Evaluation of Climate Comfort for Red Tourism in the Shaanxi-Gansu-Ningxia Region Based on GIS

JIN Shuang, REN Jiahui, FENG Fang, HUANG Qiaohua, HE Ping
(School of Geography, Geomatics and Planning, Jiangsu Normal University, Xuzhou 221116, Jiangsu, China)

Abstract

Assessing climate comfort in the Shaanxi-Gansu-Ningxia region is essential for the development of red tourism resources and the promotion of ecological civilization. Using daily meteorological data from 1953 to 2020, including average temperature, wind speed, and relative humidity, this study applies a comprehensive climate comfort evaluation model integrated with GIS-based spatial interpolation and zoning methods to systematically analyze the spatiotemporal distribution characteristics of climate comfort. The results show that, temporally, the climate is generally comfortable from May to September, while discomfort prevails from December to February. Spatially, northern Shaanxi exhibits relatively favorable climatic conditions, whereas the southwestern Xihaigu region is less comfortable. Against the backdrop of global warming, the annual average number of comfortable days shows an increasing trend, while the annual average number of uncomfortable days has significantly decreased since 2000. Comprehensive zoning indicates that southwestern and central high-altitude areas experience lower comfort levels, while other regions remain relatively favorable. Further analysis reveals that for each unit change in the climate comfort index, the red tourism visitor flow index changes by 0.593%. Yan'an, due to its rich red tourism resources and suitable climate, has an attractiveness index far exceeding other regions. Future red tourism planning should be dynamically optimized to address climate change and evolving tourist demands. This study provides a scientific reference for regional tourism development and the sustainable advancement of red tourism activities.

Keywords: climate comfort degree; red tourism; Shaanxi-Gansu-Ningxia Region; comprehensive zoning; gravity model

Introduction

Climate conditions are closely related to human comfort. Climate comfort degree is a biometeorological index that evaluates human comfort levels under different climatic conditions based on meteorological elements such as temperature, humidity, and wind speed. In recent years, climate comfort evaluation has received increasing attention due to global warming and has become an important reference for assessing regional suitability for residence or tourism. Numerous studies have evaluated climate comfort at national, provincial, and typical tourist site scales, providing scientific evidence for residential settlement, travel, and tourism decision-making. Red tourism, as an important component of the tourism economy, represents both a significant political and cultural initiative and an economic project of great importance for promoting red culture and inheriting revolutionary heritage.

The Shaanxi-Gansu-Ningxia region, located in the loess hilly-gully area of the central Loess Plateau, faces severe soil erosion problems, with an arid and unstable climate and extremely fragile ecological conditions. As a typical ecologically vulnerable area in northwest China, it is sensitive to climate change, and global warming will alter regional climate comfort, thereby affecting tourism activities. The region's pillar industry is agriculture, but its development is constrained by natural conditions. However, the area is rich in red tourism resources. According to statistics, the Shaanxi-Gansu-Ningxia region has numerous red tourism resources with a rapidly growing number of visitors. Taking Yan'an City as an example, tourist numbers increased from 1024.3×10⁴ in 2000 to 7308.3×10⁴ in 2019, while comprehensive tourism revenue rose from 53.88×10⁸ yuan to 495.31×10⁸ yuan, with its proportion of tertiary industry value-added increasing from 34.3% to 96.2%. Tourism has become a significant driver of local economic development, with 83.4% of tourists concentrated at red tourism sites, demonstrating that red tourism has become an important pathway for economic and social development in the region.

Currently, research on red tourism in the Shaanxi-Gansu-Ningxia region has primarily focused on the spatial distribution characteristics of tourism resources, tourism route optimization, and resource integration. Climate comfort, as a crucial environmental factor affecting tourists' outdoor activities, is particularly critical in this region. However, systematic research on tourism climate comfort in this area remains in its infancy. Therefore, this study selects the Shaanxi-Gansu-Ningxia region as the research area, utilizes long-term meteorological data from 1953 to 2020, and employs a comprehensive climate comfort evaluation model to conduct a refined assessment of regional climate comfort. Building upon this, regression models are constructed to quantitatively analyze the impact of climate comfort on red tourism visitor numbers, while a gravity model is introduced to rank the attractiveness of different areas based on climate comfort and to propose optimization paths and strategies for future red tourism development. This research aims to provide a scientific theoretical basis for sustainable socio-economic development in the region and to effectively support the advancement of red tourism in the Shaanxi-Gansu-Ningxia area.

