Spatial Planning Research Articles

Flood prevention benefits provided by Canadian natural ecosystems

The escalating impacts of climate change have heightened concerns about the frequency and severity of natural disasters, particularly extreme flooding events. Future projections underscore the necessity for innovative flood prevention strategies, including broad-scale nature-based solutions. Here, we present the first comprehensive assessment of the flood prevention benefits provided by Canadian natural ecosystems and identify key areas crucial for human well-being. Using spatially explicit modeling, we (1) evaluated the potential runoff retention by natural ecosystems and (2) identified downstream urban and agricultural areas critically dependent on these natural benefits, particularly those in floodplains and close proximity to upstream natural ecosystems. The natural ecosystems within the top 5 % of sub-basins, representing regions with a high priority for conservation practices aimed at flood prevention, play a crucial role in safeguarding approximately 54 % (∼6,000 km2) of the total built-up area and 74 % (∼16,900 km2) of the total cropland situated within floodplains. Additionally, they are positioned upstream of floodplain-based urban zones belonging to 358 population centers, directly benefiting 3.7 million people (∼10 % of the Canadian population) and indirectly benefiting almost 20.1 million people (∼56 % of the Canadian population). Moreover, among Canada’s 5.2 million km2 of flood-preventing natural ecosystems, we identified a small fraction (10 %) whose loss or degradation would result in a significant (>50 %) increase in runoff. Several of these crucial ecosystems are situated in less populated northern regions, where local governments might want to incentivize conservation initiatives to support flood prevention. Our research underscores the imperative to integrate nature-based solutions into national strategies that consider the results of spatial planning analyses. Establishing other effective area-based conservation measures in the priority regions highlighted in this study can contribute towards reaching current ambitious environmental goals and provide critical flood prevention benefits. Additionally, our methods are transferable to other regions worldwide, leveraging globally available datasets and ensuring computational feasibility.

Pokrywa glebowa miasta Lublina (wschodnia Polska)

Lublin is a voivodeship city located in the Lublin Upland (Eastern Poland). The study aimed to present the spatial differentiation of soils of the city of Lublin and some of their properties. The knowledge of soil cover is very important for spatial planning and for protection and proper use of soil resources of each city. The environmental-genetic map of Lublin’s soils included in this work was made on the basis of soil-agricultural map in the scale 1:25 000 of Lublin and the soil-habitat map of the Świdnik Forest District. The soil units distinguished on the map were classified according to the Systematics of Soils of Poland (2019) and the international soil classification (World Reference Base for Soil Resources, WRB). The spatial variability of Lublin’s soils is determined by the occurrence of different parent rocks, relief, water relations, vegetation cover and human activities. The main soil units occurring within the city of Lublin include: brown soils (WRB: Eutric/Dystric Cambisols), rusty soils (Brunic Arenosols), podzolic soils (Albic Podzols), clay-illuvial soils/lessive soils (WRB: Albic/Haplic Luvisols), black earths (WRB: Gleyic Phaeozems), chernozemic rendzinas (WRB: Rendzic Phaeozems) and brown rendzinas (WRB: Calcaric Cambisols), chernozemic/black alluvial soils (WRB: Fluvic Phaeozems) and ordinary alluvial soils (WRB: Dystric/Eutric Fluvisols), peat soils (WRB: Hemic/Sapric Histosols) and murshic soils (WRB: Murshic Histosols), and technogenic soils (WRB: Urbic/Spolic/Ekranic Technosols). The grain size composition of Lublin’s soils is quite diverse, with the most common being silts, loams and sands with varying proportions of skeletal parts. The reaction of the Lublin soils studied also varies. Very acidic and acidic reaction is present mainly in podzolic and rusty soils and typical acid brown soils. In contrast, proper brown soils are slightly acidic to neutral in the upper genetic horizons. Lessive soils also have an acid reaction in the upper genetic horizons. Fluvisols have a slightly acidic to alkaline reaction, and black earths have a neutral to alkaline reaction. The alkaline reaction is found in rendzinas and technogenic soils, in which significant amounts of calcium carbonate are present. Soil organic matter is mainly accumulated in organic soils (peat and muck soils), as well as in the surface organic horizons (O) of forest soils. In the mineral soils of Lublin, the highest content of organic carbon (C-org) was found in such soils as black earths, chernozemic rendzinas, chernozemic alluvial soils and in some technogenic soils. The usable quality of Lublin’s soils is high. There is a phenomenon of management of land with high bonitation classes for non-agricultural purposes, despite the high fees for excluding such land from agricultural production.

