SVG3

workflows_docs/pipelines/Camtrap_occ_model/README.Rmd

@@ -10,7 +10,7 @@ author:
 affiliation: "Instituto de Investigación de Recursos Biológicos Alexander von Humboldt - IAvH"
 output: 
   #md_document:
-  md_document:
+  github_document:
     md_extension: +gfm_auto_identifiers
     preserve_yaml: true
     toc: true
@@ -30,11 +30,11 @@ If you already have a consolidated file that includes site and detection variabl
 
 This workflow loads and adjusts spatial covariates of site/landscape to the study area. For this, it loads raster files from your local computer and from STAC repositories. If you want to load files as covariates only from the local machine, use pipeline X, and if you want to load only covariates from the STAC, consult pipeline Y.
 
-
 
 
 
-<div style="width: 100%; overflow-x: auto;">
+
+<div style="width: 50%; overflow-x: auto;">
   <img src="README_figures/full_workflow.svg" alt="Descripción de la imagen" style="max-width: none;">
 </div>
 Para faciltiar la visualizacion del pipeline descarga la version svg aca 

workflows_docs/pipelines/Camtrap_occ_model/README.md

@@ -10,19 +10,24 @@ author:
 affiliation: "Instituto de Investigación de Recursos Biológicos Alexander von Humboldt - IAvH"
 output: 
   #md_document:
-  md_document:
+  github_document:
     md_extension: +gfm_auto_identifiers
     preserve_yaml: true
     toc: true
     toc_depth: 6
 ---
 
--   [Section 1: Loading and organizing camera trap
-    data](#section-1-loading-and-organizing-camera-trap-data)
--   [Section 2: Generation of the detection matrix and unmarked
-    format](#section-2-generation-of-the-detection-matrix-and-unmarked-format)
--   [Section 3: Loading and organizing spatial inputs as site
-    covariates](#section-3-loading-and-organizing-spatial-inputs-as-site-covariates)
+Camtrap_occ_model pipeline - Estimating Occupancy Models from Camera
+Trap Data Pipeline
+================
+truetruetrue
+
+- [Section 1: Loading and organizing camera trap
+  data](#section-1-loading-and-organizing-camera-trap-data)
+- [Section 2: Generation of the detection matrix and unmarked
+  format](#section-2-generation-of-the-detection-matrix-and-unmarked-format)
+- [Section 3: Loading and organizing spatial inputs as site
+  covariates](#section-3-loading-and-organizing-spatial-inputs-as-site-covariates)
 
 This pipeline is designed to estimate occupancy models from camera trap
 data. The main inputs required to run it are record files (1.1) and
@@ -51,27 +56,31 @@ and from STAC repositories. If you want to load files as covariates only
 from the local machine, use pipeline X, and if you want to load only
 covariates from the STAC, consult pipeline Y.
 
+<div style="width: 50%; overflow-x: auto;">
+
 <img src="README_figures/full_workflow.svg" alt="Descripción de la imagen" style="max-width: none;">
 
+</div>
+
 Para faciltiar la visualizacion del pipeline descarga la version svg aca
 
 Sections 1 and 2 mostly refer to column names of input files to execute
 the analysis.
 
 ### Section 1: Loading and organizing camera trap data
 
--   1.1: Path to the CSV file with record data (default:
-    /inputs/camtrap\_records.csv).
--   1.2: Path to the file with sampling data (default:
-    /inputs/camtrap\_sp\_covs.csv).
--   1.3: Name of the column referring to the scientific name of species
-    (default: scientificName).
--   1.4: Name of the column referring to the camera site (default:
-    Cam\_Site).
--   1.5: Name of the common column with the camera trap ID (default:
-    Cam\_Site).
--   1.6: Name of the column with longitude (default: Long\_Y).
--   1.7: Name of the column with latitude (default: Lat\_X).
+- 1.1: Path to the CSV file with record data (default:
+  /inputs/camtrap_records.csv).
+- 1.2: Path to the file with sampling data (default:
+  /inputs/camtrap_sp_covs.csv).
+- 1.3: Name of the column referring to the scientific name of species
+  (default: scientificName).
+- 1.4: Name of the column referring to the camera site (default:
+  Cam_Site).
+- 1.5: Name of the common column with the camera trap ID (default:
+  Cam_Site).
+- 1.6: Name of the column with longitude (default: Long_Y).
+- 1.7: Name of the column with latitude (default: Lat_X).
 
 The main input for section 1 is the paths to the CSV files of records
 (1.1) and sampling data (1.2) associated with camera trap surveys. The
@@ -82,15 +91,15 @@ and time (2.2) of records.
 
 Inputs 1.3 and 1.4 are used in FilterData to obtain only the records of
 the species of interest, while 2.1 and 2.2 will be necessary in
-CamTrap\_format as metadata for date and time to organize events in the
+CamTrap_format as metadata for date and time to organize events in the
 detection matrix.
 
 Both the record file (1.1) and the sampling data file (1.2) must have a
 common column (1.5) specifying a unique ID for each camera trap that
 will be used to merge these files into one compiled through
-Join\_datasets. This common column (1.5) will also be used as a unique
+Join_datasets. This common column (1.5) will also be used as a unique
 identification of camera traps for the detection matrix in
-CamTrap\_format.
+CamTrap_format.
 
 The sampling data file (1.2) must contain columns referring to the
 longitude (1.6) and latitude (1.7) coordinates of the camera trap
@@ -100,28 +109,28 @@ coordinate format specified in input 3.3 and will allow the data table
 to be spatialized to add spatial covariates to the records. The columns
 for installation date (2.3) and removal (2.4) are also necessary to
 organize the sequence of events in the detection matrix in
-CamTrap\_format.
+CamTrap_format.
 