1.1 Study Area Overview

The Shaanxi-Gansu-Ningxia region is located at the junction of Shaanxi, Gansu, and Ningxia provinces, covering a total area of 13.8×10⁴ km² with a population of approximately 1004×10⁴. The study area encompasses 25 counties in Yan'an and Yulin cities of Shaanxi Province, 7 counties in Qingyang City of Gansu Province, and 8 counties in southern Ningxia Hui Autonomous Region [FIGURE:1]. Situated in the loess hilly-gully region of the central Loess Plateau, this area represents a core zone for ecological protection and management in the middle and upper reaches of the Yellow River, as well as one of the most severely affected regions by soil erosion worldwide. The regional climate is arid and unstable, located in a transitional zone from East Asian monsoon climate to typical continental climate, belonging to arid and semi-arid climate zones. The ecological environment is extremely fragile, with forest coverage of only about 17%. Precipitation is concentrated in summer and autumn, with significant interannual variability, primarily in the form of strong convective rainstorms with high intensity and short duration, which easily induce soil erosion and flood disasters.

Currently, the Shaanxi-Gansu-Ningxia region is relatively economically underdeveloped, constrained by both natural and historical factors, with 21 counties designated as national poverty counties. The "Shaanxi-Gansu-Ningxia Red Tourism Area" is one of China's 12 key red tourism regions. As an important strategic rear area during the Chinese People's War of Resistance Against Japanese Aggression and the Liberation War, the region preserves a large number of diverse red tourism resources and possesses a glorious revolutionary tradition with abundant revolutionary heritage sites. Red tourism has become an important tourism brand in the Shaanxi-Gansu-Ningxia region. For example, the famous national-level red tourism route in Shaanxi Province includes Luochuan (Luochuan Conference Memorial Hall) → Yan'an (Pagoda Hill and other sites) → Zichang (Wafangbu Conference Site). In recent years, the state has attached great importance to the development of red cultural tourism, introducing multiple supportive policies. The Shaanxi-Gansu-Ningxia region, represented by Yan'an City in Shaanxi, Hua Chi County in Gansu, and Yuanzhou District in Ningxia, is rich in red tourism resources with enormous development potential. Driven by policy guidance and resource integration, red tourism has developed rapidly, injecting momentum into local poverty alleviation and bringing new opportunities for ecological civilization construction.

1.2 Data Sources

Meteorological data were downloaded from the China Meteorological Data Network (http://data.cma.cn), including daily average temperature, daily average wind speed, and daily average relative humidity from 1953 to 2020. During meteorological station selection, the principle of broad regional coverage and relatively uniform spatial distribution was followed, with priority given to stations with relatively complete meteorological records [FIGURE:1]. DEM data were obtained from SRTM data jointly measured by NASA and NIMA, with a resolution of 90 m×90 m. Tourism data were sourced from the "Domestic Tourism Situation" data in the Yan'an Statistical Yearbook (2000-2019) available on the official website of the Yan'an Municipal Bureau of Statistics.

1.3 Methods

1.3.1 Construction of Climate Comfort Index

Considering China's large latitudinal and longitudinal span resulting in diverse climate types and significant topographic variations, comfortable periods inevitably differ across regions. Taking into account the climatic characteristics, cultural customs of the Shaanxi-Gansu-Ningxia region, and referencing environmental hygiene indicators, the most comfortable microclimate conditions for humans were established as: average temperature 24.0°C, average wind speed 2 m·s⁻¹, and relative humidity 70%. Based on these, a comprehensive climate comfort index model was constructed:

$$
CCI = 0.68 \times |T - 24.0| + 0.5 \times |Hu - 70| + 0.07 \times |V - 2.0|
$$

where CCI is the climate comfort index; T is temperature (°C); V is wind speed (m·s⁻¹); and Hu is relative humidity (%).

Based on the probability distribution of climate comfort in the Shaanxi-Gansu-Ningxia region and referencing the World Meteorological Organization's recommended percentile method for extreme climate event calculation, the CCI values were sorted from smallest to largest, with the 5th, 25th, 75th, and 95th percentiles used as thresholds to divide climate comfort into five levels [TABLE:1].

