task 2: add attribute tabel

docs/html/_sources/methods/02_support_tools/README.rst.txt

@@ -27,14 +27,21 @@ Data
 
 The following data sources were used within this project task.
 
-**Land use**
+Land use
+~~~~~~~~~~~~~~~~~~~~~~~~
 
 In i-Tree Eco Land Use (LU) is defined as the land use type in which a tree is located. In i-Tree Eco, there are 13 default land use classes defined (see `Table 1 <tables.rst>`_).
-The land resource map FKB-AR5 (Ahlstrøm et al. 2019, Kartverket, 2023b) and the land use map from SSB (2022) are combined, and the different land use classes are translated to the Land Use classes defined in i-Tree Eco `Table 2 <tables.rst>`_ and `Table 3 <tables.rst>`_.
+The land resource map FKB-AR5 (Ahlstrøm et al. 2019, Kartverket, 2023b) and the land use map from SSB (2022) are combined, and the different land use classes are translated to the Land Use classes defined in i-Tree Eco using the lookup tables: `Table 2 <tables.rst>`_ and `Table 3 <tables.rst>`_.
 
 
-Municipal Tree Inventory
+Municipal Tree Database
 ~~~~~~~~~~~~~~~~~~~~~~~~
+
+The municipalities within the Trekroner-project each provided a tree inventory database. 
+The tree inventory databases contain information about the trees in the municipality, 
+such as tree species, tree height, tree diameter, and tree location. 
+The tree inventory databases were cleaned and standardized to ensure that the data could be used in the i-Tree Eco analysis. 
+
 .. toctree::
    :maxdepth: 1 
    :caption: Specific manual cleaning tasks for each municipality are described in the following documents:
@@ -46,6 +53,7 @@ Municipal Tree Inventory
 
 
 
+
 Methods
 -------
 
@@ -119,13 +127,25 @@ The workflow consists of three main steps:
    - Make a backup of the input data before running the scripts. 
    - Note that calculating the crown condition attributes is extremely slow (e.g., it can take more than 12 hours to run).
 
+Output
+-------
+
+The output is a cleaned municipal tree dataset that contains the mandatory input attributes for the i-Tree Eco model. 
+
+.. xlsx-table:: **Table 1:** Field design of the cleaned municipal tree inventory dataset. 
+    :file: tbl/field_design_registrerte_traer.xlsx
+    :header-rows: 1
+    :sheet: field_design
+
 **References**
 
+- Ahlstrøm, A., Bjørkelo, K., Fadnes, K.D. 2019. AR5 Klassifikasjonssystem. Klassifisering av arealressurser. NIBIO BOK 5 (5) 2019. http://hdl.handle.net/11250/2596511
 - Cimburova, Z., & Barton, D. N. (2020). The potential of geospatial analysis and Bayesian networks to enable i-Tree Eco assessment of existing tree inventories. Urban Forestry & Urban Greening, 55, 126801. https://doi.org/10.1016/j.ufug.2020.126801
+- Kartverket 2023a. FKB-Bygninger. Geografisk vektordatasett. https://kartkatalog.Geonorge.no/metadata/fkb-bygning/8b4304ea-4fb0-479c-a24d-fa225e2c6e97
+- Kartverket 2023b FKB-AR5. Geografisk vektordatasett. https://kartkatalog.geonorge.no/metadata/fkb-ar5/166382b4-82d6-4ea9-a68e-6fd0c87bf788
+- Statistisk sentralbyrå (SSB) 2022: Arealbruk 2022. Geografisk vektordatasett. https://kartkatalog.Geonorge.no/metadata/arealbruk-2022/a965a979-c12a-4b26-90a0-f09de47dbecd
 
 **Contributors**
 
 - Willeke A'Campo (NINA), [email protected]
 
-
-