LAHMP | Land Health Monitoring Platform

A browser-based self-assessment wizard that generates personalised biodiversity monitoring plans for agricultural and semi-natural landscapes.

Overview

LAHMP is a functional prototype of a four-step land health self-assessment tool developed for the IUCN Nature-Based Solutions Hub. It operationalises the IUCN Land Health Monitoring Framework (LHMF), connecting sustainable agricultural practices to measurable biodiversity indicators through a structured, evidence-based workflow.

A practitioner — land manager, field ecologist, NGO programme officer, or monitoring coordinator — works through four sequential steps:

Landscape Profile — characterise the site by location, land use, pressures, degradation challenges, and priority ecosystem services
Practice Recommendation — receive a scored and ranked shortlist of sustainable land management practices matched to the site's pressure profile
Capacity Assessment — declare team composition, field time, equipment, budget, and seasonal site access
Monitoring Plan — receive an auto-generated, capacity-fitted monitoring programme: biological indicator protocols, abiotic baselines, a 12-month survey calendar, and a plain-language narrative

The output is a complete monitoring plan rendered in the browser and printable via window.print(). No server, no accounts, no API calls.

Key objectives

Logic validation — verify that the LHMF scoring and filtering algorithms produce scientifically coherent outputs for known test landscapes
Stakeholder demonstration — share a working prototype with project partners and funders via a static URL
Development testbed — confirm JSON knowledge-base structure against algorithm output before production implementation in Laravel/Vue.js

Architecture

System overview

LAHMP is a single-page application with zero build tooling. All logic runs in the browser against static JSON knowledge bases. There is no backend, no API, and no authentication layer.

┌─────────────────────────────────────────────────────────────────┐
│  Browser                                                        │
│                                                                 │
│  index.html ──── presentation shell (113 lines)                 │
│  wizard.js  ──── all state management + algorithm logic         │
│  styles.css ──── IUCN brand styling                             │
│                                                                 │
│  data/                                                          │
│  ├── reference.json    ← pressures (28), challenges (35),       │
│  │                       services (37), EFG options,            │
│  │                       pre-population mapping tables          │
│  ├── practices.json    ← 43 sustainable land management         │
│  │                       practices with scoring metadata        │
│  ├── indicators.json   ← 41 biological indicator profiles       │
│  │                       (32 validated, 6 draft, 3 pending)    │
│  └── abiotic.json      ← 16 abiotic baseline indicators         │
│                                                                 │
│  localStorage ─────────── session persistence (resume on        │
│                            reload; not a data store)            │
└─────────────────────────────────────────────────────────────────┘

Data flow

flowchart TD
    S1[Step 1 — Landscape Profile]
    S2[Step 2 — Practice Recommendation]
    S3[Step 3 — Capacity Assessment]
    S4[Step 4 — Monitoring Plan]

    S1 -->|pressures → challenges\nchallenges → services| S1
    S1 -->|step1 object| S2
    S2 -->|scored + filtered\nselected_practices| S3
    S3 -->|computeCapacityProfile| S4

    S4 --> O1[Op 1: Practice chains\ngrouped by theme]
    S4 --> O2[Op 2: Indicator group\nselection]
    S4 --> O3[Op 3: Protocol\nassignment]
    S4 --> O4[Op 4: Capacity\nfitting]
    S4 --> O5[Op 5: Monitoring\ncalendar]

Technology stack

Concern	Choice	Rationale
Language	Vanilla ES2020 JavaScript	No build tooling; directly shareable via GitHub Pages
Markup	HTML5	Single file, no templating engine
Styling	CSS custom properties	IUCN brand tokens; zero runtime overhead
Fonts	IBM Plex Sans / Serif / Mono	IUCN-aligned; loaded via Google Fonts CDN
Data	Static JSON	Exported from canonical Excel knowledge bases
Persistence	`localStorage`	Wizard resume across page reloads
Hosting	GitHub Pages	Zero-infrastructure; no server required
PDF output	`window.print()` + print CSS	No Puppeteer or server-side rendering

Installation

Prerequisites

A modern browser (Chrome ≥ 105, Firefox ≥ 104, Safari ≥ 16, Edge ≥ 105)
A static file server for local development (the wizard loads JSON via fetch, which requires HTTP — opening index.html directly from disk will fail due to CORS restrictions)

Python 3, Node.js, or any other static server will work:

# Python 3
python3 -m http.server 8080

# Node.js (npx)
npx serve .

# Node.js (http-server)
npx http-server . -p 8080

Local setup

git clone https://github.com/daimpad/LAHMP.git
cd LAHMP
python3 -m http.server 8080
# Open http://localhost:8080

No npm install, no build step, no environment variables.

