The magnitude and distribution of organic carbon (OC) transport from the terrestrial surface to the oceans is not well understood on a global scale. This hinders our understanding of terrestrial and marine carbon cycles. In this study, we determined the characteristics of OC flux. Our results showed that approximately 420 Tg C/yr of OC are transported from the terrestrial surface to the oceans, including 220 Tg C/yr of particulate organic carbon (POC) and 200 Tg C/yr of dissolved organic carbon (DOC). Asia, with only 32.46

Vegetation-covered water bodies (VCW) are a vital component of wetlands, and their distribution information is crucial for studying the dynamic interactions between vegetation and water. However, due to vegetation obstruction, optical remote sensing has limitations in extracting such water bodies, as it typically identifies only open water areas effectively. In contrast, microwave remote sensing, with its vegetation-penetrating capability and specular reflection characteristics, provides a more comprehensive identification of wetland water bodies. Previous studies have shown that the additional water body areas (SW) identified by SAR but not by optical sensors are often accompanied by significant vegetation cover. However, a systematic assessment of SW’s potential in mapping VCW is still lacking. This study uses the Caohai Wetland in Guizhou, China, as an example, leveraging Sentinel-2A and RadarSat-2 imagery from adjacent periods and multiple water body extraction methods to extract SW and explore its performance in mapping VCW during the dry season. Results show that during the initial stage of vegetation senescence (7 January 2019), the use of SW achieved high accuracy in mapping VCW, with overall accuracy, kappa coefficient, and F1 score reaching 84.2%, 68.4%, and 85.3%, respectively. However, as vegetation senescence deepened (12 January 2020), these metrics dropped to 76.2%, 60.7%, and 87%, respectively, indicating a significant decline in accuracy. During the vegetation regrowth stage (7 April 2020), the overall accuracy, kappa coefficient, and F1 score were 71.1%, 57.2%, and 70.9%, respectively. As vegetation continued to grow (21 April 2019), these metrics improved to 79.4%, 67.2%, and 86.6%. In summary, SW extracted from high-resolution optical and SAR imagery can preliminarily map VCW during the dry season. Furthermore, its identification accuracy improves significantly with increasing vegetation density. This study provides a novel perspective for wetland water body monitoring and the study of vegetation-water interactions.

In order to clarify the response relationship between rocky desertification and land use under different lithology background in karst area. We obtained the land use distribution in 2005, 2010 and 2015 by using supervised classification, and then carried out superimposed analysis with the rocky desertification and lithology data in the same period. The result shows that woodland and shrubbery are mainly distributed on limestone interbedded with clastic rock, with an area of approximately 51.73 km2. Grasslands and arable land are mainly distributed on continuous limestone and limestone interbedded with clastic rock. Rocky desertification area in the limestone interbedded with clastic rock is the largest, and extremely severe rocky desertification (ESKRD) of 6.70 km2, due to the difference of lithologic types. Different levels of rocky desertification are correlated with different land use types and lithology types. The type of rocky desertification in forest land is mainly light rocky desertification (LKRD), contributing more than 40

Remote sensing image with high spatial and temporal resolution is very important for rational planning and scientific management of land resources. However, due to the influence of satellite resolution, revisit period, and cloud pollution, it is difficult to obtain high spatial and temporal resolution images. In order to effectively solve the “space–time contradiction” problem in remote sensing application, based on GF-2PMS (GF-2) and PlanetSope (PS) data, this paper compares and analyzes the applicability of FSDAF (flexible spatiotemporal data fusion), STDFA (the spatial temporal data fusion approach), and Fit_FC (regression model fitting, spatial filtering, and residual compensation) in different terrain conditions in karst area. The results show the following. (1) For the boundary area of water and land, the FSDAF model has the best fusion effect in land boundary recognition, and provides rich ground object information. The Fit_FC model is less effective, and the image is blurry. (2) For areas such as mountains, with large changes in vegetation coverage, the spatial resolution of the images fused by the three models is significantly improved. Among them, the STDFA model has the clearest and richest spatial structure information. The fused image of the Fit_FC model has the highest similarity with the verification image, which can better restore the coverage changes of crops and other vegetation, but the actual spatial resolution of the fused image is relatively poor, the image quality is fuzzy, and the land boundary area cannot be clearly identified. (3) For areas with dense buildings, such as cities, the fusion image of the FSDAF and STDFA models is clearer and the Fit_FC model can better reflect the changes in land use. In summary, compared with the Fit_FC model, the FSDAF model and the STDFA model have higher image prediction accuracy, especially in the recognition of building contours and other surface features, but they are not suitable for the dynamic monitoring of vegetation such as crops. At the same time, the image resolution of the Fit_FC model after fusion is slightly lower than that of the other two models. In particular, in the water–land boundary area, the fusion accuracy is poor, but the model of Fit_FC has unique advantages in vegetation dynamic monitoring. In this paper, three spatiotemporal fusion models are used to fuse GF-2 and PS images, which improves the recognition accuracy of surface objects and provides a new idea for fine classification of land use in karst areas.

