Development Of Built-up Areas Research Articles

ANALISIS PERKEMBANGAN LAHAN TERBANGUN BERDASARKAN METODE SUPERVISED CLASSIFICATION MENGGUNAKAN GOOGLE EARTH ENGINE (STUDI KASUS: DESA CIPUTI, KECAMATAN PACET, KAB.CIANJUR)

Monitoring the development of built-up areas can be done by observing remote sensing time series data such as Satellite Imagery. Google Earth Engine (GEE) makes it easy for users to access satellite image data, data processing and data analysis. GEE provides various machine learning algorithms to extract land cover data. This research aims to analyze the development of built-up areas using time series of remote sensing data, namely Sentinel 2A images recorded in 2019 and 2023 and comparing Random Forest (RF), Classification and Regression Tree (CART), Support Vector Machine (SVM) and Gradient Tree Boost (GTB) algorithms and predicts built-up areas in 2027. Based on the results of this research, RF is the algorithm with the highest accuracy in mapping land cover in Ciputri Village with an Overall Accuracy (OA) of 92% and a Kappa Coefficent (KC) of 0.89 in both the 2019 and 2023 classification results, while the lowest accuracy is the SVM algorithm. A comparison of the built-up land area between the 2019 and 2023 classification results shows a decrease in the built-up land area of 3.08 ha. Meanwhile, the prediction results for 2027 show an increase in built-up areas to 114.72 ha.

Monitoring and predicting development of built-up area in sub-urban areas: A case study of Sleman, Yogyakarta, Indonesia

Monitoring built-up areas in the previous year and possible predictions for the following year are important in planning regional development and controlling the expansion of built-up areas. This study detects changes in the built-up area (2018–2022). It predicts the future (2026) using Landsat satellite imagery in the Sleman Regency, Yogyakarta Special Region, Indonesia study area. Mapping built-up areas is identified using the Normalized Difference Built-Up Index (NDBI). Vegetation conditions were analyzed using the Normalized Difference Vegetation Index (NDVI). Changes in the built-up area are predicted using the CA-Markov chain model for 2026. The prediction is calibrated by comparing the simulated map with the results of the classification of built-up areas in 2022. The research findings show that the built-up area has increased by 12.84 % from 2018 to 2022 and is predicted to increase by 15.48 % in 2026. The existence of built-up areas has an influence on land surface temperatures where the analysis results show a moderate correlation between NDBI and LST, namely 2018 (R2 = 0.401), 2019 (R2 = 0.323), 2020 (R2 = 0.401), 2021 (R2 = 0.415), and 2022 (R2 = 0.384). The higher the NDBI value, the higher the LST value, and vice versa. Therefore, regional development planning, mainly built-up areas, is an important recommendation for decision-makers in the study area.

URBAN LANDSCAPE TRANSFORMATION: LAND COVER CHANGE ANALYSIS IN SIRIMAU SUB-DISTRICT, AMBON CITY

This study aims to analyze the Pattern of Land Cover Change in Sirimau District, Ambon City, Indonesia. The introduction of the research discusses the importance of understanding the dynamic interaction between human activities and land resources in the context of spatially distributed land cover. The research method used was descriptive quantitative with a spatial approach, conducted in Sirimau Sub-district, Ambon City, which experienced high population growth and development of built-up areas. Satellite image data analysis was used to identify patterns of land cover change from 2014 to 2024. The results showed the dominance of agricultural land in 2014, with certain areas converted to residential and built-up land in 2019 and 2024. The findings provide valuable insights in understanding the dynamics of land cover change in Sirimau sub-district and its relevance in sustainable land resource management.

Analisis Perkembangan Kota Bukittinggi dan Sekitarnya Tahun 2005-2022 Menggunakan Metode Spatial Metric

The aim of this research is to: 1) Understand the physical development of Bukittinggi City and its surroundings in the period 2005-2015 and 2022, 2) Understand the spatial pattern of development of Bukittinggi City and its surroundings. This type of research is quantitative, using secondary data, namely SPOT images for the period 2005, 2015 and 2022. The analysis technique used is manual digitization to produce maps of built-up areas and metric spatial analysis to determine city development patterns using 5 methods, namely: PD , NP, LPI, LSI, and MPS. The overlay method is used to obtain patterns of development of built-up land regarding slopes, roads, distribution of facilities and population development. This research found: The physical development of the City of Bukittinggi and its surroundings in the period 2005-2022 shows a lot of development and improvement, which can be seen by the shrinking of non-built-up areas in each time period tending towards Urban Sprawl marked by an increase in built-up areas which spread towards the outskirts of the city. due to population growth. The development of built-up areas in the city of Bukittinggi and its surroundings tends to grow in areas with flat and gentle slopes and tends to gather on main and central roads, so it can be concluded that the development of the city of Bukittinggi and its surroundings is still concentric.

