Based on the above methods and methodology, the acquired results are given and analysed below:
3.1 LULC and LST
LST increases as a result of LULC change. The LULC in Hisar city changed significantly during the 31 years between 1991 and 2022 because of rapid urbanization. A 1991 study revealed that the areas under the categories "water bodies", "vegetation", "built-up areas" and "barren land" were 1.99 (1.8%), 61.73 (56.49%), 18.76 (17.17%), and 26.83 (24.54%) km2 respectively. There were 1.75 (1.6%), 36.44 (33.33%), 41.72 (38.17%) and 29.40 (26.90%) km2 under the "water body", "vegetation", "built-up area" and "barren land" classes, respectively, in 2001 (Fig. 6). "Water bodies", "vegetation", "built-up areas", and "barren land" accounted for 4.43 (4.05%), 34.90 (31.94%), 53.66 (49.09%), and 16.31 (14.92%) km2 respectively, of the total area in 2011. Water bodies, vegetation, built-up areas, and barren land made up 3.36 (3.07%), 30.05 (27.49%), 64.14 (58.69%), and 11.76 (10.75%) km2 of the total area in 2022, respectively. Only 18.76 km2 of the city area was developed in 1991, but 64.14 km2 has been developed in 2022, representing almost 58.69% of the total city area (Table 2). In this period of 31 years, the built-up area of Hisar city increased by nearly 41.51%, resulting in a 41.51% reduction in other land use. The area under the “vegetation” and “barren land” classes decreased by -46.75% from 1991 to 2020 and were converted to built-up areas and waterbodies (Fig. 4, Fig. 5; Table 3). As a result of these changes in LULC, the LST in Hisar city was significantly affected. The areas with higher temperatures can be observed in (Fig. 3), which shows mostly built-up areas. In total, approximately ten spots with the highest temperatures were taken from the LST of 2022 for ground truthing. Industrial, commercial, agricultural and residential establishments are most likely to be hot spots with the highest temperatures. During the period 1991–2022, the minimum LST reached 37.40°C, up from 17.02°C in 1991. Moreover, the highest temperature in 2022 has risen upward from 30.00°C in 1991 to 47.24°C (Table 4).
In the period 1991–2022, the lowest and highest temperatures in the city increased by almost 20.38°C and 17.24°C, respectively. Meteorological department officials said that maximum temperature rose five notches in Hisar city, and a hot summer occurred in Haryana, where Hisar has experienced 48°C temperatures on its hottest day in 2022 [73]. The maximum temperature in this study was 47.24°C in 2022, which matches the recorded data from meteorological departments. There is a 0.76°C variation here. It is evident from this that the study is relatively accurate and shows a reasonable degree of agreement. The relative values (RLSTs) from 1991 to 2022 are shown in Fig. 7. In Table 5, the minimum, maximum, and average LST values for 1991–2022 are shown. LSTs reached their highest point in 2022 (42.3°C), while they reached their lowest point in 1991 (23.51°C). For Hisar, the reported air temperature for the corresponding date was not significantly greater than 0.76 degrees Celsius, which confirms the accuracy of the LST data. The low resolution of Landsat images may limit the ability to compare different years due to limitations in image capture. A regional heat island (RHI) was defined as an area with an RLST > 3°C. There has been a significant increase in RHI connectivity since 1991, especially in the central, western, southeastern, and northeastern parts of Hisar. In the past few years, several isolated patches have gradually merged. This may be due to the rapid economic development and urbanization that has taken place in Hisar, which has led to the expansion of built-up land. In Hisar's central, western, southeastern, and northeastern regions, the RHI increased from 1991 to 2022, but in its northwestern (lower land area) regions, the RHI decreased significantly, especially where the RLST was low.
