docs: enhance consistency (#201)

geospaitial-lab · Aug 11, 2024 · 9037c54 · 9037c54
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diff --git a/docs/aviary/index.md b/docs/aviary/index.md
@@ -18,8 +18,8 @@ so canopies don't cover buildings or impervious surfaces.
 
 ### Requirements
 
-- channels: RGB (red, green, blue) and NIR (near-infrared)
-- ground sampling distance: 0.2m
+- Channels: RGB (red, green, blue) and NIR (near-infrared)
+- Ground sampling distance: 0.2m
 
 ---
 

diff --git a/docs/cli_reference/postprocessing_pipeline.md b/docs/cli_reference/postprocessing_pipeline.md
@@ -7,9 +7,9 @@
 The postprocessing pipeline is a pre-built pipeline designed to postprocess geospatial data.
 It consists of the following components:
 
-- a path to the geodataframe
-- a [`GeodataPostprocessor`](../api_reference/geodata/geodata_postprocessor.md) to postprocess the geodata
-- a path to export the geodataframe
+- A path to the geodataframe
+- A [`GeodataPostprocessor`](../api_reference/geodata/geodata_postprocessor.md) to postprocess the geodata
+- A path to export the geodataframe
 
 These components are set up in a configuration file (.yaml file) that is passed to the pipeline.<br />
 The configuration file must have the following structure:

diff --git a/docs/cli_reference/segmentation_pipeline.md b/docs/cli_reference/segmentation_pipeline.md
@@ -7,11 +7,11 @@
 The segmentation pipeline is a pre-built pipeline designed to run a segmentation model on your data.
 It consists of the following components:
 
-- a [`DataFetcher`](../api_reference/data/data_fetcher.md) to fetch data from a source
-- a [`DataPreprocessor`](../api_reference/data/data_preprocessor.md) to preprocess the fetched data
-- a [`ProcessArea`](../api_reference/process_area.md) to define the area of interest
-- a [`Model`](../api_reference/inference/model.md) to do the inference on the preprocessed data
-- an [`Exporter`](../api_reference/inference/exporter.md) to export the predictions dynamically as geospatial data
+- A [`DataFetcher`](../api_reference/data/data_fetcher.md) to fetch data from a source
+- A [`DataPreprocessor`](../api_reference/data/data_preprocessor.md) to preprocess the fetched data
+- A [`ProcessArea`](../api_reference/process_area.md) to define the area of interest
+- A [`Model`](../api_reference/inference/model.md) to do the inference on the preprocessed data
+- An [`Exporter`](../api_reference/inference/exporter.md) to export the predictions dynamically as geospatial data
 
 These components are set up in a configuration file (.yaml file) that is passed to the pipeline.<br />
 The configuration file must have the following structure: