The long-awaited next generation cellular data is here: Coverage zones across Kathmandu Valley, Pokhara & Biratnagar, actual download/upload speed test benchmarks, compatible iPhone & Android handsets, and step-by-step 5G / eSIM activation.

Ncell has entered into a strategic partnership with the Nepal Association of Travel Operators (NATO) to improve mobile connectivity and WASH facilities for international tourists visiting Nepal. The agreement, signed by Ncell's Upanga Dutta and NATO's Bishwesh Shrestha, also aims to promote Nepal as a tourist destination through the #NepalCalling campaign.

Ncell has extended its free voice, data, and SMS services for another seven days in areas affected by the Bhotekoshi River flood in Rasuwa, aiming to support rescue and relief efforts. Meanwhile, several companies, including HIDCL, Maruti Cements, Riddhi Siddhi Cement, and Shaurya Cement, have contributed significant amounts to the Prime Minister's Disaster Relief Fund to aid flood recovery and rehabilitation.

Ncell has extended its free voice, data, and SMS services for an additional seven days in flood-affected areas to aid communication, search, rescue, and relief distribution. The company has also restored 18 disrupted mobile towers and contributed to the Prime Minister's Disaster Relief Fund. Meanwhile, other efforts include the Army evacuating over 2,100 people and banks being allowed to relocate without prior approval from Nepal Rastra Bank.

Nepal Telecom und Ncell haben nach der Flut im Land 70 Telekommunikationsmasten repariert, die durch die Überschwemmungen beschädigt wurden. Die Unternehmen bieten derzeit kostenlose Kommunikationsdie… · Photo : dhilung · CC BY · Flickr

I am trying to sample a raster (pixel values= 1 or NA, where 1 means opportunity as defined for my research). The specs of my raster are class : RasterLayer dimensions : 15838, 3808, 60311104 (nrow, ncol, ncell) resolution : 60, 60 (x, y) extent : 2402625, 2631105, 788651, 1738931 (xmin, xmax, ymin, ymax) crs : +proj=utm +zone=43 +ellps=WGS84 +units=m +no_defs source : not including in this post names : not including in this post values : 1, 1 (min, max) I want to sample 30 random points in all pixels with value=1 for further analyses and research. sampled_points 0 is not TRUE is present. I have used sampleRandom() multiple times before in other analyses an dhave not encountered this problem. How do I solve this problem?

A case has been filed in the Kathmandu District Court against 22 defendants, including officials from Ncell, Smart Telecom, and Nepal Investment Mega Bank, seeking the recovery of Rs 96.12 billion. The prosecution alleges fraud, criminal breach of trust, and organized crime following an investigation by the Central Investigation Bureau into the disputed auction of Smart Telecom's assets to Ncell.

I am working in R and have netCDF files that I need to pre-process beforehand. One file can be downloaded here: https://drive.google.com/file/d/14tbMvFaYSvHpDWTOdbSSdverkowEhNyV/view?usp=share_link There are daily 0.25 ERA5 variables: class : RasterBrick dimensions : 720, 1440, 1036800, 365 (nrow, ncol, ncell, nlayers) resolution : 0.25, 0.25 (x, y) extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax) crs : +proj=longlat +datum=WGS84 +no_defs source : t2m.daily.an.era5.1440.720.2018.nc names : X2018.01.01, X2018.01.02, X2018.01.03, X2018.01.04, X2018.01.05, X2018.01.06, X2018.01.07, X2018.01.08, X2018.01.09, X2018.01.10, X2018.01.11, X2018.01.12, X2018.01.13, X2018.01.14, X2018.01.15, ... Date : 2018-01-01, 2018-12-31 (min, max) varname : t2m I need to remap from 0.25 to 0.5 + select a specific area. I have tried the following with CDO: #!/bin/sh var=$1 yr=$2 name=$3 flist=/****/****/**/0d25_daily/${var}/${var}.daily.an.era5.1440.720.${yr}* for f in $flist; do echo $f cdo -remapbil,r720x360 -sellonlatbox,-80,10,-20,15 $f ${name}_daily_ERA5_${yr}.nc done however when I open the file in R, I get 0 layers while normally for one year I should get a layer per day. class : RasterBrick dimensions : 360, 720, 259200, 0 (nrow, ncol, ncell, nlayers) resolution : 0.5, 0.5 (x, y) extent : -180.25, 179.75, -90, 90 (xmin, xmax, ymin, ymax) crs : +proj=longlat +datum=WGS84 +no_defs source : Tair_daily_ERA5_2018.nc names : layer varname : t2m