Perkembangan Lahan Terbangun Kota Pekanbaru Tahun 2000-2020

This research aims describe the development of built-up area and identify trends the development of built-up area in Pekanbaru City in 2000-2020. The approach in research is descriptive quantitative with stages of temporal landsat image interpretation, field verification, and spatial analysis. The study population is the entire pixel data in satellite imagery with sampling techniques for the image interpretation process. Supervised classification is used in the interpretation process, kappa index with 22 sample points is used to test the accuracy of the interpretation results, and map overlays are used in spatial analysis. The results of the analysis show that in the last two decades (2000-2020) the built-up area in Pekanbaru City increased by 13,45% (85,99 km2) with an average increase of 0.67% (4,30 km2) annually. Spatially, the distribution of development of built up area is unevenly, but forms a patterns and directions that tends to be the same, namely the pattern of spreading from the city center to the fringe area with development trends in the south and southwest following the main road route.

An Evaluation of the Impact of Urban Growth on Runoff in Abeokuta, Southwestern Nigeria

Abeokuta is one of the urban areas in Nigeria with high cases of runoff fatalities in recent times, indicating the need for a proper understanding of prominent runoff-generating mechanisms, as well as the causative factors. Consequently, this paper, which is focused on flood-prone settlements, is aimed at providing information on the impact of change in urban land use on runoff in the study area. The specific objectives were to determine the change in average runoff in terms of the Soil Conservation Service Curve Number (SCN-CN), and to assess the impact of urban growth on runoff in the area. The SCN-CN was derived from the 30m spatial Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM). At the same time, land cover change was estimated using Landsat TM+ from 2000 and Landsat 8 OLI from 2018. Data were analysed using the Hydrologic Engineering Centre’s Hydrologic Modelling System (HEC-HMS) and ArcGIS (version 10.1). The results showed a 14% increase (from 39% in 2000 to 53% in 2018) in urban areas of selected catchments; and a relative increase in average CN from 76.9 units in 2000 to 79.9 units in 2018, suggesting an increase in runoff potential relative to the increase in urban/impermeable space in the catchment. Annual discharge depth increased from 891.84mm to 956.9mm, while peak discharge increased from 161.9m3 /s to 196.2m3 /s. Runoff in the study area tends to exhibit spatial variability that is similar to the pattern exhibited by built-up areas across the study area, suggesting that the development of built-up areas can explain runoff exacerbation in part of the area. The use of SCN-CN and satellite images makes the approach reproducible, and the mixed methods of geographic information system and hydrological model revealed the spatial variability typically hidden in stand-alone hydrological models. The paper recommends further studies with the use of less coarse datasets, as well as the implementation of policies that focus on sustainable urban growth in the region, and other cities.

Spatiotemporal Analysis and Prediction of Urban Land Use/Land Cover Changes Using a Cellular Automata and Novel Patch-Generating Land Use Simulation Model: A Study of Zhejiang Province, China

Urban land use/land cover (LULC) monitoring and prediction are vital for understanding the spatiotemporal change dynamics of future land uses. They provide the necessary data for effectively planning and managing natural land resources. In this study, we analyzed and simulated the changes in urban LULC within Zhejiang Province, a region in China experiencing rapid urbanization. By exploring the historical change dynamics of the region, we observed substantial transformations in the extent of built-up areas, forests, and agricultural land from 1995 to 2020. Specifically, the study area witnessed the expansion in urban built-up areas by approximately 6126.93 km2, while forests and agricultural land witnessed decreases of 3252.47 km2 and 2885.13 km2, respectively. To predict the study area’s future LULC, a cellular automata (CA) model was utilized in combination with an advanced patch-generating land use simulation (PLUS) model. This integrated approach allowed for multiple land use predictions based on different scenarios. Under the baseline scenario (BLS), it was projected that the area of urban expansion in Zhejiang Province would be approximately 4501.62 km2. However, under the scenario of cultivated land and ecological protection, i.e., CLPS and EPS, urban growth was observed to be 538.64 km2 and 1776.16 km2, respectively. These findings indicate that the extent of built-up area development in Zhejiang Province is significantly reduced when the CLPS and EPS are implemented in comparison to the BLS. Therefore, policy interventions are crucial to protect agricultural land and conserve ecological areas. This research provides the scientific data needed for proper planning and serves as reference data for other regions with similar rapid urbanization.

