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Messages - Subir Paul

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Data / Free GIS Data
« on: March 11, 2019, 11:38:41 PM »
The following contains information on variable wise as well as country wise free GIS datasets. A very good summary!
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Dear Colleagues,

You are cordially invited to submit an abstract to our AOGS 2019, 16th Annual Meeting (28th July to 2nd August 2019 in Singapore) session on

" Hydrologic Extremes in a Changing Climate" 

 Session Details (HS10):

The goal of this session is to contribute to the discussions on the consequences of climate change and its impact on  hydrological  extremes. In this session, studies addressing but not limited to the following questions are welcome:

i. Surface and Ground water management under climate change

ii. Variations in extreme hydrological events and possible attributing factors

iii. Present methodologies adopted, limitations and advances

iv. Stationarity/ Non-stationarity factors

v. Case studies on climate change impact assessment at local/ basin/ regional scales

vi. Flood and Drought analyses

vii. Streamflow assessment and Reservoir operation

viii. Future climate and hydrology

ix. Change in spatio-temporal pattern of precipitation

x. Adaptation and Mitigation strategies

xi. Policy making

xii. Remote sensing applications

Please feel free to forward this invitation to anyone who might be interested in this session.

Last date of Abstract Submission is 12th February 2019.

Warm Regards,

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Programming / List of R Packages for Hydro Research by Sam Zipper
« on: July 20, 2018, 03:42:50 PM »
Sam Zipper( @ZipperSam ) has compiled a list of packages which can be useful in water resources engineering and research.

Twitter Thread :
Link to Doc :
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Dear all


The India-UK Water Centre is inviting applications from Indian and UK water scientists to participate in a workshop on Advancing Drought Monitoring, Prediction, and Management Capabilities to be held in Lancaster, UK 18th – 20th September 2018.

Last date for application: 17 May 2018

For more details;
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Study material / MathWorks seminar-Materials
« on: November 17, 2017, 12:05:08 PM »
Dear all


We had a MathWorks seminar event on Advanced Programming Techniques in MATLAB at NITK recently. I am attaching the presentation and demo codes here
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Data / Download FREE LULC Data for INDIA
« on: November 06, 2017, 12:20:34 PM »
Hello Everyone,

This is a website from which you can download free Land Use Land Cover data for the Indian region. It is based on a recent paper by P.S.Roy et al.

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If you are dealing with huge datasets that are saved in .mat format, loading them to workspace eats lot of RAM. So, matlab has an option to read part of such files without loading them to memory. Have a look at this link:
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Programming / Re: Python Resources for Hydrologists
« on: January 06, 2017, 11:22:58 AM »
Congrats Sat Kumar.. Your contribution for the Python community @ Python in Hydrology and library AMBHAS have been listed @
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Programming / Lyx: Easy LaTeX document Processor
« on: January 06, 2017, 10:52:55 AM »
LyX is an open sourcedocument processor based on top of the LaTeXtypesetting system. Unlike most word processors, which follow the WYSIWYG ("what you see is what you get") paradigm, LyX has a WYSIWYM ("what you see is what you mean") approach, where what shows up on the screen is only an approximation of what will show up on the page.

Links to download Lyx:

Using Lyx, we can easily prepare LaTeX documents without worrying too much about different technical stuffs.
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Programming / Python Resources for Hydrologists
« on: January 06, 2017, 12:09:07 AM »

Programming / Re: R vs Python
« on: December 29, 2016, 03:31:06 PM »
I think MATLAB can be competent enough for GIS functionality, its just that the toolbox is not well explored. MATLAB has a dedicated MAPPING toolbox. I had a task of plotting spatial maps to present my results and I was not satisfied with the colormaps of R and Python (may be I was not patient enough to edit the preset colormaps to my requirements), this lead me to MATLAB. I presented my findings from toolbox in a MATLAB primer seminar series held at IISc. The following code plots a spatial map of mean daily rainfall (mm) over India. I plotted the same data in R and Python and felt MATLAB produced satisfactory outcome.

Code: [Select]
% Geo-Spatial Plotting in MATLAB using MAPPING Toolbox %

% Unzip data.rar and change directory to unzipped folder; Load requisite data for plot
load data_spatial_mapping.mat;                 
% Read shapefile of India
S = shaperead('India.shp','usegeocoords',true);
% Define map projection
axesm('MapProjection', 'eqdcylin')
% Set map axis limits and labels
setm(gca,'GLineStyle','--', 'GColor',[0.83 0.82 0.78], 'Grid','on','Frame','on')
setm(gca, 'MapLatLimit',[8 37.2],'MapLonLimit',[68 97.5],...
    'MlabelLocation', 5,'MLabelParallel','north', 'MeridianLabel','on',...
% Plot shapefile of India
geoshow(S.Lat,S.Lon,'LineWidth', 2,'Color',[0 0 0])
% Overlay with data
% geoshow(lat_mesh,lon_mesh,data_mesh,'DisplayType','surface');
colormap hsv;
xlabel('Mean Daily Rainfall (mm)','FontSize',14)      % Add title to the map

I can say that 'setm' is the heart of this code which sets the requisite parameters of the map.
Functions list in Mapping Toolbox can be found from here:

I would suggest interested people to edit this code and see the changes happening in the map.

