View of Analysis of changes in land use and land cover in Central Kashmir of the Great Himalayas using geospatial technologies

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Analysis of changes in land use and land cover in Central Kashmir of the Great Himalayas using geospatial technologies

ARTICLE INFO ABSTRACT

Received : 28 April 2022 Revised : 31 July 2022 Accepted : 28 August 2022 Available online: 15 January 2023 Key Words:

Arc GIS

Change Detection Kappa Coefficient Satellite Imagery Supervised Classification

Remote sensing data may identify changes in land use and land cover (LU/LC).

Land cover changes include changing from one land cover category to another and changing conditions within a category. LU/LC change is an essential aspect of current environmental management techniques. It is vital for land conservation, sustainable development, and water resource management. The study's goal is to investigate changes in land use and land cover in Central Kashmir of the Great Himalayas. This study used LISS III 23.5 m resolution images between 2000 and 2017 to detect land cover change. Changes were identified using Arc GIS 10.4.1. This method identified seven land use/cover classes: water bodies, glaciers/snow; forests; agriculture; horticulture;

wasteland/barren; and built-up/utility. Ground truthing was done to test the accuracy of the preprocessing and categorization of the images. This study found that in the previous 17 years, all land use classes in Central Kashmir have changed significantly. Remote sensing and Geographic Information Systems (GIS) have been used to better comprehend the consequences of physical changes. The study's findings can be used to design resource conservation measures. To protect unwanted LU/LC change in Central Kashmir, proper land management methods, integrated watershed management, and community engagement should be encouraged.

Introduction

Land use refers to the employment and management approaches that human agents or land managers envision for the land cover in order to exploit it. It reflects anthropogenic accomplishments such as industrial zones, residential zones, agricultural fields, grazing, logging ,and mining Land cover, on the other hand, refers to the characteristics of the earth's land surface captured in the distribution of vegetation, water, desert, and ice, as well as the immediate subsurface, which includes biota, soil, topography, surface and groundwater, and structures created

solely by human activities like mine exposures and settlements (Lambin et al., 2003; Ahamad et al., 2022). Land use connects the land cover to anthropogenic activities that alter the land. Land cover changes take two forms: conversion from one category of land cover to another and modification of condition within a category (Meyer and Turner- II 1991). Land cover change stemming from human land uses represents a major source and a major element of global environment change (William et al., 1994; Houghton et al., 2012). The most potent contemporary forces that drive LU/LC change are

Journal homepage:https://www.environcj.in/

Environment Conservation Journal

ISSN 0972-3099 (Print) 2278-5124 (Online)

Syed Rouhullah Ali

Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Shalimar, Srinagar, J&K., India.

Junaid N. Khan

Rohitashw Kumar

Farooq Ahmad Lone

Shakeel Ahmad Mir

Imran Khan

Corresponding author E-mail: [email protected] Doi:https://doi.org/10.36953/ECJ.12542350

This work is licensed under Attribution-Non-Commercial 4.0 International (CC BY-NC 4.0)

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184 increasing human activities and climatic change (Xu 2008). However, the same land cover change can have different sources in different areas (Meyer and Turner-II 1991; Salazar et al., 2015). LU/LC change is a key component of current systems for managing natural resources and monitoring environmental changes. Conventional ground survey methods were time-consuming, arduous, costly, and manpower-intensive, making them unsuitable for monitoring dynamic changes over a short period of time because of time constraints.

However, the exorbitant costs of such surveys led to their downfall in the late 1960s. Change detection based on remote sensing data has become an essential technique for providing appropriate and wide-ranging information to various decision support systems for environmental sustainability and management of natural resources. Advances in the ability of geographic information systems to incorporate social, physical, and remote sensing information have also been significant. This is often done to understand how processes at local scales are nested in regional, national, and global dimensions. Collecting accurate and timely information on LU/LC is crucial for LU/LC change research (Giri et al., 2005). Repeated satellite images can allow for timely and consistent estimates of changes in LU/LC trends over large areas and have the additional advantage of ease of data capture into GIS, which can facilitate the analysis and presentation of such data (Shalaby and Tateishi 2007) greatly. In the Himalayan region, use of this tool was introduced in the mid-eighties (Singh et al., 1985) to identify landscape/land-use patterns, mapping, monitoring and change detection (Joshi et al., 2003).