Usage

Live deployment

https://daimpad.github.io/LAHMP

URL parameters

Parameter	Values	Effect
`?fixture=`	`TEST-01`, `TEST-02`, `TEST-03`	Pre-loads a complete test assessment
`&step=`	`1`, `2`, `3`, `4`	Jumps directly to the specified step

Examples:

# Load the Skoura M'Daz Morocco test case, jump to Step 4 output
https://daimpad.github.io/LAHMP?fixture=TEST-01&step=4

# Load the Vietnam VSA test case at Step 1
https://daimpad.github.io/LAHMP?fixture=TEST-03

Test landscapes

Three pre-configured fixtures cover distinct land system types and climate zones:

ID	Name	Location	Primary EFG	Key pressures
`TEST-01`	Skoura M'Daz	Drâa-Tafilalet, Morocco	T7.2 — Sown pastures	Overgrazing, soil erosion, drought
`TEST-02`	PK-17	Trarza, Mauritania	T7.5 — Semi-natural pastures	Desertification, overgrazing, invasive species
`TEST-03`	Vietnam VSA	Mekong Delta, An Giang	T7.1 + F3.3 — Annual cropland / Rice paddies	Pesticide use, water pollution, agrobiodiversity loss

Typical workflow

Open the wizard and enter landscape location details (Step 1, Block 1)
Select IPCC land use categories, EFG codes, and soil types (Block 1.2)
Mark active pressures for each of 28 pressure types (Block 4); Block 5 challenges auto-populate
Confirm relevant land health challenges and rank priority ecosystem services (Blocks 5–6)
Complete the pre-screen and review scored practice recommendations; select your programme's practices (Step 2)
Declare team composition, field days, equipment, budget, and seasonal access calendar (Step 3)
Step 4 generates automatically: review the narrative, indicator tables, and 12-month calendar; print via the browser print dialog

The wizard saves state to localStorage after every input — closing and reopening the tab resumes from the last position.

Configuration

IUCN brand tokens

Defined as CSS custom properties in styles.css:

:root {
  --iucn-navy:   #003478;
  --iucn-yellow: #FDC82F;   /* action/accent only — never decorative */
  --iucn-green:  #1A7A52;
}

Knowledge base data files

All content is loaded at runtime from data/. These files are the canonical source of truth for the browser application. Do not edit them directly — they are generated by the export scripts in export/.

File	Records	Description
`data/reference.json`	28 pressures, 35 challenges, 37 services, 15 IPCC land use categories, 10 soil types, ~120 EFG options	Block 4/5/6 lists and pre-population mapping tables
`data/practices.json`	43 practices across 11 themes	Practice Matrix: scoring metadata, eligibility rules, pre-screen linkages
`data/indicators.json`	41 profiles (32 validated, 6 draft, 3 pending)	Indicator Linkage Matrix: 3-level protocol assignments, seasonal windows, EFG/IPCC linkages. Draft profiles (14, 19, 22, 23, 37, 38) appear in Step 4 output with "Protocol proposed" badge; pending profiles (39–41) are excluded pending expert authoring. See `docs/profiles_pending.md`.
`data/abiotic.json`	16 indicators	Abiotic Reference Table: baseline measurement protocols and universal baseline flags

Assessment state object

All wizard state is held in window.assessment. Its structure is intentionally identical to the production assessment record JSON so prototype data can directly test the production algorithm:

window.assessment = {
  assessment_id:  String,   // UUID — generated on first load
  landscape_name: String,
  created_at:     ISO8601,
  last_updated:   ISO8601,
  step1:          { /* landscape profile */ },
  step2:          { /* selected practices */ },
  step3:          { /* capacity inputs */ },
  step4_outputs:  { /* algorithm outputs */ },
};

See CLAUDE.md for the complete field-level schema. See FORM_DOCUMENTATION.md for structured guidance on every user-facing input form.

