Spatiotemporal Land Use Change Research Articles

Changes in Land Use and Cover and Their Environmental Impacts in the Cerrado of Mato Grosso Do Sul, Brazil

In Brazilian regional landscapes, the Cerrado has one of the richest flora among the savannas in the world, with a high level of endemism; however, many plant species are threatened with extinction as a consequence of spatio-temporal changes in land use and cover. This study aimed to analyze changes in land use and cover in the upper course of the Ceroula stream basin, located in the Cerrado of Mato Grosso do Sul, Brazil, based on maps of land use and cover in 1985 and 2022, the normalized difference vegetation index (NDVI), precipitation data, and fieldwork. The results indicated that in 1985, forest vegetation was replaced by pasture, and in 2022, in addition to pasture, there was the introduction of soybean monoculture with corn in the off-season, influenced by the international commodities market. These land use and cover alterations, without adequate management and in the absence of conservation practices, led to environmental impacts, such as accelerated linear erosive processes (rill, ravine, and gully). The results may help provide important insights into the dynamics of land use and cover, the consequences of the lack of conservation practices, and the environmental impacts in the Cerrado of Mato Grosso do Sul, contributing to better understanding of the environmental challenges faced in the region and the need to provide subsidies for the development of sustainable management strategies.

Spatio-temporal Land Use and Land Cover Change Assessment: Insights from the Ouémé River Basin

The rapid increase in population and urban development are exacerbating the transformation of natural environments into unnatural forms. While detailed assessment of the environment is beneficial for efficient ecosystem system management, it can also be time and resources-consuming. This study aimed to map and quantify the spatio-temporal changes in land use and land cover (LULC) using the Ouémé River Basin as a case study. The supervised classification in Google Earth Engine (GEE) cloud-computing platform was employed to distinguish Landsat images for 1986, 2000, 2015 and 2023 into forest areas, settlements/bare lands, savanna areas (woodlands), agricultural lands and water bodies. Analysis of the LULC changes revealed that savanna areas and woodlands which were predominant in the basin in 1986 have steadily declined by 24 % in area in 2023. Forest areas have diminished by 4.3 % at an annual rate of 4 %. Agricultural lands have however grown exponentially by 28 % since 1986, with a more rapid increase between 2015 and 2023 at an annual rate of 3.7 %, driven by rising food demand due to population growth within and around the basin. Settlements and bare areas tripled in area, reflecting a similar trend to Benin's urban population growth. Accuracy statistics of the LULC classification showed overall accuracy and kappa statistic values above 90 % and 86 %, respectively, indicating the admirable performance and reliability of the Simple Composite Landsat algorithm for image composition, and the Random Forest Classifier for LULC classification approach applied in this study. The approach also demonstrates the robustness and potential of LULC mapping in large and complex ecosystems using the GEE cloud-based remote sensing tool, which is underutilized in the study area. Overall, the LULC trends provide beneficial insights useful to policy-makers and any other stakeholders involved in sustainable ecosystem management planning in the basin.

Land use change in coastal zones of China from 1985 to 2020

Coastal regions stand as pivotal zones of interaction between the marine and terrestrial environments, holding substantial significance for both ecosystems and human societies. Since the 1980s, China’s coastal zones (CCZ) have undergone rapid economic expansion, a surge in urban development activities, and a considerable population increase, instigating significant alterations in land use along the coast. However, in recent years, studies regarding changes in land use along China’s coastal zones have been notably scarce. Utilizing the Comprehensive Lands Cover Database (CLCD) dataset, this study scrutinized the spatiotemporal patterns of land use along the Chinese coastline since 1985. It delved into the temporal and spatial variations in land use, ecological land transformations, and the spatiotemporal evolution of land use development intensity, examining these facets across provinces, municipalities, and different distance bands from the coastal zone. The research findings indicated: Overall, cropland and forest land predominantly occupied coastal zones, encompassing over 80% of the total area. Between 1985 and 2020, the primary changes involved a decrease in cropland and an increase in construction land, with a reduction of 5.97% in cropland, largely transitioning into construction land (84927.21 km2) and forest land (4218.55 km2), resulting in a 5.98% increase in construction land. Despite the intensification of land development, ecological land exhibited an initial rise followed by a declining trend. There existed distinct disparities in land use patterns among provinces and cities, with cropland and forest land prevailing in all areas except Macau. Construction land and land use development intensity witnessed significant increases, most notably in Macau and least pronouncedly in Guangxi. Variations in ecological land alterations were considerable, with Hebei and Guangdong witnessing increases while other regions tended towards stability or reduction. Each distance band manifests a unique land use pattern. Except for the 100-150 km zone, construction land demonstrates an increasing trend across all bands. Ecological land expanded initially but fluctuated further from the coastline. Land use development intensity decreased initially, then stabilized, with the 0-10 km zone showed the highest development intensity. Analyzing the spatiotemporal changes in land use along China’s coastal zones from 1985 to 2020 can offer valuable insights into the management and sustainable development of China’s coastal zones.