I want to get quantiles of each cell across layers on a stacked set of RasterLayers on R. My RasterStack looks like this dimensions : 721, 1440, 1038240, 18628 (nrow, ncol, ncell, nlayers) I run the following line to get a layer whose values are 25th and 75th percentiles for each cell qtiles

I have a netcdf file with daily data and I calculate for each week some statistics, using the "apply.weekly" command in the "xts" library. However, I would like to calculate bi-weekly statistics, using daily data from every two weeks as input. How could i do this in R? library("ncdf4") library("rts") library("xts") # prec = stack("pr.nc") # prec # class : RasterStack dimensions : 12, 19, 228, 365 (nrow, ncol, ncell, nlayers) resolution : 0.125, 0.125 (x, y) extent : 21.75, 24.125, 39.875, 41.375 (xmin, xmax, ymin, ymax) coord. ref. : +proj=longlat +datum=WGS84 +ellps=WGS84 +towgs84=0,0,0 names : X2018.01.01, X2018.01.02, X2018.01.03, X2018.01.04, X2018.01.05, X2018.01.06, X2018.01.07, X2018.01.08, X2018.01.09, X2018.01.10, X2018.01.11, X2018.01.12, X2018.01.13, X2018.01.14, X2018.01.15, ... min values : 1.062151e-13, 1.080165e-13, 1.061332e-13, 1.757816e-02, 4.101618e-02, 3.535164e-01, 2.539131e-02, 2.674782e-02, 1.932025e-02, 2.027835e-05, 2.576398e-06, 6.366093e-13, 7.227548e-05, 1.345976e-04, 2.202405e-08, ... max values : 7.53125000, 0.69336098, 0.09375487, 9.00326061, 23.77886200, 16.37112999, 6.83587980, 4.03569651, 21.04327393, 6.23503065, 3.15138841, 1.24927104, 4.46353579, 3.46504283, 4.42247295, ... # indices = seq.Date(min(as.Date("2018-1-1")), max(as.Date("2018-12-31")), by="day") # prec_rt = rts(prec, indices) # rr_2018_weekly_sum = apply.weekly(prec_rt, sum)

I am getting the error: In matrix(values, nrow = ncell(x), ncol = nlayers(x)) : data length [6691] is not a sub-multiple or multiple of the number of rows [25628]. In reaction to knr

I have some code that returns a raster nested in a large list, I want to extract the raster from the list and save it as a tiff so that I can export it and use it in ArcGIS. my_rasterlayer crs units class n_classes OK >1 1 projected m integer 2 v # get spatialized lsm area_patch area_patch [[1]] [[1]]$lsm_p_area class : RasterLayer dimensions : 598, 790, 472420 (nrow, ncol, ncell) resolution : 33.54191, 33.54191 (x, y) extent : 5313077, 5339575, -2247065, -2227007 (xmin, xmax, ymin, ymax) crs : +proj=merc +a=6378137 +b=6378137 +lat_ts=0 +lon_0=0 +x_0=0 +y_0=0 +k=1 +units=m +nadgrids=@null +wktext +no_defs source : memory names : value values : 0.112506, 21099.15 (min, max) So I want to get the raster 'lsm_p_area' out of the list and as a stand alone tiff. rast

