Soil salinity prediction in the Lower Cheliff plain(Algeria) based on remote sensing and topographic feature analysis

Soil salinity and ground surface morphology in the Lower Cheliff plain（Algeria） can directly or indirectly impact the stability of environments. Soil salinization in this area is a major pedological problem related to several natural factors, and the topography appears to be important in understanding the spatial distribution of soil salinity. In this study, we analyzed the relationship between topographic parameters and soil salinity, giving their role in understanding and estimating the spatial distribution of soil salinity in the Lower Cheliff plain. Two satellite images of Landsat 7 in winter and summer 2013 with reflectance values and the digital elevation model（DEM） were used. We derived the elevation and slope gradient values from the DEM corresponding to the sampling points in the field. We also calculated the vegetation and soil indices（i.e. NDVI（normalized difference vegetation index）, RVI（ratio vegetation index）, BI（brightness index） and CI（color index）） and soil salinity indices, and analyzed the correlations of soil salinity with topography parameters and the vegetation and soil indices. The results showed that soil salinity had no correlation with slope gradient, while it was significantly correlated with elevation when the EC（electrical conductivity） values were less than 8 d S/m. Also, a good relationship between the spectral bands and measured soil EC was found, leading us to define a new salinity index, i.e. soil adjusted salinity index（SASI）. SASI showed a significant correlation with elevation and measured soil EC values. Finally, we developed a multiple linear regression for soil salinity prediction based on elevation and SASI. With the prediction power of 45%, this model is the first one developed for the study area for soil salinity prediction by the combination of remote sensing and topographic feature analysis.

Significance of Aspergillus spp. isolation from lower respiratory tract samples for the diagnosis and prognosis of invasive pulmonary aspergillosis in chronic obstructive pulmonary disease

Background Chronic obstructive pulmonary diseases （COPD） is an emerging population at risk for invasive infection of Aspergillus. Isolation of Aspergillus from lower respiratory tract （LRT） samples is important for the diagnosis of invasive pulmonary aspergillosis （IPA）. The purpose of this study was to investigate the value of Aspergillus isolation from LRT samples for the diagnosis and prognosis of IPA in COPD population. Methods Clinical record with Aspergillus spp. isolation in COPD and immunocompromised patients was reviewed in a retrospective study. Patients were categorized and compared according to their severity of illness （admitted to general ward or ICU） and immunological function （COPD or immunocompromised）. Results Multivariate statistical analysis showed that, combined with Aspergillus spp. isolation, APACHE II scores 〉18, high cumulative doses of corticosteroids （〉350 mg prednisone or equivalent dose） and more than four kinds of broad-spectrum antibiotics received in hospital may be predictors of IPA in COPD （0R=9.076, P=0.001; 0R=4.073, P=-0.026; OR=4.448, P=-0.021, respectively）. The incidence of IPA, overall mortality, mortality of patients with IPA and mortality of patients with Aspergillus spp. colonization were higher in COPD patients in ICU than in general ward, but were similar between COPD and immunocompromised patients. Conclusions Aspergillus spp. isolation from LRT in COPD may be of similar importance as in immunocompromised patients, and may indicate an increased diagnosis possibility of IPA and worse prognosis when these patients received corticosteroids, antibiotics, and need to admit to ICU. Aspergillus spp. isolation from LRT samples combined with certain risk factors mav be useful in differentiating colonization from IPA and evaluating the prognosis of IPA in COPD patients.