Land Use and Cover Changes in Brazilian Biomes between 1985 and 2018

In the last decades, there have been changes in land use and cover in the Brazilian territory, many resulting from anthropic activities. However, these changes impact the environmental system, compromising biodiversity and ecological services. In this context, integrative geographic information about environmental changes in the Biomes allows the identification of the main Spatio-temporal changes in land use and cover and can contribute to efficient environment planning. Thus, this paper proposes to describe and synthesize the Spatio-temporal changes in Brazilian Biomes between 1985-2018 using spatial statistics techniques and Principal Component Analysis with data from the MapBiomas project. It has employed the Google Earth Engine and QGIS for the analysis, with emphasis on spatial statistics and Principal Components Analysis which enabled the identification of the main changes in land use and cover. From the Principal Components Analysis, it was possible to reduce the data set with 34 images to two Principal Components that represent significant percentages of the variance of the original database. The results showed that the Brazilian Biomes had undergone significant changes over 34 years. The main vectors that drove these transformations were anthropic activities, such as urban growth, the advancement of agriculture, and cattle ranching in the countryside. Amazon and Cerrado present the largest area altered in square kilometers. And the fastest changes occurred on Amazon, Cerrado, and Pantanal. This work presents a synthesis of the main patterns and spatial-temporal changes in the use and cover of Brazilian Biomes, which can assist in the national environmental planning.

Application of GIS and Remote Sensing Techniques for Detection and Analysis of Spatio-Temporal Changes in Land Use and Land Cover in Rampurhat Block-II, Birbhum, Eastern India

Application of GIS and Remote Sensing Techniques for Detection and Analysis of Spatio-Temporal Changes in Land Use and Land Cover in Rampurhat Block-II, Birbhum, Eastern India

Application of GIS and Remote Sensing Techniques for Detection and Analysis of Spatio-Temporal Changes in Land Use and Land Cover in Rampurhat Block-II, Birbhum, Eastern India

Application of GIS and Remote Sensing Techniques for Detection and Analysis of Spatio-Temporal Changes in Land Use and Land Cover in Rampurhat Block-II, Birbhum, Eastern India

Spatiotemporal changes in land use and residential satisfaction in the Huai River-Gaoyou Lake Rim area

Abstract This research investigates the dynamic interplay between land use changes and landscape ecological risks in China’s Jiangsu Province, specifically focusing on the Huai River-Gaoyou Lake region. Leveraging multi-temporal remote sensing data from 2000 to 2020, we conducted a comprehensive analysis of shifting land cover patterns and their implications. Employing geostatistical techniques, we developed a landscape ecological risk assessment model to quantify ecological vulnerabilities. Additionally, we conducted a resident satisfaction survey aligned with the “Production–Living–Ecological” framework to gain insights into societal perceptions of land use dynamics. Our findings reveal significant land use shifts driven by urbanization, industrialization, and agricultural modernization. While farmland areas have decreased, water bodies and artificial surfaces have expanded, reflecting societal demands and economic growth. The landscape ecological risk assessment model highlights localized vulnerabilities, emphasizing the intricate relationship between land use changes and ecological risks. The resident satisfaction survey indicates overall contentment with various aspects of land use, especially in terms of residential comfort and transportation convenience. However, ecological concerns underscore the need for a balanced approach to land management that prioritizes ecological sustainability alongside economic development.