Soil erosion is a major global soil degradation problem that threatens land, freshwater and oceans. Rainfall erosivity has led to an increasing in the global soil erosion rate, while vegetation restoration is a safeguard measure to reduce soil erosion. Therefore, probing the influence of precipitation and vegetation on the spatial distribution of soil erosion is important for understanding the mechanism of erosion. In order to assess the degree of global soil erosion, based on the RUSLE model, a global soil erosion data set from 2000 to 2015 (0.25 degrees x 0.25 degrees) was created, showing that soil erosion was increasing in 70.80% of the study area, where precipitation was the dominant factor. Different grades of erosion showed that the soil erosion area of mild and above mild erosion increased by 44.88 x 10(6) ha, an increase of 5.39%. Spatial erosion is mainly distributed in Asia and North America. The difference from North America is that the erosion in Asia showed a decreasing trend during the study period. Different climatic zones show that erosion mainly occurs in the temperate zone, accounting for 39.97% of the area. Precipitation and vegetation increasing signifi- cantly in 24.43% and 16.74% of the regions. However, the proportion of regions where precipitation and vegetation had a negative contribution to erosion was 29.12% and 53.81%. Above results will deepen our understanding of the mechanism of erosion.

Introduction Accurate assessment of the net ecosystem productivity (NEP) is very important for understanding the global carbon balance. However, it remains unknown whether climate change (CC) promoted or weakened the impact of human activities (HA) on the NEP from 1983 to 2018. Methods Here, we quantified the contribution of CC and HA to the global NEP under six different scenarios based on a boosted regression tree model and sensitivity analysis over the last 40 years. Results and discussion The results show that (1) a total of 69% of the areas showed an upward trend in the NEP, with HA and CC controlled 36.33 and 32.79% of the NEP growth, respectively. The contribution of HA (HA_con) far exceeded that of CC by 6.4 times. (2) The CO2 concentration had the largest positive contribution (37%) to NEP and the largest influence area (32.5%). It made the most significant contribution to the NEP trend in the range of 435–440 ppm. In more than 50% of the areas, the main loss factor was solar radiation (SR) in any control area of the climate factors. (3) Interestingly, CC enhanced the positive HA_con to the NEP in 44% of the world, and in 25% of the area, the effect was greater than 50%. Our results shed light on the optimal range of each climatic factor for enhancing the NEP and emphasize the important role of CC in enhancing the positive HA_con to the NEP found in previous studies.

It is crucial to determine the factors affecting the carbon use efficiency (CUE) and water use efficiency (WUE) of vegetation in ecosystems. However, the relationships between climate changes and CUE and WUE by karst vegetation in China are still unclear. The response of the CUE and WUE to regional climate change was studied by using trend analysis and partial derivative method. In addition, the distribution characteristics of the CUE and WUE of different land use types were analyzed. The following results were found. (1). From 2000 to 2018, the average of CUE in karst areas of China was 0.557, and the average value of WUE was 1.237g C kg -1 H2O. (2) The CUE of grassland was higher than that of forest land (0.051), whereas the WUE value of grassland was far lower than that of forest land (1.415 g C kg -1 H2O). (3) CUE was affected by precipitation (P), exhibiting an increasing trend (5.5 x 10-3 yr -1), and the most obvious increase occurred in the grassland (7.2 x 10-3 yr -1). Under the influence of solar radiation (SR), the WUE decreased (-1.5 x 10-3 g C kg -1 H2O yr -1), and the largest decrease occurred in the shrub land (-8.4 x 10-3 g C kg -1 H2O yr -1). (4) 90.31 % CUE increase depended on P and SR, while 78.32 % of the decrease in the WUE was due to P and SR. This study makes important contributions to clarifying the responses of the CUE and WUE of ecosystems to climate changes in karst areas, optimizing the management of regional water and soil resources, and promoting healthy development of the ecological environment.

