Land Use Trends Research Articles

Analysis and Research on Farmland Use Changes in Changchun City Based on ArcGis Remote Sensing Images

Abstract Land is an essential basis for the sustained existence and development of human beings, arable land resources are the fundamental guarantee of food replenishment, contemporary scholars also put forward high requirements for the study of remote sensing image feature type classification extraction, the study of remote sensing image feature type classification and algorithms are very necessary. Therefore, based on remote sensing image data, this paper combines supervised classification with unsupervised classification, selects the advantages of the algorithm and improves it, refers to the classification system to select the classification standard, improves the support vector machine algorithm and compares it with other classification algorithms to improve the classification accuracy. Firstly, unsupervised classification is used to extract forest land, cultivated land and grassland into one category, and then secondary extraction is used to classify and subdivide them with SVM classification in supervised classification. Through conducting experiments on image data over a period of three years, the information of cultivated land is extracted from the remotely sensed image data of Changchun City in the years 2000, 2010, and 2020. By observing the change trend of land use, it is found that the cultivated land in Changchun City demonstrates a decreasing tendency from 2000 to 2020. Finally, it is concluded that Changchun’s cultivated land shows a decreasing trend from 2000 to 2020. Finally, this paper takes ten years as a gradient and obtains remote sensing image data in three time periods to analyze the change of cropland utilization. The results show that the method is effective in practical application and can save human and material resources to analyze the type of feature data.

Panarchy to explore land use: a historical case study from the Peruvian Amazon

The overexploitation of natural resources is an important driver of the global environmental crisis. The scientific community engages in an ongoing debate about the most suitable frameworks for analyzing trends in land use. In this paper, we use the conceptual lens of the adaptive cycle and panarchy to explore complex social–ecological dynamics in the Peruvian Amazon. Through an extensive literature review and interviews with key informants, we provide a historical analysis of extractive activities over the last two centuries in the department of Madre de Dios, Peru. We identify periods of growth, conservation, and sometimes release and reorganization for each resource and for the overall social–ecological system. We identify a general trend toward more diversification in extractive activities over time and inter-scale linkages between adaptive cycles of different time and space scales. Based on these results, we explore future development, hypothesize a possible domination of the agricultural sector, and suggest that land-use policies and management interventions should draw from past lessons to design adaptive land planning. Finally, we present new evidence highlighting the relevance of panarchy for understanding historical changes in complex social–ecological systems and demonstrate its utility in exploring both past land use and future development.

Environmental sustainability of diets among children and adolescents in the German DONALD cohort study: age and time trends, and nutrient adequacy

BackgroundIdentifying diets beneficial for both human and planetary health has become increasingly important. However, to date, there is limited research on sustainable diets for children and adolescents, a vulnerable population group with specific nutritional needs. ObjectivesWe aimed to identify 1) the main determinants; 2) age and time trends of greenhouse gas emissions (GHGE), land use (LU), and water use (WU) of diets of children and adolescents; and 3) analyze the associations of dietary GHGE, LU, and WU with nutrient adequacy. MethodsA total of 5510 3-d-weighted dietary records (n = 856; 6–17 y; 48% ♀) of the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study between 2000 and 2021 were analyzed. Values of GHGE (kgCO2eq), LU (m2 × year), and WU (L) determined by life cycle assessment were assigned to all recorded foods. For nutrient adequacy, the mean adequacy ratio (MAR = ∑(nutrient intake / recommended intake) / number of nutrients) was used. Data were analyzed using polynomial mixed-effects regression models. ResultsThe main contributors to GHGE and LU were meat products (GHGE: 25.6%; LU: 32.8%), dairy products (22.2%; 17.7%), and sweets and pastries (14.0%; 14.3%); to WU, nonalcoholic beverages (24.3%), meat products (18.9%), and vegetables and fruits (17.7%). GHGE, LU, and WU per 1000 kcal increased with age (P < 0.01). GHGE and LU per 1000 kcal increased between 2000 and 2010 and decreased after that in females (P < 0.01) and males (GHGE only: P = 0.02). No significant time trend was found for WU (P > 0.05). A higher MAR was directly associated with GHGE/1000 kcal (MAR: β: 0.011, 95% CI: 0.008, 0.013, P < 0.0001), LU/1000 kcal (MAR: β: 0.009, 95%CI: 0.005, 0.013, P < 0.0001), and WU/1000 kcal (MAR: β: 0.429, 95% CI: 0.325, 0.533, P < 0.0001). ConclusionsOur findings underscore the further need and the capacity for change toward more environmentally sustainable diets. Yet, the tradeoff between environmental sustainability and nutrient adequacy in the diets of children and adolescents requires specific attention to dietary composition.

