> ## Documentation Index > Fetch the complete documentation index at: https://docs.mapxagent.com/llms.txt > Use this file to discover all available pages before exploring further. # Carrying Capacity Assessment · Jakarta > Assess how terrain, wetness, flood depth and rainfall constrain Jakarta's growth, grade carrying capacity, and flag the districts where pressure is highest. Carrying Capacity Assessment asks how much development a city can absorb before its water, climate and hazard constraints become the binding limit. For Jakarta — a low, flat delta city with frequent waterlogging — the study reads four constraints together, grades the result, and separates "constrained land" from "land under pressure". The Jakarta scenario as delivered: carrying-capacity classes 1–4, overload cells and the constraint-composition chart ## What the scenario ships Six prepared layers cover the Jakarta window. | Layer | Data | Role in the study | | - | - | - | | River network | OSM waterways | Drainage and flood corridor | | Administrative boundaries | 46 kecamatan (OCHA COD-AB ADM3); 44 on the mainland | Study-area definition, attribution and district labels | | Precipitation | CHIRPS, \~5.35 km | Rainfall membership (waterlogging constraint) | | Population | WorldPop, 100 m | Exposure and pressure axis | | Flood hazard | WRI Aqueduct, \~900 m | Flood-depth membership | | Terrain | SRTM, 30 m | Slope and topographic wetness | *All layers come from the [built-in catalog](/en/concepts/builtin-datasets) with source and attribution attached, and they are not limited to Jakarta: the catalog provides the same datasets for other cities at the same specification — switch the study area, add the same entries, and this chapter's method chain transfers in minutes.* ## How the study works The design follows the "shortest stave" reading of carrying capacity: the most limiting factor decides the class, not the average. | Stage | Question | What MapX runs | Output | | - | - | - | - | | 1. Build the capacity classes | Which factor limits each place, and how strongly? | Slope, Topographic wetness index, Fuzzy membership, Raster calculator (`minimum`), Focal statistics repair, Euclidean distance, Reclassify | Four-class carrying-capacity raster with the 300 m drainage-corridor adjustment | | 2. Diagnose pressure | Where is low capacity combined with high population? | Grid at 1 km, Zonal statistics, Quadrant (median split) | Overload cells, population per cell, district pressure table | | 3. Explain and mitigate | Which constraint dominates, and what should each district do? | Raster class area, Zonal statistics, Charts, Report | Class-area and dominant-constraint tables, mounted pressure chart and report | In short, the study first converts the four constraints — terrain, wetness, flood and rainfall — into comparable membership scores and composes them into capacity classes on a shortest-stave rule; it then crosses the classes with population in a quadrant read to find the overloaded cells where capacity is low and pressure high; finally it breaks down the dominant limiting factor per district and assembles the classes, overload grid and measures into charts and a report. ## Run it The screenshots below come from this scenario's reference workspace. Each step names the platform surface it uses, so you can follow the same path in your own project. **Suggested question:** *"Run a resource-and-environment carrying-capacity study for Jakarta: assess how water, climate and flood constraints limit growth, flag overloaded areas, then recommend measures by dominant constraint; deliver layers, charts and a report."* ### 1. Open the scenario Open **Scenarios** in the top menu, select this card and choose **Open scenario**. The whole bundle imports at once: every layer keeps its default style, legend, source and attribution, and the camera flies to the study area. Use the **Layers** panel to switch layers on and off before you type anything. The Jakarta scenario opened in a fresh project: the layer bundle imported, the Layers panel expanded, and the chat panel confirming the import with the suggested question ### 2. Ask the suggested question and review the plan Send the **suggested question** in the box above — or edit it first. [Plan mode](/en/concepts/plan-mode) asks how to read the study extent, whether to use the strict limiting-factor rule or the compensating variant, and which numbers the report should quote — then writes the plan document with its data inputs, method, quality checks, risks and deliverables. The Jakarta plan document in full-width view: side panels collapsed, plan sections and recorded decisions readable ### 3. Approve the plan and run the analysis The run chains deterministic [analysis](/en/concepts/analysis) tools: slope and topographic wetness, fuzzy membership for each limiting factor, focal-statistics repair for the two disclosed input gaps, the limiting-factor composite (shortest stave), the 300 m drainage corridor, the 1 km grid, zonal statistics and the pressure quadrant. The **Analysis** panel keeps every run's operator, inputs, parameters and result layer, and the workflow graph in the centre visualises the whole chain. The analysis view for Jakarta: the Analysis panel lists every operator run on the left, with the workflow graph in the centre ### 4. Style the result on the map The carrying classes use a reversed blue ramp so the most constrained land is the darkest; the overload cells sit on top in orange, and district labels come from an anchor layer instead of the boundary polygons. The style editor on a deliverable layer: classed-colour breaks and label settings, with the layer editing panel highlighted in red ### 5. Turn the result into charts and a report The constraint-composition chart answers which factor decides each class, and the district charts rank the pressure. Both are **[charts](/en/concepts/charts)** you can restyle or pin, and the **[report](/en/concepts/reports)** collects the threshold table, the coverage statement and the class shares in one document. A chart from this scenario in the chart editor, with the editing area highlighted in red The scenario report opened in the report canvas, with an executive summary, figures and embedded maps ## Example output The screenshots above come from one example run with the default settings on the shipped data. They show the shape of the deliverables, not what your run will return. A finished run hands back a named, reusable set of deliverables instead of a single map: * **Layers** — the four-class carrying-capacity raster with the drainage-corridor adjustment, the overload cells, the 1 km population grid and the district label layer. * **Tables** — the class-area table with its admin cross table, the dominant-constraint table and the district pressure list. * **Charts** — the constraint-composition chart and the pressure ranking, editable and ready to pin. * **Report** — the assessment document with the threshold table, the data-repair statement and the five acceptance checks. The layer names follow the run language, but the deliverable set is stable enough to plan a handover around. ## Related * [Scenarios](/en/concepts/scenarios) — the full catalog and how scenarios work * [Development Suitability Baseline](/en/concepts/scenarios/development-suitability-baseline) — the companion suitability study for Nairobi * [Land-use Conflict Screening](/en/concepts/scenarios/landuse-conflict-screening) — constraint logic applied to built-up land * [Analysis](/en/concepts/analysis) — fuzzy overlay, raster calculator and statistics tools * [Built-in datasets](/en/concepts/builtin-datasets) — where every layer comes from This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.