Karst ecosystems are important to several billion people, so it is necessary to accurately diagnose and evaluate the health of these ecosystems for socioeconomic development; however, the existing evaluation methods have many limitations, so they cannot accurately evaluate the ecosystem health in karst areas. In particular, they ignore the influence and restriction of the soil formation rate on the ecosystem health. To this end, we established a new index to represent the actual health status of karst ecosystems. The soil formation rate was found to pose a threat to the health of 28 % of the world's karst ecosystems, covering an area of 594 km2. In addition, a dataset of global karst ecosystem health index values with a spatial resolution of about 8 km × 8 km from 2000 to 2014 was created, and the proportion of unhealthy areas was found to be as high as 75.91 %. This study highlights the contribution of the soil formation rate to karst ecosystem health and provides a new method and deeper scientific understanding for further accurate evaluation of karst ecosystem health, which can improve future ecosystem health research and social management.

Landslides are very complicated natural phenomena that create significant losses of life and assets throughout China. However, previous studies mainly focused on monitoring the development trend of known landslides in small areas, and few studies focused on the identification of new landslides. In addition, karst areas, where the vegetation is dense, the mountains are high, the slopes are steep, and the time incoherence is serious, have difficulty in tracking Differential Interferometric Synthetic Aperture Radar (DInSAR) landslides. Therefore, based on DInSAR technology, we use ALOS-2 PALSAR data to conduct continuous monitoring of existing hazards and identify new geological hazards in karst areas. The major results are as follows: 1) From June 11 to 6 August 2017, it was discovered that a hidden point of landslides occurred on the 420 m northwest mountain near the town of Zongling. It was determined that the landslide hidden point had been slipping for two consecutive years, with an average slip of 6.0 cm. From 4 September 2016 to 22 January 2017, undiscovered hidden points in the landslide account were found in Yinjiazhai. On 13 September 2016 and 22 November 2016, the discovered potential hazards in the landslide log book were the mountain hazards in southwestern Shiping village, and the deformation was 7.8 cm. 2) The DInSAR monitoring results from September to November 2016 showed that large deformations occurred in the landslide area of Shiping village. During a field visit, large cracks on the surface were found. The length of surface cracks in the southwest direction of Shiping village was 2.8 m. On 13 July 2017, Shiping collapsed as a result of the collapse of the mountainous area where the disaster occurred. The average slope of the landslide in the landslide area was approximately 65°, the height was 95 m, the length and width were 150 m and 25 m, respectively, and the thickness was 5 m. The method has shown great potential in precisely identifying some new geological hazards sites, as well as tracking and monitoring the potential hazards of geological disasters listed on the landslide account.

Net biome productivity (NBP), which takes into account abiotic respiration and metabolic processes such as fire, pests, and harvesting of agricultural and forestry products, may be more scientific than net ecosystem productivity (NEP) in measuring ecosystem carbon sink levels. As one of the largest countries in global carbon emissions, in China, however, the spatial pattern and evolution of its NBP are still unclear. To this end, we estimated the magnitude of NBP in 31 Chinese provinces (except Hong Kong, Macau, and Taiwan) from 2000 to 2018, and clarified its temporal and spatial evolution. The results show that: (1) the total amount of NBP in China was about 0.21 Pg C/yr1. Among them, Yunnan Province had the highest NBP (0.09 Pg C/yr1), accounting for about 43% of China’s total. (2) NBP increased from a rate of 0.19 Tg C/yr1 during the study period. (3) At present, NBP in China’s terrestrial ecosystems is mainly distributed in southwest and south China, while northwest and central China are weak carbon sinks or carbon sources. (4) The relative contribution rates of carbon emission fluxes due to emissions from anthropogenic disturbances (harvest of agricultural and forestry products) and natural disturbances (fires, pests, etc.) were 70% and 9.87%, respectively. This study emphasizes the importance of using NBP to re-estimate the net carbon sink of China’s terrestrial ecosystem, which is beneficial to providing data support for the realization of China’s carbon neutrality goal and global carbon cycle research.