I am trying to plot some Sentinel 2 Tif Data. > library(raster) > > # Sentinel 2 Raster Data > S2_2017_05_B04 S2_2017_05_B08 S2_2017_05_B04 class : RasterLayer dimensions : 10980, 10980, 120560400 (nrow, ncol, ncell) resolution : 10, 10 (x, y) extent : 3e+05, 409800, 5590200, 5700000 (xmin, xmax, ymin, ymax) crs : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs source : S2_2017_05_B04.tif names : Grayscale > S2_2017_05_B08 class : RasterLayer dimensions : 10980, 10980, 120560400 (nrow, ncol, ncell) resolution : 10, 10 (x, y) extent : 3e+05, 409800, 5590200, 5700000 (xmin, xmax, ymin, ymax) crs : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs source : S2_2017_05_B08.tif names : Grayscale > plot(S2_2017_05_B08, col = gray(0:100 / 100)) Error in .local(x, ..., value) : unused argument (warn = FALSE) > traceback() 17: `crs But I am getting this error message: Error in .local(x, ..., value) : unused argument (warn = FALSE) What did I do wrong?

I want to rasterize a shapefile into a raster according to another raster (97284, 154208, 15001971072 (nrow, ncol, ncell)). Since the raster is very big, I am using gdal_rasterize following the code below rp

I am trying to sample a raster (pixel values= 1 or NA, where 1 means opportunity as defined for my research). The specs of my raster are class : RasterLayer dimensions : 15838, 3808, 60311104 (nrow, ncol, ncell) resolution : 60, 60 (x, y) extent : 2402625, 2631105, 788651, 1738931 (xmin, xmax, ymin, ymax) crs : +proj=utm +zone=43 +ellps=WGS84 +units=m +no_defs source : not including in this post names : not including in this post values : 1, 1 (min, max) I want to sample 30 random points in all pixels with value=1 for further analyses and research. sampled_points 0 is not TRUE is present. I have used sampleRandom() multiple times before in other analyses an dhave not encountered this problem. How do I solve this problem?

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I am working in R and have netCDF files that I need to pre-process beforehand. One file can be downloaded here: https://drive.google.com/file/d/14tbMvFaYSvHpDWTOdbSSdverkowEhNyV/view?usp=share_link There are daily 0.25 ERA5 variables: class : RasterBrick dimensions : 720, 1440, 1036800, 365 (nrow, ncol, ncell, nlayers) resolution : 0.25, 0.25 (x, y) extent : -180, 180, -90, 90 (xmin, xmax, ymin, ymax) crs : +proj=longlat +datum=WGS84 +no_defs source : t2m.daily.an.era5.1440.720.2018.nc names : X2018.01.01, X2018.01.02, X2018.01.03, X2018.01.04, X2018.01.05, X2018.01.06, X2018.01.07, X2018.01.08, X2018.01.09, X2018.01.10, X2018.01.11, X2018.01.12, X2018.01.13, X2018.01.14, X2018.01.15, ... Date : 2018-01-01, 2018-12-31 (min, max) varname : t2m I need to remap from 0.25 to 0.5 + select a specific area. I have tried the following with CDO: #!/bin/sh var=$1 yr=$2 name=$3 flist=/****/****/**/0d25_daily/${var}/${var}.daily.an.era5.1440.720.${yr}* for f in $flist; do echo $f cdo -remapbil,r720x360 -sellonlatbox,-80,10,-20,15 $f ${name}_daily_ERA5_${yr}.nc done however when I open the file in R, I get 0 layers while normally for one year I should get a layer per day. class : RasterBrick dimensions : 360, 720, 259200, 0 (nrow, ncol, ncell, nlayers) resolution : 0.5, 0.5 (x, y) extent : -180.25, 179.75, -90, 90 (xmin, xmax, ymin, ymax) crs : +proj=longlat +datum=WGS84 +no_defs source : Tair_daily_ERA5_2018.nc names : layer varname : t2m