Assessing the impact of urban land expansion on ecosystem carbon storage: A case study of the Changzhutan metropolitan area, China

The extension of urban development can encroach onto ecologically important land, such as forests and farmland, and have a significant impact on regional ecosystem carbon storage. Although there has been extensive research on the carbon storage response to land use changes, limited exploration has been conducted on the changes in ecosystem carbon storage resulting from the expansion of construction land.. In the current research, we analyzed the characteristics involved in the growth related to built-up space in the Changzhutan metropolitan area from 1990 to 2020. Using the InVEST model, we evaluated the resulting effects on ecological carbon sequestration, and using the PLUS model, we simulated the effects of building land expansion under four scenarios: natural development, farmland protection, ecological protection, and comprehensive development. Additionally, our aim was to quantify the possible implications of the development of built-up areas on regional carbon storage. (1) The Changzhutan metropolitan area expanded its construction land by 721.58 km2 from 1990 to 2020, with the expansion mainly concentrated in the urban fringe areas, and the land type mainly changed from forests and farmland to construction land. (2) The ecosystem carbon sequestration in the Changsha-Zhuzhou-Xiangtan metropolitan area decreased by 22.66 × 106 t from 1990 to 2020, with the most significant decrease occurring from 2005 to 2010 when the expansion of construction land was 284.43 km2. (3)By 2030, the Changzhutan metropolitan area is projected to expand its construction land by 312.05 km2, 175.65 km2, 68.21 km2, and 68.90 km2 under the scenarios of natural development, farmland protection, ecological protection, and comprehensive development, respectively. Land use change in each scenario is expected to cause carbon storage losses of 10.01 × 106 t, 11.01 × 106 t, 2.07 × 106 t, and 1.95 × 106t, compared to 2020. (4) Over the investigation time span, expansion of construction ground in metropolitan Changzhutan had a negative impact on regional carbon storage, reaching a stable state from 2005 to 2020, and the effect pertaining to growth from the area of development upon the carbon accumulation of regional ecosystems under the comprehensive protection scenario in 2030 was −0.46. Considering the spatial heterogeneity analysis of regional carbon storage, this scenario would substantially upgrade the functional area surrounding the region and increase the biological system stabilization, which is conducive to achieving carbon neutrality goals.

Urban footprint extraction derived from worldview-2 satellite imagery by random forest and k-nearest neighbours algorithm

High-resolution spatial data regarding the distribution of urban areas is fundamental concerning regional spatial planning and monitoring the development of built-up areas. Many researchers have extracted urban footprints using low to medium-resolution satellite imagery. For applications on a global and regional scale, low to medium image resolution are suitable. Nevertheless, higher image resolution is required on a local scale, down to a small urban area level. This study objective to mapping the built-up land and examine the accuracy of 2 machine learning algorithms. This investigation employs a novel approach that combines the utilization of remote sensing technology with the implementation of machine learning algorithms. We use Random Forest (RF) and K-Nearest Neighbours (KNN) machine learning algorithms. This study used a high-resolution (0.5 meter) satellite image derived formWorldView-2. We only used three visible channels (Red-Green-Blue) with a 450 – 690 nm wavelength. Integrating remote sensing and machine learning can adequately investigate the urban footprint area. Based on this research, the RF better than KNN algorithm. It is proven by the confidence iteration value and the overall accuracy of the RF and KNN algorithms, i.e., 73.32%, 71.99%, 82.08%, and 77.89% respectively. Based on WorldView-2 imagery acquired in 2015, the proportion of urban footprint is still lower than the green area with 41.75%: 58.24%, especially in the centre of the capital city of Bali Province. Such conditions are undoubtedly different in other urban areas in Bali. Even one city area, e.g., West Denpasar, which almost the entire area is dominated by the urban footprint area. Such conditions are a particular concern for the local government in managing future spatial planning regulations. It is recommended that the proportion of green open space remains a priority so that there are no environmental problems in urban areas (e.g., air pollution, flooding due to runoff problems, etc.).