Forests are an important part of the ecological environment, and changes in forests not only affect the ecological environment of the region but are also an important factor causing landslide disasters. In order to correctly evaluate the impact of forest cover on landslide susceptibility, in this paper, we build an evaluation model for the contribution of forests to the landslide susceptibility of different grades based on survey data for forest land change in Bijie City and landslide susceptibility data, and discuss the effects of forest land type, origin, age group, and dominant tree species on landslide susceptibility. We find that forests play a certain role in regulating landslide susceptibility: compared with woodland, the landslide protection ability of shrubland is stronger. Furthermore, natural forests have a greater inhibitory effect on landslides than artificial forests, and compared with young forest, mature forest and over-mature forest, middle-aged forest and near-mature forest have stronger landslide protection abilities. In addition, the dominant tree species in different regions have different impacts on landslides. Coniferous forests such as Chinese fir and Cryptomeria fortunei in Qixingguan and Dafang County have a low ability to prevent landslides. Moreover, the soft broad tree species found in Qianxi County, Zhijin County, Nayong County and Jinsha County are likely to cause landslides and deserve further research attention. Additionally, a greater focus should be placed on the landslide protection of walnut economic forests in Hezhang County and Weining County. Simultaneously, greater attention should be paid to the Cyclobalanopsis glauca tree species in Weining County because the area where this tree species is located is prone to landslides. Aiming at addressing the landslide susceptibility existing in different forests, we propose forest management strategies for the ecological prevention and control of landslides in Bijie City, which can be used as a reference for landslide susceptibility prevention and control.

Cropland area has long been used as a key indicator of food security. However, grain yield is not solely controlled by the area of the cropland. Therefore, we proposed a new indicator to assess food security. Results show that from 1992 to 2004, the global cropland area increased by 840 200 km 2 (99.4%), but the grain yield increased only by 310 million t (29.1%); and from 2004 to 2015, the cropland area decreased by 39 000 km 2 (4.64%), but the grain yield increased by 370 million t (70.84%). This result showed that grain yield was not linearly correlated with cropland area, and delimiting the threshold of cropland protection may not guarantee food security. Combined with further correlation analysis, we found that the increase in the global grain yield was more closely related to the harvested area ( R 2 = 0.94), which indicated that the harvested area is a more scientific and accurate indicator than cropland area in terms of guaranteeing food security. Therefore, if governments want to ensure the food security, they should choose a new and more accurate indicator: harvested area rather than cropland area.

Abstract The Carbonate rock weathering Carbon Sink (CCS) and Silicate rock weathering Carbon Sink (SCS) play a significant role in the carbon cycle and global climate change. However, the spatial‐temporal patterns and trends of the CCS and SCS from 1950 to 2099 have not been systematically quantified. Thus, Supported by long‐term hydrometeorological data under the RCP8.5, we use the accepted Suchet and Hartmann models to determine the following. First, we found except for the difference in their weathering rates, the SCS covers 37.2 million km2 more area than the CCS. The CCS Flux (CCSF) and SCS Flux (SCSF) are 5.36 and 1.22 t/km2/yr, respectively. Similarly, the Full CCS (FCCS, 0.3 Pg/yr) is more than the Full SCS (FSCS, 0.08 Pg/yr). Furthermore, the CCS (7.01 kg/km2) and SCS (3.95 kg/km2) are in a state of overall increase. In addition, the mid‐to‐high latitudes of the northern hemisphere are aggravated by warming (0.03°C) and humidity (0.65 mm), while the decrease in runoff in the mid‐latitudes of the southern hemisphere reduces karstification. Specifically, by 2099, the CCSF in the mid‐latitudes of the southern hemisphere will decrease by 5.72%. Instead, the CCSF in the northern hemisphere and lower latitudes of the southern hemisphere will exhibit a gentle upward slope. Particularly, the peak regions of the global FCCS (65.63 Tg/yr) and FSCS (33.01 Tg/yr) are the tropical zone. In conclusion, this study contributes a high‐resolution and long‐time series CS datasets for the CCS and SCS. We provide data and a theory for solving terrestrial carbon sink loss.

