Research on Optimization Technology of Cross-Regional Synergistic Deployment of Fire Stations Based on Fire Risk

Round 1

Reviewer 1 Report

The spatial planning of fire stations is closely related to urban fire risk and response time. This work takes the Yangtze River Delta demonstration area as the research object, analyzes the multi-regional fire risk level through multi-source data and stipulates the response time, and finally proposes an optimization plan for the fire space planning. This is a good vision for cross-regional fire planning, the paper is well organised and then before publishing this manuscript, it needs some revision. My comments are as follows:

1. The manuscript (introduction, methods and results sections) could be substantially improved by relying and citing more literature.

2. Fire risk result analysis is not comprehensive and it is recommended to further describe the spatial distribution of fire risk.

3. It is recommended to map the Table 3 Coverage of fire stations in single administrative areas to better compare the differences in results.

4. It is suggested to compare the results of spatial layout optimization of fire stations with chart description.

5. Figure 4 to Figure 6 clarity needs further adjustment compared to Figure 3.

6. It is suggested that the economic factors of spatial planning of fire stations should be studied in consideration of coverage.

7. "Error! Reference source not found" is displayed in several places in the Introduction, so please adjust it.

 

8. The lines of the block diagram in Figure 2 have overlapping areas, and the text formatting and size are inconsistent. It is recommended that this be adjusted.

Author Response

Response to Reviewer 1Comments

Point 1: The manuscript (introduction, methods and results sections) could be substantially improved by relying and citing more literature.

Response 1:Thank you very much for your comments, we have cited more in the manuscript ( introduction, methods and results sections )

The healthy, sustainable and coordinated development of urban agglomerations has gradually become the leading force for sustainable economic and social development in China[1]. Two or more cities break through the constraints of administrative divisions, embracing the free flow and optimal allocation of development elements and resources between them. By doing so, an overall effect of complementary advantages and common prosperity is formed. However, the increasingly complex urban structure also brings new challenges to the layout of public emergency stations[2] such as fire stations and emer-gency centers[3]. The Yangtze River Delta region, as a pilot area for integrated develop-ment of super-large urban agglomerations[4], has unique advantages and actual needs in terms of industrial coordination[5], cross-regional policies[6], synergistic risk response[7], etc. It is meaningful to study the optimization technology of cross-regional synergistic de-ployment of fire stations in the region.

