**3. Results**

### *3.1. Analysis of the LULC Mapping*

The LULC of the English Bazar block was classified into five categories, i.e., water bodies, built-up area, vegetation, barren land, and agricultural land (Figure 3), based on the level-I classification scheme of the National Remote Sensing Centre (NRSC). This study observed a significant shift in LULC patterns in the last 20 years. The results for the LULC map of 2001 showed that a 109 km<sup>2</sup> area was covered by vegetation cover, followed by agricultural land (70.1 km2), water bodies (21.11 km2), built-up area (15.4 km2), and barren land (18.4 km2). In 2011, the results showed that a 92 km<sup>2</sup> area was covered by agricultural land, followed by vegetation cover (80 km2), built-up area (26.8 km2), water bodies (17.26 km2), and barren land (12.4 km2). In the case of 2021, the built-up area and agricultural land increased significantly, and agricultural land covers 98 km2, followed by the vegetation cover (72 km2), built-up area (35.91 km2), water bodies (19.2 km2), and barren land (7.64 km2) (Figure 3). The amount of built-up and agricultural land has grown, while vegetation and barren land decreased. Water bodies also increased in the south-eastern part of this study area, owing to lowlands that were flooded in 2017 [53], resulting in stagnant water bodies. Further, new farm ponds were dug under the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) scheme by the union, as well as the state government, to increase fish production and maintain the ecological balance, especially of aqua life. Agricultural land has primarily expanded near built-up areas because of many people involved in agricultural activity, mostly in rural areas, and to meet the growing need for food for an expanding population, both show urban growth. Barren land has been changed to agricultural land, built up, and certain areas have been converted to vegetation, particularly mango forests, since Malda District is noted for them [54]. The built-up area was expanding all over the block at a very high pace. The main growth was noticed in the surroundings part of the municipal area, which is located in the eastern part of the study area. High built-up growth was noticed in the northern part, where the expansion was mainly increased along the banks of Kalindri River. To the western part and southern part, the built-up area was increased along the State Highway (SH) 10 and National Highway (NH) 34. Maheshpur has seen a massive increase in settlements area, located on the left bank of Mahananda River, a very short distance from the municipal area (southern part). The built-up area increased by 30% during 2001–2011 and 44.28% from 2011 to 2021. The reason for the rapid urbanisation in the north-eastern part of the study area is the presence of the rapidly growing English Bazar municipality, type-I city, and decentralisation of several medium and small microenterprises (MSME), educational centres, and health centre. These governmental and private centres accelerate the process for growing urban centres across the study area rapidly, not only the north-eastern part. According to the census of 2001, the population density of this municipality was 881 persons/km2, which was increased by 1100 persons/km2. Therefore, it can be stated that the urban centres have been growing rapidly over time.

**Figure 3.** LULC mapping using SVM for the years of ( **A**) 2001, (**B**) 2011, and ( **C**) 2021 of the English Bazar block.

### *3.2. Validation of the LULC Classification*

The accuracy of the prediction of a certain class is shown by the metric of the producer accuracy. The consistency of the group to the user is revealed by the user's accuracy. The LULC maps of 2001 had an overall average of 90.05%, 93.67% in 2011, and 96.24% in the 2021 (Table 3). These results indicate that the performance of the SVM model for classifying the LULC maps was highly satisfactory. Previous studies reported that the overall accuracy of greater than 80% could be considered satisfactory [55,56]. The results of the LULC maps of three periods showed that the LULC of 2021 had the highest user accuracy of 96.24%, followed by 93.67% in 2011, and 90.05% in 2001. The built-up area was found to be more reliable because of the 98% user accuracy for the LULC of 2021, followed by vegetation (96%), and agricultural land (96%). In the case of the LULC of 2011, vegetation had the highest user accuracy of 95%, followed by built-up area (94%) and water bodies (93%). The accuracy assessment of the LULC of 2001 showed that built-up areas achieved the second-highest user accuracy of 88%. Therefore, it can be stated that the built-up area achieved the highest accuracy compared to the other four LULC classes.