Development

Repository structure

lahmp/
├── index.html                      ← Presentation shell — structural HTML only
├── wizard.js                       ← All state management and algorithm logic (~2 500 lines)
├── styles.css                      ← IUCN brand styling (~1 300 lines)
├── data/
│   ├── reference.json              ← Pressures, challenges, services, mapping tables
│   ├── practices.json              ← 43 practice profiles
│   ├── indicators.json             ← 41 biological indicator profiles
│   ├── abiotic.json                ← 16 abiotic baseline indicators
│   └── test_fixtures/
│       ├── TEST-01.json            ← Skoura M'Daz, Morocco (T7.2)
│       ├── TEST-02.json            ← PK-17, Mauritania (T7.5)
│       └── TEST-03.json            ← Vietnam VSA (T7.1 + F3.3)
├── indicators/                     ← DOCX source files for all 41 indicator profiles
│   ├── LAHMP_Indicator_Profile_Template.docx
│   └── LAHMP_Profile_01_Soil_Bacteria.docx  … (41 files)
├── raw/                            ← Canonical Excel and CSV source data
│   ├── LAHMP_Practice_Matrix.xlsx
│   ├── LAHMP_Indicator_Linkage_Matrix_Populated.xlsx
│   ├── LAHMP_Abiotic_Reference_Table.xlsx
│   └── IUCN - LHMT - *.csv        … (7 files)
├── export/
│   ├── convert.py                  ← raw/*.xlsx → data/*.json
│   └── extract_indicators.py       ← indicators/*.docx → data/indicators.json
├── CLAUDE.md                       ← Canonical developer specification and open items
├── FORM_DOCUMENTATION.md           ← Complete reference for all user-facing input forms (Steps 1–3)
└── LICENSE

`wizard.js` internal structure

The file is organised into clearly labelled sections that map to the step and operation numbers in the specification documents:

Constants and lookup tables
  MONTHS, TEAM_PROTOCOL_LEVEL, BUDGET_OPTS, THEME_TO_CHAIN,
  PRESSURE_LAND_USE_KEYWORDS, PRESCREEN_ANSWERS, SITE_COUNT_MIDPOINT

Assessment state initialisation

Step 1 algorithms
  prepopulateChallenges(pressures, landUseComposition)
  prepopulateServices(challenges)
  scorePractice(practice, step1)

Step 3 algorithms
  computeCapacityProfile(step3)

Step 4 algorithms
  Operation 1 — practice chain grouping
  Operation 2 — selectIndicatorGroups(indicators, step1, step2)
  Operation 3 — assignProtocol(group, capacityProfile)
  Operation 4 — capacityFit(groups, cap, step2, step1)
  Operation 5 — buildMonitoringCalendar(groups, accessCalendar)
               └── parseSeasonalWindow(text)
               └── splitIntoWindows(indices)
               └── stageSpeed(monitoringStage)

runStep4Algorithm()

Render functions
  renderStep1(), renderStep2(), renderStep3(), renderStep4()

Event wiring, navigation, localStorage persistence

Code conventions

All algorithm logic in wizard.js — render functions in the same file for simplicity, but clearly separated
All content from data/ — no labels, option lists, or tooltips are hardcoded in JS or HTML
Function names match spec terminology — prepopulateChallenges, scorePractice, assignProtocol, computeCapacityProfile, selectIndicatorGroups
No external dependencies — no npm, no bundler, no polyfills beyond what browsers provide natively

Updating the knowledge bases

The files in raw/ are the canonical source of truth. Always edit the source file first, then re-export to JSON. Never edit the JSON files in data/ directly.

# Re-export practices.json, abiotic.json, reference.json from raw/*.xlsx
cd export/
pip install pandas openpyxl python-docx
python3 convert.py

# Re-extract all 41 indicator profiles from indicators/*.docx
python3 extract_indicators.py
# Reads from indicators/ (tracked), falls back to indicators_dl/ cache,
# downloads from GitHub only if neither exists. Writes data/indicators.json

Testing

Manual end-to-end validation

The primary test mechanism is loading a pre-configured test fixture and inspecting Step 4 output:

# Full run
https://daimpad.github.io/LAHMP?fixture=TEST-01

# Jump directly to output
https://daimpad.github.io/LAHMP?fixture=TEST-01&step=4
https://daimpad.github.io/LAHMP?fixture=TEST-02&step=4
https://daimpad.github.io/LAHMP?fixture=TEST-03&step=4

