This quick start guide introduces the AIMAC (AI-assisted Assessment and Monitoring) tool developed by Landscape Alliance to support assessment and monitoring of landscape sustainability and adaptation performance. The guide outlines the workflow for creating assessments, including contextualization of principles, criteria, and indicators; weighting of assessment components using ranking, rating, or Analytic Hierarchy Process (AHP) methods; and scoring of indicators based on defined guidelines. Users can customize criteria and indicators to reflect local conditions, assign relative weights, evaluate performance, and generate adaptation and sustainability assessment results. The tool incorporates artificial intelligence features to assist users in developing and refining assessment frameworks and supports the documentation of landscape conditions through structured, indicator-based evaluation. AIMAC is designed to facilitate evidence-based decision-making, environmental monitoring, sustainable land management, and landscape governance by providing a standardized platform for assessing forests, agroforestry systems, and broader landscape restoration and adaptation initiatives.
This work is licensed under CC-BY 4.0
This work is licensed under CC-BY 4.0
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Publisher
CIFOR and ICRAF as Landscape Alliance: Bogor, Indonesia and Nairobi, Kenya
Publication year
2026
Authors
Language
English
Keywords
agroforestry system, artificial intelligence, climate change adaptation, forest management, landscape management


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