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Peer-Review Record

Reliability Analysis of LandScan Gridded Population Data. The Case Study of Poland

Reviewer 1: Anonymous
Reviewer 2: Anonymous
ISPRS Int. J. Geo-Inf. 2019, 8(5), 222; https://doi.org/10.3390/ijgi8050222
Received: 22 March 2019 / Revised: 23 April 2019 / Accepted: 4 May 2019 / Published: 8 May 2019

Round 1

Reviewer 1 Report

My concern has been addressed in this version.


Can you revise Figure 3 to ensure all words can be clearly presented in the Figure? In the current version, the numbers of axles on the bottom left are hided by the note.

Author Response

The authors thank to the anonymous reviewer for their work and attention given on this paper.

Figure 3 is corrected.


Reviewer 2 Report

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 11.0px 'Helvetica Neue'; color: #000000; -webkit-text-stroke: #000000} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 11.0px 'Helvetica Neue'; color: #000000; -webkit-text-stroke: #000000; min-height: 12.0px} span.s1 {font-kerning: none}

In this paper, the authors try to estimate the reliability of LS data, with a comparison with PPG. The comparison suggests that LS data is quite good, in spite of some inconsistencies, e.g. under/over estimations.


The manuscript is well balanced, detailed, with a good structure. The literature review is quite detailed. The research questions are also clearly stated. The problem statement is OK. In general, this is a good piece of paper.


Nonetheless, I have some remarks. In Fig. 3, we observe too much spread. Using R-squared and slope, might not be enough to conclude anything about the match between LS and PPG.


In addition, in lines 256-257, you cannot state that « for at least 55% of Polish territory the 257 relatedness of PPG and LS data is very high ». R-square is just a statistical metric that measures how good a prediction is. Here, it is difficult to assess the matching between LS and PPG based on R-square only, in my opinion. Some further clarification is needed. 


I have a minor remark regarding the methodology, I think that the authors should propose some further extensions that would provide more insights into the comparison between LS and PPG. This can be discussed in the concluding remarks for further research.


Author Response

Replay to review comments – in green

(1)    The sentence It allows to formulate the preliminary assertion that for at least 55% of Polish territory the relatedness of PPG and LS data is very high is deleted. We of course agree with the reviewer remark that R-squared is a statistical measure of how good the prediction is, and the high spread of data observed in Fig 3 does not entitled to draw any conclusions regarding the relationship between LS and GUS data. We are very sorry for this mistake. Figure 3 is now corrected.

(2)    We also added some information about further extension of presented research.


This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.


Round 1

Reviewer 1 Report

In this study, the reliability of LandScan gridded population data is analysed by the comparison with official population grid. A series of indicators are proposed to evaluate the difference between two data sets and to reveal the quality of the LandScan gridded population data. The contents in the study are well organised and presented. The proposed indicators for assessing data sets are reasonable and effective in analysis. A primary concern about this study is that if it is reasonable to regard the offical population grid as the "true value"? I believe that the official population grid is also an estimation data sets, and there has to be various sources of errors. Can you briefly introduce how the official population data set is derived and what kind of errors it contains? If there are several types of errors of the data, can you improve the data analysis methods to address the problem that the "true value" contains errors?

Reviewer 2 Report

This paper estimates Landscan reliability based on the official Polish Population Grid. I have the following concerns of the current version of the manuscript:

 

1.     IJGI is an international journal; therefore, the authors have to address why such reliability analysis of LandScan data is beneficial to an international readership beyond a case study itself of Poland.

2.     A literature review session of Landscan data and its applications is missing.

3.     It is recommended to add a table to compare LandScan and other publicly available spatialized population distribution datasets at the end of the introduction. It may also be worthwhile to compare and contrast the reliability of Landscan VS those publicly available population estimate products.

4.     The metrics and thresholds (Table 1) are somehow arbitrary. Justifications and related sensitivity analysis are needed.


Reviewer 3 Report

The paper could be of interest to a reader if it was not restricted to one regional data set. The paper only discusses one type of population data and it does not explain how to extend this successfully to other types of data or other regions. The novelty of the methods is very limited. One may ask how it is possible to extend this method to other grid types such as Discrete Global Grids which are becoming the standard of data representation and data integration. The models used in the paper are very simple. There is no novelty or creativity in models such as absolute disparity index or Spatial Contiguity Index. These are pretty standard and simple models. Simplicity is fine but then the question is what are the main contributions of the paper? The paper is full of grammar mistakes and awkward sentences. A major revision in terms of ESL is needed to make the paper ready for publication. My overall judgement is that the paper in its current form is not acceptable. These minimum modifications are needed: 1) Clear statement of the scientific contribution of the paper. 2) Proper comparison with other methods and base-lines. 3) Significantly shorten the paper specially introduction. 4) Proper proof-reading and grammar checks of the paper as well as correcting the reference style. 5) Discussion on how this method can be of use of scientists studying similar problems with different data sets. 


Some of the needed grammar modifications:

line 12: broaden "the" understanding

line 14: on "a" change detection approach

line 15: the results---> our results

line 23: agricultural "areas"

line 28: A better understanding of many

line 30:  the "Earth"

Figure 2, 3 need more description

line 213: is "based on"

line 308: In the industrial zones","

line 310: To balance the totals","

line 315: Moreover","

line 378: luck-->lack

Reference 3: Bielecka, E

References need consistent usages of ; and ,


ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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