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Open AccessArticle
Peer-Review Record

A Novel Urban Composition Index Based on Water-Impervious Surface-Pervious Surface (W-I-P) Model for Urban Compositions Mapping Using Landsat Imagery

Remote Sens. 2021, 13(1), 3;
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Remote Sens. 2021, 13(1), 3;
Received: 10 December 2020 / Revised: 18 December 2020 / Accepted: 19 December 2020 / Published: 22 December 2020
(This article belongs to the Special Issue Optical Remote Sensing Applications in Urban Areas)

Round 1

Reviewer 1 Report

The subject of this manuscript is one of importance to mankind, given the excessive globalization and very rapid development of urban areas. In this context, monitoring urban compositions spatially and temporally is a crucial issue for urban planning and management.

The article entitled "Urban Composition Index for Mapping Compositions of Urban Environments Based on Water-Impervious Surface-Pervious Surface (W-I-P) Model by Using Landsat Imagery" is a very interesting one,  very well written, the text is coherent, well linked, very descriptive and the way it is completed with figures and tables makes it representative.

The working method is quite explicit, so that the reader can easily understand the working mode, the source of the information and the techniques used. At the same time, it is well documented, has many bibliographic sources of great importance and relevance for the subject in question.

This way, I would like to congratulate the authors for the results and for the work done.

Author Response

It's my pleasure that our work can be recognized and praised by you. Your approval is a warm ray of sunshine in the cold winter. Thank you very much. Best wishes to you and your family.

Reviewer 2 Report

The research work presented by the authors is aimed at developing and validating a novel Urban Composition Index (UCI) in order to identify a widely usable methodology for urban compositions extraction. The rapid urbanization with its environmental impacts on the territories require a continuous monitoring and analysis of the components present. Indeed, different procedures have been validated through techniques based on remote sensing images. Among these, methods based on spectral indices have proved promising, due to the many advantages in their effective implementation. On the other hand, several indices have been developed but each of them is single composition indices and often correlated to the type of scenario investigated. The authors have thus structured a verification and validation test of the multi-composition UCI, comparing the results obtained on 4 different scenarios with the results obtainable from the implementation of other spectral indices. Through an exhaustive discussion of the inferential statistical procedures, the authors demonstrated the effective efficiency of their proposal in extracting each urban compositions (ISA, PSA, and water).   The work is acceptable with minor revisions. The authors are advised to make changes to the title of the paper in order to make it easily interpretable. An improvement in the drafting of the Abstract could convey a better framing of the work to the reader.
  Below are some minor revisions: Lines 62-69. It is suggested that the indexes be listed in a table in order to improve readability. Line 77. Explain the ISA acronym to readers. The acronym will be explained a few lines later, but leave the doubt in this first case. Line 310. Briefly explain the differences between Tables 2-3-4 and then indicate what they refer to. This may help the reader to better interpret the results.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

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