Using Classification Consistency in Interscene Overlap Areas to Model Spatial Variations in Land-Cover Accuracy over Large Geographic Regions

Author(s):  
Bert Guindon ◽  
Curtis Edmonds
2002 ◽  
Vol 15 (4_suppl) ◽  
pp. 21-26 ◽  
Author(s):  
Marni Brownell

This study compared tonsillectomy rates for Manitoba children across geographic regions and over time. Shortly after the publication of clinical guidelines for tonsillectomy, provincial rates of this procedure dropped by over 25% between 1994/95 and 1996/97. By 1998/99, rates for non-Winnipeg children had increased to pre-guideline levels, whereas the rates for Winnipeg children remained lower. Significant regional variation existed in all years examined, suggesting that quality of care remains an issue for this procedure.


2022 ◽  
Vol 324 ◽  
pp. 107717
Author(s):  
Julian Brown ◽  
Scott V.C. Groom ◽  
Romina Rader ◽  
Katja Hogendoorn ◽  
Saul A. Cunningham

2019 ◽  
Vol 16 (19) ◽  
pp. 3801-3834 ◽  
Author(s):  
Alberto V. Borges ◽  
François Darchambeau ◽  
Thibault Lambert ◽  
Cédric Morana ◽  
George H. Allen ◽  
...  

Abstract. We carried out 10 field expeditions between 2010 and 2015 in the lowland part of the Congo River network in the eastern part of the basin (Democratic Republic of the Congo), to describe the spatial variations in fluvial dissolved carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) concentrations. We investigate the possible drivers of the spatial variations in dissolved CO2, CH4 and N2O concentrations by analyzing covariations with several other biogeochemical variables, aquatic metabolic processes (primary production and respiration), catchment characteristics (land cover) and wetland spatial distributions. We test the hypothesis that spatial patterns of CO2, CH4 and N2O are partly due to the connectivity with wetlands, in particular with a giant wetland of flooded forest in the core of the Congo basin, the “Cuvette Centrale Congolaise” (CCC). Two transects of 1650 km were carried out from the city of Kisangani to the city of Kinshasa, along the longest possible navigable section of the river and corresponding to 41 % of the total length of the main stem. Additionally, three time series of CH4 and N2O were obtained at fixed points in the main stem of the middle Congo (2013–2018, biweekly sampling), in the main stem of the lower Kasaï (2015–2017, monthly sampling) and in the main stem of the middle Oubangui (2010–2012, biweekly sampling). The variations in dissolved N2O concentrations were modest, with values oscillating around the concentration corresponding to saturation with the atmosphere, with N2O saturation level (%N2O, where atmospheric equilibrium corresponds to 100 %) ranging between 0 % and 561 % (average 142 %). The relatively narrow range of %N2O variations was consistent with low NH4+ (2.3±1.3 µmol L−1) and NO3- (5.6±5.1 µmol L−1) levels in these near pristine rivers and streams, with low agriculture pressure on the catchment (croplands correspond to 0.1 % of catchment land cover of sampled rivers), dominated by forests (∼70 % of land cover). The covariations in %N2O, NH4+, NO3- and dissolved oxygen saturation level (%O2) indicate N2O removal by soil or sedimentary denitrification in low O2, high NH4+ and low NO3- environments (typically small and organic matter rich streams) and N2O production by nitrification in high O2, low NH4+ and high NO3- (typical of larger rivers that are poor in organic matter). Surface waters were very strongly oversaturated in CO2 and CH4 with respect to atmospheric equilibrium, with values of the partial pressure of CO2 (pCO2) ranging between 1087 and 22 899 ppm (equilibrium ∼400 ppm) and dissolved CH4 concentrations ranging between 22 and 71 428 nmol L−1 (equilibrium ∼2 nmol L−1). Spatial variations were overwhelmingly more important than seasonal variations for pCO2, CH4 and %N2O as well as day–night variations for pCO2. The wide range of pCO2 and CH4 variations was consistent with the equally wide range of %O2 (0.3 %–122.8 %) and of dissolved organic carbon (DOC) (1.8–67.8 mg L−1), indicative of generation of these two greenhouse gases from intense processing of organic matter either in “terra firme” soils, wetlands or in-stream. However, the emission rate of CO2 to the atmosphere from riverine surface waters was on average about 10 times higher than the flux of CO2 produced by aquatic net heterotrophy (as evaluated from measurements of pelagic respiration and primary production). This indicates that the CO2 emissions from the river network were sustained by lateral inputs of CO2 (either from terra firme or from wetlands). The pCO2 and CH4 values decreased and %O2 increased with increasing Strahler order, showing that stream size explains part of the spatial variability of these quantities. In addition, several lines of evidence indicate that lateral inputs of carbon from wetlands (flooded forest and aquatic macrophytes) were of paramount importance in sustaining high CO2 and CH4 concentrations in the Congo river network, as well as driving spatial variations: the rivers draining the CCC were characterized by significantly higher pCO2 and CH4 and significantly lower %O2 and %N2O values than those not draining the CCC; pCO2 and %O2 values were correlated to the coverage of flooded forest on the catchment. The flux of greenhouse gases (GHGs) between rivers and the atmosphere averaged 2469 mmol m−2 d−1 for CO2 (range 86 and 7110 mmol m−2 d−1), 12 553 µmol m−2 d−1 for CH4 (range 65 and 597 260 µmol m−2 d−1) and 22 µmol m−2 d−1 for N2O (range −52 and 319 µmol m−2 d−1). The estimate of integrated CO2 emission from the Congo River network (251±46 TgC (1012 gC) yr−1), corresponding to nearly half the CO2 emissions from tropical oceans globally (565 TgC yr−1) and was nearly 2 times the CO2 emissions from the tropical Atlantic Ocean (137 TgC yr−1). Moreover, the integrated CO2 emission from the Congo River network is more than 3 times higher than the estimate of terrestrial net ecosystem exchange (NEE) on the whole catchment (77 TgC yr−1). This shows that it is unlikely that the CO2 emissions from the river network were sustained by the hydrological carbon export from terra firme soils (typically very small compared to terrestrial NEE) but most likely, to a large extent, they were sustained by wetlands (with a much higher hydrological connectivity with rivers and streams).