Table 2
Calculation of Temporal LULC area and (%) of Hisar
LULC Class | 1991 | 2001 | 2011 | 2022 |
---|
(Area) | (Area) | (Area) | (Area) |
---|
(km2) | (%) | (km2) | (%) | (km2) | (%) | (km2) | (%) |
---|
Water Body | 1.99 | 1.80 | 1.75 | 1.6 | 4.43 | 4.05 | 3.36 | 3.07 |
Vegetation | 61.73 | 56.49 | 36.44 | 33.33 | 34.90 | 31.94 | 30.05 | 27.49 |
Built-up Area | 18.76 | 17.17 | 41.72 | 38.17 | 53.66 | 49.09 | 64.14 | 58.69 |
Barren Land | 26.83 | 24.54 | 29.40 | 26.9 | 16.31 | 14.92 | 11.76 | 10.75 |
Table 3
Temporal change in LULC from 1991 to 2022
Sr. No. | Class to Class Change | Area (km) | Sr. No. | Class to Class Change | Area (km) |
---|
1. | Barren Land - Built-up Area | 19.75 | 9. | Vegetation - Built-up Area | 29.86 |
2. | Barren Land - Vegetation | 3.84 | 10. | Vegetation - Vegetation | 22.22 |
3. | Barren Land - Barren Land | 2.95 | 11. | Vegetation - Barren Land | 7.38 |
4. | Barren Land - Water Body | 0.29 | 12. | Vegetation - Water Body | 2.20 |
5. | Water Body - Built-up Area | 0.96 | 13. | Built-up Area - Built-up Area | 13.55 |
6. | Water Body - Vegetation | 0.37 | 14. | Built-up Area - Vegetation | 3.58 |
7. | Water Body - Barren Land | 0.10 | 15. | Built-up Area - Barren Land | 1.32 |
8. | Water Body - Water Body | 0.55 | 16 | Built-up Area - Water Body | 0.32 |
Table 4
Area (km) under different temporal LST ranges in Hisar city
Year | LST Range |
---|
0–19.7 | 19.7–23.2 | 23.2–27.5 | 27.5–37.4 | 37.4–40.5 | 40.5–42.9 | 42.9–47.3 |
---|
1991 | 20.18 | 62.12 | 25.36 | 1.65 | - | - | - |
2001 | 2.66 | 15.11 | 31.68 | 59.86 | - | - | - |
2011 | - | 16.64 | 57.61 | 35.06 | - | - | - |
2022 | - | - | - | - | 14.43 | 46.90 | 47.24 |
Table 5
Statistics of Temporal LST of Hisar
Years | LST |
---|
Minimum | Maximum | Mean | Std. Deviation |
---|
1991 | 17.02 | 30.00 | 23.51 | ± 1.98 |
2001 | 18.15 | 36.38 | 27.26 | ± 3.20 |
2011 | 19.72 | 34.86 | 27.29 | ± 2.50 |
2022 | 37.40 | 47.2 | 42.3 | ± 1.43 |
The RHI of the standard deviation ellipse (SDE) results are presented in Fig. 8. In 1991 and 2022, the SDE ranges were mostly located in the central region and gradually shifted to the southwest, southeastern, north-eastern, and eastern regions. Furthermore, Table 6 demonstrates a decrease in rotation from 73.20 in 1991 to 69.26 in 2022, indicating a change in the spatial pattern of RHI from the centre to the east, west, and south with rapid urbanization in Hisar.
Table 6
Temporal analysis of SDEs
Years | Minor Axis (km) | Major Axis (km) | SD_X | SD_Y | Rotation |
---|
1991 | 18.2 | 78.45 | 4.21 | 7.58 | 73.20 |
2001 | 17.1 | 79.23 | 4.35 | 8.21 | 71.24 |
2011 | 18.4 | 82.32 | 4.22 | 7.91 | 70.36 |
2022 | 17.3 | 82.56 | 4.33 | 6.84 | 69.26 |
3.2 Correlation between the NDBI and NDVI and between the LST
The LST of any surface area is strongly correlated with the NDVI and NDBI. The vegetation cover is greatest and the LST is lowest. The NDVI values ranged from (-0.3125 to 0.7183), which indicated that most of the area had more vegetation cover than did a built-up area, water body, or barren land (Fig. 9).