Incorporating functional traits with habitat maps: patterns of diversity in coastal benthic assemblages

Benthic species assemblages are groups of species that co-occur on the seafloor. Linking assemblages to physical environmental features allows for understanding and predicting their spatial distribution. Species identity and abundance are commonly quantified using a taxonomic approach to assess benthic diversity, yet functional traits that describe the behavior, life history, and morphology of a species may be equally or more important. Here, we investigate the biodiversity of five benthic species assemblages in relation to their habitat and environmental conditions in an Ecologically and Biologically Significant Area (EBSA) along Canada’s east coast, using both a taxonomic approach and biological traits analysis. Random Forest regression was applied to map spatial patterns of functional and taxonomic diversity metrics, including richness, Shannon index, and Rao’s quadratic entropy. We evaluate discrepancies between related taxonomic and trait measures, and the community-weighted mean of trait data was calculated to characterize each assemblage. Taxonomic and functional richness – representing the number of species and the species community volume in the trait space, respectively – showed similar spatial patterns. However, when considering diversity, which also accounts for the relative abundance and differences among species or traits, these patterns diverged. Taxonomically different assemblages exhibited similar trait compositions for two assemblages, indicating potential trait equivalencies, while one assemblage exhibited traits potentially indicating sensitivity to human activity. The taxonomic and functional metrics of richness and diversity were low close to the coast, which could be indicative of disturbance. Consideration of functional metrics can support spatial planning and prioritization for management and conservation efforts by assessing the sensitivity of traits to different stressors.

A global assemblage of tax haven clusters: profit shifting, tax dodging and money laundering

In this paper we explore a selection of tax haven clusters in the US and Europe as diverse but recognisable species of some fifty of the phenomena worldwide that have been seldom studied from an economic geography or spatial planning viewpoint. We treat the objects of study as being almost perfect expressions of the classical, canonical cluster configuration. They are: spatial agglomeration, untraded as well as market dependencies, small and medium-sized enterprise status, associative or agentic relationships, interaction with large firms inside or outside the cluster and knowledge acquisition, advisory, consultancy and knowledge translation services from research and innovation intermediaries - public and/or private. However, we think their characteristics demand further recognition of the interactive and often innovative communication networks by means of which these cluster incumbents interact globally. This is because they are set within a worldwide system that can be conceptualised as an exemplar of the well-known construct known as an ‘assemblage’ (Deleuze and Guattari, 2004a). Unlike more recent treatments from De Landa (2019) and others, we try to concentrate on the motive power of the ‘agentic’ impulses of ‘desire’ that motivate human action (e.g. regarding ‘God, Gold or Glory’ as commonly-rehearsed motivators for colonialism of various kinds). It has been more common to use ‘assemblage theory’ to analyse the interlocking ‘machinic’ elements of complex systems like power networks or laboratory interactions. To unlock the mysteries of system interlocking in our selected tax havens, which comprise Wilmington, Delaware (US), Ireland (EU) and Gibraltar (former EU, now British Overseas Territory) – post-Brexit - occupying a ‘quantum’ space ‘in which both the colonial and post-colonial find expression’ (Perera, 2021). Methodologically, we seek ‘pattern recognition’ to identify the lineaments that explain these clusters and the ‘agentic’ actors that motivate them.

