Dynamicity of Land Use/Land Cover (LULC): An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation (DMC) in India

doi:10.1016/j.regsus.2023.05.001

Abstract

Abstract:

The availability of better economic possibilities and well-connected transportation networks has attracted people to migrate to peri-urban and rural neighbourhoods, changing the landscape of regions outside the city and fostering the growth of physical infrastructure. Using multi-temporal satellite images, the dynamics of Land Use/Land Cover (LULC) changes, the impact of urban growth on LULC changes, and regional environmental implications were investigated in the peri-urban and rural neighbourhoods of Durgapur Municipal Corporation in India. The study used different case studies to highlight the study area’s heterogeneity, as the phenomenon of change is not consistent. Landsat TM and OLI-TIRS satellite images in 1991, 2001, 2011, and 2021 were used to analyse the changes in LULC types. We used the relative deviation (RD), annual change intensity (ACI), uniform intensity (UI) to show the dynamicity of LULC types (agriculture land; built-up land; fallow land; vegetated land; mining area; and water bodies ) during 1991-2021. This study also applied the Decision-Making Trial and Evaluation Laboratory (DEMATEL) to measure environmental sensitivity zones and find out the causes of LULC changes. According to LULC statistics, agriculture land, built-up land, and mining area increased by 51.7, 95.46, and 24.79 km², respectively, from 1991 to 2021. The results also suggested that built-up land and mining area had the greatest land surface temperature (LST), whereas water bodies and vegetated land showed the lowest LST. Moreover, this study looked at the relationships among LST, spectral indices (Normalized Differenced Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI)), and environmental sensitivity. The results showed that all of the spectral indices have the strongest association with LST, indicating that built-up land had a far stronger influence on the LST. The spectral indices indicated that the decreasing trends of vegetated land and water bodies were 4.26 and 0.43 km²/a, respectively, during 1991-2021. In summary, this study can help the policy-makers to predict the increasing rate of temperature and the causes for the temperature increase with the rapid expansion of built-up land, thus making effective peri-urban planning decisions.

Key words: Land Use/Land Cover (LULC), Peri-urban and rural neighbourhoods, Normalized Differenced Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Land surface temperature (LST), Environmental sensitivity

Subrata HALDAR, Somnath MANDAL, Subhasis BHATTACHARYA, Suman PAUL. Dynamicity of Land Use/Land Cover (LULC): An analysis from peri-urban and rural neighbourhoods of Durgapur Municipal Corporation (DMC) in India[J]. Regional Sustainability, 2023, 4(2): 150-172.

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Product	Sensor	Date	Path/row	Band		Spatial resolution
Landsat 5	TM	9 February, 1991	139/044	Band 1	Blue	30 m
				Band 2	Green
				Band 3	Red
				Band 4	Near infrared
				Band 6	Thermal infrared
Landsat 5	TM	20 February, 2001	139/044	Band 1	Blue	30 m
				Band 2	Green
				Band 3	Red
				Band 4	Near infrared
				Band 6	Thermal Infrared
Landsat 5	ETM	16 February, 2011	139/044	Band 1	Blue	30 m
				Band 2	Green
				Band 3	Red
				Band 4	Near infrared
				Band 6	Thermal infrared
Landsat 8	OLI-TIRS	27 February, 2021	139/044	Band 2	Blue	30 m
				Band 3	Green
				Band 4	Red
				Band 5	Near infrared
				Band 10	Thermal Infrared Scanner-1
				Band 11	Thermal Infrared Scanner-2

Kappa coefficient	Characteristics
<0.40	Poor or very poor agreement
0.40-0.55	Fair agreement
0.55-0.70	Good agreement
0.70-0.85	Very good agreement
>0.85	Excellent agreement

Year	LULC types
	Agriculture land		Built-up land		Fallow land
	Area (km²)	Percentage (%)	Area (km²)	Percentage (%)	Area (km²)	Percentage (%)
1991	196.16	31.24	32.57	5.19	89.82	14.30
2001	230.13	36.64	61.96	9.86	110.15	17.54
2011	270.73	42.99	99.64	15.86	96.61	15.38
2021	247.93	39.33	128.03	20.39	46.95	7.47
Year	Vegetated land		Mining area		Water bodies
Year	Area (km²)	Percentage (%)	Area (km²)	Percentage (%)	Area (km²)	Percentage (%)
1991	299.99	47.76	0.88	0.14	9.02	1.44
2001	217.28	34.59	3.25	0.52	5.69	0.91
2011	149.86	23.86	8.35	1.33	3.27	0.52
2021	172.14	27.41	25.67	4.08	7.75	1.23

LULC types	RD (%)
LULC types	1991-2001	2001-2011	2011-2021	1991-2021
Agriculture land	17.32	17.64	-8.42	26.39
Built-up land	90.24	60.81	28.49	293.09
Fallow land	22.63	-12.29	-51.40	-47.73
Vegetated land	-27.57	-31.03	14.87	-42.62
Mining area	269.32	156.92	207.43	2817.05
Water bodies	-36.92	-42.53	137.00	-14.08

Accuracy	LULC types	Year
Accuracy	LULC types	1991	2001	2011	2021
Producer accuracy (%)	Agriculture land	97.14	96.61	93.55	95.16
	Built-up land	94.73	92.16	95.74	95.83
	Fallow land	90.63	93.55	96.67	96.67
	Mining area	90.48	90.48	90.00	94.74
	Vegetated land	100.00	98.00	97.96	100.00
	Water bodies	93.55	96.43	90.63	90.63
User accuracy (%)	Agriculture land	97.14	95.00	96.67	98.33
	Built-up land	90.00	94.00	90.00	92.00
	Fallow land	96.67	96.67	96.67	96.67
	Mining area	95.00	95.00	90.00	90.00
	Vegetated land	98.00	98.00	96.00	98.00
	Water bodies	96.67	90.00	96.67	96.67
Overall accuracy (%)		95.83	95.01	94.58	95.83
Kappa coefficient		0.95	0.94	0.93	0.95