Soil Erosion in a Changing Environment over 40 Years in the Merguellil Catchment Area of Central Tunisia

Soil degradation and erosion in semi-arid regions can significantly impact agricultural development, environmental sustainability, and hydrological balance. Understanding the impacts of land use changes and soil and water conservation (SWC) technique implementation on soil erosion and sediment yield is critical to planning effective watershed management. This study aims to evaluate the impacts of environmental changes in the Merguellil watershed (Central Tunisia) over the last forty years. To achieve this, remote sensing techniques and a geographic information system (GIS) will be employed to classify Landsat images from 1980 to 2020. Additionally, the Revised Universal Soil Loss Equation model will be utilized to estimate soil erosion rates, while the sediment delivery distributed model will be employed for sediment yield modeling. Spatiotemporal changes in land use and land cover and in areas treated with SWC techniques were analyzed as the main factors influencing changes in erosion and sediment yield. The combined impact of land use change and SWC techniques resulted in a decrease in the annual soil erosion rate from 18 to 16 t/ha/year between 1980 and 2020 and in sediment yield from 9.65 to 8.95 t/ha/year for the same period. According to the model’s predictions, both soil erosion and sediment yield will experience a slight increase with further degradation of natural vegetation and a reduction in the efficiency of SWC works. This emphasizes the importance of continued efforts in adopting and sustaining SWC techniques, as well as preserving natural vegetation cover, to proactively combat soil degradation and its adverse effects on the environment and communities. Continuous dedication to these measures is crucial to preserving our ecosystem, promoting sustainable practices, and protecting the well-being of both the environment and society.

Dynamic landscapes and the influence of human activities in the Yellow River Delta wetland region

The Yellow River Delta (YRD) wetland is one of the largest and youngest wetland ecosystems in the world. It plays an important role in regulating climate and maintaining ecological balance in the region. This study analyzes the spatiotemporal changes in land use, wetland migration, and landscape pattern from 2013 to 2022 using Landsat-8 and Sentinel-1 data in YRD. Then wetland landscape changes and the impact of human activities are determined by analyzing correlation between landscape and socio-economic indicators including nighttime light centroid, total light intensity, cultivated land area and centroid, building area and centroid, economic and population. The results show that the total wetland area increased 1426 km2 during this decade. However, the wetland landscape pattern tended to be fragmented from 2013 to 2022, with wetlands of different types interlacing and connectivity decreasing, and distribution becoming more concentrated. Different types of human activities had influences on different aspects of wetland landscape, with the expansion of cultivated land mainly compressing the core area of wetlands from the edge, the expansion of buildings mainly disrupting wetland connectivity, and socio-economic indicators such as total light intensity and the centroid mainly causing wetland fragmentation. The results show the changes of the YRD wetland and provide an explanation of how human activities effect the change of its landscape, which provides available data to achieve sustainable development goals 6.6 and may give an access to measure the change of wetland using human-activity data, which could help to adject behaviors to protect wetlands.

Spatiotemporal Analysis of Land Use Land Cover Mapping and Change Detection in Dambatta Local Government Area

This research studied the spatiotemporal changes in land use (LU)/land cover (LC) in Dambatta local government area, with a view to identifying the effect arising from the observable changes in land use patterns. The imageries used in the study were obtained from the National Space Research and Development Agency (NARSDA), Abuja. Spatial analytical techniques and descriptive statistical techniques were employed to analyze the data. The results showed 66.8% reduction in agricultural lands, 45.5% reduction in vegetation cover, 223.2% increase in built-up areas, 269.1% increase in bare lands and 70% increase in water bodies within the 20 years. Spatio-temporal analysis of the three imageries revealed that agricultural lands were largely been taken over by urbanization while vegetation had rapidly given way to bare lands within the 20 years. It was observed that these changes resulted from anthropogenic activities, environmental factors and climate change. These result in the loss of farmlands, inadequate food supply, unemployment, inadequate industrial raw materials, reduction in revenue generated, forest depletion, desertification, wildlife extinction and temperature increase. While it is recommended that reforestation, land reclamation and irrigation agriculture should be promoted in the area, it is also suggested that further research should focus on the impact of climate change on land cover change in the area.

History, neighborhood, and proximity as factors of land-use change: A dynamic spatial regression model

Spatio-temporal land-use change (LUC) modeling provides vital information about land development dynamics. However, accounting for such dynamics faces methodological challenges. This research introduces a Dynamic Spatial Panel Data (DSPD) modeling framework for LUC, incorporating spatial and temporal dependencies. A continuous response variable is introduced to take advantage of traditional spatial regression models. The DSPD model is applied to balanced spatial panel data at the block-group level covering Florida between 2010 and 2019 and incorporating both new and previously used proxy variables. The urban growth impacts of site-specific, proximity, neighborhood, socio-economic, and transportation factors are investigated. This study contributes to the literature by providing extensive insights into spatial autocorrelation, spillover, heterogeneity, and temporal lag effects in urban growth. Also, the study reveals the importance of mobility and mortgage financing in land development. The proposed modeling framework achieves high accuracy. The dynamic structure of this model provides an opportunity to predict future urban growth without the need for a land development scenario. Such predictions provide insights about future land development to practitioners and policymakers.