Urban growth simulation guided by ecosystem service trade-offs in Wuhan metropolitan area: Methods and implications for spatial planning

The effective integration of ecosystem services (ESs) and urban growth simulation is crucial for spatial planning decisions that support sustainable and high-quality development. Interactions (i.e., trade-offs, synergies, and irrelevance) generally exist among ESs, however, few studies have been done on the methodology for simulating urban growth that optimizes the synergistic effect of ESs. In this study, the Wuhan metropolitan area was taken as the research area. Four key ESs in 2000, 2010, and 2020: water yield (WY), carbon storage (CS), habitat quality (HQ), and soil retention (SR) were evaluated by using the InVEST model. Then the ordered weighted averaging (OWA) method was applied to optimally allocate ESs trade-offs and identify ecological priority protection areas (EPPAs). Finally, the PLUS model was used to simulate urban growth scenarios under different levels of ESs protection constraints and propose spatial planning strategies. The results revealed the following. (1) From 2000 to 2020, the three ESs (i.e., WY, CS, and HQ) exhibited the spatial distribution pattern with high in the east and low in the west, and higher in the woodland than in built-up areas, except SR, which remained at a weak level throughout the region. (2) During the 20 years, SR and the other three ESs, HQ and CS showed a synergistic relationship; WY exhibited a very weak trade-off with HQ; and WY and CS changed from a very weak trade-off to a weak synergy. (3) Seven ecosystem service patterns (ESPs) were generated, and ESP 5 was compared as the ideal option. The weights of SR, WY, CS, and HQ in this pattern were 0.063, 0.187, 0.313, and 0.437, respectively. (4) By 2030, the built-up areas will exhibit edge expansion and interconnection development trends, with the high-constraint ecological protection scenario as the most compact mode, and the spatial structure of “two districts, one axis, four cities as one” is consistent with the development tendency. Our findings can help to enrich the method of urban growth management oriented by ecological protection, and provide a scientific basis for ecological environment restoration and land use spatial planning practices.

The impact of town planning on direct residential CO2 emissions in rural China

China's commitment to carbon neutrality by 2060 has made decarbonization a key principle for spatial planning (also referred to as urban/city/town planning). Although the mitigation effect of spatial planning in urban areas has been well documented, its significance in rural development has yet to be investigated. This paper addresses this research gap by empirically examining the influence of town planning on rural direct residential CO2 emissions (DRCEs) across 30 provinces in China. Based on various quantitative models, this study not only confirms the significant impact of town planning on rural DRCEs and the moderation effect of plan implementation capacity but also discloses that different dimensions of town planning have disparate roles in rural DRCE reduction. Additionally, regional variations in the mitigation effects of town planning on rural DRCEs were observed. The study also reveals spatial spillover effects, indicating that the influence of town planning on rural DRCEs extends beyond individual areas. Overall, China's experiences demonstrate that well-managed town planning could play an essential role in low-carbon rural revitalization or, otherwise, it may augment rural DRCEs per capita. Consequently, governments should ascribe great importance to low-carbon town planning and allocate sufficient resources to towns, especially those in the central and western regions, so that they can afford professional planning consultation and adequate staffing in plan implementation. Moreover, governments should cooperate to promote knowledge sharing and transferring of low-carbon planning.

Megabenthic Diversity Patterns on a Seamount in the Philippine Sea: Implications for Conservation Planning on the Kyushu-Palau Ridge.

The oligotrophic tropical western Pacific region is characterized by a high density of seamounts, with the Kyushu-Palau Ridge (KPR) being the longest seamount chain here. Effective spatial management plans for seamount ecosystems necessitate an understanding of distribution patterns and key environmental factors influencing benthic communities. However, knowledge regarding deep-sea biodiversity patterns over intricate topography remains limited. In this study, we investigated a seamount with a water depth of 522 m at the summit located in the southern section of KPR. Survey transects were conducted from 522 m to 4059 m. By analyzing video-recorded data obtained by a human-occupied vehicle (HOV) during dives and environmental variables derived from bathymetry, distinct assemblages were identified through noise clustering. α- and β-diversity patterns within the seamount megabenthic community were analyzed across the depth gradient, along with investigation of their environmental drivers. A total of 10,596 megafauna individuals were documented, categorized into 88 morphospecies and statistically separated into six distinct community clusters using noise clustering analysis. Species abundance and richness were highest within the 700-800 m water depth range, declining notably beyond 2100 m, indicating a critical threshold for habitat classification in this region. The β-diversity of megabenthic communities was high (0.836). Although β-diversity patterns along the depth gradient were mostly dominated by differences in species richness, the contribution of species replacement increased with depth, becoming dominant at depths greater than 3000 m. Depth emerged as the primary driver of spatial variation in community structure, while near-bottom current velocity, topographic parameters (bathymetric position index, slope), and substrate type also influenced the formation of microhabitats. The study highlights the depth gradients, thresholds, and other intricate environmental factors shaping the spatial heterogeneity of these communities. It provides valuable insights for the future development of effective survey and conservation strategies for benthic biodiversity on the KPR.