Spatiotemporal changes of green cover pattern in urban areas of Batticaloa, Sri Lanka

Sri Lanka’s cities are subject to varying green cover patterns due to rapid population growth in urban areas. Over the last two decades, urbanization has driven the rampant development of built-up areas, predominantly residential development. As a developing city in Sri Lanka, Batticaloa involves rapid construction development after the civil war. This trend increases pressure on green cover, making the city population more susceptible to urban challenges. This study investigates the spatial and temporal dynamics of green cover changes in selected urban areas in Batticaloa, Sri Lanka, from 2000 to 2020. Three (3) nearby areas were selected for the study, namely Kallady, Arayamapthy, and Kattankudy. ArcGIS Normalized Difference Vegetation Index (NDVI) analysis was used to identify the green cover pattern and changes using Landsat Images. The changing patterns were detected between 2000 - 2010 and 2010 – 2020. The study reveals that the total loss of green cover was high in the first decade, approximately 44.15%, which has slightly increased about 12.58% in the second decade of the selected years. The Kattankudy zone shows a high built-up density, while the Arayampathy zone is low. This pattern has led to the further loss of green cover in the Kattankudy zone, while the other two (2) zones are significantly mixed with the green cover. A significant proportion of the green cover is occupied by the newly built-up areas, mainly residential areas throughout the period. Thus, the green cover conservation should prioritize the built-up expansion to protect the environment. The residential green cover is essential for humans’ daily lives, and one of the most vital mechanisms in the urban green cover system cannot be ignored. This finding can contribute to the land use planning application and make policies to conserve the green cover in the future.

Unplanned urban built-up growth creates problem in human adaptability: Evidence from a growing up city in eastern Himalayan foothills

The unprecedented and unplanned urban growth in Indian cities is a great threat to the sustainable urban development and urban resilience. Therefore, the present study emphasized in identifying rapid urban growth, future resilience, and human adaptability in Siliguri Municipal Corporation (SMC) area. For this purpose, the land use land cover (LULC) map has been prepared for 2001, 2011 and 2021 and then cellular automata-Markov chain (CA-MC) with four suitable fuzzy factors have been incorporated to simulate the prediction of built-up areas in 2031. Finally, future human adaptation susceptibility zone map has been prepared using the prediction-adaptation-resilience (PAR) approach. The built-up area has been increased by 10.25 km2 in last 20 years while other natural landscape has been reduced by the encroachment of urban pavement surface towards peripheral regions. The ward wise human adaptability zone indicates that total 14 municipal wards will be in most vulnerable situation within 2031. Consequently, water logging, sewage issues, congestions, environmental issues, solid waste issues will be the most challenging issue. So, the outcome of this study may be useful for the policy makers to take proper planning for built-up area development and give attention to increase the green space in the down town region.

Wind aspects in built environment

The dynamic development of built-up areas observed in the last few decades resulted in strong environmental transformations, especially in terms of climate phenomena. One of the factors which significantly affects the climate and bioclimate of urban areas is wind. Wind can cause discomfort to pedestrians or heat loss in buildings, if the wind speed around buildings is too high. The paper presents two examples of research conducted by the author, related to the issues of wind flow in built-up areas, based on the numerical simulations. The numerical simulations become an increasingly frequently used tool to determine the wind climate. Simulation results provide designers with important information on the influence of the buildings and their layout on the local changes in airflow. They allow testing of alternative solutions and effectiveness of various remedial measures.

THE CONTRIBUTION OF HOUSING AREA TO LAND SURFACE TEMPERATURE IN BANDUNG

Following the development of built-up areas in Bandung predominantly for housing purposes, the land surface temperature (LST) in the region has increased significantly. In urban planning, particularly in housing, environmental aspects related to LST have yet to be widely considered. The aim of this study is to identify the relationship between housing densities and LST. The information regarding elevation, density, LST and tree cover (vegetation coverage) in housing areas in Bandung have been collected. Landsat 8 satellite images were used to assess LST levels and to calculate the normalised difference in vegetation index (NDVI). Statistical analyses have been conducted to determine whether the NDVI and the housing density are factors that influence LST values. A correlation analysis demonstrates a strong inverse relationship between LST and NDVI while controlling for elevation of the housing area, with Pearson correlations of -0.575, -0.612 and -0.754. Meanwhile, an ANOVA test showed that LST comparisons at each elevation were statistically significant (p<0.05), it presents the idea that LSTs for high- density housing and medium-density housing have significant differences. The statistical test results indicate that the housing densities and the lack of urban tree cover contributes to LST. These findings are an invaluable source for spatial planning in housing areas and support sustainable development in Bandung city.

