Spatial Tools for Inclusive Landscape Governance: Negotiating Land Use, Land-Cover Change, and Future Landscape Scenarios in Two Multistakeholder Platforms in Zambia

Round 1

Reviewer 1 Report

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Comments for author File: Comments.docx

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

General comments:

The manuscript, entitled "Spatial Tools for Inclusive Landscape Governance: Negotiating Land Use, Land-Cover Change, and Future Landscape Scenarios in Two Multistakeholder Platforms in Zambia" focuses on the roles of spatial tools as boundary objects for negotiated governance in community-based landscape planning in the Kalomo District of Southern Zambia. There are some issues with this manuscript, mainly related to the readability and composition of the manuscript.

 Please review the quality of your English throughout the manuscript.

I would like to see some recommendations of this study to policymakers and implementers at the end of the abstract section.

Specific comments:

Point 1: Line 339, Figure 3: I suggest that use the appropriate font size.

Point 2: Line 375, Figure 4: Map the two land cover maps (1984 and 2020) in one frame and lacks visibility and do it again according to cartographic standards. Use the appropriate font size for the legend, scale grid etc.

Point 3: Discussion section (Line 582), this is an important part of the study and I suggest that the authors compare your results with other similar studies in order to emphasize the originality and novelty of the study.

Point 4: Line 707 I suggest that write recommendations at the end of the conclusion section or separately to the policymakers.

Author Response

Please see the attachment. Thank you

Author Response File: Author Response.docx

Reviewer 3 Report

The present paper is an attempt to investigate how spatial tools can support inclusive landscape negotiations and governance. The paper has several major issues as follows:

In the introduction section, it is not clear what the research gap is. There is a lack of comprehensive evaluation of the previous studies in adopting spatial tools for inclusive landscape negotiations and governance. I would suggest adding a “related work” section and showing clearly what the research gap is.

The provided information on Satellite Data Preparation and Analysis (section 3.3.1) is insufficient.

What supervised classification method did you use? Classification methodology and accuracy assessment are very superficially explained.

The reference collection strategy should be scientifically explained. Do they represent enough numbers and good distribution statistically?

Please provide the number of samples per class.

Built-up and bare land are separate classes in the FAO classification system, but the authors merged them into one class, why?

Figure 2 is very confusing. Except for part C, other parts are not well-matched with the mentioned LC classes. How does part a signify water class?   

Please apply a change accuracy assessment.

Please follow the following papers in the land cover classification and accuracy assessment sections

Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V., Woodcock, C. E., & Wulder, M. A. (2014). Good practices for estimating area and assessing the accuracy of land change. Remote sensing of Environment, 148, 42-57.

Why do the authors use only two-time steps for generating land cover/use changes?

Lines 306-308:

“Cropland had the lowest producer accuracy of 54% due to the seasonal effect (dry season) in distinguishing it from grassland classification resulting in a wide spectral signature. For the 2020 map, the built-up area classification had the lowest producer accuracy of 66.7%.”

Obtaining a producer accuracy of 54% or 66.7% is not acceptable while the authors only had 5 classes in their classification. This low producer accuracy can be related to the class imbalance problem. I would suggest reading the following papers:

Naboureh, A., Li, A., Bian, J., Lei, G., & Amani, M. (2020). A hybrid data balancing method for classification of imbalanced training data within google earth engine: Case studies from mountainous regions. Remote Sensing, 12(20), 3301.

Minor revisions:

Line 21: What is "MSPs"? Multi-stakeholder Platforms?

Please define all abbreviations the first time they appear in each of the three sections (the abstract, the main text, and the first figure or table).

The quality of Figure 1 can be improved.

Table2. I would suggest using “rangeland” instead of grassland.

Line 205: Downloaded?

I would suggest removing this word from your sentence. Within GEE, users bypass downloading part.

Line 207: You already defined GEE in line 205. Please, only use the “GEE’ here.

Line 210, line 99

(See [42]),   [20, p. 33], [20, p1439]

Please simply use [42] in line 210, and [20] in line 99 for citing references. You can read the instructions for authors provided by the journal.

Lines 218-220, Signature data were then used to build land-cover classes for the whole images based on spectral signatures from the area of interest, with September and October (dry season) as filter dates for both images to reduce seasonal variability.

Please add a reference

Author Response

Please see the attachment

Author Response File: Author Response.docx

Round 2

Reviewer 3 Report

Author Response

Kindly find attached the responses on important issues of concerns you brought to our attention

Author Response File: Author Response.docx