Material and Methods

This study emphasizes land use/land cover change detection in the Central Kashmir Himalayas. The LU/LC analysis was studied using a comprehensive methodological framework that included the generation of various data sets. Remote sensing data, satellite imageries (LISS III 23.5 meters), and image processing techniques were used between 2000 and 2017 to ascertain LU/LC change detection. The changes were determined using the Arc GIS 10.4.1 software. Employing Supervised Classification, it was possible to categorize land use and land cover into seven distinct classes. Figures 1

and 2 offer a general overview of the various methodological steps described in detail below.

The Central Kashmir Valley's boundaries were determined using ASTER DEM, which comprises three districts and six watersheds. The details of the datasets used were downloaded from the various websites given in table 1. In order to generate the LU/LC map using satellite images, a LU/LC classification technique has been used. The appropriate number of LU/LC classes depends on the requirements of a specific project for a specific application (Saha et al., 2005). Seven major LU/LC classes were chosen for mapping the entire study area viz; waterbodies/wetlands, glacier/snow, forests, agriculture, horticulture/plantation, wasteland/barren, and built-up/utility. Following the development of the classification scheme, one of the most extensively used image classification techniques supervised classification, was used to map all of the land use/land cover classes to assess the land use pattern and its geographic variation using widely available satellite data. Prior to choosing training samples, the empirical approach of satellite data, Google Earth photographs, and toposheet of the subject region were thoroughly explored. The minimum number of training samples for most of the classes was 100. Before being utilized as an input for any applications, the classified images were further checked for accuracy. Individual accuracy evaluation parameters can be used in the study to evaluate the model performance of a specific category or class of interest. The accuracy of this study was assessed using an error matrix.

Table 1: Datasets used for the present study

S# Data Set Source 1. ASTER

DEM (30 m) https://search.earthdata.nasa.gov/search 2. LISS III

(23.5 m) https://bhuvan.nrsc.gov.in/

3.

SOI (Toposheets) Scale 1:50,000

https://www.surveyofindia.gov.in/

Results and Discussion

Land use/land cover analysis – 2000

The study's LU/LC analysis included a period of nearly 17 years, spanning from the year 2000 to

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Environment Conservation Journal 2017. The time spans have been chosen based on

the temporal representation and the availability of relevant remote sensing data. It was found that the research region in 2000 had seven different LU/LC classes as given belowin figure 3. In the study area, forest was the most prominent category of land cover with 1339.20 km², constituting more than 40

% of the total Central Kashmir Himalayan area.

The area under Snow/Glacier was 784.83 km² (23.85 %), while Agriculture accounts for 515.72 km² (15.67 %). Horticulture covered 293.81 km²

(8.93 %), and Wasteland/Barren is spread over an area of 215.31 km² (6.54 %) of the total area as shown in table 2 and figure 4. The area under Waterbody/Wetland/Water and Built-up/Utility constituted 2.40 % and 1.90 %, respectively of the total area of Central Kashmir Himalayas (Figure-3

& 4) (Table-2). A kappa value of 0.721 and an overall classification accuracy of 82.3 % were observed in the analysis. In light of the substantial kappa coefficient, the classified image is considered suitable for further investigation.

Table 2: Land Use/Land Cover statistics from 2000 to 2017

LU/LC 2000 2017 Relative Change

km² % km² % km² %

Waterbody/Wetland 79.00 2.40 69.66 2.12 9.34 -0.28

Snow/Glacier 784.83 23.85 799.98 24.31 -15.15 0.46

Built Up/Utility 62.64 1.90 170.01 5.17 -107.38 3.26

Forest 1339.20 40.70 1099.02 33.40 240.18 -7.30

Horticulture/Plantation 293.81 8.93 463.19 14.08 -169.39 5.15

Agriculture 515.72 15.67 357.15 10.85 158.58 -4.82

Wasteland/Barren 215.31 6.54 331.48 10.07 -116.17 3.53

Figure 1: Location map of the study area Figure 2: LU/LC change matrix methodology

Figure 3: LU/LC of Central Kashmir generated from LISS III 2000

Figure 4: Percentage area of LU/LC categories, 2000 2.40%

23.85%

1.90%

40.70%

8.93%

15.67% 6.54%

Waterbody/Wetland Snow/Glacier Build Up/Utility Forest Horticulture/Plantation Agriculture

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Figure 5: LU/LC of Central Kashmir generated from LISS III 2017

Figure 6: Percentage area of LU/LC categories, 2017

Figure 7: Percentage change of LU/LC categories, 2000 & 2017

Figure 8: Analysis of conversion of different LU/LC categories of Central Kashmir

Land use/land cover analysis – 2017

It was revealed in 2017 that there were seven distinct classes of land use and land cover (LU/LC) in the Central Kashmir as shown in figure 5.

