{"title":"利用地理空间技术评估古吉拉特邦大吉尔景观区森林破碎化","authors":"Abhinav Mehta, Shital H. Shukla, Shrey Rakholia","doi":"10.58825/jog.2022.16.2.43","DOIUrl":null,"url":null,"abstract":"Due to the negative consequences of climate change, the fragmentation of forest areas worldwide as a result of increased anthropogenic pressure has become a source of concern. The objective of this research study was to evaluate forest fragmentation analysis around the Greater Gir Landscape, Gujarat. The Fragmentation assessment was performed based on Land-use & Land-cover (LULC) analysis using the Landsat 8 OLI images of 2015 and 2019 as primary datasets for the study. Geographic Information System (GIS) techniques were employed for LULC mapping with seven classes showing increment in the agriculture and vegetation patches with the year 2019 in compare to year 2015 due to accumulative rainfall pattern. The Spatial Metric was performed with the use of FRAGSTATS software, where Landscape Metrics were quantified using Class level, Landscape level and Moving Window Analysis. The trend observed in all the metrics calculated indicates increasing of continuity in Greater Gir Landscape. The forest has not undergone severe degradation but a rise in the natural classes like agriculture, vegetation patches, and waterbodies has led to increase in the level of continuity which is leading to conversion of these land patches in homogeneity of the areas using geospatial techniques. These spatial metrics using FRAGSTATS helps in simplifying quantification of the complex spatial processes and can be used for generating a positive framework for forest conservation.","PeriodicalId":53688,"journal":{"name":"测绘地理信息","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of forest fragmentation in greater Gir landscape area, Gujarat using geospatial techniques\",\"authors\":\"Abhinav Mehta, Shital H. Shukla, Shrey Rakholia\",\"doi\":\"10.58825/jog.2022.16.2.43\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Due to the negative consequences of climate change, the fragmentation of forest areas worldwide as a result of increased anthropogenic pressure has become a source of concern. The objective of this research study was to evaluate forest fragmentation analysis around the Greater Gir Landscape, Gujarat. The Fragmentation assessment was performed based on Land-use & Land-cover (LULC) analysis using the Landsat 8 OLI images of 2015 and 2019 as primary datasets for the study. Geographic Information System (GIS) techniques were employed for LULC mapping with seven classes showing increment in the agriculture and vegetation patches with the year 2019 in compare to year 2015 due to accumulative rainfall pattern. The Spatial Metric was performed with the use of FRAGSTATS software, where Landscape Metrics were quantified using Class level, Landscape level and Moving Window Analysis. The trend observed in all the metrics calculated indicates increasing of continuity in Greater Gir Landscape. The forest has not undergone severe degradation but a rise in the natural classes like agriculture, vegetation patches, and waterbodies has led to increase in the level of continuity which is leading to conversion of these land patches in homogeneity of the areas using geospatial techniques. These spatial metrics using FRAGSTATS helps in simplifying quantification of the complex spatial processes and can be used for generating a positive framework for forest conservation.\",\"PeriodicalId\":53688,\"journal\":{\"name\":\"测绘地理信息\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"测绘地理信息\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.58825/jog.2022.16.2.43\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"测绘地理信息","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.58825/jog.2022.16.2.43","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Computer Science","Score":null,"Total":0}
Assessment of forest fragmentation in greater Gir landscape area, Gujarat using geospatial techniques
Due to the negative consequences of climate change, the fragmentation of forest areas worldwide as a result of increased anthropogenic pressure has become a source of concern. The objective of this research study was to evaluate forest fragmentation analysis around the Greater Gir Landscape, Gujarat. The Fragmentation assessment was performed based on Land-use & Land-cover (LULC) analysis using the Landsat 8 OLI images of 2015 and 2019 as primary datasets for the study. Geographic Information System (GIS) techniques were employed for LULC mapping with seven classes showing increment in the agriculture and vegetation patches with the year 2019 in compare to year 2015 due to accumulative rainfall pattern. The Spatial Metric was performed with the use of FRAGSTATS software, where Landscape Metrics were quantified using Class level, Landscape level and Moving Window Analysis. The trend observed in all the metrics calculated indicates increasing of continuity in Greater Gir Landscape. The forest has not undergone severe degradation but a rise in the natural classes like agriculture, vegetation patches, and waterbodies has led to increase in the level of continuity which is leading to conversion of these land patches in homogeneity of the areas using geospatial techniques. These spatial metrics using FRAGSTATS helps in simplifying quantification of the complex spatial processes and can be used for generating a positive framework for forest conservation.