Scientific assessment of urban fire risk and construction of a reasonable mathemati-cal model are important factors in the deploymentof fire stations. According to factors such as urban development, building type and previous fires, Ferreira et al.[8] drew the fire-prone areas in the historical center of Jimaldes by using the GIS tool. Zhang[9] com-prehensively analyzed the urban fire risk in Haikou City from the aspects of fire risk, vul-nerability and fire prevention capacity. Wu et al.[10] evaluated the fire evolu-tion and consequences of subway stations and established a comprehensive model based on the Bayesian network and the Delphi method. Kiran et al.[11]  analyzed regional fire risk through small-area population prediction and found the firefighting force gap based on the coverage-maximized model. Shahrooz et al.[12] combined the location allocation model with the geographic information system (GIS) to re-plan the optimal location of fire stations, raising the coverage rate within a 5-minute response time from 81% to 95%. After evaluating the similarity of disaster types, the exposure of disaster environment and the probability of disaster consequences, Liu[13] proposed the model and procedure of urban fire disaster risk assessment to determine the disaster risk level. Ming et al.[14] proposed a mixed integer linear programming model by taking vehicle coverage and time coverage as indicators. Besides, they demonstrated the relationship among vehicle coverage ratio, time coverage ratio, number of fire stations, number of fire trucks, FPTVC and total budget through case analysis and multiple sensitivity analysis on historical data in Hefei City. Wang et al,[15] proposed an ArcGIS-based method to determine the spatial distribution of urban fire risk according to the various POIs, historical fire accident data and expert judgment. Against the backdrop of big data, geographic information data can effectively transmit information such as the name, longitude and latitude coordinates and street ad-dress information of geographic entities, and then deploy fire stations through the “loca-tion-allocation” model. Based on 443,400 pieces of POI data and relevant data like road network, Wang et al.[16] evaluated the spatial distribution of fire risk within the Fifth Ring Road in Beijing City using the SAVEE model and the expert scoring method. In addition, they obtained the final optimization results of fire stations in the research area on the basis of coverage-maximized, facility point-minimized and impedance-minimized model algo-rithms. Based on 34,035 POI data in a district of Wuhan City, Jiang et al.[17] divided the city into flammable and explosive areas, vulnerable population areas, densely populated areas, key protected areas and general risk areas, and evaluated the appropriate areas for deploying fire stations using the analytic hierarchy process. Considering that the surface light intensity information recorded by nighttime light images can reflect the basic char-acteristics of human social and economic activities, Wang et al.[18]  assessed the fire risk in Hefei City by combining the POI data and the NPP/VIIRS nighttime light image data. Meanwhile, the layout of fire stations is closely related to the specified fire response time. In the United States, it is stipulated that the layout of fire stations shall ensure that the driving time for occupational fire stations does not exceed 4 min[19] and the response times of volunteer fire stations vary according to different fire grades[20]. In the United Kingdom, the fire brigade area is divided into six categories, i.e., A, B, C, D, remote areas and special risk areas, according to a uniformly used risk grading method, and the re-sponse time is also determined according to the risk level. In China, the layout of fire sta-tions mainly is stipulated inStandard for Construction of Urban Fire Stations[21], as fol-lows:the location is determined according to the principle that fire trucks can reach the edge of the jurisdiction within 4 min. However, with the rapid construction and irregular expansion of cities, the layout of existing fire stationsis faced with indirect problems such as insufficient fire fighting forces in high-risk fire areas like densely populated old urban areas[22] and redundant fire fighting forces in low-risk areas like new urban areas with scattered buildings[23]. Scholars all over the world have proposed different response times concerning varying risk levels. With Istanbul as the research object, Başar et al.[24] proposed a risk-based dynamic multi-coverage fire station location planning model which divided the response time into four levels: 5 min, 8 min, 10 min and 15min. Such a model can scientifically and reasonably deployfirefighting forces. He et al.[25] proposed a method for evaluating the layout of urban fire stations which specified the response times of 3 min, 5 min, 8 min and 10 min in accordance with four assessed fire risk levels A, B, C and D, respectively. The evaluation results can be tested by three indicators, i.e., the re-sponse coverage rate, cross-response coverage rate and average response time of fire sta-tions. Existing researches are primarily focused on the coverage of fire station planning and site optimization in a single city, while the research on the layout of fire stations across administrative boundaries in urban agglomerations is rarely reported.

This study proposes a method that integrates multi-city geographic information and expert scoring evaluation to comprehensively deployfire stations. The method can effec-tively promote regional fire rescue coverage, shorten fire response time, reduce fire rescue costs, and decrease fire rescue losses. The research results are expected to provide a theo-retical basis for the optimization of urban fire station location in the Yangtze River Delta integrated demonstration zone (YRDIDZ).

 

Point 2: Fire risk result analysis is not comprehensive and it is recommended to further describe the spatial distribution of fire risk.

Response 2:Thank you very much for your comments, we further describe the fire risk in the manuscript according to your suggestions.

The ranges of primary and secondary indicators of urban fire risk are standardized. Subsequently, since different factors may exert varying effectson the fire risk, experts are invited to weight them according to the actual situation of urban fire risk in the research area (Table 2). Afterwards, the weighted indicators are brought into the iterative formula to calculate the fire risk distribution in the research area (Fig. 3). Specifically, the research ar-ea is divided into 1,935 regions which are then classified into three levels (163 high-risk regions, 539 medium-risk regions and 1,233 low-risk regions) using the natural break classification method.

From the perspective of spatial distribution, the northeast, northwest, southeast and southwest areas witness medium- and high-risk regions, that is, these regions are highly susceptible to fires. A large number of low-risk regions exist in the central area. From the perspective of risk level, high-risk regions are mainly concentrated in Yingpu Street and Xujing Town of Qingpu District, Wujiang Economic Development Zone and Oriental Silk Market of Wujiang District and Huimin Street of Jiashan County. These regions are densely populated and contain numerous high-rise buildings, hazardous chemical enter-prises and underground buildings, featuring fire proneness, considerable fire losses and poor fire rescue conditions. Medium-risk regions mainly include the periphery of high-risk regions, the connecting zone of high-risk regions and some urban regions. Compared with high-risk regions, these regions contain fewer densely populated places and no large commercial buildings or complex underground buildings, but they are close to high-risk regions. This means that a fire occurring there is likely to trigger a fire in buildings in high-risk regions within a short time. Low-risk regions are concentrated on the periphery of cities, mostly at the junction of administrative areas where the population density is low and urbanization needs to be further strengthened. In addition, some low-risk regions are located near the lakes and waters.