Author(s):  
V. Samoilenko ◽  
V. Plaskalnyi

In order to progress previously proposed interoperable for Ukrainian and all-European approaches procedure of anthropization extent analysis for Ukrainian landscapes, new operating scale of anthropization extent for physical-geographic taxons of Ukraine was substantiated and developed. The operating scale of anthropization extent relies, first of all, on created geoinformation basis, which is accessible for area of examination selected for the scale realization. Such area consists of physical-geographic regions and districts as plain landscape aggregations for zones of mixed and broad-leaved forests and forest-steppe. The geoinformation basis was organized by application and appropriate processing of up-to-date open digital spatial data sources. These sources contain, in particular, interactive raster land cover maps of European Space Agency (2015) and National Geomatics Center of China (2011), data of cartographic web-service OpenStreetMap, subject raster electronic maps collected in the National Atlas of Ukraine and other representative sources. There were stated peculiarities of development and implementation for the operating scale of anthropization extent, which embodies 55 operating land use and/or land cover (LULC) systems causing determinate anthropization extent, presented by corresponding to mentioned systems categories and indexes. Initial verifying realization of the anthropization extent operating scale was executed for the examination area, namely for its 25 physical-geographic regions, considering 130 physical-geographic districts, which form these regions. Realization of the scale proved, for the first, overall for examination area unfavorable geoecological situation in land use. Under such situation most of investigated regions and districts are indicated by categories of moderate-great and great anthropization (or β-euhemerobic and α-euhemerobic degree). For the second, there was constructed classed choropleth of anthropization extent categories’ fields, which were simulated for 1 km grid. For the third, there were typified percent distributions by regions for total LULC systems’ areas according to categories of these systems defined by their geoecological favorableness / unfavorableness (or degree of naturalness). Verifying-analogous comparison obtained model anthropization indicators with adequate representative foreign European results (concerning Germany and plain territory of central and west parts of Europe on the whole) proved their coincidence by content. All these jointly verify the objectivity of tools, proposed for model assessment of anthropization extent, and implementation validity of these tools. Prospects for further research were defined, aimed at detailed anthropization extent analysis, first of all by analysis of anthropization extent categories’ fields within physical-geographic districts especially by application of appropriate quasi-spectra and cumulative curves for anthropization indexes and areas.