Towards data-driven tropical forest restoration: Uncovering spatial variation, interactions and historical management effects on nutrients along soil depth gradients

Data scarcity hinders global conservation initiatives, and there is a pressing demand for spatially detailed soil and species data to restore human-altered tropical forests. We, therefore, aimed to generate foundational soil environment and habitat suitability data and high-resolution soil maps to aid restoration efforts in a critical ecosystem of the threatened Indo-Burma Biodiversity Hotspot region, i.e., Tarap Hill Reserve (THR) in Bangladesh. Using multiple soil depths and vegetation data, we answered three major questions. (QI) How do spatial distribution and the relationships between soil physicochemical properties (i.e., pH, sand, silt, and clay percentages, organic carbon, and nutrients – N, P, K, Ca, Mg, Fe, and Zn) vary from surface to deeper soils (top 1 m)? (QII) How do different forest management interventions, i.e., old-growth forests (OGF), mixed plantations (MXP), and mono-specific plantations (MOP), influence soil properties, nutrients, and carbon in different soil depths? (QIII) Which spatial interpolation methods are best suited for making more accurate soil property predictions at different depths? Our analyses reveal decreasing availability of critical nutrients like N, P, Mg, and Fe from surface to subsurface soils, while pH, soil organic carbon, and clay content increased with depth. Several soil properties showed significant interactions, although the strength of the interactions changed from surface to deeper soils. Besides, forest management interventions significantly influenced soil functionality by having higher nutrient availability and soil organic carbon in OGF than MXP and MOP. Predictive performances of the deterministic and geostatistical interpolation methods varied for different soil properties in different soil depths, and soil maps revealed substantial heterogeneity in the distribution of soil properties across space and along depths. This study represents a pioneering step in data-driven tropical forest restoration, and our novel findings and high-resolution soil maps could guide future studies focusing on species habitat preferences, restoration ecology, and spatial conservation planning in the Indo-Burma Biodiversity Hotspot region and elsewhere in the tropics.

Landslide susceptibility assessment along highways (SH-12 and NH-717A) in Darjeeling Himalayas

Landslides are the utmost damaging natural along with anthropogenic hazards which cause huge damage to assets and human lives in hilly environments all over the world. The key aim of this study is to explore landslide susceptibility (LS) maps along highways (SH-12 and NH-717A) in the Darjeeling Himalayas, India. Four data-driven bivariate statistical models (BSMs) were used to develop LS maps based on geospatial techniques. A total of 90 (100%) polygons with different size of landslide locations were identified to develop landslide inventory/distribution (LI/LD) map by incorporating Google Earth and satellite imageries, and filed investigation through the global positioning system (GPS). The LI/LD map is distributed into testing 30% (27 landslide locations), and training 70% (63 landslide locations) of the models. Eighteen landslide causative factors (LCFs) were selected to develop LS maps. Multicollinearity analysis showed that there is no collinearity problem in the LCFs. The receiver operating characteristics (ROC) curve and frequency ratio (FR) value techniques were applied for validation. The relative importance of each LCF for each model has been measured using Jack-knife test. The LS maps were divided into six landslide susceptibility zones (LSZs). The ROC curve showed the accuracy of the LSZ maps is 93.50% for FR, 85.90% for evidential belief functions (EBFs), 81.80% for fuzzy membership (FM) using FR, and 77.20% for FM using cosine amplitude (CA) approaches respectively. Among all models, the FR model showed the highest percentage of accuracy for LS assessment and prediction. The FR values of six LSZs rise from very low to very high LSZs which indicate a positive correlation between LSZs and FR values. The results of Jack-knife test showed that terrain ruggedness index (TRI) factor has the highest relative importance for all models in LSZ mappings. The study findings will help to the planner, and policymakers for spatial planning, implement slope management strategies, land use management in mountainous environments.