Spatiotemporal changes in land use and landscape fragmentation in coastal plain areas—A case study of Yancheng City, China

Coastal regions in China have the highest levels of economic development due to their prominent geographical locations and corresponding supporting policies. Global research concerns now include the spatiotemporal analysis of urban land use and landscape fragmentation in coastal plains. Research on coastal land use in China and related topics can provide a scientific basis for urban land use and sustainable development in other countries. In this study, a quantitative analysis of spatiotemporal changes in land use and landscape fragmentation was carried out based on land use data from Yancheng City, China. The dynamic degree of land use, Markov transition matrix and landscape indices were all subject to analysis. The results demonstrated that land use patterns in Yancheng City underwent substantial changes from 1990 to 2020. Cropland was found to be the dominant landscape in Yancheng City. Water rapidly increased whereas Grassland and Woodland dramatically decreased during the study period. Frequent transformations in and out of urban land were observed. In the late study period, the Tidal flat was gradually transformed into Grassland and Water. Variations in the landscape indices indicated significant changes in the landscape patterns. The landscape patterns in Yancheng City over a 30-year study period were found to be complicated. The special characteristics of Tidal flat land areas further intensified the landscape heterogeneity of the spatial range. Based on the above analyses, it was concluded that human activities (urban construction, beach reclamation, land development, and utilization activities) increased landscape fragmentation in Yancheng City throughout the three stages and gradually increased the degree of disturbance. These findings indicated that human intervention, the social economy and urban planning development could influence landscape fragmentation in coastal cities. This study used a spatially explicit approach to understand the relevant drivers of urban land-use change in a coastal plain. Moreover, it reduced the knowledge gap between land-use change and landscape fragmentation research from a temporal and spatial perspective.

Spatio-Temporal Changes in Land Use and Habitat Quality of Hobq Desert along the Yellow River Section

As a key area in the Yellow River basin for sand control and management, the land change process in the Hobq Desert plays a crucial role in keeping the river and desert ecosystems and promoting the construction of ecological civilization in human systems. Based on multi-temporal remote sensing from 1991 to 2019 in the Hobq Desert along the Yellow River section, this study selected spatial statistical methods (land-use monitoring and landscape metrics) to examine land-use change dynamics. Then, we evaluated habitat quality using the InVEST model and quantitatively analyzed the factors causing spatial changes in habitat quality using geographic detectors. Finally, this paper predicted the pattern of land use and habitat quality in 2030 using the PLUS model. The results reveal that (1) from 1991 to 2019, the total area of forest grassland increased by 3572.5 km2, providing the most vegetation cover, and the sandy land and water area decreased continuously, while the cultivated land and construction land increased. There were 38.01% conversions of land types, with the land-use dynamic decreasing the greatest in sandy land (-12.66%) and increasing the greatest in construction land (9.26%); the comprehensive land-use dynamics were the highest in 2010-2019 (1.68%), which was the most active stage during our study period. (2) Both of the landscape indices NP and PD showed "N" type fluctuations during 1991-2019, and CONTAG and LSI rose from 69.19% to 70.29% and 36.01% to 38.89%, respectively, indicating that the land-use degree of landscape fragmentation increased, landscape connectivity turned better, and landscape dominance was enhanced, balanced, and developed evenly in overall landscape type. (3) From the overall region analysis, the average habitat quality in 1991, 2000, 2010, and 2019 was 0.3565, 0.5108, 0.5879, and 0.6482, respectively, with the overall habitat value showing a gradually increasing trend. Spatially, the habitat quality along the Yellow River section of the Hobq Desert has a certain regularity, and the overall pattern there is high in the south and low in the north, high in the east and west, and low in the middle. (4) The change in land use between 2019 and 2030 is similar to the previous period, but the change rate is generally lower. The habitat quality improved significantly, with the growth of high and medium habitat quality.