It is evident that there was an increase in "built-up areas" and a decrease in vegetated areas in 2001, judging by the NDVI values ranging from − 0.5 to 0.4767 and negative values increasing over this time period. In 2011, the NDVI values ranged from (-0.5 to 0.4767) and the decreases were more pronounced than those in 2001's decreases, indicating that urban areas have grown more while vegetated areas have decreased more. Over 70% of the area has negative NDVI values in 2022, with 58.69% of the land under the built-up category. Figure 4, shows that most of the areas in the “vegetation” and “barren land” classes from 1991 to 2022 were converted into the “built-up” class. A simple linear regression model demonstrated a significant relationship between LST, and NDVI, and between LST and the NDBI (Fig. 10; Fig. 11). According to this relationship, the change in land use contributes to rising temperatures. The NDVI and NDBI variables were selected as independent variables for a simple linear regression model. When the vegetation density is high, the temperature decreases, while when the vegetation density is low, it increases (Fig. 9). As shown in Fig. 9, the NDVI exhibited an inverse relationship with the LST with R2 values of 0.50, 0.38, 0.20 and 0.31 for 1991, 2001, 2011 and 2022. On the other hand, the NDBI and LST are strongly correlated, as indicated by the R2 values for 1991 to 2022 respectively (Fig. 10). There is a clear relationship between the built-up area and temperature, such that the higher the area is, the greater the temperature. The LST and NDVI have a negative correlation, which suggests that green space can reduce UHIs.
3.3 Urban heat island (UHI), comfort level of urban thermal load(CLUT) and UTFVI
Based on the results, the UHI effect increases in all directions from the inward to the outward direction of the city. There was a notable increase in UHIs from in 1991 to 2022 in parts of the city that had built-up and lost vegetation, particularly in the southwestern, central, southern, and southeastern areas of Hisar city. The results showed that the temperature increased from 20.18°C in 1991 to 47.24°C in 2022. The UHI effect has increased over the past 31 years (Fig. 12). Based on these results, the maximum UHI over Hisar city were 28°C in 1991, 30°C in 2001, 37°C in 2011, and 47°C in 2022. The minimum UHIs value (18°C) occurred in 1991, whereas the minimum UHI value (37°C) increased in 2022. To determine the urban thermal comfort level and discomfort zone for human life, the UTFVI is classified into six classes based on the UHI effect. As a result, 57.01 km2 (52.15%), 65.46 km2 (59.87%), 59.01 km2 (53.94%), and 39.72 km2 (36.3%) have excellent-normal comfort for human life while 51.23 km2 (47.35%), 43.85 km2 (40.13%), 50.30 km2 (46.06%) and 69.59 km2 (63.7%) have the strongest-strongest UHIs in 1991, 2001, 2011 and 2022, respectively categorized as the worst-worst zones for human life due to heat and warming (Table 7). The ecological status of the Hushi city was determined by the UTFVI and UHI values.
Figure 12: UHI and CLUT maps (A, A1; B1, B2; C1, C2; C1,C2 for 1991;2001;2011;2022)
Table 7
Measurement of UHI and CLUT based on the UTFVI
UTFVI | Phenomenon of UHI | Comfort level of urban thermal (CLUT) | HUI/CLUT | HUI/CLUT | HUI/CLUT | HUI/CLUT |
---|
Area (1991) | Area (2001) | Area (2011) | Area (2022) |
---|
sq. km | (%) | sq. km | (%) | sq. km | (%) | sq. km | (%) |
---|
< 0 | None | Excellent | 11.96 | 10.95 | 19.63 | 17.95 | 13.85 | 12.67 | 6.04 | 5.5 |
0–0.005 | Weak | Good | 24.34 | 22.26 | 16.97 | 15.52 | 35.52 | 32.45 | 18.82 | 17.21 |
0.005–0.01 | Middle | Normal | 20.71 | 18.94 | 28.86 | 26.4 | 9.64 | 8.82 | 14.86 | 13.59 |
0.01–0.015 | Strong | Bad | 34.57 | 31.62 | 19.79 | 18.1 | 23.28 | 21.34 | 38.23 | 34.91 |
0.015–0.02 | Stronger | Worse | 13.20 | 12.07 | 8.73 | 7.98 | 18.18 | 16.63 | 10.58 | 9.67 |
> 0.02 | Strongest | Worst | 4.53 | 4.16 | 15.33 | 14.05 | 8.84 | 8.09 | 20.78 | 19.12 |
Table 8
Accuracy assessment analysis
LULC Class | User Accuracy (%) | Producer Accuracy (%) |
---|
1991 | 2001 | 2011 | 2022 | 1991 | 2001 | 2011 | 2022 |
---|
Water Body | 89.0 | 90.0 | 92.1 | 95.0 | 86.6 | 93.5 | 90.2 | 95.0 |
Vegetation | 88.0 | 90.0 | 93.0 | 95.0 | 84.1 | 91.2 | 93.1 | 95.0 |