Multi-Scenario Simulation and Eco-Environmental Effects Analysis of Land Use/Cover Change in China by an Integrated Cellular Automata and Markov Model

Land use transitions play a critical role in ecological environmental restoration, but they are also plagued by ecological environmental problems caused by excessive land resource development. In this study, we propose a methodological framework for unveiling the nexus profile of land use/cover change (LUCC) and eco-environmental effects. This study explored the spatiotemporal evolution patterns of LUCC over a long time series based on high-precision land use data from 1990 to 2020. Then, the ecological values (EVs) of various cities were calculated to obtain the ecological contribution rate of different land use types in the process of change. Finally, the future development trends of land use and ecological environmental quality were predicted under multiple scenarios using the cellular automata–Markov model, and scientific policy recommendations were proposed. The results showed that the expansion trajectory of the construction land in the urban agglomeration mainly expanded inwards along the mouth of the Pearl River, and the conversion of cultivated land to construction land was the most significant type of land use change. The overall ecological environmental quality of the study area showed a downwards trend, with Shenzhen exhibiting the largest decrease in EVs. Cultivated land contributed significantly to improving regional ecological environmental quality, while the land use transition types with relatively large contributions to environmental quality deterioration were conversions to construction land. Under the scenario of coordinated protection, the degree of cultivated land area reduction was significantly reduced, and the area of forestland showed a positive growth trend, with the expansion trend of construction land being reversed. These research findings can enrich the theoretical research on the sustainable development of urban agglomerations and provide reliable data support for policy-making.

Study on urban land use in Henan Province under the background of high-quality development

With the rapid development of the economy and continuous urban expansion, the sharp increase in land demand under the existing land scale and the limited supply of land resources have led to a serious intensification of contradictions. Improving land use efficiency, especially construction land use efficiency, has become an inevitable direction for future development. This is also a challenge faced by the comprehensive and sustainable development of China’s urban economy and society. Among other benefits, evaluating the efficiency of urban construction land use can maximize the distribution of land resources, improve the overall advantages of construction land, and encourage land management. This paper establishes and illustrates the evaluation based on three aspects: economic benefits, social benefits, and ecological benefits, to establish an index system for the evaluation of urban construction land use efficiency in Henan Province. In this paper, the coordination trend and efficiency of land use in urban construction in Henan Province are analyzed, discussed, and evaluated.

Grey markov land pattern analysis and forecasting model incorporating social factors

The focus of attention has shifted to land use and land cover changes as a result of the world’s fast urbanisation, and logical planning of urban land resources depends greatly on the forecast and analysis of these changes. In order to more precisely forecast and assess patterns of land use change, the study suggests a grey Markov land pattern analysis and prediction model that incorporates social aspects. The study builds a land pattern analysis and prediction model using a major city as the research object. The outcomes demonstrated the high accuracy and reliability of the grey Markov land pattern analysis and prediction model incorporating social factors, which can more accurately reflect and predict the land use pattern of the study area, with an average relative error of less than 0.01, an accuracy of more than 98%, and an overall fit that has increased by more than 3%. The overall pattern of change is very consistent with the reality. The model predicts that the main trend of future land use in the study area is the continued expansion of urban land such as industrial land, land for transport facilities and land for settlements, while non-construction land such as agricultural land and forest land will continue to decrease. The optimized land pattern analysis and prediction model of the study has a good application environment.

Trends of Land Use and Land Cover Change in the Savannah Ecological of the Protected Area Reserve Partielle de Dosso, Niger

Trends of Land Use and Land Cover Change in the Savannah Ecological of the Protected Area Reserve Partielle de Dosso, Niger

Land Use and Land Cover Trends and Their Impact on Streamflow and Sediment Yield in a Humid Basin of Brazil’s Atlantic Forest Biome