Forests were again the most prevalent land cover category, covering 1099.02 km² (33.40 %).

Snow/Glaciers occupied about 799.98 km²(24.31

%). Horticulture constituted 463.19 km²(14.08 %) while Agriculture covered an area of 357.15 km²(10.85 %), followed by Wasteland/Barren as 331.48 km² (10.07 %). However, Built-up covered an area of 170.01 km² (5.17 %) while the Waterbody/Wetland was 69.66 km²(2.12 %) to the total area of the Kashmir Himalayas (Figure-5 & 6) (Table-2). The image categorized with an accuracy of 84.7% and a kappa value of 0.742. The kappa coefficient is substantial, indicating that the categorized imagery is appropriate for further analysis.

Change detection analysis of land use/land cover for Central Kashmir Himalayas

Comparisons of post-classification LU/LC change have showed significant changes in several LU/LC categories. The area under Horticulture/Plantation, Built-up/Utility, and Wasteland/Barren has continuously increased while the area under Forest and Agriculture has constantly shown a decreasing trend from 2000 to 2017. Table 2 shows that the forest area has decreased from 1339.20 km² in 2000 to 1099.02 km² in 2017, thus registering a decline rate of 7.30 % as reflected in figure 7. The agricultural class has also shown a decreasing trend from 2000 to 2017. The area has decreased from 515.72 km² to 357.15 km²,with an area loss of 158.58 km² (4.82 %) (Table-2). Similarly, the Built-up category increased from 118.98 km² in 2000 to 186.73 km² in 2017 (Table-2), indicating a 3.26 % increase (Figure-7). From 2000 to 2017,

2.12%

24.31%

5.17%

33.40%

14.08%

10.85%

10.07%

Waterbody/Wetland Snow/Glacier Build Up/Utility Forest Horticulture/Plantation Agriculture Wasteland/Barren

-0.28 0.46 3.26

-7.30 5.15

-4.82 3.53

-8.00 -4.00 0.00 4.00 8.00

Percentage Change

LU/LC Category

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Environment Conservation Journal there had been an increase in horticulture class as

well. 169.39 km² have been increased to the area, from 293.81 km² to 463.19 km² (Table-2) (5.15 %).

The area under Water in 2000 was 79.00 km² and got reduced to 69.66 km² in 2017 with a decrease of 9.34 km² (-0.28 %) (Figure-7, Table- 2).Glaciershave also shown a decreasing trend from 2000 to 2017. The area in 2000 was 784.83 km²while it got reduced to 799.98km² in 2017 with a decrease of 118.48 km² (-0.89 %) (Figure-7, Table-2).

Conversion of land use/land cover for Central Kashmir Himalayas

The analysis of the study has revealed that different LU/LC classes have shown conversion into different LU/LC categories. Agriculture showed conversion into three LU/LC categories: Barren, Built-up, and Horticulture. Barren category got changed into four LU/LC classes Agriculture, Built-up, Horticulture, and Forest. The land cover category of the forest showed the conversion into three LU/LC categories, viz. Agriculture, Barren, and Horticulture, while the Built-up category led no conversion. Horticulture showed the conversion into three Barren, Forest, and Built-up categories.

Water bodies/wetlands got changed into Built-up, Agriculture, and Horticulture, while Glacier/Snow

showed the conversion into two categories of Barren and Forest can be observed in figure 8.

Conclusion

It can be concluded from the initial results that the Central Kashmir Himalaya has indeed changed to LU/LC from the year 2000-2017. Out of all seven LU/LC classes, significant changes have occurred in forest areas, which showed a continuous decrease, and at the same time, Horticulture/Plantation land showed an increase of 5.15%. All these results infer and establish the apprehensions of the locals that the area is turning more into horticulture and arable area. This investigation was prompted by the local community's concerns about the changing landscape. This study illustrates how remotely sensed data combined with ground truth data might help to solve LU/LC management problems in the Central Kashmir Himalaya. A protective strategy should lead to several land use strategies. Local government should come up with planning and conservation groups to protect these valuable natural resources.

Conflict of interest

The authors declare that they have no conflict of interest.

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