Built-up Area | 89.0 | 90.0 | 94.0 | 95.0 | 86.0 | 93.1 | 95.0 | 95.0 |
Barren Land | 83.0 | 90.0 | 90.0 | 95.0 | 80.2 | 86.5 | 90.3 | 95.0 |
| Overall Accuracy (%) | Kappa Coefficient (%) |
1991 | 2001 | 2011 | 2022 | 1991 | 2001 | 2011 | 2022 |
Water Body | 86.6 | 93.0 | 92.0 | 95.0 | 80.0 | 80.8 | 81.6 | 84.1 |
Vegetation | 85.0 | 92.0 | 92.0 | 95.0 | 80.0 | 81.0 | 81.6 | 84.1 |
Built-up Area | 86.2 | 93.0 | 92.0 | 95.0 | 80.0 | 81.0 | 81.6 | 84.1 |
Barren Land | 82.0 | 86.0 | 92.0 | 95.0 | 80.0 | 80.8 | 81.6 | 84.1 |
Discussion
According to the present study, there were clear correlation between UHI, biodiversity loss, and ecosystem degradation and LULC around cities. Impacts, such as the decline in vegetation coverage, the increase in minimum and maximum temperatures, which directly affect the urban thermal environment, have been identified. Biodiversity and natural ecosystems are adversely affected by rapid urbanization [74]. With the exponential growth of Hisar city’s population, and with its massive industrial and commercial expansion, its land use has changed significantly. Prior to 1991, the land in Hisar city was mainly agricultural, barren land, and covered with vegetation and these areas were converted into industries and residential areas after 1991. Its rapid population growth coupled with residential industrial, and commercial expansion had major impact on its solar radiance and longwave radiation (LST). In the built-up areas, the temperature increased significantly between 1991 and 2022. There are several densely developed commercial and residential areas in the city, including the Jindal industrial area, automobile market, Mil Gate, Azad Nagar, bus stand, airport, court complex, and old Hisar area. Due to the low amount of vegetation and water bodies in this area, heat islands and higher LST values are now predominant here. The above places had the highest heat island spots, while agricultural university and city boundary had the lowest LST values. As this study revealed, the average temperature in Hisar city increased with increasing minimum temperatures.
LULC types and LSTs have been found to be directly related to UHI trends. The NDVI and LST in the study area were inversely related for all types of LULC. Compared to other areas, industrial, residential and commercial areas had the highest LSTs and the greater influence on the NDVI. Increasing vegetation cover in Hisar city is therefore the best way to reduce temperature. The study area's urban heat characteristics can be improved by increasing vegetation cover in built-up areas, particularly industrial, commercial and nearby residential areas. Based on the NDVI analysis of 1991, the city in 2022 could not be accurately represented, because there was a decrease in vegetation in most of the locations. As a result of infrastructure construction projects encroaching into existing vegetation, trees are being cut down, contributing to a higher LST. In addition, this results in pollution that worsens Hisar’s situation. As an industrial city, Hisar should prioritize low carbon emissions. It is important for local governments to take precautions to encourage industries to reduce emissions and implement green initiatives. Youths in Hisar city should be made aware of extreme heat risks through a pilot campaign. Through the creation of short videos with messages in the local language, the campaign focused on the risks of heat and the ways to reduce them. Youths and policymakers were able to engage through this platform [75]. As a means of raising awareness, local governments could take this type of initiative. It is important the local governments to promote early warning or robust forecast systems to reduce the effects of LSTs and UHIs, even though their resources and budget are limited. They can also create spray parks for cooling, urban forests, cooling centres for communities, elimination of smoke-emitting vehicles, and paint roofs to cool them. A heat action plan should also be prepared by the national government and the local government because different regions have different drivers and intensities of heat. By doing so, we will be able to identify city hotspots and take action to reduce the effects of UHIs.