Understanding the trends in land use and land cover (LULC) is crucial for modeling streamflow and sediment yield, particularly in hydrological basins. This study examined the impact of LULC on the dynamics of streamflow and sediment yield within a humid tropical basin of the Atlantic Forest biome in Brazil, focusing on the period from 2000 to 2016. Changes in LULC were analyzed using annual MapBiomas data products for the same period. The Soil and Water Assessment Tool (SWAT) model was deployed to simulate streamflow and sediment yield based on LULC changes. To investigate temporal trends in LULC, a suite of non-parametric statistical tests, including the Mann–Kendall, Pettitt, and Sen’s slope estimator tests, was employed. Ecological diversity indices such as Shannon–Weaver, Simpson, and Pielou were applied to assess forest fragmentation, along with the Forest Fragmentation Index. The results revealed a growing trend in urban and sugarcane areas, coupled with a decline in dense vegetation, mangroves, and other forms of dense vegetation. With regard to the correlation between land uses and hydrological variables, the findings indicate minor variations in hydrological balance, attributable to the not-so-significant changes among the studied land-use scenarios, except for sediment yield estimates, which showed more considerable alterations. Notably, the estimates for 2000 and 2013–2016 were the most divergent. In a broader scientific context, this research conclusively establishes that the incorporation of dynamic LULC data into the SWAT model augments the precision and robustness of simulations pertaining to agricultural watersheds, thereby enabling a more comprehensive hydrological characterization of the study area.

Pemberdayaan Lahan Sempit Bagi Masyarakat Perkotaan dalam Meningkatkan Minat Berwirausaha pada Subsektor Usaha Tani Perkotaan

Land management is the process of making and planning decisions, directing, organizing, and managing human, physical, financial, and information resources to achieve organizational goals in efficient and effective land management. Changes in land use in urban areas are increasing along with urban expansion and development. Trends in land use in metropolitan areas reflect economic and demographic expansion, as well as societal preferences as drivers of land use change. To achieve household food self-sufficiency and sustainable urban growth, urban areas need regulations to limit changes in land use. Agricultural techniques in urban environments are currently developing according to zone features and land availability. Vegetables, horticultural, ornamental, and medicinal plants are the only crops grown in the city. The purpose of this research is to show how limited urban space can be used for agriculture and family food self-sufficiency.

Spatio-Temporal Dynamics and Physico-Hydrological Trends in Rainfall, Runoff and Land Use in Paraíba Watershed

The detection and monitoring of changes in land use and land cover play a crucial role in understanding land degradation and are fundamental to preserving agroecosystems. Their association with hydrological information allows essential responses to changes in hydrological patterns to be identified, contributing to water security in watersheds. Therefore, this study aimed to assess spatio-temporal dynamics and physico-hydrological trends in rainfall, runoff and land use in the Paraíba watershed. The study was conducted in the Paraíba watershed, using land use data and information from pluviometric and fluviometric stations with temporal series of more than 30 years. The Mann-Kendall statistical test was adopted to verify trends. Results indicate annual reduction trends for both native forest area and water bodies in the Paraíba watershed. On the other hand, the area designated for agriculture showed a significant increase. The correlation analysis between water bodies and forests (R² = 0.63) highlights a strong association between the decrease in forest area and the reduction in water availability, influencing the decrease in annual flow. These results serve as a warning to expand water resource management for the region, aiming to preserve and to enhance sustainable use. Therefore, the implementation of conservation measures, monitoring procedures, and adequate management is required to face the challenges imposed by climate change and land use and occupation, ensuring the water availability for the future.

Spatiotemporal trends of urban-induced land use and land cover change and implications on catchment surface imperviousness

Urbanization, changes in land use and land cover (LULC), and an increase in population collectively have significant impacts on urban catchments. However, a vast majority of LULC studies have been conducted using readily available satellite imagery, which often presents limitations due to its coarse spatial resolution. Such imagery fails to accurately depict the surface characteristics and diverse spectrum of LULC classifications contained within a single pixel. This study focused on the highly urbanized Dry Creek catchment in Adelaide, South Australia and aimed to determine the impact of urbanization on spatiotemporal changes in LULC and its implications for the land surface condition of the catchment. Very high spatial resolution imagery was utilized to examine changes in LULC over the past four decades. Support Vector Machine-learning-based image classification was utilized to classify and identify the changes in LULC over the study area. The classification accuracy showed strong agreement, with a kappa value greater than 0.8. The findings of this analysis showed that extensive urban development, which expanded the built-up area by 34 km2, were responsible for the decline in grass cover by 43.1 km2 over the last 40 years (1979–2019). Moreover, built-up areas, plantation, and water features, in contrast to grass cover, have demonstrated an increasing trend during the study period. The overall urban expansion over the study period was 136.6%. Urbanization intensified impervious area coverage, increasing the runoff coefficient, equivalent impervious area, and curve number by 60.6%, 60.6%, and 7.9%, respectively, while decreasing the retention capacity by 38.6%. These modifications suggest a potential variability in catchment surface runoff, prompting the need for further research to understand the surface runoff changes brought by the changes in LULC resulting from urbanization. The findings of this study can be used for land use planning and flood management.

