VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA THROUGH GEO-INFORMATICS APPROACH

The study was conducted in Uttara Kannada districts during the year 2012&ndash;2014. The study area lies between 13.92&deg;&thinsp;N to 15.52&deg;&thinsp;N latitude and 74.08&deg;&thinsp;E to 75.09&deg;&thinsp;E longitude with an area of 10,215&thinsp;km<su...

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Main Authors: A. G. Koppad, B. S. Janagoudar
Format: Article
Language:English
Published: Copernicus Publications 2017-05-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1-W1/219/2017/isprs-archives-XLII-1-W1-219-2017.pdf
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spelling doaj-64b931928e4a4dd3b45b6998d9f4afbe2020-11-24T21:11:50ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-05-01XLII-1-W121922310.5194/isprs-archives-XLII-1-W1-219-2017VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA THROUGH GEO-INFORMATICS APPROACHA. G. Koppad0B. S. Janagoudar1College of Forestry Sirsi-581401,Karnatak, IndiaUniversity of Agricultural Sciences, Dharwad, IndiaThe study was conducted in Uttara Kannada districts during the year 2012&ndash;2014. The study area lies between 13.92&deg;&thinsp;N to 15.52&deg;&thinsp;N latitude and 74.08&deg;&thinsp;E to 75.09&deg;&thinsp;E longitude with an area of 10,215&thinsp;km<sup>2</sup>. The Indian satellite IRS P6 LISS-III imageries were used to classify the land use land cover classes with ground truth data collected with GPS through supervised classification in ERDAS software. The land use and land cover classes identified were dense forest, horticulture plantation, sparse forest, forest plantation, open land and agriculture land. The dense forest covered an area of 63.32&thinsp;% (6468.70&thinsp;sq&thinsp;km) followed by agriculture 12.88&thinsp;% (1315.31&thinsp;sq.&thinsp;km), sparse forest 10.59&thinsp;% (1081.37&thinsp;sq.&thinsp;km), open land 6.09&thinsp;% (622.37&thinsp;sq.&thinsp;km), horticulture plantation and least was forest plantation (1.07&thinsp;%). Settlement, stony land and water body together cover about 4.26 percent of the area. The study indicated that the aspect and altitude influenced the forest types and vegetation pattern. The NDVI map was prepared which indicated that healthy vegetation is represented by high NDVI values between 0.1 and 1. The non-vegetated features such as water bodies, settlement, and stony land indicated less than 0.1 values. The decrease in forest area in some places was due to anthropogenic activities. The thematic map of land use land cover classes was prepared using Arc GIS Software.http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1-W1/219/2017/isprs-archives-XLII-1-W1-219-2017.pdf
collection DOAJ
language English
format Article
sources DOAJ
author A. G. Koppad
B. S. Janagoudar
spellingShingle A. G. Koppad
B. S. Janagoudar
VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA THROUGH GEO-INFORMATICS APPROACH
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet A. G. Koppad
B. S. Janagoudar
author_sort A. G. Koppad
title VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA THROUGH GEO-INFORMATICS APPROACH
title_short VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA THROUGH GEO-INFORMATICS APPROACH
title_full VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA THROUGH GEO-INFORMATICS APPROACH
title_fullStr VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA THROUGH GEO-INFORMATICS APPROACH
title_full_unstemmed VEGETATION ANALYSIS AND LAND USE LAND COVER CLASSIFICATION OF FOREST IN UTTARA KANNADA DISTRICT INDIA THROUGH GEO-INFORMATICS APPROACH
title_sort vegetation analysis and land use land cover classification of forest in uttara kannada district india through geo-informatics approach
publisher Copernicus Publications
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 1682-1750
2194-9034
publishDate 2017-05-01
description The study was conducted in Uttara Kannada districts during the year 2012&ndash;2014. The study area lies between 13.92&deg;&thinsp;N to 15.52&deg;&thinsp;N latitude and 74.08&deg;&thinsp;E to 75.09&deg;&thinsp;E longitude with an area of 10,215&thinsp;km<sup>2</sup>. The Indian satellite IRS P6 LISS-III imageries were used to classify the land use land cover classes with ground truth data collected with GPS through supervised classification in ERDAS software. The land use and land cover classes identified were dense forest, horticulture plantation, sparse forest, forest plantation, open land and agriculture land. The dense forest covered an area of 63.32&thinsp;% (6468.70&thinsp;sq&thinsp;km) followed by agriculture 12.88&thinsp;% (1315.31&thinsp;sq.&thinsp;km), sparse forest 10.59&thinsp;% (1081.37&thinsp;sq.&thinsp;km), open land 6.09&thinsp;% (622.37&thinsp;sq.&thinsp;km), horticulture plantation and least was forest plantation (1.07&thinsp;%). Settlement, stony land and water body together cover about 4.26 percent of the area. The study indicated that the aspect and altitude influenced the forest types and vegetation pattern. The NDVI map was prepared which indicated that healthy vegetation is represented by high NDVI values between 0.1 and 1. The non-vegetated features such as water bodies, settlement, and stony land indicated less than 0.1 values. The decrease in forest area in some places was due to anthropogenic activities. The thematic map of land use land cover classes was prepared using Arc GIS Software.
url http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-1-W1/219/2017/isprs-archives-XLII-1-W1-219-2017.pdf
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AT bsjanagoudar vegetationanalysisandlanduselandcoverclassificationofforestinuttarakannadadistrictindiathroughgeoinformaticsapproach
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