Error in timeline for Recreation Model

I’m really excited to try this ecosystem service software for recreation.

I am master student from National University of Colombia and I want to use INVEST recreation model in my study of tools for assessing nature bases tourism in Colombia, specifically Cauca Valley Region from 2017-2019.

I try to run the model with different end years, however I get the same error. I realize that the model might be only working for 2017, but in previous topic there was the intention of uploading 2018 and 2019.

So, my question is, does the InVEST Recreation Model allows the analysis for 2018 and 2019, and if it’s not yet, when can it be?.

Also, I would show you what the model points as an error for your help on this matter.

2020-05-02 21:32:55,880 utils.prepare_workspace(109) INFO Writing log messages to D:\Sharon\InVEST-Recreation-Model-log-2020-05-02–21_32_55.txt
2020-05-02 21:32:55,880 model._logged_target(1633) Level 100 Starting model with parameters:
Arguments for InVEST natcap.invest.recreation.recmodel_client 3.7.0:
aoi_path D:/Sharon/Tesis/Co$ting Nature/9. TN14 Mapa potencial y realizado/Realizado/ValleSOLO.shp
cell_size meters
compute_regression False
end_year <=2018
grid_aoi True
grid_type square
n_workers -1
start_year >=2015
workspace_dir D:\Sharon

2020-05-02 21:32:55,895 model._logged_target(1639) ERROR Exception while executing <function execute at 0x0FBB3470>
Traceback (most recent call last):
File “Z:\opt\atlassian\pipelines\agent\build\env\lib\site-packages\natcap\invest\ui\”, line 1636, in _logged_target
File “Z:\opt\atlassian\pipelines\agent\build\env\lib\site-packages\natcap\invest\recreation\”, line 156, in execute
ValueError: invalid literal for int() with base 10: ‘<=2018’
2020-05-02 21:32:55,895 model._logged_target(1642) INFO Execution finished
2020-05-02 21:32:55,895 utils.prepare_workspace(115) INFO Elapsed time: 0.02s

Hope you will provide me much information on this.
Thanks in advance.

Sharon Aguirre

Hi Sharon, thanks for posting. The Recreation model only supports queries through 2017. I don’t have any predictions for you regarding when we might add support for more recent years. In most applications, the photograph data are sufficiently limited such that it is recommended to include as many years as possible. For example, PUD_YR_AVG will have similar spatial patterns for averages across 2010-2017 as for 2010-2019, if that were possible.

To get the model to work, simply remove the >= symbols and only enter integers for the start_year and end_year values.