Deep learning for land use and land cover classification from the Ecuadorian Paramo.

The paramo,plays an important role in our ecosystems as They balance the water resources and can retain substantial quantities of carbon.This research was carried out in the province of Tungurahua,specifically the Quero district.The aim is to develop a classification of the land use land cover(LULC)in the paramo using satellite imagery using several classifiers and determine which one obtains the best performance,for which three different approaches were applied:Pixel-Based Image Analysis(PBIA),Geographic Object-Based Image Analysis(GEOBIA),and a Deep Neural Network(DNN).Various parameters were used,such as the Normalized Difference Vegetation Index(NDVI),the Bare Soil Index(BSI),texture,altitude,and slope.Seven classes were used:paramo,pasture,crops,herbaceous vegetation,urban,shrubrainland,and forestry plantations.The data was obtained with the help of onsite technical experts,using geo-referencing and reference maps.Among the models used the highest-ranked was DNN with an overall precision of 87.43%,while for the paramo class specifically,GEOBIA reached a precision of 95%.

Thermo-bioconvection transport of nanofluid over an inclined stretching cylinder with Cattaneo–Christov double-diffusion

In this paper,Newtonian nanofluid flow is observed under the effects of the magnetic field,activation energy and motile microorganisms over an inclined stretchable cylinder.The magnificent aspects of nanoliquid are demonstrated by enduring the Brownian motion and thermophoresis diffusion features.Nonlinear higher order partial differential equations are transformed into first-order ordinary differential equations with suitable similarity variables.The attained sets of governing equations are then cracked by bvp4 c procedure in MATLAB mathematical software.The numerical and graphical outcomes of controlling parameters such as Prandtl number,mixed convection,activation energy,thermophoresis,Brownian parameter,Biot number,Lewis number,Peclet number and motile concentration parameter against the velocity,temperature,volumetric concentration and motile concentration of nanoparticles of the fluid are discussed.The velocity is enhanced with the growth valuation in mixed convection and decay by rising variation of buoyancy ratio parameter,magnetic parameter and bio-convective Rayleigh parameter.The evolution in motile microorganisms is due to the increasing values of microorganisms Biot number.The presented data can be helpful in enhancement of manufacturing processes,biomolecules,extrusion systems applications and energy production improvement.