The spatial trend of fire risk in the YRDIDZ is given in Figure 4. As can be observed from the projection plane, the fire risk points at multiple locations overtop the overall situ-ation. On the whole, the risk trend is distributed in two lines: the east-west line and the north-south line, both of which are high at both ends and low in the middle. This fur-ther indicates that the four corners of the YRDIDZ is more prone to fires than the central area.

Table 2. Fire risk indicators and weights.

Indicator		Weight	CR
Population density		0.2179	0.0439
Road density		0.0824
Water source distance		0.1469
POI category	High-rise buildings	0.0746
	Underground buildings	0.0657
	Chemicals	0.1112
	Population-intensive places	0.219
	Vehicles	0.0401
	Specials	0.026
	Others	0.0162

Figure 3. Distribution of fire risk levels in the YRDIDZ.

Figure 4. Spatial trend of fire risk.

Point 3: It is recommended to map the Table 3 Coverage of fire stations in single administrative areas to better compare the differences in results.

Response 3:Thank you very much for your suggestion, I have mapped Table 3 to better compare the coverage of individual areas.

Point 4: It is suggested to compare the results of spatial layout optimization of fire stations with chart description.

Response 4:Thanks for your suggestion, the optimization results are further described according to your suggestion.

To improve the coverage of high-risk regions, considering the economic factor, the minimum number and location of fire stations were calculated based on the facility point-minimized model. On the basis of the calculation results,two deployment schemes were proposed: first, to re-plane the location of fire stations without regard to existing fire stations; second, to build more fire stations while retaining existing ones for fully covering high-risk regions.

The following calculation results are obtained: In Scheme 1, without regard to the status of fire stations, 35 stations (9 in Qingpu District, 20 in Wujiang District and 6 in Jiashan County) need to be built to fully cover high-risk regions within 3 min (Fig. 8(a)).  In Qingpu District, three fire stations are centralized in Yingpu Street on account of the concentrated high-risk regions there, and the rest are relatively uniformly distributed. In Wujiang District, many fire stations are arranged for the two high-risk regions, namely Wujiang Economic Development Zone and Oriental Silk Market. In Jiashan County, three fire stations are set in Huimin Street to ensure the fire safety there. In this case, the cov-er-age rate of medium- and low-risk regions within the specified response time is over 70%. In Scheme 2, if the existing fire stations are taken into account, 25 new stations (5 in Qingpu District, 14 in Wujiang District and 6 in Jiashan County) need to be built to fully cover high-risk regions within 3 min (Fig. 8(b)). Just like Scheme 1, the newly built fire sta-tions are mainly located in medium- and high-risk regions as well as the regions with weak firefighting forces. Compared with the spatial distribution of fire stations before op-timization, Scheme 2 covers 527 more regions and raises the coverage rate from 55% to 82%, covering most areas in the research area. In this case, the coverage rate of medium- and low-risk regions within the specified response time can also reach 80%. That is, the coverage of fire forces in most areas is satisfied.

Under comprehensive consideration of factors such as construction cost and cover-age in the two schemes, whether the present fire stations need to be redeployed are judged through simulation using the facility points-minimized model. According to the simula-tion results, Scheme 2 can significantly improve the coverage of the YRDIDZ and thus is recommended as the final optimization scheme. It is noteworthy that since cities are con-tinuously developing complex systems, their fire station distribution concerning fire risk also deserves continuous exploration

 

Point 5: Figure 4 to Figure 6 clarity needs further adjustment compared to Figure 3.

Response 5:Thanks for your suggestion, I further improved the resolution of Fig.4-Fig.6.

 

 

Point 6: It is suggested that the economic factors of spatial planning of fire stations should be studied in consideration of coverage.