### *3.3. Analysis of the LULC Dynamics*

During 2001–2021, urbanisation and development activities had the most significant impact on restructuring the land use and land cover in the English Bazar region. Figure 4 depicts how the urbanisation process, also known as built-up expansion, changed the land use at the expense of vegetation, agricultural land, and barren land, as seen in the Figure 4. From 2001 to 2011, roughly 6.2 km<sup>2</sup> of agricultural land and 4.6 km<sup>2</sup> of vegetation cover were transformed into built-up areas, while between 2001 and 2011, almost 12.5 km<sup>2</sup> of vegetation cover was converted into agricultural land, and between 2011 and 2021, a nearly 15.6 km<sup>2</sup> vegetation cover was converted to agricultural land. From 2001 to 2021, a considerable shift in the barren land was observed, with a total area of 12.63 km<sup>2</sup> being transformed into built-up areas, agricultural land, and vegetative cover. During the investigation, water bodies were converted into agricultural land and built-up land. The total built-up area was increased to about 35.8 km<sup>2</sup> between 2011 and 2021, which covered about 14.4% of the total area of the English Bazar block. It was also noticed that a large area was converting from water bodies to agricultural land by almost 15 km2. The vegetation cover also decreased over time, which was transformed into agricultural land and barren land in 28 and 5.2 km2. A significant change in barren land was noticed in a 3.2 km<sup>2</sup> area, which was transformed into a built-up area, while a 6.3 km<sup>2</sup> area was converted into agricultural land during 2001–2021. The area under water bodies has gained from the area under agricultural land through the conversion of 3.5 km2.

During 2001–2021, the pattern of built-up expansion is shown in Figure 5, which illustrates how the built-up area expanded in the region. Here, we observed four classes of built-up changes, with non-built-up to built-up showing an increasing trend. The term unchanged built-up refers to a region that was built up during a preceding time. In the English Bazar block built-up area expanding all sides of the block, some parts increased quickly and some parts slowly. In Figure 5, the changing pattern from 2001 to 2021 showed a huge increase of the built-up area; this expansion was mainly done along the road and riverside. The built-up area witnessed linear expansion along the SH-10 in the western part and NH-34 in the south-central part, as well as beside the Mahananda in the eastern part and Kalindri River in the northern part of the English Bazar block. Although, we observed few unusual conversions in the present study. That is, few small amounts of areas were converted from built-up to non-built-up (other LULC classes) because of frequent flooding and the eviction of unlawful settlements, such as slums, especially from the riverbank of Mahananda River, as reported by the local authorities.

**Figure 4.** The LULC transition matrix using a heatmap between the periods of 2001 and 2021.

**Figure 5.** Built-up change maps between the years of (**A**) 2001 and 2011, (**B**) 2011 and 2021, and (**C**) 2001 and 2021 of English Bazar.

### *3.4. Analysis of the Built-Up Expansion Process*

We employed a landscape fragmentation and frequency approach model to demonstrate the process of built-up expansion in the English Bazar. Using these models, we could easily explore the process of built-up expansion growth, its trend, and pattern. The process of built-up expansion was modelled using fragmentation indices, and it classified the built-up area into six fragmentation indices, such as large core, medium core, small core, perforated, edge, and patch (Figure 6). The large core indicates a built-up area of more than 500 acres and can be considered as the most stable and permanent built-up area. In contrast, the small core indicates an area of less than 250 acres and can be considered as the concentration of a newly formed built-up that has been expanding outwards from the main core. The results showed that the large core of the built-up area covered 2.92 km<sup>2</sup> in 2001, which then increased to 3.8 km<sup>2</sup> and was amplified by 7.42 km2. This scenario shows that the large core of the built-up area, identified in 2001, was fixed three times. However, the medium core and small core during 2001 and 2011 were concentrated, along with the large core areas, and, ultimately, converted into large core areas in 2021. This scenario reflects increasing the large core of the built-up area through the process in the study area. Additionally, the small and medium cores in the study area observed increasing areas; for instance, in 2001, the small and medium cores were 1.4 and 0.94 km2, which increased to 4.4 and 5.36 km2. The small and medium cores observed significant growth because of the fresh and isolated built-up node conversion. In 2001, the core area was mainly concentrated in English Bazar City, but as the population grew over time, the municipality grew proportionately. The core area expanded in the northern and south-western parts, primarily along national highway-34 and state highway-10. Bagbari, Daulatpur, Milki, Makdumpur, Sonatala, Uttarjadupur, Maheshpur, Uttarramchandrapur, and other regions were identified as small and medium cores in the extreme northern, southern, and western parts of this study area in 2021. The edge and perforated areas mainly showed surrounding English Bazar City, particularly fresh and isolated urban nodes, as well as new patches, which can be found sparsely in the western, southern, and northern parts, namely Sultanpur, Shyampur, Niamatpur, and Kirki. The results showed that the areas under the perforated and patch categories were 6.24 km<sup>2</sup> and 13.42 km<sup>2</sup> in 2001, which increased to 13.23 km<sup>2</sup> and 17.86 km<sup>2</sup> in 2021 (Figure 6). These fresh and isolated built-up nodes were once a rural neighbourhood, but the economic and infrastructural growths triggered the urbanisation process to take place over there. Therefore, some of the perforated and patch areas progressed outwards and were connected with small and medium cores over time. This is how the small, medium, and large cores have increased tendencies. During this research, it was discovered that substantial expansion has occurred along the transportation network, primarily the road and railway [61].

