five

Forest data organizer Python tool

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DataCite Commons2026-02-24 更新2026-05-04 收录
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https://mostwiedzy.pl/en/open-research-data/forest-data-organizer-python-tool,202512291145199623131-0
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VERSION 1.1: The visualisation feature added.  Modified (3 files):• forest_data_organizer.py - Added ~400 lines of visualization code (7 plotting methods, 300 DPI output)• requirements.txt - Added matplotlib>=3.4.0• README.md - Documented visualization features Created (1 file):• generate_visualizations.py - Standalone utility to regenerate visualizations from CSV files\   DESCRIPTION This dataset contains a Python tool for processing forest inventory data and calculating standard forestry and ecological metrics. The tool reads Excel spreadsheets containing forest inventory data and outputs organized datasets with derived variables. All formulas based on published literature. See code documentation for specific citations. The related dataset https://doi.org/10.34808/nhf1-dg46  provides processed data for immediate use, whereas this dataset provides the processing tool for users with their own inventory data or custom analysis requirements. Input processing: Reads XLSX format inventory file Standardizes species names to forestry codes Parses age class categories Classifies tree types and age categories Metric calculation: Biodiversity indices: Shannon Index (H' = -Σ(pi × ln(pi))), Simpson Index (D = 1 - Σ(pi²)), Pielou's Evenness (J' = H'/ln(S)), Species Richness Age structure: Weighted mean age, age class distribution percentages, coefficient of variation Composition: Coniferous/deciduous ratios by area and volume, dominant species identification Growth: Mean Annual Increment (Volume/(Area × Age)), Current Annual Increment (ΔVolume/Area) Temporal: Year-over-year changes in area and volume Data provenance tracking: Tags each derived value with source type Categories: RAW, RAW_SUMMED, CALCULATED, COUNTED, DETERMINED, ESTIMATED Generates metadata file explaining categories Implementation Details: Language: Python 3.7+ Dependencies: pandas (≥1.3.0), numpy (≥1.21.0), scipy (≥1.7.0), openpyxl (≥3.0.0) Lines of code: ~680 Processing time: <10 seconds for 1,260 records Input Requirements: Excel file (.xlsx) with columns: Species (text) Year (integer) Tree_Type (text) Category (text, e.g., "Age_41-60") Volume_m3 (float) Area_ha (float) Documentation: README: Installation, usage, API reference Usage examples: 16 practical scenarios Validation report: Detailed test results Limitations: - Designed for hierarchical age-class inventory data- Assumes standard forestry category naming conventions- Growth metrics require age class information- MAI calculation depends on age class midpoint estimates
提供机构:
Gdańsk University of Technology
创建时间:
2025-12-29
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