1.3.2 Climate Comfort Zoning and Evaluation

Elevation significantly influences meteorological conditions. In the comprehensive climate comfort zoning process, GIS spatial analysis technology was employed to integrate temperature, relative humidity, wind speed with DEM data, achieving gridded comfort zoning for more precise evaluation.

(1) Temperature Gridding: Since the 25 meteorological stations are discretely distributed, station temperature data were first interpolated horizontally. Considering that temperature decreases with altitude (0.65°C per 100 m increase), DEM data were used for vertical correction of the interpolation results. Through horizontal interpolation and vertical correction, the spatial distribution of average temperature in the study area was obtained.

(2) Relative Humidity Gridding: As air relative humidity is closely related to temperature and elevation, the relative humidity at a certain elevation during interpolation is calculated as:

$$
RH_z = RH_0 \times 10^{\left(\frac{7.5 \times T_0}{237.3 + T_0} - \frac{7.5 \times T_z}{237.3 + T_z}\right)}
$$

where RH_z is air relative humidity at elevation z (%), RH_0 is surface observed relative humidity (%), T_0 is surface temperature (°C), T_z is temperature at elevation z (°C), and β_z is a constant (0.014). The spatial distribution layer of relative humidity in the Shaanxi-Gansu-Ningxia region can be obtained through horizontal interpolation and vertical fitting using the above formula.

(3) Wind Speed Gridding: As terrain effects on wind speed are complex, elevation factors were not considered in the spatial distribution analysis of wind speed. GIS technology was directly used to interpolate wind speed data and generate the spatial distribution layer of average wind speed in the study area.

2.1 Spatiotemporal Distribution Characteristics of Climate Comfort

Based on daily meteorological data from 1953 to 2020 and the constructed comprehensive comfort model, the multi-year average monthly comfort index for the Shaanxi-Gansu-Ningxia region was calculated [FIGURE:2]. The results show that the comfort index values from May to September are relatively small, ranging from 3.60 to 7.95, indicating that this period has a relatively comfortable climate suitable for tourism activities. Among them, September has the lowest comfort index at only 3.60, making it the most suitable month for tourism climate conditions throughout the year. The comfort index values from March to April and October to November are 6.92 to 17.52, all within the "normal" range [TABLE:1]. Winter months (December to February) have comfort index values of 20.68 to 23.05, indicating "relatively uncomfortable" conditions. December reaches 23.05, the only month exceeding the "least comfortable" grade threshold, representing the most unfavorable period for tourism climate conditions. Overall, the Shaanxi-Gansu-Ningxia region has comfortable climate suitable for tourism from May to September, while winter months (December to February) have poor comfort and are unsuitable for tourism.

The spatial distribution of annual average comfortable days, normal days, and uncomfortable days from 1953 to 2020 was analyzed [FIGURE:3]. The results indicate that northern Shaanxi has the most annual comfortable days, with most areas exceeding 122 days, including 133 days in Luochuan County and 124 days in Hengshan District. Generally, as the terrain rises from east to west, the continentality of the climate increases and aridity intensifies, resulting in a gradual decrease in annual comfortable days. The Xihaigu region in southern Ningxia (such as Xiji, Haiyuan, and Guyuan) has significantly fewer comfortable days, only 76-87 days, with Xiji County having the fewest at about 76 days, and Haiyuan County and Guyuan City at about 87 days each. Annual normal days are higher in the southern region (157-166 days), while areas in northern Shaanxi such as Hengshan District and Suide County have relatively fewer normal days (about 127-128 days). The spatial distribution of annual uncomfortable days shows the opposite pattern, with the Xihaigu region having the most uncomfortable days (about 120 days), while northern Shaanxi areas such as Luochuan County have fewer (about 90-100 days). In summary, northern Shaanxi has relatively comfortable climate suitable for tourism activities, while the southwestern Xihaigu region, with its rising terrain from east to west and increasingly dry and cold climate, has significantly lower comfort and the most annual uncomfortable days, making it the region with the poorest tourism climate conditions.