The frequency approach was used in this study to illustrate the built-up expansion of the English Bazar block, and the results were promising. The probability of an occurrence, according to the frequency theory, is the upper limit of the relative frequency with which the event occurs in repeated trials under essentially identical conditions. Thus, using this model, we can immediately grasp the newly developed extended area that has been constructed. The built-up regions for three different eras were layered in this model, and a final map was created that depicted three different periods: three times, two times, and one time, respectively. Consequently, we could quantify the built-up expansion over time rapidly. The results demonstrated that the number three represents a permanent or stable built-up area, which reflects that built-up areas were common in 2001, 2011, and 2021 in those particular places, as depicted by the sky blue hue (Figure 7). While value two in the frequency approach shows that the region has observed a built-up area two times in particular places (2001 and 2011), as represented by the deep blue colour. Value one shows that the region has witnessed one instance of a newly constructed built-up area, shown by the red colour. Therefore, the findings show that the fresh and isolated built-up nodes covered a 10.98 km<sup>2</sup> area, indicated by value one, while the built-up transition area, indicated by value two, covered a 10.24 km<sup>2</sup> area (Figure 7). The transition zone is the most

unstable area, which gains areas from fresh and isolated built-up areas and loses to stable or permanent built-up areas. The most economical and infrastructural growth can be observed in this zone recently. In the case of new and isolated built-up nodes, medium and small enterprises, as well as health and educational centres, help them grow into urban areas.

**Figure 6.** Built-up expansion process model using landscape fragmentation index for (**A**) 2001, (**B**) 2011, and (**C**) 2021 in English Bazar.

**Figure 7.** Frequency approach model to show the expanded built-up area over time.

### *3.5. Analysis of Built-Up Expansion Probability*

Using SAGA GIS, we first created the dominance, diversity, and connectivity models as parameters for analysing the structural pattern of the built-up area. It used to understand the present situation and probability of built-up expansion. In this context, the parameter, like urban dominance, refers to the web of influences that particular cities sustain within a system of cities as the new orthodoxy in urban planning and development; diversity makes cities more cosmopolitan and economically productive, with different economic activity and opportunities. Diverse roles in the municipality in the urban hierarchy attract a vast population. Connectivity refers to how easily passengers or freights may move from one node to another, either directly (directly) or indirectly (through another node or a series of nodes). It is a crucial indicator of built-up growth. The values in these three models varied from 0 to 1, with 0 showing a low built-up concentration and 1 showing a high one. In this three-model analysis, it was discovered that a substantial concentration zone existed in the municipality and its surroundings and several areas next to the NH-34. The municipal area, particularly *Rathbari*, is a key transit hub for the Malda and North Bengal regions. As a result, the development grew from the municipal territory to both sides of the road network. After that, we used the fuzzy membership tool in arc GIS to unidirectionally show all the parameters, resulting in a fuzzified dominance, diversity, and connectivity model that varied from 0 to 1, showing the same outcome as before. Then, with the help of the fuzzy overlay tool and the and/or gamma operators, we utilised these three fuzzified models to build the final built-up expansion model. Its values ranged from 0 to 1, and the final map depicts the future built-up expansion probability of the English Bazar block (Figure 8).

