According to the global population data sheet, the worldwide population reached a total of 8.1 billion individuals in the year 2023. Projections suggest that this figure is expected to rise to 9.9 billion by the year 2050 [1]. Consequently, there are increasing concerns regarding the escalating demand for food resources [1]. Within this particular framework, the expeditious transformation of agricultural land into urban regions is resulting in a reduction in food resources, presenting a significant obstacle to Pakistan's economy, which is primarily dependent on agriculture and accounts for 21% of the Gross Domestic Product (GDP) [2]. The significance of agricultural output in Pakistan is of utmost importance, given its direct influence on the livelihoods of around 70% of the nation's populace [3]. Agriculture has a pivotal role in providing both economic sustenance and livelihoods for a substantial segment of the population, underscoring its fundamental significance in bolstering rural communities and the broader economy [4].

Wheat is a prominent staple crop that plays a crucial part in fulfilling the dietary requirements of the nation. In addition to wheat, several other crucial crops, including rice, maize, corn, and sugarcane, jointly contribute to the rich agricultural panorama of Pakistan [5]. These agricultural commodities not only play a crucial role in the dietary patterns of the nation but also make a significant contribution to the economic productivity of the agricultural sector. Nevertheless, the exponential growth of metropolitan regions presents a substantial obstacle for the agricultural industry [6]. The rapid expansion of cities and urban infrastructure is resulting in the conversion of agricultural land into residential and commercial areas [7]. The phenomenon of urbanization has resulted in a decrease in the amount of land that is available for agricultural purposes, hence causing a drop in the overall productivity of the agricultural sector. The expansion of urban development into agricultural regions requires the use of meticulous and strategic resource management practices in order to alleviate the negative impacts on food production.

Due to these prevailing constraints, it is crucial for Pakistan to implement comprehensive plans that effectively address the demands of urban development while simultaneously safeguarding agricultural land [8]. The optimization of land usage, implementation of sustainable agriculture practices, and utilization of technical breakthroughs are key areas of focus for strategic resource management methods, with the aim of enhancing productivity. In order to effectively tackle the growing food demands, it is imperative to adopt a collaborative approach that encompasses the perspectives and expertise of several stakeholders, including government agencies, farmers, researchers, and urban planners. It is imperative for policymakers to establish and execute policies that endorse sustainable farming methods, safeguard fertile soil, and foster the advancement of rural areas. Furthermore, the implementation of programs aimed at fostering innovation in agricultural practices, efficient water resource utilization, and the integration of technological advancements can play a significant role in alleviating the adverse effects of urban sprawl on agricultural output [5].

Within the domain of agricultural productivity, the comprehension and effective management of ecological elements assume a crucial position in guaranteeing the attainment of maximum crop output. Various factors, including soil quality, temperature, moisture, and soil pH, have a substantial impact on the growth of plants and, subsequently, on the nutritional composition of crops [9]. Notwithstanding the indisputable influence of these parameters, there is a conspicuous deficiency in farmers' awareness concerning their significance in assessing wheat production per acre. Given the identified knowledge gap, it is imperative to undertake broad educational activities targeted towards farmers. Through the dissemination of information regarding the distinct characteristics of soil and the elucidation of the interrelationship between these ecological parameters and the productivity of wheat crops, farmers are empowered to make well-informed decisions that foster enhanced yields and promote agricultural sustainability on a broader scale [10][11].

In the endeavor to improve agricultural production, it is crucial to implement recommended measures that emphasize the significant importance of soil compatibility in attaining desired crop yields. An instrumental technique can be employed to classify soil into subclasses, thus facilitating a comprehensive comprehension of its characteristics and potential. The utilization of the Geographical Information System (GIS) has become increasingly significant in this context, as it facilitates the examination and depiction of soil suitability from a spatial standpoint [12]. The incorporation of Geographic Information Systems (GIS) with Multi-Criteria Evaluation (MCE) methodologies serves to augment the accuracy of delineating areas of appropriateness. The MCE framework takes into account various essential parameters such as soil quality, temperature, moisture, and pH [13]. This comprehensive approach aims to maximize crop yield while reducing any potential production losses. The utilization of analytical synergy provides agricultural stakeholders with significant insights into the complexities of the agricultural landscape, hence facilitating more efficient decision-making processes.

Moreover, the progress in technology has played a crucial role in enhancing the precision of these analytical procedures. The utilization of Google Earth Engine (GEE) has demonstrated its efficacy as a robust instrument for the production of comprehensive land-use and Land Surface Temperature (LST) cartography [14]. Utilizing the Google Earth Engine (GEE) platform for the purpose of mapping activities introduces a heightened level of complexity to the study, hence enabling a more dynamic and contemporaneous evaluation of the agricultural terrain. The integration of Generalized Estimating Equations (GEE) with Geographic Information Systems (GIS) not only enhances the efficiency of the mapping procedure but also enables a comprehensive exploration of the geographical and temporal factors that impact agricultural productivity [15].

