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{\center
\Large{Project0A\\
\today\\}}

\section{When the data has been collected?}

In~\cite{Datt03}, the data has been collected {\em over two southern hemisphere summer growing
seasons (2000/2001 and 2001/2002).}

\section{Where is the area monitored?}

In~\cite{Datt03}, it is mentioned that the area monitored is
{\em near Coleambally in New South Wales (NSW), Australia}.

\section{What is it expected to be used for?}

In~\cite{Datt03}, it is claimed that 
the collected allows {\em monitoring and measurement of crop growth from a space
platform based on field-scale calibration. The aim is to assess
changes in plant chemistry, including changes in nitrogen levels
such as those developed for forests, and to model crop
yields.}

\section{Why this dataset is publicly available?}

In~\cite{Christovam19}, it is  mentioned in the abstract that this dataset has been created and made publicly available. He explains that
{\em  since
classification results are directly dependent on the dataset used, it is fundamental to compare and validate the classification approaches
in public datasets.}

\section{What are the wavelengths being used?}

Table~3 of page~1249 in~\cite{Datt03} gives the signification of an approximate information upon the different wavelengths 
provided. 
\begin{itemize}
\item The first $50$ are for visible and near infrared wavelengths. 
\item The remaining $126$ are for short wave infrared wavelengths. 
\end{itemize}

\section{What are the different classes in the ground truth?}

\begin{enumerate}
\item Dense Urban Fabric
\item Mineral Extraction Sites
\item Non Irrigated Arable Land
\item Fruit Trees
\item Olive Groves
\item Broad leaved Forest
\item Coniferous Forest
\item Mixed Forest
\item Dense Sclerophyllous Vegetation
\item Sparse Sclerophyllous Vegetation
\item Sparsely Vegetated Areas
\item Rocks and Sand
\item Water
\item Coastal Water
\end{enumerate}


\section{What is the spatial resolution?}

Based on~\cite{Datt03}, the resolution is $2$m per pixel. 

\section{Is it calibrated?}

In~\cite{Datt03}, the data is claimed to be {\em well calibrated}.


\bibliography{bib}{}
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\appendix

\section{How the database has been extracted}

This is the  website where data has been found.
\begin{verbatim}
https://zenodo.org/record/1222202
\end{verbatim}

This is the Matlab code used to build the database
\begin{verbatim}
clear
cd 'C:\Users\utilisateur\Downloads\HyRANK_satellite\HyRank_satellite\TrainingSet'
im=imread('Dioni.tif');
im_GT=imread('Dioni_GT.tif');
cd L:\u0\RECH_T\FENG\TEACHING
X=zeros(size(im,1)*size(im,2),size(im,3));
Y=zeros(size(im,1)*size(im,2),1);
n=1;
for i=1:size(im,1)
  for j=1:size(im,2)
    for k=1:size(im,3)
      X(n,k)=im(i,j,k);
      Y(n)=im_GT(i,j);
    end
    n=n+1;
  end
end
metadata.size=[size(im,1) size(im,2)]; 
metadata.classes_l={'Dense_Urban_Fabric','Mineral_Extraction_Sites',...
'Non_Irrigated_Arable_Land','Fruit_Trees','Olive_Groves',...
'Broad_leaved_Forest','Coniferous_Forest','Mixed_Forest',...
'Dense_Scleorophyllous_Vegetation','Sparse_Sclerophyllous_Vegetation',...
'Sparsely_Vegetated_Areas','Rocks_and_Sand','Water','Coastal_Water'};
metadata.C=14;
metadata.features_s.VNIR_428_to_926=[1:(57-8+1)];
metadata.features_s.SWIR1_933_1346=...
  metadata.features_s.VNIR_428_to_926(end)+[1:(120-79+1)];
metadata.features_s.SWIR2_1427_1810=...
  metadata.features_s.SWIR1_933_1346(end)+[1:(166-128+1)];
metadata.features_s.SWIR3_1942_2385=...
  metadata.features_s.SWIR2_1427_1810(end)+[1:(223-179+1)];
i=uint16(ceil(rand(1)*size(im,1))); 
j=uint16(ceil(rand(1)*size(im,2))); 
metadata.i=i; 
metadata.j=j;
metadata.x_ij=reshape(im(i,j,:),1,176);
metadata.y_ij=im_GT(i,j); 
metadata.F=size(im,3); 
save project0a.mat X Y metadata;
\end{verbatim}


\end{document}