Based on the parameters (dominance, diversity, and connectivity), the final output using a fuzzy logic model ranged between 0 and 1, indicating high to low built-up expansion probability in stretch format. Then, we used a natural break algorithm to classify the stretch built-up probability expansion index into three classes, such as high, moderate, and low built-up expansion probability zones. The results showed that a 103.2 km<sup>2</sup> area has been predicted as a high built-up expansion probability zone, followed by moderate (89.01 km2) and low built-up expansion probability zones (59.62 km2) (Figure 9A). All the parameters positively influenced the built-up expansion, which indicate that where the value of the parameters is higher, the probability of built-up expansion will also be higher. As the higher value of the dominance, diversity, and connectivity parameters were seen in the eastern part of the study area, therefore, these parts have experienced a higher built-up expansion probability. A higher concentration of all the parameters means a higher accessibility rate of the region, which will also experience higher built-up growth in the future. It appears that the surrounding rural areas of the municipality will have a greater chance to convert into urban areas, primarily the area adjacent to NH-34, so its expansion will be concentrated in the southwest and northern parts of the study area. Furthermore, while being a rural residential area, its western half has a good chance of growing in population. *Barbara*, *Sonatala*, and *Milik* were designated as census towns in 2011, and our research revealed that this area is in a high built-up probability expansion zone, implying that these areas have a high proclivity to expand their built-up areas and that this area has also been transformed into an urban area because of urban expansion (Figure 9). *Maheshpur*, *Makdumpur*, *Pirozpur*, *Lalapur*, *Mathurapur*, and *Uttarramchandrapur* are among the 11-g panchayats in the English Bazar block, with the majority of them having moderate built-up expansion likelihood. As a result of the spread effect of the English Bazar municipal area, its fringe areas such as *Makdumpur*, *Barbara*, *Uttarramchandrapur*, and *Maheshpur* have seen significant changes in terms of built-up expansion, and they may be converted into urban areas and merged with the municipality of English Bazar block. The areas with the lowest built-up expansion potential were found in some parts of the study area's north, south, west, and central regions, because this area either has the mango forest or water bodies, and parallel to this, these parts also suffered from lousy connectivity. Though the municipality of the English Bazar block is a type-I city, according to the 2011 Census with a population of 274,627 and a

population density of 1100/km<sup>2</sup> and, also, the municipality had a 2.16 lakhs population, it has a high chance or probability of expanding their built-up area with a much higher rate in the future, and our study also revealed the probable expansion zone. A significant reason for this high expansion is its nodal connectivity location, fertile soil, which enhanced the agricultural activities, primarily mango groves and some food processing industries, and its growing business capacity.

The field survey was conducted to see how the built-up expansion has been taking place in the study area, such as nursing homes, two/four-wheeler showrooms, residences, apartment houses, and retail malls, and soon, which have been developed on open land. One of the most striking observations we made was that most construction activity has been taking place along the roadside, mostly alongside NH-34. Here are some photographs from the field that we took during the survey (Figure 10).

**Figure 8.** Triggering factors for built-up expansion probability modelling using a fuzzy logic model, such as (**A**) a dominance model, (**B**) a diversity model, and (**C**) a connectivity model. The fuzzification of the parameters using the membership function, such as (**D**) the fuzzified dominance model, (**E**) fuzzified diversity model, and (**F**) fuzzified connectivity model.

**Figure 9.** Fuzzy logic-based (**A**) built-up stability model, and (**B**) built-up expansion probability model for English Bazar.

**Figure 10.** *Cont*.

**Figure 10.** Under construction built-up areas on national highway-34 beyond the administrative boundary of the municipal areas, such as (**a**) a housing lodge at *Gabgachi* (1 km away from the University of Gour Banga); (**b**) a car showroom at the nearby area of *Gabgachi*, which can help to emerge other allied services in very soon upcoming days; (**c**) nursing home towards *Gazole* (another emerging site for the built-up area), which will help other allied services, hotels, restaurant, and others in the upcoming days; and (**d**) a shopping mall at *Madhabnagar* (southwards from the municipal areas), which will help to grow new built-up areas, like a garage, petrol stations, small shops, and others.