Gauging the possibility of using property tax to respond to the rapid expansion of built-up area in Depok Municipality

Over the last three decades, Depok Municipality has experienced rapid expansion of built-up area, due to the city’s strategic location as a satellite city of Jakarta that functions primarily as a dormitory town. Agricultural, plantation and vacant lands have been largely converted into different forms of built-up area. Some efforts should therefore be made to control this extensive land-use conversion. In particular, a fiscal instrument such as a property tax can be used not only as a source of city revenue, but also as a means for urban environmental control. In this study, we aim to gauge the potentiality of property tax in addressing large scale expansion of built-up area. In doing so, we employed Pearson Correlation and Moran’s Index analyses by comparing built-up area development and property tax performance in 2014 and 2019. The results indicate that property tax has not functioned very effectively as an instrument to steer built-up area expansion in Depok.

Examining the Use of Urban Growth Boundary for Future Urban Expansion of Chattogram, Bangladesh

With the rapid and unregulated nature of urban expansion occurring in Chattogram, Bangladesh, the adoption of urban growth restriction mechanisms such as the urban growth boundary (UGB) can provide a robust framework necessary to direct the development of built-up areas in a way that curtails the growth in environmentally sensitive areas of the city. Using a support vector machine (SVM)-based urban growth simulation model, this paper examines the areas of future contiguous expansion of the city to aid in the delineation of the UGB. Utilizing landcover, topographic, and population density data from a variety of sources for the past twenty years, the SVM method with the radial basis function (RBF) kernel is used to develop a model based on fourteen predictor variables. A grid-search is used to tune the hyperparameters and determine the best performance combination of the hyperparameters for the RBF kernel function used in the SVM. The final SVM model using the best performance combination of the hyperparameters indicates a high percentage agreement of 91.79% and a substantial agreement for the Kappa coefficient of 0.7699. The developed SVM simulation model identifies potential areas that are more likely to undergo urban expansion in Chattogram in the next twenty years and provides aids for a stringent and strict delineation of UGB for this region.

Quantifying the Spatial Fragmentation Pattern and Its Influencing Factors of Urban Land Use: A Case Study of Pingdingshan City, China

In the context of rapid urbanization, the phenomenon of spatial fragmentation in Chinese inland central cities is significant. The scientific measurement and evaluation of urban spatial fragmentation are conducive to its transformation, advancement, and sustainable development. Based on the fractal dimension index and Shannon index, this study measures urban spatial fragmentation in terms of form and function, respectively. In addition, multi-scale geographic weighted regression (MGWR) is used to study the influencing factors of spatial fragmentation. The conclusions are as follows: ① the measurement results of spatial form fragmentation and functional fragmentation of urban built-up areas are consistent. The fragmentation degree of the new urban area (new urban district and high-tech district) is higher than that of the old urban areas, and the urban space fragmentation degree around railways and rivers is high. The urban space fragmentation degree of coal resource concentrated distribution areas in the north is lower. The cold spot area of the fragmentation phenomenon appears in the old urban area, and the hot spot area is in the new urban area and along the railway. ② The positive influencing factors of urban spatial fragmentation in Pingdingshan city are the NDVI and the distance from CBD. The negative influencing factor is the number of bus stops per unit area. The DEM and population density have no significant impact on urban fragmentation in Pingdingshan city. ③ Among the variables with significance, its influence has a certain spatial heterogeneity. The spatial scale from small to large is the number of bus stops per unit area, NDVI, and the distance from CBD. The degree of urban fragmentation is very sensitive to the number of bus stops per unit area and the impact scale is quite small. The spatial impacts of the NDVI and the distance from CBD are relatively stable. This study provides a reference and basis for the spatial development of built-up areas of inland central cities and promotes the transformation, advancement, and sustainable development of inland central cities.

U-Net feature fusion for multi-class semantic segmentation of urban fabrics from Sentinel-2 imagery: an application on Grand Est Region, France

ABSTRACT Urban areas are increasing since several years as a result of development of built-up areas, network infrastructure, industrial areas or other built-up areas. This urban sprawl has a considerable impact on natural areas by changing the functioning of ecosystems. Mapping and monitoring Urban Fabrics (UF) is therefore relevant for urban planning and management, risk analysis, human health or biodiversity. For this research, Sentinel-2 (level 2A) single-date images of the East of France, with a high spatial resolution (10 m), are used to assess two semantic segmentation networks (U-Net) that we combined using feature fusion between a from scratch network and a pre-trained network on ImageNet. Moreover three spectral or textural indices have been added to the both networks in order to improve the classification results. The results showed a performance gain for the fusion methods in classifying several UF. However, there is a difference in performance depending on the urbanization gradient; highly urbanized areas provide a better distinction of some UF’s classes than rural areas.