 ## Section 2: Generation of the detection matrix and unmarked format
 
 2.1: Name of the column with the event date (default: eventDate). 2.2:
 Name of the column with the event time (default: eventTime). 2.3: Name
 of the column with the installation date (default: Instal.Date). 2.4:
 Name of the column with the last event date (default: Last.eventDate).
-2.5: Name of the observation variables (default: eventTime|1|hour). If
+2.5: Name of the observation variables (default: eventTime\|1\|hour). If
 NULL, it is ignored. Several can be specified separated by commas
-(default: eventTime|1|hour, effort|1, moonPhase). If only the name is
+(default: eventTime\|1\|hour, effort\|1, moonPhase). If only the name is
 specified, the variable collapses according to unique values. If the
 specified variable column is numeric, it rounds using
-name|rounding\_value, and if it is temporal with
-name|rounding\_value|time\_unit. Factors are not rounded. Temporal units
+name\|rounding_value, and if it is temporal with
+name\|rounding_value\|time_unit. Factors are not rounded. Temporal units
 can be specified according to all formats detailed in
-lubridate::round\_date. Specification errors will result in them being
+lubridate::round_date. Specification errors will result in them being
 ignored. 2.6: Time interval in days in which detections are grouped or
 collapsed as sampling events (default: 6). 2.7: Minimum number of events
 per site to include in the detection matrix (default: 7). Input 2.5
 refers to observation covariates (e.g., time, moon phase, weather) that
-will be used in CamTrap\_format and occ\_model\_results to organize the
+will be used in CamTrap_format and occ_model_results to organize the
 detection matrix and estimate the occupancy model. These must correspond
 to column names in the record files (1.1) or sampling data (1.2),
 otherwise, they will be omitted. When specifying, the column name must
@@ -130,13 +139,13 @@ for the same site, they must be grouped/collapsed for the correct
 organization of the unmarked object, which receives unique entries per
 site. When only the name is given, it will collapse in unmarked by the
 number of unique values of that column, or if it is numeric, it can be
-rounded specifying it as name|rounding value (e.g., eventTime|1). When
+rounded specifying it as name\|rounding value (e.g., eventTime\|1). When
 they are factors, they are not rounded. Numeric variables are specified
-with the variable name and the rounding factor in the form eventTime|1,
+with the variable name and the rounding factor in the form eventTime\|1,
 where 1 is the rounding value. Temporal variables are accepted and
 rounded by adding a third temporal unit factor in the form
-eventTime|1|hour, where hour is the rounding unit. Temporal units from
-lubridate::round\_date are accepted.
+eventTime\|1\|hour, where hour is the rounding unit. Temporal units from
+lubridate::round_date are accepted.
 
 Inputs 2.6 and 2.7 are numerical arguments for the CamTrapFormat box
 that organize the detection matrix and the unmarked object. Input 2.6
@@ -150,11 +159,11 @@ excluded from the matrix and the unmarked object.
 
 3.1: Path to the vector file of the study area (default:
 /inputs/Putumayo.gpkg). 3.2: Name to be given to the base raster of the
-study area (default: ID\_grid). 3.3: EPSG numerical coordinate system to
+study area (default: ID_grid). 3.3: EPSG numerical coordinate system to
 which the base raster will be adjusted (default: 4326). 3.4: Numerical
 resolution value in meters to which the base raster will be adjusted
 (default: 1000). 3.5: Path to the folder where the raster files of the
-landscape covariates are located (default: /inputs/Putumayo\_layers). If
+landscape covariates are located (default: /inputs/Putumayo_layers). If
 set to NULL, no layers are loaded from the local machine. 3.6: Path to
 the STAC repository where the landscape covariates of interest are
 located (default: <https://io.biodiv/>). If set to NULL, no layers are
@@ -163,7 +172,7 @@ of the specified STAC repository of the landscape covariates of
 interest. Ignored if 3.6 is NULL. The inputs in section 3 correspond to
 cartographic parameters of the study area. The main input required is
 the path to a vector file of the study area (3.1). This file is used as
-a base mask in studyarea\_to\_grid to generate the base raster grid that
+a base mask in studyarea_to_grid to generate the base raster grid that
 will support the analysis and will have parameters such as a name given
 in 3.2, numerical EPSG cartographic projection defined in 3.3, and
 spatial resolution in meters defined in 3.4.
@@ -175,16 +184,15 @@ repositories.
 
 To load covariates from a local repository, the folder path must be
 specified in 3.5 where the raster files are stored. The
-AlignRasters\_ToGrid box will load those files and align them to the
-base grid.
+AlignRasters_ToGrid box will load those files and align them to the base
+grid.
 
 To load covariates from the STAC repository, the STAC URL must be
 defined in 3.6 and in 3.7 the name of the collection and the required
-layer, separated by | in the form collection|layer. Multiple layers can
-be specified, separated by commas. The Stac\_From\_Grid box will load
+layer, separated by \| in the form collection\|layer. Multiple layers
+can be specified, separated by commas. The Stac_From_Grid box will load
 those layers online and align them to the base raster.
 
 The information of the covariates is incorporated into the spatial
-dataset obtained from poins\_data\_to\_spatial through the add\_covs
-box, which adds the values of the loaded raster covariates as new
-columns
+dataset obtained from poins_data_to_spatial through the add_covs box,
+which adds the values of the loaded raster covariates as new columns