Objectives:

This study represents a notable progression in the agricultural methodologies employed in the districts of Sheikhupura, Gujranwala, Hafizabad, and Nankana Sahib. The primary objective of this research is to evaluate the appropriateness of land for agricultural purposes by considering temperature patterns and soil attributes. In contrast to many modern approaches that employ Python-based techniques, this study chooses to apply well-established procedures for the analysis and improvement of agricultural practices in these places. This research deliberately employs a traditional method, taking into consideration the continuous development of agricultural technology and the widespread use of machine learning techniques. The main aim of this study is to utilize MCE methods within the framework of the GIS to discover optimal areas appropriate for wheat growing. The selection of this technique is predicated upon the distinct environmental and agricultural needs specific to the districts of Sheikhupura, Gujranwala, Hafizabad, and Nankana Sahib.

The research technique encompasses the careful examination of several variables that are essential for assessing wheat growth parameters. The assessment technique relies on critical components such as soil pH, drainage, electrical conductivity, soil type, and temperature data. By conducting a thorough examination of these factors, the study seeks to identify possible locations for the growing of wheat, so enhancing the ability to make well-informed decisions regarding agricultural practices at the local level. While acknowledging the practicality of Python-based methodologies in many settings, this research underscores the significance of a geographically targeted and traditional methodology. This highlights the importance of conducting temperature and soil-based analyses that are specifically designed to suit the unique conditions and intricacies of the districts of Sheikhupura, Gujranwala, Hafizabad, and Nankana Sahib. The implementation of proven procedures guarantees that the research findings are in accordance with the particular requirements and attributes of the study area, hence fostering sustainable agricultural growth in this region.

Study Area:

The research area comprises the administrative divisions of Sheikhupura, Gujranwala, Hafizabad, and Nankana Sahib, located in the agriculturally productive plains of Punjab, Pakistan. These regions collectively constitute an important agricultural belt, famous for their substantial contribution to Pakistan's wheat output. Situated in the central region of Punjab, the city of Sheikhupura is renowned for its vast and fertile agricultural terrains [16]. The district exhibits a wide variety of soil types, encompassing both alluvial and loamy soils. These soil characteristics have a significant impact on the cultivation of wheat in the region. The interdependence of the regional economy and agricultural activities necessitates the evaluation of wheat viability by considering many elements such as soil pH, drainage, and temperature. Gujranwala, renowned for its rich plains and thriving agricultural sector, holds a significant position in Pakistan's wheat output. The Chenab River exerts a significant influence on the fertility of the surrounding soils [17]. The suitability of wheat cultivation in Gujranwala is determined by various elements, including soil texture, moisture levels, and temperature fluctuations. An in-depth comprehension of these factors is crucial for maximizing wheat productivity in this geographical area.

The inclusion of Hafizabad, given its varied geography and agricultural techniques, is of paramount importance in this study. The soils within the district exhibit a range of characteristics, varying from loamy to clayey compositions, which in turn have implications for water retention and drainage capabilities [18]. In order to evaluate the appropriateness of wheat cultivation in Hafizabad, a comprehensive analysis of the region's agroecological characteristics is necessary. This assessment should encompass several elements such as soil composition, water availability, and temperature trends. Nankana Sahib, the location of origin of Guru Nanak, possesses substantial cultural importance and constitutes an integral component of the wheat-producing topography [2]. The soils within the area display a considerable degree of variety, which underscores the importance of conducting a thorough analysis of key characteristics such as soil pH, texture, and temperature in order to appropriately assess the viability of wheat cultivation. In the context of assessing the suitability of wheat production, it is important to carefully evaluate the commonalities and distinctions seen across different areas. The objective of this study is to investigate the complex interconnections of soil properties, temperature fluctuations, and other significant variables in order to offer specific knowledge for enhancing wheat farming techniques in the districts of Sheikhupura, Gujranwala, Hafizabad, and Nankana Sahib [19]. The results of this study will provide valuable insights for making well-informed decisions regarding sustainable and productive wheat cultivation in this crucial agricultural region.

Data Collection:

The data collection procedure employed in this study was conducted with great care and was a crucial element in obtaining thorough information for the assessment of wheat suitability in the districts of Sheikhupura, Gujranwala, Hafizabad, and Nankana Sahib. The data collection encompassed a variety of criteria, such as soil properties, satellite data, fluctuations in temperature, and patterns of land usage.