Enhancing crop production in the Haihe Basin while addressing challenges related to water quantity and quality

To tackle the challenge of ensuring food security while managing water availability and quality constraints in the Haihe Basin, a critical grain-producing region in China with a dense population and severe water degradation issues, we have developed a comprehensive spatial optimization (CSO) strategy. This approach integrates various crop and soil management practices, land consolidation, and cutting-edge breeding technologies. It also uses a spatial planning model based on linear programming, considering water quantity and quality constraints. Our research shows that crop yields may drop by 14 % (3780 Kt) compared to levels in 2017 due to restrictions on groundwater extraction and nitrogen (N) concentrations in leaching or runoff. However, by strategically maximizing overall crop yields through the integrated CSO strategy without changing the crop production structure, the total crop yield could potentially increase by 81 % (21,817 Kt) while using 3.0 % (86 Kha) less cultivated land than in 2017. This would help to fulfill the projected food demand in 2050. If the integrated aims to minimize the sown area after fulfilling the demand for crops in 2050, around 28 % of the sown area, or 820 Kha cropland, could be reduced compared with 2017. This reduction may save more land for natural conversation. Furthermore, total N losses, including ammonia, nitrous oxide emissions, runoff, and leaching, could be reduced by 23 %–43 % (139–252 Kt), depending on the specific optimization strategy goals. The stepwise integrated optimization strategy provides a feasible framework for the Haihe Basin, enabling the maintenance or even enhancing current crop yields while safeguarding water quality and quantity.

Drought risk assessment on arid region under different socioeconomic scenarios: A case of Loess Plateau, China

Quantitative understanding of drought risks on arid region is vital in drought risk mitigation and ecological restoration. However, no study has been conducted on the drought risk variance between different shared socioeconomic pathway (SSP) scenarios and China’s dual carbon goals scenario on arid region. This study evaluates drought risks of Loess Plateau between the year of 1980–2100 based on the Coupled Model Intercomparison Project phase 6 data sets and the United Nations International Strategy for Disaster Reduction drought risk assessment framework. The average values of the drought risk index in four scenarios during the projection period (2030–2100) are 0.29 (±0.026) for the low carbon emission scenario, 0.257 (±0.019) for the China’s dual carbon target scenario, 0.232 (±0.057) for the medium carbon emission scenario, and 0.248 (±0.059) for the high carbon emission scenario, which are higher than the historical period (i.e. 1980: 0.210; 2020: 0.215). Accordingly, the Loess Plateau will have severe drought risks in the future. In the zone of increased drought risk indices on the Loess Plateau, the areas of woodland and croplands increased, whereas the area of grasslands increased in the zone of decreased drought risk indices. China’s dual carbon goals (i.e. SSP1-2.6) scenario has the smallest degree of variability in drought risk, which is the most reliable pathway of across the four scenarios. We emphasize the potential of spatial planning based on regional characteristics and creating ecological buffer zones for endemic biome habitats to address the uncertainty of drought risk in arid and semi-arid regions like the Loess Plateau.

Investigating the efficacy of a fast urban climate model for spatial planning of green and blue spaces for heat mitigation

Problems caused by urban heat have prompted the exploration of urban greenery and blue spaces for heat mitigation. Various numerical models can simulate heat-related processes, but their use as support-tools to urban planners remains underexplored, particularly at the city-scale, due to high computational demand and complexity of such models. This study investigates the spatial relationships between urban heat, urban form and urban green and blue spaces with the fast climate model TARGET (The Air-temperature Response to Green/blue-infrastructure Evaluation Tool), which only requires minimal inputs of standard meteorological data, land cover and building geometry data. Using the City of Zurich as our case study, we: (i) validated the TARGET model against air temperature measurements from private sensor networks, (ii) performed a sensitivity analysis to identify key variables affecting urban heat, and (iii) investigated urban heat relationships with blue-green cover at locations frequented by pedestrians. Presence of urban green and blue spaces across the region shows potential for reducing local air temperatures by up to 5.2 °C (with urban forest). Investigating this relationship at different locations in the city revealed key districts that should potentially be targeted for reduction of pedestrian heat-impacts, due to their high pedestrian traffic, fewer green and blue spaces and high daytime air temperatures. Our results not only provide insights into the cooling effect of different amounts of green and blue features in the urban environment, but also demonstrates the application and integration potential of simplified models like TARGET to support the planning of more liveable future cities.