2.2 Interannual Variation of Climate Comfort Index

The interannual variation of climate comfort index reflects the long-term evolution of regional climate comfort conditions. The spatial distribution of linear tendency rates for annual comfortable days, normal days, and uncomfortable days from 1953 to 2020 was analyzed [FIGURE:4]. All areas show positive linear tendency rates for annual comfortable days, indicating an overall increasing trend. The most significant increases occur in Jingbian County and Xifeng District, with rates of 5.07-5.89 days per decade, while the smallest increases (2.21-2.97 days per decade) occur in Suide County and Hengshan District of northern Shaanxi; other areas range between 3.86-5.66 days per decade. The linear tendency rates for annual normal days are very small, with some areas such as Huan County, Wuqi County, and Xiji County showing slight decreasing trends (-0.66 to -0.34 days per decade). Annual uncomfortable days show decreasing trends across all areas, with Xihaigu region decreasing by 1.10-2.78 days per decade and other areas decreasing by 3.58-4.66 days per decade.

The M-K test was applied to detect abrupt changes in annual comfortable days, normal days, and uncomfortable days in the Shaanxi-Gansu-Ningxia region [FIGURE:5]. Before the 1990s, the UF statistic curve for annual comfortable days showed minor fluctuations and remained below the 0 axis, indicating insignificant changes. After the 1990s, the UF curve gradually rose above 0, and around 2000, it exceeded the 1.96 confidence limit, showing a significant increasing trend. The UF and UB curves intersected within the ±1.96 confidence interval around 2000, indicating a significant mutation in comfortable days. Since 2000, the UF curve has remained above the confidence limit, showing a continuous upward trend. The UF curve for annual normal days remained within the ±1.96 confidence interval for most of the period and intersected with the UB curve multiple times, indicating no significant change or obvious mutation. The UF curve for annual uncomfortable days has been declining since the 1990s and remained below the 0 axis after 2000, indicating a decreasing trend. The UF and UB curves intersected within the confidence interval around 2005, suggesting a mutation in annual uncomfortable days after approximately 2000. Overall, since the 21st century, the number of uncomfortable days in the Shaanxi-Gansu-Ningxia region has shown a significant decreasing trend, indicating improved climate comfort.

2.3 Comprehensive Climate Comfort Zoning

Located in the marginal transition zone of temperate monsoon climate with loess plateau hills and gullies as the main topography, the Shaanxi-Gansu-Ningxia region's climate comfort is primarily distributed across three grades: "relatively comfortable," "normal," and "relatively uncomfortable" [FIGURE:6]. No areas exhibit extreme grades of "most comfortable" or "most uncomfortable." The southwestern and central parts of the region have higher elevations, with lower average temperatures in all seasons, particularly in winter. For example, the average winter temperature in Xiji County is only -12.8°C, far below the optimal human temperature of 24°C. Additionally, the region has dry climate, with Xiji County's average relative humidity in all seasons at only about 45%, below the human comfort humidity level (70%). The average wind speed in all seasons is generally greater than 2 m·s⁻¹. Under the combined effects of these factors, the climate comfort grade in this area is mainly "relatively uncomfortable."

The "relatively comfortable" climate zones are mainly distributed in eastern Shaanxi (northern Shaanxi), Xifeng area of Gansu's Qingyang City, and some low-altitude areas in southern Ningxia (such as Tongxin County). Due to the overall terrain being higher in the west and lower in the east, the eastern regions have lower elevations with temperature, humidity, and wind speed conditions closer to human optimal ranges, thus dominated by the "relatively comfortable" grade. The central part of Shaanxi-Gansu-Ningxia mostly belongs to climate "normal zones," where meteorological elements are at intermediate levels with balanced temperature, humidity, and wind conditions, showing no significant dry or wet characteristics.

3.1 Spatiotemporal Characteristics of Climate Comfort and Their Impact on Tourism Development in the Shaanxi-Gansu-Ningxia Region

Climate comfort is an important factor affecting tourism development and tourists' willingness to engage in outdoor activities. Analysis of climate comfort evaluation results for the Shaanxi-Gansu-Ningxia region over the past 68 years reveals that, on an intra-annual timescale, the region's climate comfort index is lower from May to September, with generally comfortable climate representing the optimal season for tourism activities, while the index is higher from December to February, with generally uncomfortable conditions unsuitable for outdoor tourism. Spatially, northern Shaanxi has the most annual comfortable days, while the Xihaigu region has the fewest, showing an overall decreasing pattern from east to west. Therefore, tourism activities should be scheduled during locally suitable periods, avoiding unfavorable seasons such as winter. From an interannual variation perspective, the number of comfortable days has generally increased over the past 68 years, while uncomfortable days have gradually decreased, particularly since 2000 when comfortable days increased significantly, indicating that regional climate conditions are becoming more favorable for tourism activities. Against the background of climate warming, the increase in comfortable weather days helps extend the suitable period for tourism activities, thereby positively impacting the sustainable development of the tourism industry. Comprehensive climate zoning results show that the Shaanxi-Gansu-Ningxia region does not have extremely unfavorable climate conditions for tourism, and most areas possess a good foundation of climate comfort, providing a favorable climatic background for regional red tourism development.

