Upload README.md

README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - other
+language:
+  - ko
+  - en
+tags:
+  - GIS
+  - benchmark
+  - geospatial
+  - LLM
+  - agent
+  - QGIS
+  - MCP
+  - spatial-analysis
+pretty_name: GIS-Bench
+size_categories:
+  - n<100
+---
+
+# GIS-Bench: A Benchmark for Evaluating LLM-based GIS Automation Agents
+
+## Dataset Description
+
+**GIS-Bench** is a benchmark framework designed to evaluate the capability of Large Language Model (LLM)-based agents in automating GIS (Geographic Information System) tasks using the Model Context Protocol (MCP).
+
+This benchmark was developed as part of a master's thesis research and targets real-world spatial analysis workflows executable in QGIS Desktop via Claude + MCP integration.
+
+- **Paper:** *GIS-Bench: LLM 기반 GIS 자동화 에이전트 평가 벤치마크* (KCC 2026, submitted)
+- **Repository:** [yiseo0/GIS-Bench](https://huggingface.co/datasets/yiseo0/GIS-Bench)
+- **License:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+
+---
+
+## Benchmark Overview
+
+| Item | Details |
+|------|---------|
+| Total Tasks | 45 |
+| Difficulty Levels | 3 (Level 1 / Level 2 / Level 3) |
+| Task Type | GIS spatial analysis & visualization |
+| Output Format | HTML (Leaflet.js map), PNG, JPG |
+| Evaluation Method | VLM-based automated scoring (Claude Sonnet) |
+| Scoring | 130-point raw → 100-point normalized |
+| Pass Threshold | 60 points (normalized) |
+
+---
+
+## Evaluated Models
+
+| Model | Condition | Pass Rate (Overall) |
+|-------|-----------|-------------------|
+| Claude (Sonnet) + QGIS MCP | Agentic | **100%** |
+| Claude (Sonnet) Baseline | No MCP | ~67% |
+| GPT-5.2 Baseline | No MCP | ~69% |
+
+> Statistical significance confirmed via McNemar's test (p < 0.05)
+
+---
+
+## Task Structure
+
+Tasks are organized across 3 difficulty levels:
+
+| Level | Description | Example |
+|-------|-------------|---------|
+| Level 1 | Basic data loading & visualization | Load a shapefile and display on map |
+| Level 2 | Spatial filtering & styling | Filter buildings by area > 500㎡ with color coding |
+| Level 3 | Multi-step spatial analysis | Buffer analysis + intersection + styled output |
+
+Each task entry includes:
+- `task_no`: Task ID (1–45)
+- `prompt`: Natural language instruction (Korean)
+- `level`: Difficulty level (1, 2, or 3)
+
+---
+
+## Data Sources
+
+All spatial datasets used in this benchmark are sourced from Korean public data portals under open licenses.
+
+| 데이터명 | 실제 파일 | 형식 | 공간 유형 | 좌표계 | 출처 | 라이선스 |
+|---------|---------|------|---------|--------|------|---------|
+| 서울시 CCTV 설치 현황 | `few_shot_test_서울시 안심이 CCTV 연계 현황` | CSV | Point | EPSG:4326 (WGS84) | [서울 열린데이터광장](https://data.seoul.go.kr) | 공공누리 1유형 |
+| 서울시 고도지구 경계 | `UQ123_용도지구(고도지구)_20250805` | SHP | Polygon | EPSG:5186 | [국토정보플랫폼](https://www.nsdi.go.kr) | 공공누리 1유형 |
+| 서울시 행정경계 | `서울시_SIG.shp` | SHP | Polygon | EPSG:5186 | [공공데이터포털](https://www.data.go.kr) | 공공누리 1유형 |
+| 수치표고모델 (DEM) | `(B080)공개DEM_34602_img_2025` | GeoTIFF | Raster | EPSG:5186 | [국토정보플랫폼](https://www.nsdi.go.kr) | 공공누리 1유형 |
+| 고해상도 위성영상 | `Landsat_위성영상의_정규물지수_2024` | GeoTIFF | Raster | EPSG:5186 | [NASA EarthData](https://earthdata.nasa.gov) | Public Domain |
+
+> All datasets are publicly available and free to use with attribution.
