The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLII-5
https://doi.org/10.5194/isprs-archives-XLII-5-285-2018
https://doi.org/10.5194/isprs-archives-XLII-5-285-2018
19 Nov 2018
 | 19 Nov 2018

FOREST CANOPY DENSITY ASSESSMENT USING HIGH RESOLUTION LISS-4 DATA IN YAMUNANAGAR DISTRICT, HARYANA

K. E. Mothi Kumar, R. Kumar, P. Kumar, Sattyam, V. Sihag, Partibha, K. Singh, S. Rani, P. Sharma, R. S. Hooda, and T. P. Singh

Keywords: Forest Canopy Density (FCD), Afforestation, LISS-4, Notified forest area, Forest Quality, AVI, BSI, CSI, ITTO

Abstract. Forest plays an important role not only in providing ecological services but also economic goods to human beings. However, with increase in population there is a wide gap between demand and supply of these goods and services. This has lead to reduction in forest cover which needs to be taken care on regular time interval. To manage the existing forest area and also to increase the forest cover Forest Canopy Density (FCD) methodology is the main factor which was given by International Tropical timber Organization (ITTO). High resolution remote sensing LISS-4 data gives us chance to assess the quality of forest in terms of FCD as Rikimaru et al (1999) stated that FCD is one important parameter to assess forest cover quality. High resolution LISS-4 data analysis for FCD was never attempted before. Authors here attempted to assess the FCD utilizing methodology adopted by Rikimaru (1999), Huang (2001), Azizia (2008). The adopted methodology is one of the most efficient and cost effective way to derive the FCD. For this study Resourcesat-2 LISS-4 post monsoon data of year 2017 for Yamunanagar district was used to assess FCD within notified forest boundary. Notified forest boundaries at cadastral level prepared previously by Haryana Space Applications Centre (HARSAC) was used. The degree of forest canopy density is expressed in percentages: i.e. < 10% FCD (scrub land), 10–20% (Open Forest-I), 20–40% (Open Forest-II), 40–60% (Moderate Dense), 60–80% (Medium Dense) and > 80% (Highly Dense). Forest Canopy Density was based on three indices i.e. Advanced Vegetation Index (AVI), Bare Soil Index (BSI) and Canopy Shadow Index (CSI). Accuracy assessment was done based on ground data and comparison with Coterminous Google Earth imagery and it was found that the devised methodology has achieved overall accuracy of 93% with kappa coefficient of 0.9153. The result shows that maximum forest area in Yamunanagar district is in medium dense FCD category which is approximately 23948.08 acres. This study tells us that 24.2% of the total forest area is under scrub land and open forest which should be focussed for activities in working plan to increase the forest cover. This paper highlights the utility of high resolution satellite data for monitoring and management of forest and improvement in its quality. This attempt provided large scale (1 : 10,000) maps to the forest managers to better equip them in planning for afforestation, reforestation and rehabilitation of water logged areas, environment management and their future aspect.