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Spatio-Temporal Assessment of Delhi’s Green Cover Change using RS & GIS

Tanvi Sharma 1, G. Areendran2, Krishna Raj3 Mohit Sharma4

1 Consultant, IGCMC, WWF-India 2

Director, IGCMC, WWF-India 3

Senior Programme Coordinator, IGCMC, WWF-India 4

GIS Officer, WWF-India

172-B Lodhi Estate, New Delhi 110003

Abstract:

Urban areas can contain rich forests that significantly contribute to the biodiversity. An urban forest such as Ridge, maintain the green cover in Delhi providing a habitat for the urban biodiversity. Delhi experienced a rapid urbanization in past few decades. Increasing pressure from anthropogenic encroachment can cause instability in the natural ecosystem of forests which can disturb the habitat of flora and fauna of the region, further also can lead to forest fragmentation. RS and GIS are efficient methods to monitor and map the extent of alterations at a place over a period of time. This project focuses upon estimating the green cover changes in past 15 years in Delhi using geospatial technology. This being a temporal study, GIS was considered advantageous for this research. The land use land cover changes of Delhi were estimated for year 2000 and 2015 to quantify the change in its green cover. The Delhi Ridge had also been specifically focused at a detail. The spatio- temporal dynamics were estimated using unsupervised classification and change detection techniques for both Delhi and Delhi ridge. Although Delhi ridge has undergone slight distortions due to expansion of urban sprawl, change detection revealed that there was a slight increase in green cover of Delhi. Various metric measures of Class metrics were calculated using FRAGSTATS to understand the forest fragmentation pattern. On focusing upon ridge, its conditions have remained almost same for northern and south-central ridge. But fragmentation seemed to have increased for central and southern ridge. There has been observed an unprecedented growth in urban sprawl which is at the cost of agricultural and sub-urban land. The use of RS and GIS are considered ideal for this temporal study of estimation of forest and overall green cover changes in Delhi.

About the Author:

Ms. Tanvi Sharma

I am 23 years old and have done my Masters in

Biodiversity & Conservation from Guru Gobind

Singh Indraprastha University. During my masters I

got introduced to the field of GIS and worked on it

in my dissertation. I graduated in Life Science from

University of Delhi, Kalindi College. Currently I am

working as Consultant at WWF-India.

E mail ID: tanvisharma93@gmail.com

Contact: +91 9873731871

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Introduction

Urban forest cover is the dense vegetation that covers the surface of an urban area. They have a significant importance in sustenance of the urban biodiversity. Delhi’s forest majorly constitutes of the Aravalli hill ranging from Rajasthan to Delhi. It is the most ancient forest cover range of Delhi and is commonly known as Delhi Ridge. Once the ridge used to be a continuous stretch but it underwent fragmentation due to increasing population and their encroachment and finally led to the division of ridge forest into 4 zones that are present today (Sinha, 2014). India State of Forest Report 2011, by the ministry of environment and forests, says Delhi’s green cover has doubled in a decade from 151 sq. km in 2001 to 296.2 sq. km in 2011. Delhi lists 20% green cover according to the report. It still needs to increase up to 33% as required under the master plan 2021 and National Forest Policy of 1988. The Delhi forest department claims the number has increased by at least 2% in 2013 as compared to previous ones (Sengupta, 2013). The use of GIS and remote sensing is an integral part of the study as it is a highly efficient and reliable method for collection of data. This data can be utilized for assessing the vegetative cover and the ecological status of ridge area. These technologies are cost effective and practical tools for mapping any change occurring over extended period of time (Coppin & Bauer, 1996; Fraser, et al., 2005). Also the land use land cover is dynamic in nature and provides a relationship between anthropogenic and environmental interactions (Prakasam, 2010).

This is a software based assessment of change in land cover of Delhi and Delhi ridge due to developmental activities from past fifteen years, i.e. from 2000-2015. This comparative study is important to study the change in the vegetative cover or the degradation of the urban forested area happening as a result of urban sprawl and to evaluate the extent of fragmentation of ridge forests that has occurred over the period of time.

Methodology

This project required for Landsat 7 and 8 satellite imageries of the study area with 30m spatial resolution as it includes the comparison of satellite images of the two years. This provides the estimates for changes in the urban forest cover and land use over the period of 15 years from 2000 to 2015. The areas studied were- the NCT Delhi and the Delhi Ridge zones. Preprocessing of the image was done which included layer stacking, georeferencing and creating subset. Unsupervised classification was run to get different land use/land cover classes. Along with Delhi state, Delhi ridge forests were also classified separately for a detailed analysis, such that the forests could be divided and studied into more number of classes conveying better specifics of the forest. For the calculation of change matrix, ERDAS imagine was used to generate the area in hectares covered by each individual class pixels. NDVI that is Normalized Difference Vegetation Index was calculated for the complete Delhi Region to show total greenness present in the area. FRAGSTATS was run to estimate extent of forest fragmentation. Class metrics were chosen to be calculated for this study. The following class metrics were computed for every patch type or class in the landscape.