Reengineering of territories and built-up areas: a conceptual framework

Introduction. The development of built-up urban areas, aimed at improving the living arrangements and standards, is implemented within the boundaries of an element of a structural plan, as well as related elements. It is important, since it affects the interests of a substantial part of the country’s population. The achievement of the goals, pursued by the national projects and programmes as socio-economic development tools, depends directly on the effective development of built-up areas. The effective development of built-up areas involves comprehensive transformation and modernization of territories and buildings on the basis of the concept of reengineering of territories and built-up areas, including methods of effective and high-quality change management.
 Materials and methods. The subject of the study is a set of measures that ensure the qualitative transformation of engineering (technological) solutions and serve as the backbone structure of reengineering in construction. The object of the study is the process of qualitative transformation of technological (technical) solutions and business processes (management decisions). It is noted that the actual focus of transformation of territories and built-up areas is implemented in the course of actions, taken within the framework of reengineering of technological processes (technical solutions), including the stages of reconstruction, renovation, technical retooling, repurposing, and reclamation. The factors, influencing the reengineering of management solutions, are provided. Features of the composition and properties of the reengineering of territories and built-up areas, characteristic of its practical implementation, are presented. Research methods include structural and functional analyses.
 Results. Current fundamental differences in the nature of regulatory impacts accompanying the traditional type of restoration (modernization), as well as impacts, made within the framework of reengineering of territories and built-up areas, are described. The authors suggest that the integrated approach of impacts, made in the process of reengineering of territories and built-up areas, is conveyed in the relationship between “property development – capital construction facilities – a technological solution”, as well as the scope and intensity of impacts. The general framework for the concept, underlying the implementation of the reengineering of territories and built-up areas, is presented.

Potential Elements of Green Infrastructure (PeGI) Inside the Core of the Village (CoV): A Case Study of Wrocław Functional Area (WFA) in Poland

This article presents a study of the elements of green infrastructure in villages located in peri-urban areas. The research focuses on the built-up areas of villages, which together with public and private green areas, are defined as the Cores of the Village (CoV). The research was based on the Wroclaw Functional Area (WFA). The main objective of the study was to identify which sites in a CoV have the potential to increase Green Infrastructure (GI) network connectivity and how these have changed with the development of built-up areas. These sites have been defined as Potential Green Infrastructure Elements (PeGI). The study was conducted over three time periods: the early 20th century, the early 21st century and future plans. The research revealed that, within the historic CoV areas, there existed PeGIs that communicated with external GI elements, but that such connections between PeGIs and GI elements have not been taken into account in future development plans. Furthermore, increases in the area of built-up land have not been matched by an increase in PeGI area. However, through the creation of greenways, among other things, there is potential for shaping PeGI inside a CoV in a way which would strengthen GI structural connectivity.

ЗАРОЖДЕНИЕ РЕНОВАЦИОННЫХ ПРОЦЕССОВ В ЖИЛИЩНОЙ СФЕРЕ КРУПНЫХ ГОРОДОВ РОССИИ (НА ПРИМЕРЕ ГОРОДА БЕЛГОРОДА)

The renovation of the housing stock in large and small cities of Russia is formed due to the deterioration of the physical and moral condition of residential buildings of the last century. The main tasks of the study are to expand knowledge about the historical prerequisites of the origin of renovation processes, to form an evidence base for the effectiveness of the integrated development of territories that meet modern requirements for the urban environment (using the example of the Belgorod city). Russian and historical experience of renovation of residential buildings of European and Asian states are considered on the example of Moscow. The specifics of measures ensuring the comprehensive development of the depressed territories of Moscow are indicated. Legislative documents promoting the development of housing construction in the second half of the 20th century and modern legislation on the All-Russian renovation of residential buildings have been studied. Prospects of renovation processes implementation in Belgorod are considered. Organizational and technical aspects of the complex development of the residential space of the regional center have been determined. The first steps of renovation processes in the part of residential development are evaluated. Examples of the implementation of the development of built-up areas of the city are given, available scenarios for the renewal of residential areas are outlined. The physical and moral condition of medium-rise houses of the first mass series is analyzed. Possible measures for the reconstruction of the housing stock of the development of the 60s of the last century have been identified. Options for development of renovation processes of residential development are presented.