What to verify

Check	Expected
Block 5 pre-population	Challenges appear when Block 4 pressures are marked `ongoing`; confidence degrades to `medium` for `past`/`not_sure`; disappears for `not_relevant`
Area weighting	Marking overgrazing `ongoing` in a landscape with < 10% grassland area produces `medium` (not `high`) confidence challenges
Practice scoring	Practices with higher Block 4/5/6 overlap score higher; score displayed on each card
Protocol assignment	TEST-03 (Types C + D, budget tier 3) should assign Level 2 protocols; TEST-02 (Types A + B, budget tier 1) should assign Level 1
Calendar windows	TEST-02 constrained months (April–June) should not appear as suggested monitoring windows
Capacity trimming	Low-capacity profiles (few days, low budget) should produce a trimmed group list in "Enhancement recommendations"

Algorithm simulation

export/extract_indicators.py includes a Python simulation of the Step 4 selection algorithm that was used during development to validate indicator counts against the three test fixtures. Run it directly to re-validate:

cd export/
python3 extract_indicators.py --validate-only
# Validates indicator selection logic against all three test fixtures.
# Expected counts will vary as B2/B1 linkages in indicators.json are updated;
# re-run after any data change to confirm the algorithm still produces non-empty output.

Testing strategy

This prototype has no automated test runner. The testing approach is:

Fixture-based end-to-end — the three test fixtures provide known inputs with expected output characteristics
Algorithm simulation — Python equivalents of the JS algorithms in extract_indicators.py were used to verify selection logic during development
Manual inspection — the rendered Step 4 output is reviewed against the scientific specification by domain experts

Automated unit tests (Jest or similar) are planned for LAHMP v1 (the production Laravel application).

Deployment

GitHub Pages

The prototype is deployed automatically to GitHub Pages from the main branch. No CI/CD pipeline is configured — any push to main that modifies index.html, wizard.js, styles.css, or data/ is immediately live.

Production URL: https://daimpad.github.io/LAHMP
Branch:         main
Deploy trigger: push to main (GitHub Pages auto-deploy)
Build step:     none

Deployment checklist

Before pushing changes that affect algorithm behaviour:

Verify all three test fixtures render correctly at ?fixture=TEST-0N&step=4
Confirm JSON files were exported from the canonical Excel source (not edited manually)
Check browser console for JavaScript errors on initial load and on each step transition
Verify localStorage resume works: fill Step 1, reload, confirm state is preserved

Environments

Environment	URL	Branch
Production	`https://daimpad.github.io/LAHMP`	`main`
Local development	`http://localhost:8080`	any

There is no staging environment. Breaking changes should be developed on a feature branch and reviewed before merging to main.

Contributing

Scope of this prototype

Before contributing, note what is deliberately out of scope for this prototype and belongs to LAHMP v1 (the production Laravel application):

Feature	Reason deferred
GEO API (globalecosystems.org polygon query)	Requires server, API key, CORS handling
ABC Map / FAO API for IPCC land use	Same
Leaflet polygon drawing	Prototype uses manual text inputs
User accounts and saved assessments	No server
PDF generation	`window.print()` is the prototype approach
LLM/AI narrative generation	IUCN AI policy clearance pending
Darwin Core field alignment	v2 feature
Automated test suite	Planned for v1

Adding a new indicator profile

Author the profile content in LAHMP_Indicator_Profile_Template.docx
Add the row to raw/LAHMP_Indicator_Linkage_Matrix_Populated.xlsx (canonical source)
Run python3 export/extract_indicators.py to regenerate data/indicators.json
Load ?fixture=TEST-01&step=4 and verify the new profile appears when its P-code linkages match the test landscape's selected practices
Set "populated": "draft" while the profile awaits expert validation; upgrade to "populated": true once validated

Branching strategy

main          ← production (GitHub Pages)
feature/*     ← new features or data updates
fix/*         ← bug fixes
data/*        ← knowledge base updates only (JSON re-exports)

Pull requests to main require at least one review. Squash-merge preferred for feature branches to keep history readable.

