Independent environmental data lab
Peta Cendekia is a collection of environmental web modules I built to explore how different public datasets can be queried, processed, mapped, and interpreted. Each module uses a different source or method, so this homepage shows the workflow and limitations instead of hiding them behind a generic “AI-powered” label.
Project modules
The modules are not forced into one method. Soil properties, weather forecasts, biodiversity records, river discharge, marine conditions, and air quality each need different sources and different scientific boundaries.
Queries modeled soil properties for a selected coordinate and turns the returned layers into an interpretable location profile.
Combines location-based forecast variables with crop context and derives a project-specific crop-health index.
Retrieves observational occurrence records by crop and location filters, then maps where target pests have been reported.
Explores marine species records by organism, location, date range, and activity context. It is an occurrence explorer, not an abundance prediction.
Explores modeled wave and ocean conditions for a selected location, including significant wave height, period, and sea-surface temperature.
Visualizes modeled river discharge and ensemble statistics near a selected coordinate. It does not claim to be a local flood-depth or inundation model.
Displays modeled biological and oceanographic indicators such as chlorophyll, dissolved oxygen, nitrate, and phosphate.
Retrieves modeled pollutant fields and forecasts for a selected coordinate and presents them as an interactive atmospheric profile.
Method transparency
Choose a module. The panel exposes the input, external data source, backend logic, displayed output, and the scientific boundary that should not be crossed when interpreting it.
Shared architecture
The modules share a Laravel application layer, but their scientific content comes from different providers. The website does not manufacture the underlying environmental observations or model fields.
A location, organism, crop, or time filter is sent to a module-specific backend route. Laravel requests the appropriate external service, normalizes the response, applies module logic where needed, and sends the result to the interactive interface.
Data provenance
These names describe where data or geocoding services come from. They do not imply sponsorship, partnership, validation, or institutional endorsement of this project.
Machine-learning soil-property maps at approximately 250 m, queried by coordinate through the SoilGrids service.
Used through separate forecast, marine, flood, and air-quality endpoints depending on the module.
Provides georeferenced observation records used in occurrence-oriented modules.
Occurrence search is used to retrieve indexed species records for spatial exploration.
Configured as a marine occurrence source for organism-based spatial exploration.
Configured for marine conditions and biological-oceanographic parameters used by marine modules.
Converts place names and coordinates so users can navigate environmental modules spatially.
Some modules calculate project-specific indices, filtering, summaries, or optional AI interpretations after the source data are retrieved.
Provider and institution names are displayed to make the data chain inspectable.
Andifa Anugerah Putra
About this project
I use Peta Cendekia as a public technical project: a place to build environmental-data modules, compare different data sources, and practice turning scientific information into interfaces that remain inspectable.
The modules are exploratory unless explicitly stated otherwise. They are intended for learning, analysis, and research-oriented prototyping. They do not replace field measurements, local monitoring networks, validated operational models, or professional decision-making.