Response 6:Thank you for your suggestion, we have taken into account the economic factors when using the minimization model. The principle is to calculate the minimum number of fire stations while ensuring a certain coverage rate. At the same time, when the scheme is finally determined, the number of new fire stations in the two schemes is compared, and a more economical scheme is selected.

 

Point 7: "Error! Reference source not found" is displayed in several places in the Introduction, so please adjust it.

Response 7:Thank you for your suggestion, I have adjusted the wrong place in the introduction

 

Point 8: The lines of the block diagram in Figure 2 have overlapping areas, and the text formatting and size are inconsistent. It is recommended that this be adjusted.

Response 8:Thank you for pointing out that I have redrawn Figure 2

 

Author Response File: Author Response.docx

Reviewer 2 Report

In this paper, the author took road density, population density, water source distance and POI as fire risk assessment indicators to obtain the fire risk level in the zone of green and integrated ecological development of the Yangtze River Delta, and then analyzed the current situation of fire stations in these areas and put forward improvement plans. However, the analysis of this paper is simple, subjective and little informative. Therefore, it needs a substantial revision before its publication.

Specific issues:

(1) There are some writing and formatting errors in this paper, such as the first sentence and the reference index in the introduction.

(2) In introduction, the logic of literature review is weak. The authors could give a more detailed research background and describe it logically.

(3) All figures are not clear enough in this paper. The map is deformed and the information in the three figures can be integrated into one figure in Fig. 1. What is more, the alignment of figures and tables in the text is inconsistent.

(4) In section 2.2, how did the authors divide the primary and secondary fire stations and what is the basis?

(5) In section 3, the natural break method cannot truly get which places have high fire risks and which places have low fire risks. Its result is relative. Can the author give a scientific division method?

(6) There are few fire risk assessment indicators. In addition to those listed by the author. The fire risk may also be related to slope, elevation, precipitation, etc. Please expand the indicators appropriately.

(7) In section 3.2.1, why did the author choose 3 min, 5 min and 8 min as the driving times and set 60 km/h as the driving speed?

(8) In section 4.1, please provide the criteria and basis for experts' scoring.

(9) In section 4.3, please consider both the actual cost of the expansion of the fire station and the fire risk to propose an improvement plan. In addition, the description is relatively simple. Please elaborate the analysis in section 4.3 clearly.

(10) In conclusion, it is not necessary to elaborate the research method in the conclusion, but to give the research results. In addition, please give more quantitative results.

Author Response

Response to Reviewer 2Comments

Point 1: There are some writing and formatting errors in this paper, such as the first sentence and the reference index in the introduction.

Response 1:Thank you for your reminder, we have changed the writing and format errors in the manuscript, please check.

 

Point 2: In introduction, the logic of literature review is weak. The authors could give a more detailed research background and describe it logically.

Response 2:Thanks for your suggestions, we have given more research background and description in the literature review section.

The healthy, sustainable and coordinated development of urban agglomerations has gradually become the leading force for sustainable economic and social development in China[1]. Two or more cities break through the constraints of administrative divisions, embracing the free flow and optimal allocation of development elements and resources between them. By doing so, an overall effect of complementary advantages and common prosperity is formed. However, the increasingly complex urban structure also brings new challenges to the layout of public emergency stations[2] such as fire stations and emer-gency centers[3]. The Yangtze River Delta region, as a pilot area for integrated develop-ment of super-large urban agglomerations[4], has unique advantages and actual needs in terms of industrial coordination[5], cross-regional policies[6], synergistic risk response[7], etc. It is meaningful to study the optimization technology of cross-regional synergistic de-ployment of fire stations in the region.

