosystems ◽  
Comparative Assessment ◽  
Habitat Associations ◽  
Shelf Break ◽  
Additive Models ◽  
Reference Points ◽  
Habitat Characteristics ◽  
Chl A

Abstract Santora, J. A., Sydeman, W. J., Schroeder, I. D., Reiss, C. S., Wells, B. K., Field, J. C, Cossio, A. M., and Loeb, V. J. 2012. Krill space: a comparative assessment of mesoscale structuring in polar and temperate marine ecosystems. – ICES Journal of Marine Science, 69: . The spatial organization, mesoscale variability, and habitat associations of krill within portions of the Antarctic Peninsula and California Current marine ecosystems are compared. Using a decade of acoustic observations and remotely sensed oceanography (2000–2009), the hypothesis that mesoscale spatial organization of krill in both systems closely relates to geospatial variability of the shelf break and is non-linearly related to geostrophic flow and positively related to chlorophyll a (Chl a) is tested. Directional-dependence analysis to measure spatial variability of krill is used along with spatially explicit generalized additive models to quantify and compare the spatial relationships among krill and habitat characteristics in both systems. The results suggest the following aspects of krill spatial organization: (i) areas of dense aggregation, i.e. hot spots, are present in both systems and are orientated in the direction of the shelf break, (ii) moderate levels of eddy kinetic energy seem to concentrate krill in favourable habitats and lessen the likelihood of advection away from the system, and (iii) variable responses to surface Chl a concentration suggest that real-time Chl a values may not be useful as a global predictor of important krill habitat. The results provide valuable reference points for marine spatial management of krill and for refining ecosystem and foodweb models.

scholarly journals THE IMPACT OF OCEANOGRAPHIC PARAMETERS CHANGES ON THE DISTRIBUTION AND ABUNDANCE OF SKIPJACK TUNA Katsuwonus pelamis IN MAKASSAR STRAIT

2019 ◽  
Vol 11 (1) ◽  
pp. 171-180 ◽  
Author(s):  
Zabhika Dinda Istnaeni ◽  
Mukti Zainuddin
Keyword(s):  
Generalized Additive Models ◽  
Secondary Data ◽  
Additive Models ◽  
Primary Data ◽  
Survey Method ◽  
Skipjack Tuna ◽  
Catch Per Unit Effort ◽  
Chl A ◽  
Level 3 ◽  
The Impact

This study aimed to identify the changes of oceanographic parameters and to analyze the effects of the parameter changes on the distribution and abundance of skipjack tuna captured by purse seine fishing gear operated in Coastal Waters of Makassar Strait. This study collected fishing and field oceanographic data from May to October 2017. A survey method was used to obtain primary data (skipjack catch per unit effort/CPUE) and secondary data including sea surface temperature (SST) and Chl-a level 3 with a monthly temporal and spatial resolution of 4 km from 2007-2017, interview, and study literature. The data were processed by using SeaDAS and ArcGIS software packages and were analyzed by anomalies, standard deviation, and Generalized Additive Models (GAMs) analyses. The results showed there were anomalies for both SST and Chl-a near study area reflecting the significant changes in the oceanographic conditions. The changes for both SST and Chl-a were 1.5ºC and -0.97 mg.m-3 respectively. This study suggests that the Chl-a parameter has more significant effects on skipjack tuna distribution and CPUE than SST. Understanding of the areas of the oceanographic changes strongly supports the available habitat for the fishing operation and conservation

Do urban tourism hotspots affect Berlin housing rents?

2017 ◽  
Vol 10 (2) ◽  
pp. 231-255 ◽  
Author(s):  
Philipp Schäfer ◽  
Jens Hirsch
Keyword(s):  
Spatial Analysis ◽  
Generalized Additive Models ◽  
Housing Markets ◽  
Ordinary Least Squares ◽  
Urban Housing ◽  
Additive Models ◽  
Urban Tourism ◽  
Content Type ◽  
Tourist Attractions ◽  
Prevailing View

Purpose This study aims to analyze whether urban tourism affects Berlin housing rents. Urban tourism is of considerable economic importance for many urban destinations and has developed very strongly over the past few years. The prevailing view is that urban tourism triggers side-effects, which affect the urban housing markets through a lack of supply and increasing rents. Berlin represents Germany’s largest rental market and is particularly affected by growing urban tourism and increasing rents. Design/methodology/approach The paper considers whether urban tourism hotspots affect Berlin’s housing rents, using two hedonic regression approaches, namely, conventional ordinary least squares (OLS) and generalized additive models (GAM). The regression models incorporate housing characteristics as well as several distance-based measures. The research considers tourist attractions, restaurants, hotels and holiday flats as constituents of tourism hotspots and is based on a spatial analysis using geographic information systems (GIS). Findings The results can be regarded as a preliminary indication that rents are, indeed, affected by urban tourism. Rents seem to be positively correlated with the touristic attractiveness of a particular location, even if it is very difficult to accurately measure the real quantity of the respective effects of the urban tourism amenities, as the various models show. GAM outperforms the results of OLS and seems to be more appropriate for spatial analysis of rents across a city. Originality/value To the best of the authors’ knowledge, the paper provides the first empirical analysis of the effects of urban tourism hotspots on the Berlin housing market.

scholarly journals Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

2020 ◽  
Vol 17 (17) ◽  
pp. 6339
Author(s):  
François Freddy Ateba ◽  
Manuel Febrero-Bande ◽  
Issaka Sagara ◽  
Nafomon Sogoba ◽  
Mahamoudou Touré ◽  
...  
Keyword(s):  
Wind Speed ◽  
Malaria Incidence ◽  
Generalized Additive Models ◽  
Community Health Center ◽  
Additive Model ◽  
Additive Models ◽  
Functional Regression ◽  
Novel Approach ◽  
Malaria Incidence Rate ◽  
Mean Wind Speed

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.

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