I am still interested in learning in detail the 'ggplot2' and other important packages of R that support GIS functionality. Although they are huge, I wish there is some tutorial that covers all the aspects of these packages.
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Feature Selection, also known as variable selection, is the process of selecting a subset of relevant features/variables/predictors.  Method for feature selection is an ever-expanding area of research. Filter type feature selection methods typically process features one at a time whereas wrapper methods consider subsets of features, and evaluate model selection criteria for each subset. Embedded methods inherently perform variable  selection as part of the learning process and include various regularization methods (such as the Lasso).  We propose a Bayesian method  for variable selection. While this is a general statistical approach, the  motivation comes from the problem of selecting relevant biomarkers  associated with (a) lymph node metastasis and (b) improved survival from Non-Small Cell Lung Cancer. Both of these are non-linear models which adds substantial complexity to the feature selection problem.
[/size]DAY & DATE:                Tuesday, 3rd January 2017
[/size]TIME:                        4.00 PM (Tea/Coffee at 5.00 PM)
[/size]VENUE:                Faculty Hall,Main Building, IISc.
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Data / High resolution irrigation maps for India : 2000-2015
« on: December 28, 2016, 01:05:54 PM »
Annual irrigated area maps at a resolution of 250 metres for the period 2000-2015 covering all the agroecological zones of India were developed and published by Prof. Vimal Mishra from IIT-Gandhinagar and his team.

Link to the article :

The maps can be downloaded @ :
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Post your question/information / Atmospheric Rivers
« on: December 23, 2016, 09:15:26 PM »
Atmospheric Rivers can be defined as narrow corridors of concentrated moisture suspended in the atmosphere. It is also known as rivers in the sky. Scientists found that it was responsible for the mysterious mass die-off of wild Olympia oysters in San Francisco Bay in 2011.

For more information, read the article below.

Title :

Atmospheric rivers and the mass mortality of wild oysters: insight into an extreme future?
Abstract :
Climate change is predicted to increase the frequency and severity of extreme events. However, the biological consequences of extremes remain poorly resolved owing to their unpredictable nature and difficulty in quantifying their mechanisms and impacts. One key feature delivering precipitation extremes is an atmospheric river (AR), a long and narrow filament of enhanced water vapour transport. Despite recent attention, the biological impacts of ARs remain undocumented. Here, we use biological data coupled with remotely sensed and in situ environmental data to describe the role of ARs in the near 100% mass mortality of wild oysters in northern San Francisco Bay. In March 2011, a series of ARs made landfall within California, contributing an estimated 69.3% of the precipitation within the watershed and driving an extreme freshwater discharge into San Francisco Bay. This discharge caused sustained low salinities (less than 6.3) that almost perfectly matched the known oyster critical salinity tolerance and was coincident with a mass mortality of one of the most abundant populations throughout this species' range. This is a concern, because wild oysters remain a fraction of their historical abundance and have yet to recover. This study highlights a novel mechanism by which precipitation extremes may affect natural systems and the persistence of sensitive species in the face of environmental change.

Link to the article :
Media report:
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Programming / Re: R vs Python
« on: December 23, 2016, 08:43:50 PM »
My views with little experience in all the three scripting languages are as below:

Sat hit the nail on the head by saying learn by coding is the best way to learn any programming language, does'nt matter which you pick. All the programming languages can solve most of the problems but picking which one is the best is very case specific. However, for solving most research problems any one among the three is ok to get started/solve ur problem. Most research students pick MATLAB because it can be very easy to learn. R has very deep learning curve and Python comes in between.

Most of the packages/algorithms in WaterResources you can most likely find in R or MATLAB.

Hello World : You can learn interactive code  @, &

ShapeFile/Raster : Coming and Python and R w.r.t GIS, although the core algos in ArcGIS/QGIS/GRASS are written in C, many packages/libraries for GIS are written in Python. As a result you see many packages in Python and R which can talk to arcGIS/QGIS/GRASS. So, if you handle lot of satellite data processing, it is good to go with R/Python.

Rewards : There are many programming courses being offered in   Matlab/Python/R. Pick any , do the course and you can write it on ur CV.
(2) You can take part in coding challenges which happen everyday/week , and to name a few, you can take part and put  your ranking on the CV.

Finally, It takes about 10 years to master one programming language. But, once you get started with one, you can easily pick the other.

Happy Coding
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