Climatic and non-climatic factors affect the chemical weathering of silicate rocks, which in turn affects the CO2 concentration in the atmosphere on a long-term scale. However, the coupling effects of these factors prevent us from clearly understanding of the global weathering carbon sink of silicate rocks. Here, using the improved first-order model with correlated factors and non-parametric methods, we produced spatiotemporal data sets (0.25 degrees x 0.25 degrees) of the global silicate weathering carbon-sink flux (SCSF alpha) under different scenarios (SSPs) in present (1950-2014) and future (2015-2100) periods based on the Global River Chemistry Database and CMIP6 data sets. Then, we analyzed and identified the key regions in space where climatic and non-climatic factors affect the SCSF alpha. We found that the total SCSF alpha was 155.80 +/- 90 Tg C yr(-1) in present period, which was expected to increase by 18.90 +/- 11 Tg C yr(-1) (12.13%) by the end of this century. Although the SCSF alpha in more than half of the world was showing an upward trend, about 43% of the regions were still showing a clear downward trend, especially under the SSP2-4.5 scenario. Among the main factors related to this, the relative contribution rate of runoff to the global SCSF alpha was close to 1/3 (32.11%), and the main control regions of runoff and precipitation factors in space accounted for about 49% of the area. There was a significant negative partial correlation between leaf area index and silicate weathering carbon sink flux due to the difference between the vegetation types. We have emphasized quantitative analysis the sensitivity of SCSF alpha to critical factors on a spatial grid scale, which is valuable for understanding the role of silicate chemical weathering in the global carbon cycle.

The transport of particulate organic carbon (POC) through rivers from land to sea affects the redistribution of global organic carbon. However, because of the limitation of the quantity and quality of monitoring data, the POC magnitude, scale and global distribution pattern of land-sea migration are still not well understood. Therefore, based on an updated GEMS-GLORI database and other reanalysis data, we use the soil erosion model (F-erosion), total suspended solids model (F-tss), and runoff model (F-runoff) to re-analyze and generate the POC flux of major rivers in the world dataset. The major results are as follows: the POC flux from global terrestrial biosphere rivers exports approximately 0.12-0.20 Pg C to oceans every year, including 0.20 Pg F-erosion, 0.17 Pg F-tss, and 0.12 Pg Frunoff. In contrast to earlier studies that the Pacific and Arctic Oceans are the main recipients of POC flux, we find that the Pacific and Atlantic received more POC flux and received 30.76%-62.51% and 26.77%-53.95%, respectively. This difference may be related to the combined effects of soil erosion, total suspended solids, and runoff. Asia exports more POC than other continents (60.50%-61.69%). The Amazon basin is the major contributor to the Atlantic POC, contributing 53.30%-58.68%. Furthermore, because of the intense human activities and the widespread distribution of many large watersheds in the highly eroded area, it was found that the POC flux has two key zones (25.75-41.5 degrees N and 4.50.N-13.50 degrees S) in the latitude zone. In summary, the above findings increase our understanding of the spatial redistribution of global organic carbon from land to sea.

Ecological projects have huge impacts on vegetation restoration (VR) in China. However, are all of the effects due to human activities (HA) without the contribution of climate change (CC)? It is unclear what role CC plays in VR. Here, we quantitatively evaluate the contributions of climate change and human activities (CC_con and HA_con) to the net primary productivity (NPP) by the method of partial derivative and six different scenarios. HA contributed 61.19% to the NPP trend and controlled 32.84% of the NPP growth in China. Among the climate factors, temperature made the largest contribution to the NPP (45.89%) and had the largest control area (36.36%). CC promoted the positive HA_con in 54% of China, and in 68.35% of the area, the enhancement effect reached more than 50%. Our results answer a longstanding question and emphasize the important role of CC in enhancing the positive HA_con to VR.

喀斯特地区石漠化对当地社会经济的可持续发展有严重的阻碍作用,因此,研究喀斯特石漠化时空特征及演变规律,对石漠化治理有着重要的意义.以西南八省为研究区,利用归一化差分植被指数(Normalized Difference Vegetation,NDVI)、净初级生产力(Net Primary Productivity,NPP)、地表反照率(Surface Albedo)和坡度(Slope)数据,借助ArcGIS等软件平台,分析石漠化在不同的坡度、土地利用和生态保护区内的变化.结果显示:(1)轻度和中度石漠化是西南主要的石漠化类型.从空间分布来看,石漠化发生分布面积最广的是贵州,其次为云南和广西.(2)从不同土地利用来看,2000-2015年间无石漠化面积最多,潜在石漠化次之.石漠化主要发生在耕地和林地两种土地类型上,其他用地上石漠化发生面积最少,但是极重度石漠化在其他用地上的发生比例很大,平均在11％左右.(3)从不同坡度来看,石漠化严重程度不随坡度的增加而加剧,在坡度6°-25°之间石漠化发生面积最大.(4)从生态保护区来看,2000 和2015 年西南喀斯特生态保护区是石漠化面积分布最多的区域,分别为27481.86 km2 和21738.65 km2.最少的是大别山山地生态功能保护区,从变化量来看,增加最多的是三峡库区,增加1641.22 km2,减少最多的是西南喀斯特生态功能保护区,减少5743.22 km2.(5)利用NPP、NDVI、地表反照率和坡度能较精准的反演石漠化,其反演权重依次为0.33、0.42、0.15 和0.1.研究时段内,西南生态环境逐渐得到改善.