3.2 Analysis of the Relationship Model Between Tourist Flow Index and Climate Comfort

To quantitatively analyze the impact of climate comfort on red tourism in the Shaanxi-Gansu-Ningxia region, Yan'an City, which has the most red tourism resources, was selected as a representative case. Yan'an has 35 red tourism resources, accounting for 51.2% of the total in the Shaanxi-Gansu-Ningxia region. According to Yan'an Statistical Yearbook data, tourist numbers reached 7308×10⁴ in 2019. Climate comfort significantly impacts tourism in Yan'an, with visitor numbers surging to the annual peak of 1025×10⁴ in October due to the National Day holiday, accounting for 14.0% of the annual total. Analysis of visitor data by attraction type shows that red tourism sites account for 83.4% of total visitors, indicating that red tourism has become the main component of Yan'an's tourism industry.

A least squares regression analysis was conducted on monthly red tourism visitor numbers and climate comfort index in Yan'an from 2000 to 2019 (with the October National Day holiday treated as a dummy variable). The resulting regression model is:

$$
Q = -0.593CCI + 0.065T + 0.128
$$

where Q represents visitor flow; CCI is the climate comfort index; and T is the National Day holiday dummy factor (1 for October, 0 for other months). The model's correlation coefficient r is 0.87, indicating a significant correlation between climate comfort index and visitor numbers. According to the regression coefficient, when the climate comfort index increases by 1 unit (i.e., human comfort decreases), the red tourism visitor flow index decreases by approximately 0.593%. This quantitatively demonstrates that climate comfort changes have a substantial impact on red tourism visitor flow, with good climate comfort conditions attracting more tourists, while uncomfortable conditions such as severe cold significantly inhibit tourist travel.

3.3 Regional Ranking of Climate Comfort Attractiveness Based on Gravity Model and Future Development Optimization Paths

Spatial differences in climate comfort create varying potential attractiveness to tourists across different locations within the Shaanxi-Gansu-Ningxia region. Using the tourism gravity model principle, "attractiveness" can be regarded as a comprehensive function of red tourism resource abundance and climate comfort, enabling regional ranking and optimization. The tourism gravity model is generally expressed as:

$$
A_i = k \times \frac{R_i^\alpha \times C_i^\beta}{D_i^\gamma}
$$

where A_i represents the tourism attractiveness of location i; k is a constant coefficient determined through regression; R_i is the red tourism resource abundance of location i (number of attractions or total scenic area grade score); C_i is the annual average number of climate comfortable days at location i; D_i is the spatial distance or travel time from location i to the regional tourism center node (such as Yan'an City); and α, β, γ represent the weight coefficients of resource abundance, climate comfort, and spatial distance on tourist attraction, respectively (generally obtained through regression fitting of actual data).

According to the gravity model, considering the dual "quality" of tourism resource quantity and climate comfort, northern Shaanxi where Yan'an is located undoubtedly has stronger tourist attraction and becomes the preferred region for future red tourism development. In contrast, areas with poor climate conditions have limited potential to attract tourists even if they are rich in red resources. Eastern northern Shaanxi areas such as Suide have nearly 124 comfortable days annually, far exceeding the less than 87 days in Xihaigu. This comfort difference means tourists prefer to visit areas with pleasant climates. The regression analysis shows that for each unit increase in climate comfort index, visitor flow decreases by 0.593%, and seasonal climate changes significantly affect tourist travel choices and seasonal distribution of tourism flow, with comfortable climate periods corresponding to tourism peaks and harsh winter climate representing the off-season. Even in months with average climate conditions (such as April or November), major holidays can cause temporary surges in visitor numbers, but these peaks are non-normal phenomena. Overall, climate comfort provides a "ceiling" and "floor" for red tourism visitor flow.