Scientific assessment of urban fire risk and construction of a reasonable mathemati-cal model are important factors in the deploymentof fire stations. According to factors such as urban development, building type and previous fires, Ferreira et al.[8] drew the fire-prone areas in the historical center of Jimaldes by using the GIS tool. Zhang[9] com-prehensively analyzed the urban fire risk in Haikou City from the aspects of fire risk, vul-nerability and fire prevention capacity. Wu et al.[10] evaluated the fire evolu-tion and consequences of subway stations and established a comprehensive model based on the Bayesian network and the Delphi method. Kiran et al.[11]  analyzed regional fire risk through small-area population prediction and found the firefighting force gap based on the coverage-maximized model. Shahrooz et al.[12] combined the location allocation model with the geographic information system (GIS) to re-plan the optimal location of fire stations, raising the coverage rate within a 5-minute response time from 81% to 95%. After evaluating the similarity of disaster types, the exposure of disaster environment and the probability of disaster consequences, Liu[13] proposed the model and procedure of urban fire disaster risk assessment to determine the disaster risk level. Ming et al.[14] proposed a mixed integer linear programming model by taking vehicle coverage and time coverage as indicators. Besides, they demonstrated the relationship among vehicle coverage ratio, time coverage ratio, number of fire stations, number of fire trucks, FPTVC and total budget through case analysis and multiple sensitivity analysis on historical data in Hefei City. Wang et al,[15] proposed an ArcGIS-based method to determine the spatial distribution of urban fire risk according to the various POIs, historical fire accident data and expert judgment. Against the backdrop of big data, geographic information data can effectively transmit information such as the name, longitude and latitude coordinates and street ad-dress information of geographic entities, and then deploy fire stations through the “loca-tion-allocation” model. Based on 443,400 pieces of POI data and relevant data like road network, Wang et al.[16] evaluated the spatial distribution of fire risk within the Fifth Ring Road in Beijing City using the SAVEE model and the expert scoring method. In addition, they obtained the final optimization results of fire stations in the research area on the basis of coverage-maximized, facility point-minimized and impedance-minimized model algo-rithms. Based on 34,035 POI data in a district of Wuhan City, Jiang et al.[17] divided the city into flammable and explosive areas, vulnerable population areas, densely populated areas, key protected areas and general risk areas, and evaluated the appropriate areas for deploying fire stations using the analytic hierarchy process. Considering that the surface light intensity information recorded by nighttime light images can reflect the basic char-acteristics of human social and economic activities, Wang et al.[18]  assessed the fire risk in Hefei City by combining the POI data and the NPP/VIIRS nighttime light image data. Meanwhile, the layout of fire stations is closely related to the specified fire response time. In the United States, it is stipulated that the layout of fire stations shall ensure that the driving time for occupational fire stations does not exceed 4 min[19] and the response times of volunteer fire stations vary according to different fire grades[20]. In the United Kingdom, the fire brigade area is divided into six categories, i.e., A, B, C, D, remote areas and special risk areas, according to a uniformly used risk grading method, and the re-sponse time is also determined according to the risk level. In China, the layout of fire sta-tions mainly is stipulated inStandard for Construction of Urban Fire Stations[21], as fol-lows:the location is determined according to the principle that fire trucks can reach the edge of the jurisdiction within 4 min. However, with the rapid construction and irregular expansion of cities, the layout of existing fire stationsis faced with indirect problems such as insufficient fire fighting forces in high-risk fire areas like densely populated old urban areas[22] and redundant fire fighting forces in low-risk areas like new urban areas with scattered buildings[23]. Scholars all over the world have proposed different response times concerning varying risk levels. With Istanbul as the research object, Başar et al.[24] proposed a risk-based dynamic multi-coverage fire station location planning model which divided the response time into four levels: 5 min, 8 min, 10 min and 15min. Such a model can scientifically and reasonably deployfirefighting forces. He et al.[25] proposed a method for evaluating the layout of urban fire stations which specified the response times of 3 min, 5 min, 8 min and 10 min in accordance with four assessed fire risk levels A, B, C and D, respectively. The evaluation results can be tested by three indicators, i.e., the re-sponse coverage rate, cross-response coverage rate and average response time of fire sta-tions. Existing researches are primarily focused on the coverage of fire station planning and site optimization in a single city, while the research on the layout of fire stations across administrative boundaries in urban agglomerations is rarely reported.

This study proposes a method that integrates multi-city geographic information and expert scoring evaluation to comprehensively deployfire stations. The method can effec-tively promote regional fire rescue coverage, shorten fire response time, reduce fire rescue costs, and decrease fire rescue losses. The research results are expected to provide a theo-retical basis for the optimization of urban fire station location in the Yangtze River Delta integrated demonstration zone (YRDIDZ).

 

 

Point 3: All figures are not clear enough in this paper. The map is deformed and the information in the three figures can be integrated into one figure in Fig. 1. What is more, the alignment of figures and tables in the text is inconsistent.

Response3: Thank you for pointing out that I have improved the resolution of all the pictures in the manuscript and modified the deformation of the map.

