The article presents good practices for estimating area and assessing accuracy of land change maps. It outlines key recommendations for designing and implementing accuracy assessments and area estimation based on reference sample data. The three major components of the process are sampling design, response design, and analysis. The primary recommendations include using probability sampling to achieve accuracy and area estimation objectives while considering practical constraints, implementing a response design based on reference data sources that provide sufficient spatial and temporal representation, and ensuring analysis is consistent with the sampling and response design protocols. Accuracy assessment should report estimated error matrices in terms of proportion of area, overall accuracy, user's accuracy, and producer's accuracy. Area of classes should be estimated based on reference classification, uncertainty should be quantified through confidence intervals, and variability in reference classification should be evaluated. Deviations from good practices should be documented. The article emphasizes the importance of accuracy assessment in land change mapping, particularly for scientific, management, and policy applications. Area estimation is a key value-added use of land change maps in land accounting applications. The accuracy of area estimates is crucial for assessing greenhouse gas emissions from forests and for climate change mitigation activities. The article also discusses the role of remote sensing in estimating forest extent and deforestation, and the need for scientifically valid protocols for forest change monitoring. The article provides a detailed discussion of sampling design, including the choice of probability sampling, stratified sampling, and cluster sampling. It highlights the importance of selecting an appropriate sampling design that meets the objectives of accuracy and area estimation. The response design is discussed in terms of the spatial unit, sources of reference data, labelling protocol, and definition of agreement. The article also discusses the use of various reference data sources, including field plots, aerial photography, satellite imagery, and other spatial data. The article concludes with a summary of the key recommendations for good practices in estimating area and assessing accuracy of land change maps. It emphasizes the importance of using scientifically valid methods and ensuring transparency and rigor in the assessment process. The recommendations are intended to guide practitioners in the design and implementation of accuracy assessments and area estimation methods for land change assessments using remote sensing.The article presents good practices for estimating area and assessing accuracy of land change maps. It outlines key recommendations for designing and implementing accuracy assessments and area estimation based on reference sample data. The three major components of the process are sampling design, response design, and analysis. The primary recommendations include using probability sampling to achieve accuracy and area estimation objectives while considering practical constraints, implementing a response design based on reference data sources that provide sufficient spatial and temporal representation, and ensuring analysis is consistent with the sampling and response design protocols. Accuracy assessment should report estimated error matrices in terms of proportion of area, overall accuracy, user's accuracy, and producer's accuracy. Area of classes should be estimated based on reference classification, uncertainty should be quantified through confidence intervals, and variability in reference classification should be evaluated. Deviations from good practices should be documented. The article emphasizes the importance of accuracy assessment in land change mapping, particularly for scientific, management, and policy applications. Area estimation is a key value-added use of land change maps in land accounting applications. The accuracy of area estimates is crucial for assessing greenhouse gas emissions from forests and for climate change mitigation activities. The article also discusses the role of remote sensing in estimating forest extent and deforestation, and the need for scientifically valid protocols for forest change monitoring. The article provides a detailed discussion of sampling design, including the choice of probability sampling, stratified sampling, and cluster sampling. It highlights the importance of selecting an appropriate sampling design that meets the objectives of accuracy and area estimation. The response design is discussed in terms of the spatial unit, sources of reference data, labelling protocol, and definition of agreement. The article also discusses the use of various reference data sources, including field plots, aerial photography, satellite imagery, and other spatial data. The article concludes with a summary of the key recommendations for good practices in estimating area and assessing accuracy of land change maps. It emphasizes the importance of using scientifically valid methods and ensuring transparency and rigor in the assessment process. The recommendations are intended to guide practitioners in the design and implementation of accuracy assessments and area estimation methods for land change assessments using remote sensing.