Based on the gravity model, using Yan'an City as the standard node (assuming D = 1 for internal distances and standardized), parameters are set as follows: red tourism resource quantity (R_i) as the resource abundance indicator; annual average climate comfortable days (C_i) as the climate comfort indicator; and distance effects temporarily ignored (or uniformly treated as D_i = 1). The formula simplifies to:

$$
A_i = k \times R_i^\alpha \times C_i^\beta
$$

Based on existing research and actual measurements, assuming model parameters of α = 0.6 (climate comfortable days weight), β = 0.4 (resource quantity weight), and k = 0.01 (standardization constant), the calculations yield: AYan'an = 175 and AXiji = 5.3. This means that under otherwise equal conditions, Yan'an and similar nodes with comfortable climate and abundant resources have approximately 33 times the attractiveness of Xihaigu.

In view of this, red tourism route optimization should focus on two aspects. First, construct a cross-regional red tourism route network, opening tourism channels between Yan'an and revolutionary sites in neighboring Gansu and Ningxia. For example, starting from Yan'an, connecting Pagoda Hill, Nanniwan and other Yan'an sites, then extending northwest to link with the Nanliang Revolutionary Memorial Hall in Gansu (Qingyang area) and the Liupanshan Red Army Long March Memorial Hall in Ningxia, forming a Shaanxi-Gansu-Ningxia red tourism loop. Second, optimize route timing according to climate comfort periods. Northern Shaanxi has cool and pleasant summers suitable for outdoor site visits from May to September; early autumn can shift to southern Ningxia and eastern Gansu to tour high-altitude or arid areas before the weather turns cold. Through such optimization, a reasonably laid-out, seasonally complementary red tourism activity trajectory map can be formed, promoting the common development of red scenic spots throughout the region. Additionally, as regional climate improves under global warming, this gap shows a narrowing trend, with annual comfortable days increasing across the study area in recent decades, most significantly in Jingbian County (northern Shaanxi) and Xifeng District (Gansu's Qingyang) at 5.07-5.89 days per decade. This indicates that future climate comfort patterns are not static, requiring dynamic adjustment of attractiveness assessments and rankings to reflect the latest climate and tourism supply-demand conditions.

4 Conclusion

This study utilizes daily meteorological data from 1953 to 2020 and DEM data for the Shaanxi-Gansu-Ningxia region, classifies climate comfort index levels according to a comprehensive evaluation model, analyzes its variation patterns and spatiotemporal distribution characteristics, and conducts comprehensive climate comfort zoning through weighted overlay of seasonal layers. Additionally, regression and gravity models were established to explore the impact of climate comfort on red tourism visitor flow. The main conclusions are:

(1) Spatiotemporal Distribution: The multi-year average climate comfort index in the Shaanxi-Gansu-Ningxia region shows smaller monthly values from May to September, with generally comfortable climate suitable for tourism; March-April and October-November have relatively normal climate; December-February has unsuitable climate for tourism. Northern Shaanxi has the most comfortable days, while Xihaigu has the fewest, showing an overall decreasing pattern from east to west.

(2) Trend Analysis: Linear trend analysis indicates that annual comfortable days are increasing across all areas, with the most significant increases in Jingbian County and Xifeng District (5.07-5.89 days per decade). The linear growth rate of annual normal days is very small, with some areas showing decreasing trends. Annual uncomfortable days show decreasing trends everywhere. Mutation tests reveal that since the 1990s, annual average comfortable days have shown an upward trend with a significant mutation occurring around 2000. Annual normal days show a non-significant upward trend after 2000, while annual uncomfortable days show a significant downward trend after 2000.

(3) Comprehensive Zoning: Climate comfort zoning shows that the Shaanxi-Gansu-Ningxia region's overall comfort grades are primarily "relatively comfortable," "normal," and "relatively uncomfortable," with southwestern and central areas being less comfortable and other areas being relatively comfortable or normal.

(4) Tourism Impact: Regression analysis shows that for each unit change in climate comfort index, the visitor flow index changes by 0.593%, indicating that climate comfort changes have a substantial impact on red tourism visitor flow. Based on the tourism gravity model, Yan'an ranks highest in attractiveness due to its rich resources and suitable climate, far exceeding other regions. To optimize red tourism development, cross-regional tourism routes should be constructed, connecting Yan'an with Gansu's Nanliang and Ningxia's Liupanshan red tourism sites, and adjusting route timing according to climate characteristics. As regional climate comfort shows an upward trend, future red tourism planning needs dynamic optimization to adapt to climate change and tourist demands, promoting sustainable regional tourism development.

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