Point 4:  In section 2.2, how did the authors divide the primary and secondary fire stations and what is the basis?

Response 4: Thank you for your question, the classification of fire stations is mainly based on China 's current ' urban fire station construction standards ' and the attributes of the fire station itself。

 

Point 5:  In section 3, the natural break method cannot truly get which places have high fire risks and which places have low fire risks. Its result is relative. Can the author give a scientific division method?

Response 5: Thank you for your advice. Our consideration is that the fire resources in the area are limited. We hope to focus the firefighting forces on places with relatively high fire risks. Of course, your advice is also very scientific and effective. We will refer to your advice in subsequent research.

 

Point 6: There are few fire risk assessment indicators. In addition to those listed by the author. The fire risk may also be related to slope, elevation, precipitation, etc. Please expand the indicators appropriately.

Response 6: Thank you for your advice, we are based on population density, road density, who is long-distance and fire classification based on POI ( point of interest ) as the evaluation index to establish a set of urban fire risk assessment system, mainly according to the geographic information in the POI is divided into 7 categories, including high-rise buildings, underground construction, chemical industry, personnel intensive, transportation, special category, other categories. We will consider your recommendations in future studies, adding geographical, atmospheric and other factors.

 

Point 7: In section 3.2.1, why did the author choose 3 min, 5 min and 8 min as the driving times and set 60 km/h as the driving speed?

Response 7: Thank you very much for your proposal. 3 minutes, 5 minutes and 8 minutes are mainly combined with the previous research situation. We also give a description in the introduction part of the manuscript. At the same time, we have found a 4-minute response provision in China 's current " urban fire station construction standard. " According to its lack of consideration of fire risk level, we give the standard of hierarchical response in combination with the situation of the Yangtze River Delta integrated demonstration area. 60km / h is based on the provisions of Article 47 of the Fire Protection Law of the People 's Republic of China : in the process of performing tasks, firefighting vehicles are not limited by driving speed, driving route, driving direction and command signal. Other vehicles, ships and pedestrians should give way and set the speed as the safe speed of most vehicles in urban roads.

 

Point8:  In section 4.1, please provide the criteria and basis for experts' scoring.

Response 8: Thank you for your advice. When we invite experts to score, we mainly rely on the experience of experts and the actual situation of the Yangtze River Delta integration demonstration area to score. We are very sorry to provide you with specific standards.

 

 

Point 9: In section 4.3, please consider both the actual cost of the expansion of the fire station and the fire risk to propose an improvement plan. In addition, the description is relatively simple. Please elaborate the analysis in section 4.3 clearly.

Response 9: Thank you for your suggestion, we have taken into account the economic factors when using the minimization model. The principle is to calculate the minimum number of fire stations while ensuring a certain coverage rate. At the same time, when the scheme is finally determined, the number of new fire stations in the two schemes is compared, and a more economical scheme is selected. In addition, we further describe the fire station optimization based on your recommendations.

To improve the coverage of high-risk regions, considering the economic factor, the minimum number and location of fire stations were calculated based on the facility point-minimized model. On the basis of the calculation results,two deployment schemes were proposed: first, to re-plane the location of fire stations without regard to existing fire stations; second, to build more fire stations while retaining existing ones for fully covering high-risk regions.

The following calculation results are obtained: In Scheme 1, without regard to the status of fire stations, 35 stations (9 in Qingpu District, 20 in Wujiang District and 6 in Jiashan County) need to be built to fully cover high-risk regions within 3 min (Fig. 8(a)).  In Qingpu District, three fire stations are centralized in Yingpu Street on account of the concentrated high-risk regions there, and the rest are relatively uniformly distributed. In Wujiang District, many fire stations are arranged for the two high-risk regions, namely Wujiang Economic Development Zone and Oriental Silk Market. In Jiashan County, three fire stations are set in Huimin Street to ensure the fire safety there. In this case, the cov-er-age rate of medium- and low-risk regions within the specified response time is over 70%. In Scheme 2, if the existing fire stations are taken into account, 25 new stations (5 in Qingpu District, 14 in Wujiang District and 6 in Jiashan County) need to be built to fully cover high-risk regions within 3 min (Fig. 8(b)). Just like Scheme 1, the newly built fire sta-tions are mainly located in medium- and high-risk regions as well as the regions with weak firefighting forces. Compared with the spatial distribution of fire stations before op-timization, Scheme 2 covers 527 more regions and raises the coverage rate from 55% to 82%, covering most areas in the research area. In this case, the coverage rate of medium- and low-risk regions within the specified response time can also reach 80%. That is, the coverage of fire forces in most areas is satisfied.