Commit style

Follow Conventional Commits loosely:

feat: add conditionality check for conditional indicator profiles
fix: correct THEME_TO_CHAIN keys to match actual practice themes
data: re-export indicators.json from populated DOCX source files
docs: update README deployment section

Code review checklist

No hardcoded content in wizard.js or index.html — all labels/options loaded from data/
No new external dependencies introduced
Algorithm changes tested against all three test fixtures
JSON schema changes are backward-compatible with existing fixture files
CLAUDE.md updated if the developer specification has changed

References

Scientific framework

IUCN Global Ecosystem Typology 2.0 — EFG classification system used for landscape characterisation and indicator linkage
IPCC Guidelines for National Greenhouse Gas Inventories — Land Use Categories — IPCC land use category framework used in Step 1
IUCN Nature-Based Solutions — Organisational context for the LHMF
Ecdysis Foundation 1000 Farms Protocol — Field-level biological monitoring methodology referenced in indicator profiles
ISO 23611-1 — Soil quality: Sampling of soil invertebrates — Protocol standard for earthworm sampling (Profile 06)

Biodiversity monitoring standards

SEBI (Streamlining European Biodiversity Indicators) — European biodiversity indicator framework
UK Countryside Survey methodology — Reference for vegetation quadrat and invertebrate survey protocols
BTO/JNCC/RSPB Breeding Bird Survey — Protocol reference for farmland bird point counts (Profiles 19–21)
UK Bat Conservation Trust Good Practice Guidelines — Protocol reference for bat acoustic monitoring (Profile 22)

Sustainable agriculture frameworks

FAO TAPE — Tool for Agroecology Performance Evaluation — Agroecological performance framework; practice matrix approach origins
LandScale Framework — Landscape-level sustainability assessment; ecosystem service methodology
Rainforest Alliance Sustainable Agriculture Standard — Practice eligibility reference

Web standards and APIs

MDN — localStorage — Session persistence mechanism
MDN — Fetch API — Used for loading JSON data files at runtime
ECMAScript 2020 specification — Language version used throughout wizard.js
CSS Custom Properties specification — Token system used for IUCN brand colours

Internal specification documents

The authoritative algorithm and data specifications are maintained as Word documents in the IUCN project SharePoint. They are the single source of truth; when any conflict exists between this README, CLAUDE.md, or the code, the specification documents take precedence.

Document	Contents
`LAHMP_Master_Developer_Document.docx`	Platform architecture, data flow, v1/v2 boundary
`LAHMP_Step1_Developer_Specification.docx`	Landscape profile, all input lists, pre-population logic
`LAHMP_Step2_Developer_Specification.docx`	Practice recommendation algorithm (4 operations)
`LAHMP_Step3_Developer_Specification.docx`	Capacity assessment, 6 questions, capacity profile
`LAHMP_Step4_Developer_Specification.docx`	Monitoring plan algorithm (5 operations), output structure

License

MIT License — see LICENSE for the full text.

LAHMP is a prototype. It is not a certified monitoring tool. All indicator protocols and practice recommendations should be validated by qualified ecologists before field deployment.

Name		Name	Last commit message	Last commit date
Latest commit History 83 Commits
data		data
docs		docs
export		export
indicators		indicators
pics		pics
raw		raw
.gitignore		.gitignore
CLAUDE.md		CLAUDE.md
CLAUDE_LOG.md		CLAUDE_LOG.md
FORM_DOCUMENTATION.md		FORM_DOCUMENTATION.md
LICENSE		LICENSE
README.md		README.md
get-map.html		get-map.html
index.html		index.html
styles.css		styles.css
wizard.js		wizard.js

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LAHMP | Land Health Monitoring Platform

Overview

Key objectives

Architecture

System overview

Data flow

Technology stack

Installation

Prerequisites

Local setup

Usage

Live deployment

URL parameters

Test landscapes

Typical workflow

Configuration

IUCN brand tokens

Knowledge base data files

Assessment state object

Development

Repository structure

wizard.js internal structure

Code conventions

Updating the knowledge bases

Testing

Manual end-to-end validation

What to verify

Algorithm simulation

Testing strategy

Deployment

GitHub Pages

Deployment checklist

Environments

Contributing

Scope of this prototype

Adding a new indicator profile

Branching strategy

Commit style

Code review checklist

References

Scientific framework

Biodiversity monitoring standards

Sustainable agriculture frameworks

Web standards and APIs

Internal specification documents

License

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