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Table 1: Class metrics calculated in FRAGSTATS Class Metrics Formula Description

Largest Patch Index

Units: Percent

a = area ( ) of patch ij. A = total landscape area ( ).

LPI equals the area (m2) of the largest patch of the corresponding patch type divided by total landscape area, multiplied by 100; i.e. LPI equals the percentage of the landscape comprised by the largest patch.

Number of Patches

Units: None

ni= number of patches of the corresponding patch type i

NP equals the number of patches of the corresponding patch type (class).

Patch Density

Units: Number per 100 hectares

ni= number of patches of the corresponding patch type i

PD equals the number of patches of the corresponding patch type (NP) divided by total landscape area, multiplied by 10,000 and 100 (to convert to 100 hectares).

Edge Density

Units: Meters per ha.

K= patch type n= No. of edge segments of patch type k; :total edge length in the landscape involving patch type k

ED equals the sum of the lengths (m) of all edge segments involving the corresponding patch type, divided by the total landscape area (m2), multiplied by 10,000 (to convert to hectares).

Total Core Area

Units: Hectares

= core area of patch ij based on specific edge depth.

TCA equals the sum of the core areas of each patch (m2) of the corresponding patch type, divided by 10,000 (to convert to hectares).

Source: McGarigal, 2015 Data Results and Analysis Land Use/ Land Cover Change Detection A difference of initial area and final area gives the change where negative value shows decrease while positive shows increase in the area. NCT Delhi region was classified into 10 classes and Delhi ridge region was classified into 6 classes. Following are the final classes of Delhi.

Table 2: Land use Land cover Classes for Delhi

Table 3: Change detection through LU/LC

Class Class Name 2000 2015 Change

Area in Hectare Percentage Area in Hectare Percentage

1 Water 4479.66 2.97 3169.35 2.10 -1310.31

2 Road 2810.34 1.86 3334.05 2.21 523.71

3 Suburban 12293.00 8.15 12844.50 8.51 551.5

4 Dense Forest 3693.78 2.45 3384.18 2.24 -309.6

5 Open Forest 4388.31 2.91 5012.82 3.32 624.51

6 Open Land 8358.12 5.54 13740.80 9.11 5382.68

7 Agriculture 59315.10 39.31 47704.90 31.62 -11610.2

8 Urban 39301.40 26.05 45293.20 30.02 5991.8

9 Tree Cover 7735.86 5.13 7389.63 4.90 -346.23

10 Parks 8504.55 5.64 9006.75 5.97 502.2

150880.12 100.00 150880.18 100.00

1. Water 2. Road

3. Suburban Area 4. Dense Forest

5. Open Forest 6. Open Land

7. Agriculture 8. Urban Area

9. Tree Cover 10. Parks

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A negative change is observed in water, dense forest and agriculture classes, inferring a decrease in area while rest of the classes shows a positive change indicating an increase in area. The suburban area has slightly increased, while there is a prominent increase in the urban area by 4%. The major change is observed in the agricultural area which has reduced from 39.31% in 2000 to 31.62% in 2015, due to increase in urban and suburban area.

Table 4: Change Matrix Table

Change Matrix After classification of both images, they were subjected to matrix union in ERDAS which produces a thematic layer that contains a separate class for every coincidence of classes in two layers based on intersection described with a change matrix diagram. The change matrix obtained from this process provides the total change in pixels. The map shown in fig. 3 represents overall changes where green color shows unchanged pixels and red indicates changed pixels.