Eco-hydrological processes affect the chemical weathering carbon sink (CS) of rocks. However, due to data quality limitations, the magnitude of the CS of rocks and their responses to eco-hydrological processes are not accurately understood. Therefore, based on Global Erosion Model for CO2 fluxes (GEM-CO2 model), hydrological site data, and multi-source remote sensing data, we produced a 0.05° × 0.05° resolution dataset of CS for 11 types of rocks from 2001 to 2018. The results show that the total amount of CS of global rocks is 0.32 ± 0.02 Pg C, with an average flux of 2.7 t C km-2 yr-1, accounting for 53% and 3% of the "missing" carbon sink and fossil fuel emissions, respectively. This is 23% higher than previous research results, which may be due to the increased resolution. Although about 60% of the CS of global rocks are in a stable state, there are obvious differences among rocks. For example, the CS of carbonate rocks exhibited a significant increase (0.30 Tg C/yr), while the CS of siliceous clastic sedimentary rocks exhibited a significant decrease (-0.06 Tg C/yr). Although temperature is an important factor affecting the CS, the proportion of soil moisture in arid and temperate climate zones is higher (accounting for 24%), which is 3.6 times that of temperature. Simulations based on representative concentration pathways scenarios indicate that the global CS of rocks may increase by about 28% from 2050 to 2100. In short, we produced a set of high-resolution datasets for the CS of global rocks, which makes up for the lack of datasets in previous studies and improves our understanding of the magnitude and spatial pattern of the CS and its responses to eco-hydrological processes.

As a carbon source/sink of atmospheric carbon dioxide, the net regional carbon budget (NRCB) of terrestrial ecosystems is very important to effect global warming, especially China with the largest emissions at present. However, the carbon consumption is difficult to measure accurately, which is caused by the emissions of CH4 and CO, the utilization of agriculture, forestry and grass, and the emissions from rivers and other physical processes, such as forest fires. Therefore, the spatial patterns and driving factors of NRCB are not clear. Here, we used multi-source data to estimate the NRCB of 31 provincial administrative divisions of China and to develop NRCB datasets from 2000 to 2018. We found that the average of NRCB was 669 TgC yr−1, and it significantly decreased at a rate of 2.56 TgC yr−1. The relative contribution rates of fluxes of emissions from anthropogenic (FEAD), reactive carbon and creature ingestion (FERCCI), autotrophic respiration (Ra), heterotrophic respiration (Rh) and natural disturbances (FEND) were 35.17%, 26.09%, 19.68%, 17.38% and 1.68% respectively. In addition, NRCB datasets of the different administrative regions of China were mapped. These datasets will provide support for China's carbon neutrality and the study of the global carbon cycle.

传统村落是中国传统文化遗产的重要载体之一,探索传统村落集聚地的土地利用变化特征,对促进传统村落及其集聚地保护与发展有重要意义.以贵州省传统村落集聚地雷山县西江镇为研究区,基于2000～2017年4期遥感影像数据,采用土地利用强度指数、土地利用程度变化模型与地理探测器,研究典型传统村落集聚地的土地利用时空动态演变特征与驱动因素.结果 表明:(1)研究区2000～2017年高强度土地利用呈现倍增,由2000年的22.59％增加到2017年的47.63％;空间上,土地利用强度变化呈现出"村寨中心指向性"和"道路指向性"的演变模式;(2)旅游开发背景下山区少数民族传统村落土地利用发生了转型,由传统农业型向生活生产结合的多功能旅游型村落转变;(3)传统村落集聚地土地利用变化是多因子共同作用的结果,土地利用发展趋势变化主要受高程、到公路距离、到公共服务地距离、到村中心距离等自然环境与社会经济因素共同约束;(4)西江镇传统村落对研究区土地利用变化的决定力在逐渐增强,决定力由2000～2005年的0.0004增加到2010～2017年的0.0239,在各驱动因子决定力排序中由第8位上升至第5位.