Assessing diurnal land surface temperature variations across landcover and local climate zones: Implications for urban planning and mitigation strategies on socio-economic factors

Rising temperatures and rapid urbanization globally reinforce the need to understand urban climates. We investigated the influence of land cover and local climate zones (LCZs) on diurnal land surface temperature (LST) in various seasons in greater Delhi region, India, and their implications on socio-economic factors. Day LST was the highest in the summer and night LST in the monsoon, which also had the lowest diurnal differences in LST. Higher height and density of built-up features contributed to greater heat at night. During the day, open built-up and vegetated areas experienced relatively less heat than their compact equivalents. The lowest diurnal difference was in medium height compact urban zones and tall vegetation. Social inequity in access to urban cooling was indicated by large low-income and heat-vulnerable populations inhabiting the hottest LCZs. This research highlighted that even in semi-arid and subtropical climates, spatial planning policy should consider both the seasonality and diurnal differences in temperature as much as appropriate morphologies for design of thermally comfortable and climate resilient urban spaces. These policies should address the evidenced social inequities in heat exposure to reduce the adverse health impacts on vulnerable groups and therefore contribute to wider societal and economic benefits of healthier populations.

Simulation of the future evolution track of “production–living–ecological” space in coastal cities based on multimodel coupling and wetland protection scenarios

Coastal cities hold a special position in the fields of production, living, and ecological research because of their unique wetland resource advantages. However, with global urbanization and rapid economic development, conflicts among production, living and ecological land are prevalent in coastal cities in the process of maintaining sustainable wetland resources and further developing the social economy. By establishing an SD-PLUS-CCD coupling model, this paper analysed the evolution characteristics and driving mechanism of the production–living–ecological space (PLES) and the effects of wetland protection (WLP) on promoting or inhibiting the coordinated development of the PLES in Dongying city during 2005–2060. The results show that (1) from 2005 to 2020, the increase in urban population resulted in a significant transfer of arable land and a reduction of 914 km2 in production space (PS); (2) from 2020 to 2060, under the WLP scenario, the conversion of wetland ecological space will reduce the PS and living space (LS) by 193.92 km2 and 107.14 km2, respectively, and increase the ecological space (ES) by 327.52 km2; and (3) wetland protection has an inhibitory effect on the coordinated development of PLES in the study area, and the total proportion of noncoordinated areas of PE and living–ecological space will continue to increase during the simulation period. This paper provides a solid theoretical support for the sustainable management and protection of wetlands in coastal cities and possible PLES conflict patterns and provides a scientific basis for future territorial spatial planning and policy balance analysis.

Recommendation for Self-Help Housing Stimulus Assistance (BSPS) Recipient Using Multi-Criteria Decision Making Methods

The Housing and Settlement Area Office aims to improve the accuracy and efficiency of selecting beneficiaries for the Self-Help Housing Assistance (BSPS) program by using the Weighted Product (WP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. This study was conducted in Sungkai Tengah Subdistrict, North Lampung, involving six criteria: land ownership, employment, house condition, income, independence, and household size.The WP method is used to determine the weight of each criterion by calculating the product of the criteria values raised to the power of their respective weights, which helps in ranking the alternatives. TOPSIS is applied to identify the best alternative by comparing the geometric distance of each option to the ideal solution, which is either the maximum or minimum value of each criterion The results indicate that the WP and TOPSIS methods can provide more objective and transparent rankings. The application of these methods resulted in the highest ranking for ID V3 with a vector V score of 0.1317. The decision support system developed from this research is expected to assist the Housing and Settlement Area Office in distributing aid more accurately, fairly, and efficiently, thereby supporting the government's goals in improving housing quality and spatial planning