Class 2000 2015

Water Road Suburban Dense Forest

Open Forest

Open Land Agriculture Urban

Tree Cover Parks Total

1 Water 38.06 2.23 0.44 0.38 0.85 18.07 25.52 8.61 4.22 1.62 100.00

2 Road 5.18 57.97 1.85 0.14 0.88 4.50 4.00 11.47 7.87 6.13 99.99

3 Suburban 1.31 0.66 44.78 0.07 0.58 3.14 1.40 27.22 9.67 11.50 100.34

4 Dense Forest 0.22 0.94 0.57 42.72 49.03 6.11 0.07 0.25 0.10 0.01 100.00

5 Open Forest 0.22 0.99 1.40 30.06 48.61 13.67 1.93 2.46 0.23 0.44 100.00

6 Open Land 1.84 3.39 3.52 3.30 7.10 30.48 12.47 24.57 5.64 7.69 100.00

7 Agriculture 1.11 0.83 11.41 0.23 0.42 7.50 69.94 4.91 2.34 1.30 100.00

8 Urban 0.35 2.04 0.09 0.04 0.13 3.16 0.39 85.14 3.31 5.35 100.00

9 Tree Cover 2.00 2.64 0.97 0.32 0.26 17.20 3.03 21.49 44.71 7.39 100.00

10 Parks 0.39 2.64 0.16 0.05 0.21 12.12 0.97 27.90 2.58 52.99 100.00

2.10 2.21 8.51 2.24 3.32 9.11 31.62 30.02 4.90 5.97 100.00

Figure 3: Change Matrix Map

Figure 2: LULC Maps for years 2000 & 2015

Figure 1: LULC Change of Delhi

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The diagonal axis in the change matrix represents no change areas i.e., the values highlighted in yellow color in the above table shows that these are percentage of unchanged pixels. Values highlighted in green are the pixels that have maximum changes. From this change matrix map, change between the two images from year 2000 and 2015 is shown distinctively. It specifically displays the conversion of pixels from each class into another. The matrix table calculated outlines the percentage change of individual classes. Normalized Differential Vegetative Index (NDVI) The NDVI value must range between -1 to +1. Values moving from negative towards positive represent more greenery. The maps in fig.4 show the NDVI results with values lying in the given range. The formula for calculation of NDVI is shown below: NDVI = (NIR- RED/ NIR + RED)

A Detailed Analysis of Delhi Ridge The Delhi ridge is particularly focused in this study. For studying the forests cover change of ridge specifically, only ridge forested area boundaries were marked and area was subsetted. This area was subjected to unsupervised classification again for the study of only forest cover variations.

Table 5: Land use Land cover Classes for Delhi Ridge 1. Dense Forest 2. Open Forest

3. Scrub Forest 4. Open Land

5. Built-up 6. Water

Table 6: Change Detection through LULC

Class Class Name 2000 2015 Change

Area in Hectare Percentage Area in Hectare Percentage

1 Dense Forest 3243.15 39.82 3227.13 39.63 -16.02

2 Open Forest 2693.43 33.07 2407.23 29.56 -286.2

3 Scrub Forest 1550.25 19.04 1312.74 16.12 -237.51

4 Open Land 298.8 3.67 651.6 8.00 352.8

5 Settlements 339.75 4.17 517.68 6.36 177.93

6 Water 18.63 0.23 27.63 0.34 9

8144.01 100.00 8144.01 100.00

The open forests have reduced from 33.07 percent to 29.56 percent and also the scrub forests have reduced from 19.04 to 16.12 percent. While the open land area has increased from 3.67 % to 8.00%. Also the settlements which were 4.17 percent in 2000 increased up to 6.36 percent contributing in further fragmentation of forest.

Figure 5: LULC Change of Delhi Ridge

Figure 4: NDVI Maps

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Figure 6: Maps showing LULC of Delhi Ridge Zones

Fragstats Results of Forest Fragmentation FRAGSTATS quantifies the Arial extent and spatial distribution of patches of forest within a landscape. The resulting class output file contains a row for every class, where the columns represent the individual metrics. (McGarigal, 2015). FRAGSTATS was run only for Central and southern ridge because the northern and south-central ridge did not had major variations with respect to forest fragmentation.

Central Ridge Table 7: FRAGSTATS results of Central Ridge for year 2000

CLASS TYPE NP PD LPI ED AREA MN TCA CORE MN

1 Forested area 27 0.77 34.53 35.46 50.89 736.92 27.29

2 Non Forested area 146 4.16 2.28 34.32 1.71 4.77 0.03

3 Water 2 0.06 0.02 0.21 0.63 0.00 0.00

Table 8: FRAGSTATS results of Central Ridge for year 2015

CLASS TYPE NP PD LPI ED AREA MN TCA CORE MN

1 Forested area 50 1.43 37.49 35.07 26.59 715.68 14.31

2 Non Forested area 119 3.39 1.36 36.27 2.47 8.01 0.07

3 Water 12 0.34 0.01 0.58 0.17 0.00 0.00

From the outputs obtained with FRAGSTATS for central ridge forest, it is evident that the number of patches which were 27 for forested areas in 2000 has increased to 50 in number. The greater the number of patches, greater is the extent of fragmentation. The core mean value have decreased down from 27.29ha to 14.31ha for forested area in 2015. Reduced core value indicated more edges which shows fragmentation of habitat. Southern Ridge

