A remotely sensed tracking of forest cover and associated temperature change in Margalla hills

Figures & data

Figure 1. Study area map showing Margalla Hills National Park and Rawal Lake.

Figure 2. Schematic flow of the implemented methodology. Preprocessing included band stacking, reprojection and subsetting. And post-classification processing included reclassification (or recoding), vectorization of classes, class extraction, merging and geometry computation.

Figure 3. Pie-charts showing percentage of area coverage of land cover classes on MHNP in 1992, 2000 and 2011.

Figure 4. Land use and Land cover map of Margalla Hills National Park for the year 1992.

Figure 5. Land use and Land cover map of Margalla Hills National Park for the year 2000.

Figure 6. Land use and Land cover map of Margalla Hills National Park for the year 2011.

Table 1. The area coverage (both in hectare and percentage) of different land cover classes in MHNP for the year 1992, 2000 and 2011.

Land cover classes	1992		2000		2011		Percentage change
	Area (Ha)	Area (%)	Area (Ha)	Area (%)	Area (Ha)	Area (%)	1992–2000 (%)	2000–2011 (%)
Agriculture	2124	11	2529	13	2613	14	9	4
Settlements	1921	10	3524	18	3656	18	83	4
Lower vegetation	5700	29	4398	22	4131	21	−22	−6
Pine forest	5007	25	2336	12	2980	15	−53	27
Scrub forest	3167	16	3489	17	3269	17	10	−6
Barren soil	1199	6	3120	16	2752	13	160	−11
Water body	594	3	316	2	311	2	−46	−1.5
Total	19,712	100	19,712	100	19,712	100

Notes: The last column specifies the percentage change in area of classes from 1992 to 2000 and 2000 to 2011. Percentage change = [(b−a)/a]×100, where a is the area of the class belonging to the erstwhile year and b is the area of the class from the more recent year. The positive sign shows an increase while the negative sign shows decrease in different years.

Figure 7. LULC changes in Margalla Hills from the year 1992–2011.

Figure 8. Post-classification comparison between the classified images of 1992 and 2000 presenting the shift among classes.

Figure 9. Post-classification comparison between the classified images of 2000 and 2011 presenting the shift among classes.

Table 2. Overall classification accuracy and kappa statistics.

	1992	2000	2011
Overall classification accuracy (%)	99.17	98.33	98.33
Overall Kappa statistics	0.9843	0.9627	0.9679

Figure 10. Boxplots for temperature difference and graph of P-values for the change classes from 1992 to 2000.

Figure 11. Boxplots for temperature difference and graph of P-values for the change classes from 2000 to 2011.

Table 3. Summary of ANOVA of the changed classes land surface temperature in the years 1992–2000 and 2000–2011.

Years	Degree of freedom	F-value	p-Value
1992–2000	36	7957	0.000
2000–2011	17	373.8	0.000

Table 4. Summary of the class shift from the year 1992 to 2000.

Class (1992)	% Unchanged	% Changed	Changed Class in 2000 in Hectares (ha)							Total (1992)
			Agriculture	Water	Soil	Pine forest	Scrub forest	Settlements	Lower vegetation
Water	1.5	1	47	305	89	2.3	2.3	41	32	518.6
Settlements	3.5	3	43	0.15	309	7	84	700	195	1338.15
Low vegetation	3	25	1332	1.3	119	1148	1811	650	576	5637
Agriculture	0.2	10	41	–	1015	4	71	669	307	2107
Soil	4.4	5.8	8	0.15	872	1	14	228	899	2022.15
Scrub forest	4.6	11.2	294	–	292	477	910	454	702	3129
Pine forest	3.4	21	736	–	338	671	1560	660	996	4961
Total (2000)	22	77	2501	306	3034	2310	4452.3	3402	3707	19712

Table 5. Summary of the class shift from the year 2000 to 2011

Class (2000)	% Unchanged	% Changed	Changed class in 2011 in hectares (ha)							Total (2000)
			Agriculture	Water	Soil	Pine forest	Scrub forest	Settlements	Low vegetation
Water	1.5	0.7	20	305	12.54	–	–	1	8	346.54
Settlements	10.4	13.9	–	–	63	0.3	2649	2058	30	4800
Low vegetation	3.9	3.96	117	–	0.3	–	743	22	776	1658.3
Agriculture	9.89	2.8	1951	–	–	424	–	1.68	133	2509.7
Soil	13.4	4.68	–	–	2652	–	0.3	926	0.22	3578.5
Scrub forest	2.2	20.4	120	–	–	725	438	13	3167	4463
Pine forest	10.2	1.78	309	–	43	2012	––	–	–	2364
Total (2011)	51	49	2517	305	2770.8	3161	3830	3021	4114.2	19712

Table 6. Summary of air temperature recorded for the month at which the images were acquired.

Year	Date of image acquisition	Minimum monthly temperature (°C)	Maximun monthly temperature (°C)	Average monthly temperture (°C)
1992	21 May (day 141)	19.5	31.0	26.3
2000	31 May (day 151)	17.35	30.1	26.0
2011	5 June (day 156)	19.7	31.7	26.0