Under comprehensive consideration of factors such as construction cost and cover-age in the two schemes, whether the present fire stations need to be redeployed are judged through simulation using the facility points-minimized model. According to the simula-tion results, Scheme 2 can significantly improve the coverage of the YRDIDZ and thus is recommended as the final optimization scheme. It is noteworthy that since cities are con-tinuously developing complex systems, their fire station distribution concerning fire risk also deserves continuous exploration

 

Point10: In conclusion, it is not necessary to elaborate the research method in the conclusion, but to give the research results. In addition, please give more quantitative results.

Response 10: Thank you for your suggestion, we have revised the conclusion section as follows.

In this paper, a set of urban fire risk assessment system was established by taking population density, road density, water source distance and fire-based POI classification indicators as the evaluation indicators. With the aid of this system, the urban fire risk was assessed by means of expert scoring and weighting. Furthermore, the evaluation criteria for the spatial layout of fire stations were proposed considering the actual situation of the YR-DIDZ. Aiming at fully covering high-risk regions, the location of fire stations was cal-cu-lated by introducing the location allocation model, and the optimization scheme was given under comprehensive consideration of factors such as construction cost and cover-age. The main conclusions are as follows:

(1) In the YRDIDZ, high-risk regions are mainly concentrated in Yingpu Street and Xujing Town of Qingpu District, Wujiang Economic Development Zone and Oriental Silk Market of Wujiang District and Huimin Street of Jiashan County; medium-risk regions mainly include the periphery of high-risk regions, the connecting zone of high-risk regions and some urban regions. The spatial trend of fire risk is distributed in two lines: the east-west line and the north-south line, both of which are high at both ends and low in the middle.

(2) The overall coverage rate of fire stations in Qingpu District is 75% (65% for high-risk regions), while those in Wujiang District and Jiashan County are both lower than 60%. A total of 31 more regions are covered when the YRDIDZ is taken as a whole for cross-regional deployment of fire stations.

(3) When 25 new fire stations are built in the YRDIDZ, the high-risk regions in the YRDIDZ can be fully covered within 3 min, and the coverage rate of medium- and low-risk regions can be raised to 80%. Besides, the overall coverage rate of the whole zone can be promoted from 55% to 82%.

 

Reviewer 3 Report

This study is aimed at investigating the optimization technology of cross-regional synergistic deployment of fire stations. To achieve this aim, with the Yangtze River Delta integrated demonstration zone taken as the research object, urban fire risk was assessed by means of range standardization, iterative equations and expert scoring and weighting on the basis of population density, road density, water source distribution and urban POI data as well as urban remote sensing images. 

This is a decent work which is acceptable for the journal based on some simple comments. The optimization method should be calibrated first through a comparison with other algorithms also. The limitation of the method can be presented, and insights can be added in the conclusion. 

Author Response

Point 1:This is a decent work which is acceptable for the journal based on some simple comments. The optimization method should be calibrated first through a comparison with other algorithms also. The limitation of the method can be presented, and insights can be added in the conclusion. 

Response 1: Thank you for your suggestion, we have revised the conclusion section as follows.

In this paper, a set of urban fire risk assessment system was established by taking population density, road density, water source distance and fire-based POI classification indicators as the evaluation indicators. With the aid of this system, the urban fire risk was assessed by means of expert scoring and weighting. Furthermore, the evaluation criteria for the spatial layout of fire stations were proposed considering the actual situation of the YR-DIDZ. Aiming at fully covering high-risk regions, the location of fire stations was cal-cu-lated by introducing the location allocation model, and the optimization scheme was given under comprehensive consideration of factors such as construction cost and cover-age. The main conclusions are as follows:

(1) In the YRDIDZ, high-risk regions are mainly concentrated in Yingpu Street and Xujing Town of Qingpu District, Wujiang Economic Development Zone and Oriental Silk Market of Wujiang District and Huimin Street of Jiashan County; medium-risk regions mainly include the periphery of high-risk regions, the connecting zone of high-risk regions and some urban regions. The spatial trend of fire risk is distributed in two lines: the east-west line and the north-south line, both of which are high at both ends and low in the middle.