Scenario-Based LULC Dynamics Projection Using the CA–Markov Model on Upper Awash Basin (UAB), Ethiopia

Understanding the spatiotemporal changes in land use and land cover (LULC) in the watershed is crucial for maintaining the sustainability of land resources. This study intents to understand the historical (1972–2015) and future (2030–2060) spatiotemporal distribution of LULC changes in the Upper Awash Basin (UAB). The supervised Maximum Likelihood Classifier technique (MLC) was implemented for historical LULC classification. The Cellular Automata-Markov (CA–Markov) model was employed to project two scenarios of LULC, ‘business-as-usual’ (BAU) and ‘governance’ (Gov). Results from the historical LULC of the study area show that urban and cropland areas increased from 52.53 km2 (0.45%) to 354.14 km2 (3.01%) and 6040.75 km2 (51.25%) to 8472.45 km2 (71.97%), respectively. Whereas grassland, shrubland, and water bodies shrunk from 2052.08 km2 (17.41%) to 447.63 km2 (3.80%), 2462.99 km2 (20.89%) to 1399.49 km2 (11.89%) and 204.87 km2 (1.74%) to 152.44 km2 (1.29%), respectively, from 1972 to 2015. The historical LULC results indicated that the forest area was highly vulnerable and occupied by urban and cropland areas. The projected LULC under the BAU scenario shows substantial cropland and urban area expansion, increasing from 8472.45 km2 (71.97%) in 2015 to 9159.21 km2 (77.71%) in 2060 and 354.14 km2 (3.1%) in 2015, 1196.78 km2 (10.15%) in 2060, respectively, at the expense of vegetation cover. These results provide insight intothe LULC changes in the area, thus requiring urgent attention by watershed managers, policymakers, and stakeholders to provide sustainable practices for the UAB. Meanwhile, the Gov scenario indicates an increase in vegetable covers and a decrease in cropland, encouraging sustainable development compared to the BAU scenario.

Spatiotemporal Variations and Influencing Factors of Urban Carbon Sink: A Case Study of Wuhan, China

Increasing carbon sinks based on a comprehensive understanding of urban carbon sinks is an effective means for building low-carbon cities and mitigating global climate change. Using the intensity analysis and regression analysis methods, the multiple types of urban carbon sinks in Wuhan from 2000 to 2020 was estimated in this study, and the spatiotemporal changes in land use and the carbon sinks were explored. The influencing factors of the urban carbon sink were also analyzed. The results showed the following: (a) the area of carbon sink land in Wuhan decreased from 2000 to 2020. The transfer area of forest land and water bodies was large. However, their annual loss intensity was lower than the uniform intensity. (b) The urban carbon sink showed a linear downward trend. Specifically, the forest carbon sink was always the main type and accounted for about 60% of the total carbon sinks. (c) The characteristics of the interannual variation in different types of carbon sinks in different districts were various, including the range and direction of variation. Only the total carbon sinks in Xinzhou District increased from 2000 to 2010, and other districts decreased from 2000 to 2020. (d) The gross domestic product per square kilometer was the common influencing factor of carbon sink change in 2000, 2010, and 2020. The land use degree, population change, and industrial structure affected the changes in the carbon sink at different times. These findings hope to help in achieving low-carbon cities and carbon neutrality.

Correction: Yang et al. A Study on the Spatio-Temporal Land-Use Changes and Ecological Response of the Dongting Lake Catchment. ISPRS Int. J. Geo-Inf. 2021, 10, 716

The authors of the published paper [...]

Spatial-Temporal Analysis of Physio-Climatic changes in Tawang- Chu River Basin, Eastern Himalaya in India

The Tawang-Chu River Basin of the eastern Himalayas is a heterogenous region that is highly vulnerable to climate change. The changing temperature patterns in this mountain river basin play a vital role in changing the ecological system and inter-ecological nexus. Landsat satellite images were used to analyze spatio-temporal changes in Land Use and Land Cover (LULC) patterns in the basin. The changing trends of Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) were analyzed (at intervals of five years) using Landsat data. Changes in rainfall trends were analyzed using the Mann-Kendall test. The results show that fluctuations in annual temperature and increasing rainfall uncertainties are affecting LULC vegetation health.

