Integrating Seismic and Environmental Hazard Factors into State Land Cadastral Valuation: A Case Study of the Bostandyk District, Almaty

1. Introduction

Sustainable spatial planning and objective land valuation are essential conditions for the high-quality development of modern cities. In the vast majority of countries, real estate taxation is based on mass property valuation algorithms [1]. Global guidelines established by the UN’s 11th Sustainable Development Goal (SDG 11) are gradually transforming purely fiscal cadastral registries into multifunctional mechanisms for managing spatial risks [2]. However, a different situation is observed in countries with transition economies, where a conservative and overly rigid administrative approach persists. In these countries, state land registration often exists in isolation from environmental constraints and up-to-date natural hazard maps.

In Kazakhstan, the initial allocation of municipal lands relies predominantly on spatial macro-indicators. The base value of a land parcel is determined by the prestige of its location, proximity to the city center, and the density of utility networks. Nevertheless, a purely commercial perspective on the urban environment is already proving to be inadequate. Ignoring local hazards inevitably distorts the true value of a territory. Such overvaluation of potentially high-risk areas sends false economic signals and essentially encourages the active development of tectonically unstable zones. The purpose of this study is to develop an applied methodology for incorporating factors of seismic activity and environmental deterioration into state cadastral valuation procedures. The Bostandyk District of Almaty serves as the empirical basis for this research [3,4,5,6,7,8].

The digitalization of economic processes has turned geographic information systems (GIS) and spatial analysis into routine yet mandatory tools for real estate management. In mass valuation calculations, it is no longer possible to ignore those negative externalities that the market mechanism is unable to compensate for [9,10,11]. In the scientific literature, such externalities are most often interpreted as direct financial losses for property owners. Additional health risks and an overall decline in the quality of life significantly narrow the permissible use scenarios for land parcels. Therefore, embedding parameters of environmental discomfort into cadastral algorithms becomes a key condition for social equity in determining property value [12].

Modern research is gradually shifting away from purely macroeconomic constructs toward a detailed study of local site characteristics. The necessity to consider the environmental situation and the specific features of the immediate surroundings has been convincingly substantiated in a number of recent studies [13]. In practice, however, these significant price-forming parameters continue to remain outside the scope of calculations, which naturally leads to overvaluations. Base rates can only be adjusted by directly incorporating actual natural constraints into the mathematical model of land valuation [14].

The development of adequate valuation algorithms begins with a clear definition of the concept of spatial vulnerability itself. In contemporary studies, the social and material instability of the urban environment is directly linked to high environmental and economic uncertainty [15]. Special indices allow the multidimensional nature of risks to be aggregated into a single calculated indicator, significantly facilitating spatial analysis and enabling the precise localization of potentially critical zones. When natural vulnerability parameters are included in the calculation of cadastral value, it establishes a fundamental basis for territorial protection within the framework of sustainable development.

High-hazard zones—such as areas along tectonic faults—are often characterized by minimal market activity or a complete lack of commercial transactions. Under such conditions, traditional direct sales comparison methods simply do not work. A solution is found in spatial extrapolation [16,17,18]: the essence of this approach lies in clustering settlements with a similar structure of price-forming factors. Geostatistics and spatial interpolation tools make it possible to compensate for the lack of market statistics and build mathematically robust models even with sparse initial data.

Global practice in mass real estate valuation has long been based on the integration of geospatial constraints and vulnerability indices. The Kazakhstani land administration system, however, significantly lags behind in this regard—local environmental and geological hazards continue to be left out of the calculations. The contradiction between purely economic pricing principles and the actual safety of sites in seismically active or debris flow-prone areas requires new mathematical tools. The development of adjustment coefficients will not only help achieve fairness in fiscal calculations but also create an economic barrier against the development of high-risk territories [19].