Open Foris Collect Earth: a remote sensing sampling survey of Azerbaijan to support climate change reporting in the land use, land use change, and forestry.

Land use, land use change, and forestry (LULUCF) are critical in climate change mitigation. Producing or collecting activity data for LULUCF is essential in developing national greenhouse gas inventories, national communications, biennial update reports, and nationally determined contributions to meet international commitments under climate change. Collect Earth is a free, publicly accessible software for monitoring dynamics between all land use classes: forestlands, croplands, grasslands, wetlands, settlements, and other lands. Collect Earth supports countries in monitoring the trends in land use and land cover over time by applying a sample-based approach and generating reliable, high-quality, consistent, accurate, transparent, robust, comparable, and complete activity data through augmented visual interpretation for climate change reporting. This article reports forest extent estimates in Azerbaijan, analyzing 7782 0.5-ha sampling units through an augmented visual interpretation of very high spatial and temporal resolution images on the Google Earth platform. The results revealed that in 2016, tree cover existed in 31.9% of total land, equal to 2,751,167ha and 1,301,188ha or 15.1% of the total land, with a 5.4% sampling error covered by forests. The estimate is 15 to 25% higher than the previous estimates, equal to 169,418 to 260,888ha of forest that was never reported in previous studies.

Ecohydrological Footprint and Climate Trends in Lotic Ecosystems of Central Western Ghats

An ecohydrological assessment of lotic ecosystems would provide insights into understanding the symbiotic interactions of hydrological and ecological processes for sustainable catchment management to ensure water security and achieve sustainable development goals (SDG). Global monitoring reveals changing climate patterns due to the unabated anthropogenic activities altering the ecohydrological behavior of waterscapes and thus affecting the sustenance of natural resources. The current research investigates the ecohydrological footprint using a modified water balance method by accounting for climatic and land-use trends across three river catchments in the northern portion of the Central Western Ghats. Assessment of landscape dynamics using temporal remote sensing data indicates the reduction in forest cover in Mahadayi, Ghataprabha, and Malaprabha river basins with increased anthropogenic activities. Evaluation of climate trends shows rising temperatures over 0.4 °C in the last century with increasing rainfall. The consequence of enhanced rainfall is increased overland flows to the extent of 35–80% in all river basins. Water availability in streams during all seasons is evident in the catchment dominated by native forest cover, while streams are intermittent and seasonal at the transition zone and plains. Analyses of temperature and rainfall in the last century indicate higher spatial variations directly influencing surface and subsurface hydrology. The reduced native forest cover has directly affected the variations in the local temperatures and precipitation patterns. This highlights the need for maintaining the ecological integrity of watersheds with native vegetation cover for sustaining the natural resources (water, etc.) that support the livelihood of farmers with socio-economic benefits.

Agricultural Practices and Soil and Water Conservation in the Transboundary Region of Kenya and Uganda: Farmers’ Perspectives of Current Soil Erosion

Poor agricultural practices among small-scale sub-Saharan African farmers can lead to soil erosion and reduce agricultural productivity. However, information on such practices is normally not well documented, making it challenging to design future mitigation strategies. We conducted a fine-scale agricultural survey on 200 farm households within the transboundary Sio Malaba Malakisi River Basin (SMMRB) between Kenya and Uganda to quantify the frequency and type of soil conservation practices (SWCPs) implemented. Information on farm sizes, ownership, crops grown, soil fertility, soil erosion, soil water conservation practices, and the decision-making processes was collected. Descriptive and chi-squared statistics were used to present trends in land use, decision-making processes and the extent of adoption of SWCPs, as well as to analyse the relationship between the SWCPs and the farmers’ perceptions on soil erosion. The region showed highly fragmented farms (mean area: 0.6 ha), primarily practising rain-fed subsistence farming. The principal decision-makers of each farm were mainly (63%) male. Various farmers (28%) lacked soil and water conservation practices (SWCPs). However, most farmers (35%) implemented one type of soil and water conservation practice, while 37% practised a combination of two to five soil and water conservation practices. Extensive soil and water conservation practices such as intercropping were widely practised as they were more affordable than intensive measures. Results on the farmers’ perceptions on soil erosion showed that most farmers in the SMMRB reported soil erosion (60%) and even more (92%) reported to have experienced a loss of soil fertility over the last 5 years. There was a significant positive correlation (X2 (2, n = 198) = 92.8, p = &lt; 0.001) between the perception of soil erosion and the perception of the change in soil fertility, suggesting that reducing soil erosion could result in a reduction in the loss of soil fertility. Thus, there is still a need for strategies and measures to address the soil erosion risks currently faced by Sio Malaba Malakisi River Basin farmers. This study is a baseline study that shows the importance of farmers’ perceptions on the practice of soil and water conservation measures in the Sio Malaba Malakisi River Basin and therefore becomes an important avenue for improving the currently practised soil and water conservation measures as well as developing adoption programs as well as future studies that combine scientific and farmers’ perception/knowledge for sustainable agriculture. Further research into the efficiency of currently adopted SWCPs as well as the extent of the farmers’ knowledge and the accuracy of their perceptions is recommended.