Response of Ecosystem Service Value to Spatio-Temporal Pattern Evolution of Land Use in Typical Heavy Industry Cities: A Case Study of Taiyuan City, China

Ecosystem services value (ESV) has been one index of quantitative evaluation for the ecological livability of heavy industry cities in the new era, which is intimately relevant to patterns of spatio-temporal changes in land use. This study aims to reveal the response of ecosystem service value in heavy industrial cities to the spatial-temporal evolution structure of land use and to analyze the cold and hot spots and sensitivity. In this study, Taiyuan was taken as an example, and Landsat images were adopted as the basic data. This study used intensity analysis, revised ESV, fishing nets, sensitivity analysis, and the methods of hotspot analysis and spatial overlay. The results showed as follows, (1) The characteristics of land use structure evolution mainly focus on the increase of construction land in the early and the rapid development stage of heavy industry cities. All land use types were partly transferred to construction land, but farmland was the main source, with the largest change intensity in the rapid development stage in Taiyuan; (2) The low-value zones of ESV were mostly distributed in the main urban area for construction and farmland, while the high-value zones were primarily distributed in the forestland and grassland. They were distributed in the Fenhe River valley, western and northern mountainous and hilly areas of Taiyuan. The total ESV continued to decline from 2003 to 2018, with a loss amount of RMB 29 million; (3) The patches of land use change were more and more broken, and the spatial distribution of the cold and hot spots was more and more dispersed. The cold and hot spots of ESV were concentrated in the eastern main urban area and its surrounding areas and expanded to the north and south; (4) The forestland was the most sensitive land factor of ESV. The study provides a theoretical method for land use planning, environmental governance, and ecological restoration in heavy industry cities in the new era.

Multiscenario simulation of land use and land cover in the Zhundong mining area, Xinjiang, China

Mining is one kind of activities for human beings to get necessary mineral resources for survival, which also leads to disturbance and damage to local ecosystem. In this paper, the authors analyzed the characteristics of spatio-temporal changes in land use and land cover (LULC) and employed the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model to analyze the comprehensive ecosystem service (CES). Markov chain (MC) and patch-generating land-use simulation (PLUS) were used to assess the spatial distribution of LULC change based on two scenarios in 2030, providing a theoretical basis for restoration of eco-environmentin the Zhundong coalfield. The results indicate that the area with the foremost LULC is the conversion from other to grassland, grassland to other, and other to built-up land in the past 20 years. The value of CES declined from 0.5397 (2000) to 0.3937 (2010) over time and then continued to decline to 0.3449 (2020); the change was weaker in the 2010–2020 period than that in the 2000–2010 period. Spatially, the ecosystem degradation of the eastern part of the Jiangjunmiao mining area and the Xiheishan mining area was more serious, while the Wucaiwan mining area was improved, which is mainly due to the contribution of ecological restoration there. In the 2030 the business-as-usual (BUA) scenario, the area of built-up land expansion increases significantly by 95.2 km2, and the value of CES continues to decrease. In the 2030 the ecological development priority (EDP) scenario, the built-up land expansion continues to decrease to 58.32 km2, the area of grassland increases significantly to 18.64 km2, the value of CES continues to decrease, and the overall LULC structure is improved. Results will guide the type of green sustainable exploitation of the Zhundong mining area.

Planning gaps: unexpected urban expansion in five Colombian metropolitan areas

Colombia has experienced rapid urbanization over the past three decades. Most Colombian cities doubled their urban extent in the last 10 years which resulted in a high demand for land. This research identifies urban expansion patterns in five of the largest urban agglomerations in Colombia. Urban growth is analysed using satellite images (Landsat 5) and census data to assess spatiotemporal land-use changes over a 30-year period (1990–2020). The actual urban extents are compared with each city’s land-use predictions, instruments, and regulations to ascertain whether local authorities have the capabilities to predict land demand and to guide development processes at the municipal level. The predictions made by local authorities are inaccurate and often underestimate the rates of population growth and land requirements. The findings reveal that local authorities lack the capabilities to manage urban growth and deliver sustainable urban development. This is leading to poor outcomes: low planning standards, urban informality and inefficient land use. <em><strong>Policy relevance</strong></em> This research reveals a significant gap between urban land-use policy instruments and actual urban growth patterns in Colombian cities. The findings reveal that the current urban expansion surpassed what local authorities had anticipated and allocated for land use. Although existing policies empower local authorities, their capabilities to effectively monitor and model population growth and associated land requirements are poor. This led to an underestimation of land requirements and poor planning outcomes. To improve future decision-making and management of urban growth, urban planners should use empirical data to inform urban growth scenarios: allocate sufficient land to allow for orderly growth, designate specific areas for development and provide for sufficient infrastructure.