2. Materials and Methods

1. Study Area

The validation of the developed mathematical model was carried out using data from the Bostandyk District of Almaty. This location was not chosen randomly: it is here that the conflict between high urban development attractiveness and a dense complex of environmental risks is particularly pronounced. For the purposes of spatial modeling, the study area was divided into 62 cadastral blocks numbered from 20313001 to 20313062. Such strict linkage of objects to local boundaries allows for the accurate aggregation of spatial data and its subsequent use in fiscal calculations [20].

The cartographic base was prepared using the ArcMap 10.8.2 software environment. Initial geodata regarding municipal divisions were extracted from the Unified State Real Estate Cadastre (USREC). The resulting polygon layer of the district served as the basis for the manual vectorization of each cadastral block.

OpenStreetMap (OSM) data were utilized as a basemap for spatial detailing. This open-source service facilitated the supplementary digitization of key urban environment elements: building footprints, the road network, green spaces, and administrative boundaries. The final map layout and the export of the finished materials were performed using standard cartographic layout tools (Figure 1) [21].

3. Methodology

In international mass valuation practice, any territorial constraints—whether they be regulations for zones with special conditions—are interpreted as negative externalities. Ultimately, these externalities translate into direct financial losses for real estate owners. Economic damage arises from the restriction of development rights, additional health risks, and a decline in overall environmental quality. To establish a socially fair value for land parcels, such hidden locational defects must be recorded in cadastral registries; otherwise, the calculations will remain incomplete [10].

The weight of each individual hazard is determined using the Analytic Hierarchy Process (AHP) or Multi-Attribute Value Theory (MAVT). The MAVT framework allows for the construction of a branching dendrogram and a step-by-step adjustment of the base land price, taking into account the natural vulnerability of the territory. In this process, the multidimensional nature of local risks is aggregated into a single index. Consolidating disparate parameters into a common indicator of socio-material vulnerability significantly facilitates comparative spatial analysis [13].

In this study, the AHP modeling is focused on the mathematical weighting of two fundamental criteria: seismic hazard (C1) and environmental discomfort (C2). The numerical values for the second factor are calculated based on remote sensing data. The algorithm for calculating the weight coefficients of spatial factors using the AHP method is illustrated in Figure 5.

Multi-Attribute Value Theory. Multi-Attribute Value Theory (MAVT) helps structure complex multi-criteria problems through the construction of hierarchical decision trees. This method is employed because it allows for the mathematical integration of vastly different phenomena, such as geological hazards and microclimatic parameters, within a single measurement scale [30].

The MAVT framework is based on compensatory logic: when calculating the final score, some criteria can offset others. In cadastral practice, this manifests quite clearly—extensive green spaces can algorithmically mitigate the impact of certain locational defects, whereas pronounced environmental discomfort, conversely, accelerates the decline in land value. The degree of such mitigation is strictly constrained by the assigned system of weights. Since the model is additive, weights are introduced as scalar constants, and all marginal value functions must operate within the same numerical intervals [31].

Each spatial alternative (x) is evaluated against a specific attribute (i) through an individual value function (vi(x)) [32]. The final aggregated indicator is obtained by summing all the functions multiplied by their corresponding weights.

$$\mathrm{V}(\mathrm{x})={\displaystyle {\sum }_{\mathrm{i}=1}^{\mathrm{n}}}\mathrm{w}\mathrm{i}\times \mathrm{v}\mathrm{i}(\mathrm{x})$$

(3)

In our model for calculating the integral risk (K risk) for a cadastral block, this formula is expressed as follows:

V(x) - the K risk coefficient for a specific cadastral block x.

N - the number of attributes, where in our model n = 2 (attribute 1 is seismic hazard; attribute 2 is environmental discomfort). Here, n is the number of attributes, wi is the weight of attribute i, and vi(x) is the value function for an individual attribute, reflecting the performance of alternative x with respect to attribute i.

wi — are scalar constants obtained previously by us using the Analytic Hierarchy Process (AHP). For the seismic factor, w1 = 0.833, and for the environmental factor, w2 = 0.167.

vi(x)- the attribute value function. It is not feasible to directly input “seismic intensity points” or “surface temperature degrees” into the equation. The function vi(x) transforms actual physical measurements into a normalized scale ranging from 0 to 1.