ТЕОРЕТИЧНИЙ АНАЛІЗ ПОНЯТТЯ РЕГУЛЯТОРНА ПОЛІТИКА У ПЛАНУВАННІ ТА ЗАБУДОВІ МІСТА: ОСНОВНІ ПІДХОДИ ТА СУЧАСНІ ТЕНДЕНЦІЇ

Regulatory policy in the field of urban planning and development is a key element of public administration aimed at ensuring economic stability, social welfare and sustainable development. In the conditions of globalization and intensive technological progress, effective regulation of urban planning processes is becoming more and more important for solving modern challenges. The purpose of this study is to carry out a theoretical analysis of the concept of regulatory policy in urban planning and development, to study the main approaches to its implementation, as well as to determine modern trends and opportunities for adapting international experience for Ukraine. In particular, the research aims to identify effective models of regulatory policy that can be integrated into national legislation and practice to improve the management of urban development. The research uses a comprehensive approach, which includes the analysis of scientific publications, comparative analysis of regulatory policies of different countries, methods of critical literature review and data synthesis. Special attention is paid to the experience of countries such as the USA, Germany and Singapore, where various approaches to the regulation of urban planning processes are used. The analysis showed that regulatory policy in urban planning and development is a multifaceted phenomenon, which includes such basic approaches as zoning, strategic spatial planning, energy efficiency, integration of transport infrastructure and active involvement of the public in the decision‒ making process. Modern trends in regulatory policy have been identified, including innovative approaches to planning, the use of digital technologies, an emphasis on sustainable development and environmental safety. A comparative analysis of the regulatory policies of the USA, Germany, and Singapore made it possible to identify effective models that can be adapted to the conditions of Ukraine. The study confirmed that an effective regulatory policy is an important prerequisite for sustainable economic development, social stability and protection of citizens' rights. Further research should focus on the integration of digital technologies into regulatory processes, improvement of control and monitoring mechanisms, which will contribute to the sustainable development of cities in Ukraine.

POSSIBILITIES OF CREATING TOURIST AND RECREATIONAL COMPLEXES BASED ON THE LANDSCAPE CONDITIONS OF THE MOUNTAINOUS DISTRICTS OF THE ALMATY REGION, KAZAKHSTAN

The Almaty region, which is rich in natural landscapes, was established again in 2022. In this regard, the importance of regional spatial planning is taking on new forms. Considering the unique landscape potential, this project aims to create a framework for developing tourist and recreational complexes in the Uygur, Kegen, and Raiymbek regions. Creating a landscape diversity database to classify recreational resources; developing a typology for tourist and recreational complexes, considering the landscape's features and the tourism specializations. The research methods used in this study include field observations and landscape descriptions provided by the authors. A classification method has been developed to divide recreational resources into groups and sub-groups, determining their locations. The process of the developed typology is based on examples of specific types of tourist and recreational activities, as well as existing and potential tourist areas in the Almaty region and the Republic of Kazakhstan. The theoretical and methodological basis for the proposed classification and typology is based on the work of various authors and materials from the National Science Foundation of Kazakhstan. Issues of the possibilities of agricultural enterprises to provide tourists with local, natural food products have been analy zed. Based on these factors, recommendations were formulated for further developing promising tourist and recreational complexes in these areas. All authors have read and agreed to the published version of the manuscript.