(2) The overall coverage rate of fire stations in Qingpu District is 75% (65% for high-risk regions), while those in Wujiang District and Jiashan County are both lower than 60%. A total of 31 more regions are covered when the YRDIDZ is taken as a whole for cross-regional deployment of fire stations.

(3) When 25 new fire stations are built in the YRDIDZ, the high-risk regions in the YRDIDZ can be fully covered within 3 min, and the coverage rate of medium- and low-risk regions can be raised to 80%. Besides, the overall coverage rate of the whole zone can be promoted from 55% to 82%.

Round 2

Reviewer 1 Report

The authors should further revise the format and layout of the manuscript. In addition, I agree to accept this manuscript.

Author Response

Point 1:The authors should further revise the format and layout of the manuscript. In addition, I agree to accept this manuscript.

Response 1: Thank you very much for your suggestion. I have revised the format and layout of the manuscript, including some writing errors in the article, the clarity of the picture and so on.

Reviewer 2 Report

The revision did not substantially improve the level of the paper. Although the method is very interesting, the content of the paper is relatively simple and has no amount of information, and no meaningful analysis has been drawn.

Specific comments are as follows:

1.     There are still many writing and formatting errors in this paper. Please check the full paper carefully.

2.     In introduction, the logic of literature review is more weak.

3.     All figures are still not clear in this paper. The information in the three figures are not integrated into one figure in Fig. 1.

4.     Other modifications are also unqualified. In addition, this analysis is meaningless in section 4.3. The authors compared the initial state with and without fire stations and found that it is better to build fire stations on the premise of having fire stations, but the comparison results are obvious and meaningless.

Author Response

Point 1: There are still many writing and formatting errors in this paper. Please check the full paper carefully.

Response 1: Thank you very much for your suggestion. I have revised the format and layout of the manuscript, including some writing errors in the article, the clarity of the picture and so on.

Point 2: In introduction, the logic of literature review is more weak.

Response 2: Thank you for your suggestion. I have revised the literature review. The logic is mainly based on the trend of urban agglomeration integration construction. Urban fire planning is mainly studied from two aspects : urban fire risk assessment and location model. With the progress of urban geographic information, spatial data such as POI provide good help for fire risk assessment and fire planning. In addition, we found that different cities have different regulations on the response time of fire fighting, and finally put forward our research ideas.

Point 3: All figures are still not clear in this paper. The information in the three figures are not integrated into one figure in Fig. 1.

Response 3: Thank you very much for your suggestion. I have improved the clarity of the pictures in the paper. As for the problem of Figure 1, in order to show the situation of the study area more clearly, three figures are used to illustrate. The first figure is a map of China, the shadow part is the Yangtze River Delta region, the second figure is to further enlarge the Yangtze River Delta region, the shadow part is the location of the study area, that is, the Yangtze River Delta integration demonstration area, and the third figure is the image map of the study area. If placed in a picture, the specific location and related information will not be able to see clearly because the study area is too small.

Point 4: Other modifications are also unqualified. In addition, this analysis is meaningless in section 4.3. The authors compared the initial state with and without fire stations and found that it is better to build fire stations on the premise of having fire stations, but the comparison results are obvious and meaningless.

Response 4: We have further modified your previous recommendations, such as giving more quantitative data and improving picture clarity. Besides, thank you very much for your advice, we listened to your advice and re-planned the plan. First, considering the existing fire station to calculate the fire risk area full coverage of the required fire station. At this time, we found that some fire stations are too concentrated to cause problems such as long-term idle fire equipment, resulting in waste of resources. Therefore, we deleted some unnecessary fire stations and simulated 1-19 additional fire stations to calculate the coverage of high, medium and low risk areas. Finally, we found that when 17 fire stations were added, the coverage of high-risk areas exceeded 90 %, and the coverage of medium-low-risk areas also exceeded 70 %, which can well meet the fire risk prevention and control needs of the Yangtze River Delta integrated demonstration area.

Round 3

Reviewer 2 Report

It can be accepted.