4. Practical Application of the Value Functions Vi(x):

- For the seismic factor (v1): The value function is calculated as the proportion of the cadastral block area covered by a 10-point seismic intensity zone or a tectonic fault. If the block is completely intersected by a fault, v1(x) = 1.0. If it is half-covered, v1(x) = 0.5. In the absence of a fault, v1(x) = 0.0.

- For the environmental factor (v2): This function utilizes satellite monitoring data (NDVI and LST). If the block consists of continuous concrete development experiencing the urban heat island effect with an absence of vegetation, the function v2(x) approaches 1.0 (maximum discomfort). Conversely, if it is a green park area, v2(x) approaches 0.0.

Final Calculation Example

Suppose a cadastral block located in the foothills is being evaluated. It is 50% intersected by a tectonic fault (v1 = 0.50) but possesses excellent environmental conditions with abundant vegetation (v2 = 0.10). Substituting these values into the MAVT equation yields:

Krisk = (0.833 × 0.50) + (0.167 × 0.10) = 0.4165 + 0.0167 = 0.433

Thus, the final risk coefficient for this cadastral block amounts to 0.433. It is mathematically justified that its base cadastral value should be reduced by exactly this percentage (43.3%).

5. the Dendrogram Is Presented in Figure 6

The specific nature of real estate segments in high-hazard areas, particularly those situated directly over tectonic faults, is characterized by minimal market activity or a complete absence of commercial transactions. The resulting information deficit renders the application of the traditional sales comparison approach impossible. This lack of data can be compensated for through the methodology of spatial extrapolation of base parameters. By grouping parcels with similar spatial characteristics into homogeneous clusters, a foundation is established for constructing a generalized statistical model.

The determination of an objective cadastral value is achieved using regression equations. The baseline mathematical framework, which accounts for traditional macro-factors such as distance from the city center and infrastructure provision, is expanded through local spatial adjustments. The calculation of the unit cadastral value relies on classic linear regression analysis or hybrid algorithms capable of simultaneously processing macroeconomic markers and qualitative descriptors of environmental conditions.

A GIS overlay of the water network and seismic hazard vector layers enables the calculation of a precise reduction coefficient for vulnerable locations, including cadastral block 20313054, which is intersected by a fault. The final equation for the modified value takes the following form:

$$CV = SICV\times S \times (1 - K risk)$$

(4)

$CV$- the cadastral value of the land parcel; SICV- is the base unit cadastral value accounting for infrastructure; S- is the area of the parcel; and Krisk - is the cumulative coefficient reflecting the impact of negative external factors (debris flows, seismicity, environmental conditions). The determination of the exact K risk coefficient is carried out through GIS spatial analysis of the proportion of the block’s area exposed to natural hazards.

3.1. Spatial Distribution of Natural Hazards

To spatially localize the epicenters of natural and environmental vulnerability, the overlay method was applied. The base vector grid, encompassing the 62 cadastral blocks of the Bostandyk District, was sequentially superimposed with seismic microzoning maps based on the MSK-64(K) scale.

The GIS synthesis revealed substantial spatial heterogeneity in the distribution of hazards. The northern and northwestern blocks (numbers 20313001–20313010) are consistently located within the 9-point zone. Moving toward the southern foothills, the calculated seismic intensity increases to a critical 10 points. Additional restrictions on permanent construction are imposed by active tectonic faults that intersect the central and southern parts of the district. The situation is exacerbated by river arteries: their channels pose a direct debris flow hazard and necessitate the establishment of water protection strips, which further narrows the possibilities for economic development.

For each registered block, an integral risk coefficient (Krisk) was calculated, summarizing the local territorial defects. The minimum value (0) was assigned to parcels with a standard 9-point background and no additional complications. The highest values, reaching 0.3–0.4, were recorded where 10-point seismicity overlaps with fault lines and proximity to debris flow-prone channels.