P02-050-23 Age and Time Trends in Greenhouse Gas Emissions and Land Use of Diets Among Children and Adolescents of the German DONALD Cohort Study

P02-050-23 Age and Time Trends in Greenhouse Gas Emissions and Land Use of Diets Among Children and Adolescents of the German DONALD Cohort Study

Spatiotemporal change and prediction of land use in Manasi region based on deep learning

The Manasi region is located in an arid and semi-arid region with fragile ecology and scarce resources. The land use change prediction is important for the management and optimization of land resources. We utilized Sankey diagram, dynamic degree of land use, and landscape indices to explore the temporal and spatial variation of land use and integrated the LSTM and MLP algorithms to predict land use prediction. The MLP-LSTM prediction model retains the spatiotemporal information of land use data to the greatest extent and extracts the spatiotemporal variation characteristics of each grid through a training set. Results showed that (1) from 1990 to 2020, cropland, tree cover, water bodies, and urban areas in the Manasi region increased by 855.3465 km2, 271.7136 km2, 40.0104 km2, and 109.2483 km2, respectively, whereas grassland and bare land decreased by 677.7243 km2 and 598.5945 km2, respectively; (2) Kappa coefficients reflect the accuracy of the mode’s predictions in terms of quantity. The Kappa coefficients of the land use data predicted by the MLP-LSTM, MLP-ANN, LR, and CA-Markov models were calculated to be 95.58%, 93.36%, 89.48%, and 85.35%, respectively. It can be found that the MLP-LSTM and MLP-ANN models obtain higher accuracy in most levels, while the CA–Markov model has the lowest accuracy. (3) The landscape indices can reflect the spatial configuration characteristics of landscape (land use types), and evaluating the prediction results of land use models using landscape indices can reflect the prediction accuracy of the models in terms of spatial features. The results indicate that the model predicted by MLP-LSTM model conforms to the development trend of land use from 1990 to 2020 in terms of spatial features. This gives a basis for the study of the Manasi region to formulate relevant land use development and rationally allocate land resources.

A Multi-Attribute Approach for Low-Carbon and Intensive Land Use of Jinan, China

This paper establishes an evaluation system based on the low-carbon intensive land use in Jinan city from 2010 to 2017 and uses a multi-attribute approach named grey fuzzy integral to build the evaluation model. In this model, based on the Mobius transformation coefficient of subjective and objective weights of index factors and the interaction degree between index factors, 2-additive fuzzy measures can be obtained; therefore, evaluation of low-carbon and intensive land use in Jinan city is processed by combining the grey correlation degree and Choquet fuzzy integral. The results show that in the study period, land input intensity, land use degree, land output benefit and land sustainability in Jinan city all show a good upward trend, but the low-carbon land use level of has been in a declining state. Although there is a good development trend of low-carbon and intensive land use in Jinan, the state is not stable. A Low-carbon and intensive land use pattern will not be achieved completely overnight, and it is bound to be a dynamic game process.

A cloud-integrated GIS for forest cover loss and land use change monitoring using statistical methods and geospatial technology over northern Algeria

