UpdateJOSS

joss/paper.md

@@ -85,7 +85,7 @@ we make use of the functionality implemented in well-known geospatial packages s
 and their underlying dependencies such as Shapely [@shapely], Pandas [@pandas], or NumPy [@numpy]. In particular, we are utilizing the powerful implementation of [Spatial Indices](https://geopandas.org/en/stable/docs/reference/sindex.html) in GeoPandas allowing for processing speed-ups by orders of magnitudes compared to performing regular overlays and spatial joins for the processing of heat demand input data.
 
 The creation of a heat demand map follows a general workflow (Fig. \ref{fig1}) followed by a data-category-specific workflow for five defined 
-input data categories (Fig. \ref{fig2} \& \ref{fig3}). The different input data categories are listed in the table below. 
+input data categories (Fig. \ref{fig2} \& \ref{fig3}). The different input data categories are listed in the table below (Tab. 1). 
 
 | Data category |      Description                                                                                                                 |
 |---------------|----------------------------------------------------------------------------------------------------------------------------------|