UAV Imagery-Based Classification Model for Atypical Traditional Village Landscapes and Their Spatial Distribution Pattern

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

In the manuscript the authors have developed the classification model based on unmanned aerial vehicle (UAV) imagery (ATVLUI) by virtue of the UAV RGB images and the object-oriented fuzzy logic membership classification technique for extracting objects according to their spectrums, textures, geometries, and context relationships of atypical traditional villages landscapes. They have demonstrated the reserach results of using the developed model taking as example the Qianfeng Chinese Village. The authors have shown the functional diagram of atypical traditional village landscape classification model based on UAV imagery.  The authors have described each functional block of the atypical traditional village landscape classification model based on UAV RGB images: determination of thresholds for object-oriented segmentation, fuzzy logic membership classification, extraction of non-buildings, extraction of buildings. The block diagram of the extraction process for traditional buildings has been demonstrated. The authors have shown the evaluation of the classification results of atypical traditional village landscapes, calculation of landscape pattern indexes. The algorithm of ATVLUI’s segmentation thresholds for modern and traditional buildings is described. The classification results of Qianfeng Chinese Village landscapes using the developed model are given.  

After minor improvements and corrections, the manuscript "The UAV Imagery-Based Classification Model for Atypical Traditional Village Landscapes and The Spatial Distribution Pattern" by Shaojiang Zheng , Lili Wei , Houjie Yu , Weili Kou can be accepted for publication.

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The article "The UAV Imagery-Based Classification Model for Atypical Traditional Village Landscapes and The Spatial Distribution Pattern" introduces the ATVLUI model, which is predicated on UAV RGB imagery for the classification of traditional village landscapes. This model employs object-oriented image segmentation and fuzzy logic classification to accurately discern traditional buildings based on their shapes, spectra, and textures, even within intricate scenarios.

The presented ATVLUI model provides a alternative to conventional methods such as manual field surveys and visual interpretation, which are often time-consuming tasks. The study underscores the imperative for efficient and precise landscape capture methodologies. Despite the high-resolution data afforded by aerial photography and laser scanning, the automatic identification of buildings remains encumbered by challenges such as scenario complexity, building variability, and sensor resolution.

The article is clear and detailed. The authors have carefully explained the models and approaches used, making the ATVLUI model easy to understand. There is provided step-by-step guide from image acquisition to classification. making the article a valuable  in landscape analysis.

Unfortunately, concerns arise regarding the data acquisition process, particularly regarding the influence of weather conditions and sunlight on RGB image analysis, which were not addressed in the study. Additionally, the authors only mentioned that the data consists of RGB images acquired by Dajiang Phantom 4 Pro drones on August 17, 2020, with specific image dimensions and spatial resolution. However, it remains unclear whether a single-time recording was sufficient for conducting all analyses, especially considering potential variations in lighting conditions and weather effects that could impact image quality and subsequent analysis outcomes.

It is recommended to provide detailed information on environmental conditions during data collection to facilitate transparency about  research

It is suggested reading carefully paragraphs and improve phrases due to some mistakes

Also style of references in some case is not proper liek 19 or 23 !

 

Comments on the Quality of English Language

Language is understandable but it is suggested reading carefully paragraphs and improve phrases due to some mistakes

 

Author Response

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Reviewer 3 Report

Comments and Suggestions for Authors

This study focuses on the development of a landscape classification model for atypical traditional villages based on UAV imagery (ATVLUI), which is able to automatically classify and quantitatively analyse the landscapes of atypical traditional villages.

According to the area, number and proportion of each class of surface features, it was possible to obtain data on the number and distribution of each type of features for which the historical value of the village was assessed

The quality of the classification carried out allows us to trust the data obtained and the conclusions drawn from them. The article may be of interest to a wide range of readers.

There are a few remarks that need clarification.

Line 163.  It is not possible to obtain orthophotos with a drone of this model. Either just images or photogrammetric processing was done. Therefore, it is necessary to clarify the type of source data.

Line 237 and Figure 3 C .Lexical inaccuracy. Roads are not buildings.

Figure 8. Grammatical error in the caption above fragment A3

Author Response

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