The collection of soil data from the Punjab Soil Survey is of utmost importance in comprehending the fundamental factors involved in wheat cultivation. The provided data encompassed details pertaining to soil pH levels, drainage properties, soil texture, and electrical conductivity. The process of collecting soil data entailed conducting sampling activities throughout the designated study region, with the aim of obtaining a comprehensive and varied selection of soil samples that accurately represented the area. These samples were then subjected to meticulous analysis.

Figure 1: Study Area map

Figure 2: Flow chart of methodology

Land Surface Temperature:

The assessment of wheat adaptability throughout its growth cycle involved the collection of data at five pivotal stages: germination, blooming, tillering, heading, and maturity. The collection of Land Surface Temperature (LST) data during these specified time intervals has yielded valuable insights into temperature fluctuations that are essential for the growth of wheat [20][21]. The utilization of a temporal method facilitated a thorough comprehension of temperature-dependent suitable points across the entire duration of wheat cultivation.

Land Use Land Cover (LULC) Classification:

The research utilized the Google Earth Engine platform to perform the categorization of Land Use and Land Cover (LULC). The methodology employed in this study encompassed the classification and spatial representation of several land utilization patterns within the designated research site, including agricultural plots, urbanized regions, and indigenous flora [20]. The utilization of LULC data provided significant insights into the existing land cover conditions, which had an impact on the overall evaluation of the suitability of wheat cultivation.

Data Integration:

Subsequently, the gathered data was amalgamated in order to generate a holistic perspective of the agricultural terrain. The analysis involved a comprehensive examination of soil data, temperature fluctuations, and land use patterns in order to ascertain the specific geographic areas that had the most favorable circumstances for the production of wheat. The integration of many parameters facilitated a comprehensive assessment of the variables that impact the appropriateness of wheat in the designated research region.

The data collection process was conducted in accordance with stringent criteria in order to guarantee precision and dependability. The study sought to offer a comprehensive and knowledgeable viewpoint on the adaptability of wheat in the particular districts under examination by integrating data on soil properties, temperature fluctuations throughout crucial growth phases, and land use patterns. The comprehensive dataset presented above is the fundamental basis for further studies and decision-making processes pertaining to sustainable agriculture practices within the designated study area.

Multicriteria Decision Analysis (MCDA):

The utilization of Multicriteria Decision Analysis (MCDA) was a fundamental component of the study's methodology, as it provided a structured framework for evaluating and incorporating several criteria that impact the appropriateness of wheat. The procedure encompassed the evaluation of several elements, such as soil properties, fluctuations in temperature, and patterns of land utilization, in order to make well-informed determinations of the most suitable areas for growing wheat [22]. In the present study, the utilization of Multi-Criteria Decision Analysis (MCDA) enabled the determination of appropriateness zones through the allocation of weights to various criteria, taking into account their respective levels of significance [23]. The utilization of a weighted scoring approach in the analysis facilitated a comprehensive evaluation of the various elements that impact the growth of wheat, so ensuring a fair and equitable assessment. By including these weighted criteria, it was possible to identify the places within the research area that are most suitable for wheat farming.

Table 1: Metadata offset light thermal bands to compute temperature in degrees Celsius

Table 2: Literature-based Optimum temperature and observed temperature for different stages of wheat Crop.

Table 3: Landsat image acquisition dates for LST estimation

Interpolation:

The utilization of interpolation techniques was important in the production of a comprehensive spatial representation of temperature-based suitability points throughout the designated study region. The study specifically concentrated on the interpolation of Land Surface Temperature (LST) data obtained at crucial stages of wheat growth, namely germination, blooming, tillering, heading, and maturity. Interpolation techniques were utilized to estimate temperature values at unobserved places, so offering a continuous and comprehensive depiction of temperature fluctuations [24]. A spatially explicit map was generated using interpolation techniques to illustrate temperature gradients and variations across the designated study region. The temperature map played a crucial role in identifying wheat suitability zones, enhancing our comprehension of the spatial arrangement of ideal circumstances for growing wheat [25].

Table 4: Soil suitability parameters

Table 5: Sensitivity Analysis for Analytical Hierarchy Process (AHP) to compute the weight of each parameter

Figure 3 illustrates the Land Use and Land Cover (LULC) map of the study area, employing the Google Earth Engine CART method. The study systematically divided the region into five distinct parts for comprehensive analysis. The results depict the predominant land cover classes, with Crops covering an extensive 14,699 square kilometers, emphasizing the substantial agricultural footprint in the area. Additionally, Built-up areas span 858 square kilometers, reflecting urban and developed regions. Other notable land cover classes include Bare land, Water Bodies, and Vegetation, each contributing to the overall landscape composition. This concise representation provides a visual overview of the land cover distribution in the study area, serving as a foundation for subsequent analyses and interpretations.