+
+> **Note:** 일부 프롬프트는 초기 실험 당시 워딩("대여소" 등)을 그대로 유지합니다. 실제 사용 데이터는 서울시 CCTV 연계 현황이며, 자연어 지시의 모호성을 처리하는 능력도 평가 요소에 포함됩니다.
+
+---
+
+## Evaluation Pipeline
+
+Evaluation is performed using **VLM-based automated scoring** with Claude Sonnet as the judge model.
+
+### Scoring Criteria (130-point raw scale)
+
+#### Basic Quality (100 pts)
+| Criterion | Max Score | Description |
+|-----------|-----------|-------------|
+| `exists` | 20 | Meaningful visualization present |
+| `accuracy` | 30 | Correct region and dataset used |
+| `requirement` | 30 | Color, filter, buffer conditions met |
+| `completeness` | 20 | Legend, title, labels complete |
+
+#### Spatial Accuracy (30 pts)
+| Criterion | Max Score | Description |
+|-----------|-----------|-------------|
+| `spatial_location` | 15 | Data displayed in correct geographic area |
+| `geometry_validity` | 5 | No polygon/buffer distortion |
+| `numeric_match` | 10 | Numeric conditions reflected in output |
+
+**Normalization:** `score_normalized = round(total_raw / 130 * 100)`
+
+Each task is evaluated **3 times** (N=3) and the average score is used for robustness.
+
+See [`evaluation/eval_criteria.md`](evaluation/eval_criteria.md) for the full evaluation prompt and criteria details.
+
+---
+
+## Reference Outputs
+
+Since GIS tasks do not always have a single deterministic "ground truth," this benchmark provides **reference outputs** — screenshots generated by the benchmark author under each task condition. These serve as visual references for what a correct result should look like.
+
+Reference screenshots are provided in `assets/screenshots/` organized by model and task ID.
+
+---
+
+## MCP Tool Dependency
+
+This benchmark was conducted using **QGIS MCP** to connect Claude to QGIS Desktop.
+
+- **Tool:** [jjsantos01/qgis_mcp](https://github.com/jjsantos01/qgis_mcp)
+- **Description:** MCP server + QGIS plugin that allows LLMs to control QGIS Desktop
+- **Note:** The MCP tool code is not included in this repository. Please refer to the original repository for installation.
+
+---
+
+## Repository Structure
+
+```
+GIS-Bench/
+├── README.md                        # This file (Dataset Card)
+├── data/
+│   └── tasks.json                   # 45 task prompts with level labels
+├── evaluation/
+│   ├── run_evaluation_vlm_v3.py     # VLM evaluation pipeline
+│   └── eval_criteria.md             # Scoring criteria & judge prompt
+├── results/
+│   └── leaderboard.json             # Evaluation results per model
+└── assets/
+    └── screenshots/                 # Reference output screenshots
+```
+
+---
+
+## Citation
+
+If you use GIS-Bench in your research, please cite:
+
+```bibtex
+@inproceedings{gisbench2026,
+  title     = {GIS-Bench: LLM 기반 GIS 자동화 에이전트 평가 벤치마크},
+  author    = {김이소 and 장두성},
+  booktitle = {한국정보과학회 학술발표논문집 (KCC 2026)},
+  year      = {2026}
+}
+```
+
+---
+
+## License
+
+- **Benchmark tasks, evaluation code, and results:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)
+- **Spatial datasets:** 공공누리 1유형 (출처 표시 조건, 각 데이터 출처 참조)
+- **QGIS MCP tool:** Not included. See [jjsantos01/qgis_mcp](https://github.com/jjsantos01/qgis_mcp)