The modified unit cadastral value (SICV new) is determined using the following formula:

$$SICVnew = SICVbase \times (1 - Krisk)$$

(5)

The final fair cadastral price of the land parcel (CVnew) is determined by multiplying the modified unit cadastral value by the parcel’s area (Slp):

$$CVnew = SICVnew\times Slp$$

(6)

To derive the local coefficients from the final table, the Multi-Attribute Value Theory (MAVT) formula introduced in the methodology is applied:

$$K risk = (w1 \times v1) + (w2 \times v2)$$

(7)

where:

w1 = 0.833 is the weighting coefficient for seismic hazard.

w2 = 0.167 is the weighting coefficient for environmental risk (dependent on the NDVI and LST indices).

v1- is the normalized seismic risk function (ranging from 0 to 1, where 1 represents maximum hazard, such as complete intersection by a tectonic fault).

v2 - is the normalized environmental risk function (ranging from 0 to 1, where 0 represents a high NDVI vegetation value and a favorable LST thermal background, whereas 1 denotes continuous built-up areas with a pronounced urban heat island effect).

Given that the final Krisk values are known, the mathematical calculations demonstrating precisely which v1 and v2 parameters (in terms of NDVI and LST) determine the final value for each cadastral block are presented below.

1. Cadastral Block 20313003 (Zone I)

Conditions: 9-point seismic intensity, no tectonic fault. Final Krisk = 0.05.

Logic for v1: Since there is no fault and the conditions are standard, v1 is set to 0.0 (in accordance with the methodology: “In the absence of a fault, v1 = 0.0”).

Mathematical derivation of v2 (Environmental factor):

$$0.833 \times 0.0 + 0.167 \times v2 = 0.05$$

$$0.167\times v2=0.05$$

$$v2={\displaystyle \frac{0.05}{0.167}}\approx 0.30$$

A v2 value of 0.30 indicates a moderate level of environmental discomfort. Satellite data demonstrate average Normalized Difference Vegetation Index (NDVI) values alongside a neutral thermal regime (LST). Vegetation is present; however, the area lacks dense park coverage.

2. The analysis of cadastral block 20313034 (Zone II) is predicated on a final risk coefficient (Krisk) recorded at 0.20. The background seismicity of the location is 9 points, and the area is simultaneously intersected by a tectonic fault and a water artery.

The seismic hazard function (v1) assumes a value of 0.20 in this context. The presence of a geological fault outside the critical 10-point zone imposes strict urban planning restrictions on one-fifth of the cadastral unit’s area. The mathematical extraction of the environmental component (v2) is executed through the following sequence of calculations:

$$0.833 \times 0.20 + 0.167 \times v2 = 0.20$$

$$0.1666+0.167\times v2=0.20$$

$$0.167\times v2=0.0334$$

$$v2={\displaystyle \frac{0.0334}{0.167}}\approx 0.20$$

A v2 value of 0.20 based on remote sensing data indicates high environmental quality. The presence of a nearby water artery stimulates an increase in vegetation density, driving the Normalized Difference Vegetation Index (NDVI) towards 1.0. This effectively stabilizes the Land Surface Temperature (LST) through evaporative cooling.

The calculation of the integral risk for cadastral block 20313054 (Zone II) is conducted in the absence of open water bodies, yet in the presence of destructive factors: 10-point seismic activity and a tectonic fault. The final Krisk coefficient for this territory amounts to 0.35.

The geological hazard function (v1) assumes a value of 0.40, reflecting that the buffer zone of the tectonic fault extends across 40% of the analyzed block’s area. The subsequent extraction of the pure environmental component (v2) is executed through the following mathematical transformations:

$$0.833 \times 0.40 + 0.167 \times v2 = 0.35$$

$$0.3332+0.167\times v2 \approx 0.35$$

$$0.167\times v2=0.0168$$

$$v2={\displaystyle \frac{0.0168}{0.167}}\approx 0.10$$

Satellite imagery data fully corroborate the minimal discomfort value (v2 = 0.10). The foothill location ensures exceptional environmental quality: dense vegetation yields peak NDVI values, and the thick green canopy reliably mitigates local thermal anomalies, a phenomenon clearly visible on LST rasters.