Table 9: FRAGSTATS results of Southern Ridge for year 2000

CLASS TYPE NP PD LPI ED AREA MN TCA CORE MN

1 Forested area 30 0.18 34.55 13.72 190.46 4189.23 139.64

2 Non Forested area 331 2.00 0.38 8.93 0.94 10.98 0.03

3 Water 28 0.17 0.04 0.44 0.53 0.00 0.00

Table 10: FRAGSTATS results of Southern Ridge for year 2015

CLASS TYPE NP PD LPI ED AREA MN TCA CORE MN

1 Forested area 64 0.39 31.55 27.20 81.89 2211.75 34.56

2 Non Forested area 1038 6.28 0.52 25.57 0.75 39.06 0.04

3 Water 30 0.18 0.04 0.60 0.74 0.00 0.00

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Southern ridge results show a considerable increase in number of patches for forested as well as non-forested area. This indicates that there are more fragmented patches in 2015 as compared to 2000. The total core area (TCA) for forested area was 4189.23 in 2000 which has reduced to 2211.75 in 2015. This means due to fragmentations, the core area have decreased, while its values have increased for non-forested area class from 10.98 to 39.06 indicating expansion of non-forested area such as built-up. The Edge Density (ED) for non-forested area is also greater than before.

Discussion

From the LULC generated by classifying the image, it was observed that the overall green cover of Delhi has increased in these years from 24322.50 ha to 24793.38 ha. A change in forest densities has been observed. Majorly there is conversion of dense forests into open forest which has caused an increase in the open forest cover by 0.41%. The LULC of Delhi has shown the expansion of urban and sub-urban settlement areas which is the main reason for the forest density changes. On specifically focusing at Ridge Forests, it was observed from FRAGSTATS results that there is an increase in fragmentation of forest due to urban area expansion.

Conclusion

Delhi’s green cover has altered during these fifteen years owing to many infrastructural variations that took place during this period. The Department of Forest and Wildlife, Government of NCT Delhi is working for maintaining the integrity of forests and green cover in Delhi through various measures like plantation drives and protection activities. This comparative analysis is important to study the change in the vegetative cover and the degradation of the urban forested area happening as a result of urban sprawl. It gives the present status of the forests of Delhi and can become useful to know priority concern areas. The use of remote sensing and geographical information system is considered to be an ideal technique for this temporal study for estimation of forest and overall green cover changes in Delhi.

Acknowledgement

I take this opportunity to express my profound gratitude and deep regards to my supervisor Dr. G. Areendran, Director, IGCMC, WWF-India for providing me the opportunity to intern with WWF-India, for his exemplary guidance, monitoring and constant encouragement throughout the course of my project and Dr. Krishna Raj, Senior Programme Coordinator, IGCMC, WWF-India, for his cordial support, valuable information and guidance, which helped me in completing this task through various stages. I am also thankful to Mr. Mohit Sharma, GIS Officer, WWF-India, for his guidance throughout my project. I also thank Mr. Ravi Singh, CEO and SG, WWF-India and Dr. Sejal Worah, Programme Director, WWF-India for their support. Also I am grateful to my teachers at Guru Gobind Singh Indraprastha University.

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References

1. Areendran G., Sankar K., Pasha K. and Qureshi Q. 2012. Quantifying Land Use Land Cover Change in Pench Tiger Reserve (Madhya Pradesh, India): A Landscape Approach. Asian Journal of Geoinformatics 12(1).

2. Coppin P. R. and Bauer M. E. 1996. Change detection in forest ecosystem with remote sensing digital imagery. Remote Senseing Reviews 13: 207-223.

3. McGarigal K., Marks B. J. FRAGSTATS: Spatial Pattern Analysis Program for Quantifying Landscape Structure. University of Massachusetts, Amherst. Available at site: http://www.umass.edu/landeco/research/fragstats/fragstats.ht ml

4. Ministry of Environment and Forest, 2013. India State Forest Report, Dehradun: Forest Survey of India. 5. Prakasam C. 2010. Land use and land cover change detection through remote sensing approach: A

case study of Kodaikanal taluk, Tamil nadu. International journal of geomatics and geosciences 1(2). 6. Sengupta, R., 2013. Delhi | The forest city. Livemint. 7. Sinha G. N. 2014. An Introduction to the Delhi Ridge. 1st ed. New Delhi: Department of Forest and

Wildlife.