Evaluating Flood Damage to Paddy Rice Fields Using PlanetScope and Sentinel-1 Data in North-Western Nigeria: Towards Potential Climate Adaptation Strategies

Floods are significant global disasters, but their impact in developing countries is greater due to the lower shock tolerance, many subsistence farmers, land fragmentation, poor adaptation strategies, and low technical capacity, which worsen food security and livelihoods. Therefore, accurate and timely monitoring of flooded crop areas is crucial for both disaster impact assessments and adaptation strategies. However, most existing methods for monitoring flooded crops using remote sensing focus solely on estimating the flood damage, neglecting the need for adaptation decisions. To address these issues, we have developed an approach to mapping flooded rice fields using Earth observation and machine learning. This approach integrates high-resolution multispectral satellite images with Sentinel-1 data. We have demonstrated the reliability and applicability of this approach by using a manually labelled dataset related to a devastating flood event in north-western Nigeria. Additionally, we have developed a land suitability model to evaluate potential areas for paddy rice cultivation. Our crop extent and land use/land cover classifications achieved an overall accuracy of between 93% and 95%, while our flood mapping achieved an overall accuracy of 99%. Our findings indicate that the flood event caused damage to almost 60% of the paddy rice fields. Based on the land suitability assessment, our results indicate that more land is suitable for cultivation during natural floods than is currently being used. We propose several recommendations as adaptation measures for stakeholders to improve livelihoods and mitigate flood disasters. This study highlights the importance of integrating multispectral and synthetic aperture radar (SAR) data for flood crop mapping using machine learning. Decision-makers will benefit from the flood crop mapping framework developed in this study in a number of spatial planning applications.

Usability of the Various Land Use Optimization Models for the Spatial Planning Purposes in the Republic of North Macedonia

The land use optimization process uses different models that generally belong to 2 groups: mathematical models and heuristics models. Variety of models shave been developed for various aims. Each of has its positive and negative sides, advantages and disadvantages. Aim of this research is to be defined usability of various land use model optimization for the purpose of spatial planning in the Republic of North Macedonia. The basic methodological tool in this chapter covers collection, study and comparative analysis of relevant literary data and evaluation of selected researches. In the absence of domestic literature, mostly literature from several countries from Europe, USA, Asia was analyzed. Then 17 models were selected for in detail analyze. To examine the possibilities of applying the optimization models described in the analyzed research. an evaluation was performed according to the following criteria: a) availability of the data used by the model, that is, the possibility of providing the data used in the model from official sources; b) number of optimization goals; c) number of land uses; d) local adaptability, which implies conformity of the goals, purposes, influencing factors, limitations and other specifics of the model with those in our conditions; e) scope of the research. More of the The reviewed papers on the analyzed optimization models and methods, marked by the authors, clearly indicate the fact or exceptional difficulty in determining the optimal land use model.

Spatial distribution and topographic gradient effects of habitat quality in the Chang-Zhu-Tan Urban Agglomeration, China

This study aimed to analyze spatio-temporal changes in habitat quality in Chang-Zhu-Tan Urban Agglomeration during the 2000–2020 period and explore its topographic gradient effects. Using land use data from this period, the InVEST model was employed to assess the spatio-temporal variations in habitat quality. The bivariate spatial autocorrelation model was used to analyze the spatial correlation characteristics between habitat quality and various topographical factors. Additionally, terrain factor analysis was utilized to study the terrain gradient effects on habitat quality in the study area. The results reveal that: (1) The primary land use changes in the study area from 2000 to 2020 predominantly involve substantial arable land and forest conversions into urban development. (2) The average habitat quality indices for 2000, 2010, and 2020 in the Chang-Zhu-Tan Urban Agglomeration stand at 0.651, 0.622, and 0.606, respectively, indicating a consistent declining trend in habitat quality. The distribution of habitat quality grades demonstrates a spatial pattern of “lower in the central surroundings, higher in the surroundings.” (3) The Chang-Zhu-Tan Urban Agglomeration shows significant positive correlations between habitat quality and topographical gradients. Spatial aggregation tendencies between habitat quality and topographical gradients primarily exhibit “high-high” and “low-low” clustering. (4) The habitat quality of the Chang-Zhu-Tan urban agglomeration exhibits a significant topographic gradient effect, primarily characterized by an increase in habitat quality with the rise of the topographic gradient. The study outcomes contribute to unveiling the spatiotemporal variations in habitat quality within the Chang-Zhu-Tan Urban Agglomeration. Moreover, leveraging different habitat types’ distinctive terrain distribution characteristics, it proposes targeted habitat conservation measures, thereby offering theoretical support for biodiversity conservation and territorial spatial planning in the study area.