A starkly different situation is observed in cadastral block 20313060 (Zone IV). Here, the final risk coefficient (Krisk) reaches a critical value of 0.45—the territory is subject to 10-point seismic intensity, is intersected by an active fault, and is additionally burdened by a debris flow-prone river channel.

The proportion of geological impact (v1) for this block was intentionally maintained at the same level as in the previous case, at 0.40. This decision allows the tectonic baseline to remain constant, making it possible to isolate exactly how the water artery influences the environmental component. The variable (v2) was recalculated according to the following procedure:

$$0.833 \times 0.40 + 0.167 \times v2 = 0.45$$

$$0.3332+0.167\times v2=0.45$$

$$0.167\times v2=0.1168$$

$$v2={\displaystyle \frac{0.1168}{0.167}}\approx 0.70$$

A v2 value of 0.70 indicates a high level of discomfort and vulnerability. In this scenario, the river functions not as a source of vegetation, but as a catalyst for a negative externality—the debris flow hazard. This proximity drastically degrades the v2 indicator, even if the NDVI values themselves appear quite acceptable (Table 1).

3.2. Modeling the Fair Cadastral Value

The calculation of the baseline regression model (SICV base) was conducted in strict accordance with the current state valuation regulations. The normative land tariff for the Bostandyk District is fixed at 6,200 tenge per square meter. The internal administrative division splits the study area into four urban planning sectors. The commercially attractive northern blocks (Zone I) are tariffed with a maximum correction multiplier (Kzone) reaching 1.50. Shifting toward the southern periphery of the district (Zone IV) naturally decreases this corrective value to a minimum of 1.03. The mathematical definition of the initial plot price is described by the following equation:

$$SICV base = 6200 \times K zone$$

(8)

For the sample of the investigated areas, the baseline parameters were as follows:

• Cadastral block 20313003 belongs to Zone I (coefficient 1.50) → Baseline value = 9,300 tenge.
• Cadastral block 20313034 belongs to Zone II (coefficient 1.33) → Baseline value = 8,246 tenge.
• Cadastral block 20313054 belongs to Zone II (coefficient 1.33) → Baseline value = 8,246 tenge.
• Cadastral block 20313060 belongs to Zone IV (coefficient 1.03) → Baseline value = 6,386 tenge.

The official valuation methodology relies exclusively on macroeconomic zoning and fails to account for specific local natural hazards, which simply remain outside the scope of state calculations. The recalculation results of the unit cadastral value for parcels with varying degrees of spatial vulnerability are summarized in Table 2.

The combination of real base rates with remote sensing data reveals an intriguing urban planning paradox typical of foothill areas. Block 20313054 falls within valuation zone II, and according to the official methodology, its value is high—8,246 KZT per square meter, which is attributed to the prestige of the location. Satellite data confirms the environmental well-being of this territory: dense vegetation (high NDVI) and the absence of thermal anomalies ensure a low level of discomfort (v2 = 0.10). However, the block is located in a 10-point seismic zone and is additionally intersected by an active tectonic fault (v1 = 0.40). The integral natural risk coefficient (Krisk = 0.35) corrects this imbalance, justifiably reducing the value to 5,360 KZT per square meter.

The method also highlights the compensatory role of ecosystems. In block 20313034, a tectonic fault (v1 = 0.20) is partially offset by the proximity of a river, which provides a mild microclimate and an abundance of greenery (v2 = 0.20). The resulting risk here is 0.20, and the value decreases moderately—by 20%, down to 6,597 KZT per square meter.

The most dramatic situation is observed in block 20313060 (zone IV). A destructive synergistic effect occurs here: the 10-point seismicity and a tectonic fault (v1 = 0.40) are compounded by the threat of mudflows from the waterway, which results in extremely high environmental discomfort (v2 = 0.70). Consequently, the real cadastral value drops by nearly half—by 45%, down to 3,512 KZT per square meter. This serves as a strong economic signal preventing dense construction in a critically hazardous zone.