Over the last two decades, forest cover has experienced significant impacts from fires and deforestation worldwide due to direct human activities and climate change. This paper assesses trends in forest cover loss and land use and land cover changes in northern Algeria between 2000 and 2020 using datasets extracted from Google Earth Engine (GEE), such as the Hanssen Global Forest Change and MODIS Land Cover Type products (MCD12Q1). Classification was performed using the pixel-based supervised machine-learning algorithm called Random Forest (RF). Trends were analyzed using methods such as Mann–Kendall and Sen. The study area comprises 17 basins with high rainfall variability. The results indicated that the forest area decreased by 64.96%, from 3718 to 1266 km2, during the 2000–2020 period, while the barren area increased by 40%, from 134,777 to 188,748 km2. The findings revealed that the Constantinois-Seybousse-Mellegue hydrographic basin was the most affected by deforestation and cover loss, exceeding 50% (with an area of 1018 km2), while the Seybouse River basin experienced the highest percentage of cover loss at 40%. Nonparametric tests showed that seven river basins (41%) had significantly increasing trends of forest cover loss. According to the obtained results, the forest loss situation in Algeria, especially in the northeastern part, is very alarming and requires an exceptional and urgent plan to protect forests and the ecological system against wildfires and climate change. The study provides a diagnosis that should encourage better protection and management of forest cover in Algeria.

Analysis of Runoff according to Land-Use Change in the Upper Hutuo River Basin

Land use affects regional hydrological processes. The alteration of regional distributions of vegetation, crop types, and land-use patterns for construction has a significant impact on the runoff process and influences the water cycle in watersheds. Studies on runoff variations in the Hutuo River Basin have concentrated on climate change and the effect of human activities without adequate attention paid to land-use changes. In order to investigate the response of runoff to land-use changes in the upper Hutuo River Basin, a soil and water assessment model was used in this study to compare and analyze the changes in runoff under five land-use scenarios from 1980–2020. The results show that the area of farmland, forest land, and grassland in the watershed gradually decreased from 1980 to 2020, with a total decrease of 3.1%, while the area of urban construction land increased rapidly by 1.5 times. Corresponding with the trend of land-use change, the differences between the simulated and natural values for regional flood peak and annual runoff increased with time, which is in line with the changing land-use trends. From 1960–2020, the differences between the simulated and natural values for the flood peaks of the five land-use scenarios were −16.8, −6.7, −3.5, 4.6, and 9.3%, respectively, and the errors between the simulated and natural values for annual runoff were −6.7, −4.4, −2.0, −2.6, and 10.8%, respectively. Overall, the increase in urban construction land and decrease in farming, forest area, and grassland has caused the regional flood peak and annual runoff volume to increase in the upper Hutuo River Basin.

Simulation of future land use/cover change (LUCC) in typical watersheds of arid regions under multiple scenarios

The rapid development of the social economy has promoted a continuous increase in the intensity and scale of land use by humans, which has seriously affected the sustainable development of the region. It is important to understand the land use/cover change (LUCC) in the arid region and its future development trends and to make reasonable planning recommendations for the sustainable development of the ecological environment. This study validates the patch-generating land use simulation (PLUS) model in a typical arid region, the Shiyang River Basin (SRB), and analyzes the applicability of the model in arid regions. On this basis, the PLUS model is combined with the scenario analysis method to design four scenarios including no policy intervention, farmland protection, ecological protection and sustainable development to analyze the dynamic changes in past and future land use in the SRB and to make corresponding planning recommendations for the development of each type of land use in the arid region. The results showed that the PLUS model had a better simulation effect in the SRB (its overall accuracy reached 0.97). Coupled models obtain better simulation results than quantitative and spatial models by comparing the mainstream models, with PLUS model that combines CA model and patch generation strategy showing better simulation results in the same category. From 1987 to 2017, the spatial centroid of each LUCC in the SRB moved to varying degrees due to a continuous increase in human activities. The spatial centroid of water bodies had the most obvious change, with a moving speed of 1.49 km/a, while the moving speed of built-up land increased year by year. The spatial centroid of farmland, built-up land and unused land all shifted toward the middle and lower plains, which is a further indication of increased human activity. Due to different government policies, the development trend of land use was also different under different scenarios. However, the four scenarios all showed that the area of built-up land will be increasing exponentially from 2017 to 2037, which would seriously affect the surrounding ecological land and have a negative impact on the local agro-ecological environment. Therefore, we proposed the following planning recommendations: (1) Land leveling work should be carried out on scattered farmland located at high altitudes and with slopes over 25°. Additionally, the land use of low-altitude areas should strictly adhere to basic farmland, increase the diversification of cropping patterns and improve the efficiency of agricultural water. (2) The relationship between ecology, farmland and cities should be reasonably coordinated and the existing idle built-up land should be efficiently used. (3) Forestland and grassland resources should be strictly protected and the ecological redline should be strictly observed. This study can provide new ideas for LUCC modeling and prediction in other parts of the world and provide a strong basis for ecological management and sustainable development in arid areas.