2020 ◽  
Vol 12 (21) ◽  
pp. 3482
Author(s):  
Evelyn Uuemaa ◽  
Sander Ahi ◽  
Bruno Montibeller ◽  
Merle Muru ◽  
Alexander Kmoch

Freely available global digital elevation models (DEMs) are important inputs for many research fields and applications. During the last decade, several global DEMs have been released based on satellite data. ASTER and SRTM are the most widely used DEMs, but the more recently released, AW3D30, TanDEM-X and MERIT, are being increasingly used. Many researchers have studied the quality of these DEM products in recent years. However, there has been no comprehensive and systematic evaluation of their quality over areas with variable topography and land cover conditions. To provide this comparison, we examined the accuracy of six freely available global DEMs (ASTER, AW3D30, MERIT, TanDEM-X, SRTM, and NASADEM) in four geographic regions with different topographic and land use conditions. We used local high-precision elevation models (Light Detection and Ranging (LiDAR), Pleiades-1A) as reference models and all global models were resampled to reference model resolution (1m). In total, 608 million 1x1 m pixels were analyzed. To estimate the accuracy, we generated error rasters by subtracting each reference model from the corresponding global DEM and calculated descriptive statistics for this difference (e.g., median, mean, root-mean-square error (RMSE)). We also assessed the vertical accuracy as a function of the slope, slope aspect, and land cover. We found that slope had the strongest effect on DEM accuracy, with no relationship for slope aspect. The AW3D30 was the most robust and had the most stable performance in most of the tests and is therefore the best choice for an analysis of multiple geographic regions. SRTM and NASADEM also performed well where available, whereas NASADEM, as a successor of SRTM, showed only slight improvement in comparison to SRTM. MERIT and TanDEM-X also performed well despite their lower spatial resolution.


2020 ◽  
Vol 51 (3) ◽  
pp. 807-820
Author(s):  
Lena G. Caesar ◽  
Marie Kerins

Purpose The purpose of this study was to investigate the relationship between oral language, literacy skills, age, and dialect density (DD) of African American children residing in two different geographical regions of the United States (East Coast and Midwest). Method Data were obtained from 64 African American school-age children between the ages of 7 and 12 years from two geographic regions. Children were assessed using a combination of standardized tests and narrative samples elicited from wordless picture books. Bivariate correlation and multiple regression analyses were used to determine relationships to and relative contributions of oral language, literacy, age, and geographic region to DD. Results Results of correlation analyses demonstrated a negative relationship between DD measures and children's literacy skills. Age-related findings between geographic regions indicated that the younger sample from the Midwest outscored the East Coast sample in reading comprehension and sentence complexity. Multiple regression analyses identified five variables (i.e., geographic region, age, mean length of utterance in morphemes, reading fluency, and phonological awareness) that accounted for 31% of the variance of children's DD—with geographic region emerging as the strongest predictor. Conclusions As in previous studies, the current study found an inverse relationship between DD and several literacy measures. Importantly, geographic region emerged as a strong predictor of DD. This finding highlights the need for a further study that goes beyond the mere description of relationships to comparing geographic regions and specifically focusing on racial composition, poverty, and school success measures through direct data collection.


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