Journal of Remote Sensing & GIS最新文献

{"title":"COMPARISON OF LAND COVER METHODS INCORPORATING LANDSAT-8 IMAGING AND ANCILLARY DATA","authors":"jwan aldoski","doi":"10.37591/.V10I3.776","DOIUrl":"https://doi.org/10.37591/.V10I3.776","url":null,"abstract":"Dramatic land-cover modifications have been documented across Malaysia over the past few centuries. Previously forested regions converted primarily into rubber, oil palms and agricultural regions. A present land-cover data required owing to the ongoing land-cover modifications that researchers, planners, and decision-makers will be using. Landsat data is an excellent source of effective land-cover maps creation and updating. The aim of this research is to establish a low-cost method together with ancillary data to enhance Landsat 8 satellite information to generate a relatively accurate and existing land-cover map for the Kota Bharu district. The comparison was made between supervised, unsupervised and merging both as hybrid classification techniques from Landsat 8 information for land-cover classification. Furthermore, land-use map and land cover masking were used as ancillary data in order to enhance the precision of the Landsat 8 classification within the same GIS system.  It has been discovered that using a combination of supervised and unsupervised training programs generates a product that is more accurate instead of using either of them individually. It was also discovered that mapping this item utilizing ancillary GIS information could enhance product precision by up to 4%. The general precision of the final result was 85%. It is proposed that implementing the method described for more remote sensing pictures taken at distinct moments can make it easier to create a database for land cover modifications.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127445458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MONITORING GLACIERS AND GLACIAL LAKES OF CHENAB BASIN USING GEOSPATIAL TOOLS","authors":"Tanisha Ghosh","doi":"10.37591/.V10I3.743","DOIUrl":"https://doi.org/10.37591/.V10I3.743","url":null,"abstract":"Glacial lakes are usual phenomenon in the glacierized basin at high elevation. Glacial Lakes Outburst Floods are becoming a cause of concern for the local inhabitants of these retreating glaciers. Therefore, a detail study of the dynamics of river of moving ice and water is of much importance. The present study aims to investigate the dynamics of the glacier using geospatial tools and remote sensing and to make an inventory and monitoring of the glaciers, glacial  lakes and water bodies in Chenab river basins of Himalayan region using Resourcesat 2 LISS 4 images and the digital elevation model for the period of 2014 to 2017. Based on the current inventory, 126 glacial lakes and water bodies and 192 glaciers with water spread area more than 30 ha and 700 ha, respectively are monitored. Apart from this, only 2 glacial lakes and water bodies with water spread area in the range 14 to 18 ha were monitored. And 16 glaciers were monitored in the area of 500 ha and above. Most of the glacier lakes and glaciers move in the south east direction with 26 and 33 in numbers respectively. The substantial increase in the number of glacial lakes in the Himalayan region is the matter of concern and therefore need a proper monitoring.  Keywords: Glaciers; Glacier lakes; Chenab River; GIS; India.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131141731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Assessment of groundwater potential zones in the basaltic terrain: a case study from in and around Gondar town, North West Ethiopia using remote sensing and GIS technologies","authors":"Muralitharan Jothimani, Zerihun Dawit","doi":"10.37591/.V10I3.714","DOIUrl":"https://doi.org/10.37591/.V10I3.714","url":null,"abstract":"Geospatial technology has wide applications within the groundwater resource assessment studies. Satellite images are increasingly being used in groundwater exploration due to their utility in distinguishing numerous geo-system options. The present study has been disbursed in and around Gondar, Ethiopia. The groundwater potential zones were depicted from the six geo-system parameters like lithology, lineament density, geomorphology, slope, land use/land cover, and drainage density using weighted overlay analysis methodology. Integration of the above mentioned geo-systems has been performed in GIS platform using weighted overlay analysis. Totally different categories of thematic maps are assigned weights supported influence on groundwater hydrology (through intensive literature review), and eventually, factor ranks area were assigned. The ultimate map indicates the potentiality values of groundwater prevalence within the study area, that was classified into 3 categories—high, moderate and low. a total of 24% of the study area fall in low groundwater potential zone, 42%in moderate potential zones and 34%of the realm in the high potential zone. Keywords : Groundwater potential zones, remote sensing, GIS, Gondar, Ethiopia.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125405542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring and Change Analysis of Qingdao Coastal Line from 1973 to 2016 Based on Remote Sensing Technology","authors":"W. Kai, Zhuang Huibo","doi":"10.37591/.V10I2.570","DOIUrl":"https://doi.org/10.37591/.V10I2.570","url":null,"abstract":"Qingdao is near the Yellow Sea and has a long coastline. In recent years, with rapid development, the coastline of Qingdao has changed greatly. Accurate detection of coastline can understand the characteristics of urban development and the relationship between urban development and ecological change. Compared with manual monitoring, remote sensing technology is widely used in coastline monitoring because of its fast monitoring speed, low monitoring cost and high monitoring accuracy. This paper proposes a combination of the threshold method, edge detection method and visual interpretation to extract the coastline of the coastal area of Qingdao. The Landsat series satellite images are used to monitor the changes of Qingdao coastline in the past 40 years from 1973 to 2016. The results show that the reclamation area in Qingdao is 92.847 km 2 from 1973 to 2016. The reclamation area is mainly located along the coast of Jiaozhou Bay and gradually expands to the southwest after 2009. From 2003 to 2014, the land reclamation area was the largest and the growth rate was the fastest, which were 43.442 km 2 and 3.949 km 2 /year respectively, accounting for 47% of the total land reclamation area in 40 years. Keywords: Automatic extraction, land-making, reclamation, visual interpretation Cite this Article Wang kai, Zhuang Huibo. Monitoring and Change Analysis of Qingdao Coastal Line from 1973 to 2016 Based on Remote Sensing Technology. Journal of Remote Sensing & GIS. 2019; 10(2): 35–42p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114910724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sub-watershed wise Runoff Modeling using Drainage Morphometric Analysis in Karur District, Tamil Nadu, India through Remote Sensing and GIS Techniques","authors":"J. Muralitharan, K. Palanivel","doi":"10.37591/.V10I2.577","DOIUrl":"https://doi.org/10.37591/.V10I2.577","url":null,"abstract":"Morphometric examination, being extensively used to evaluate the drainage individuality and have been found to be a helpful tool to identify areas runoff prone sub-watersheds in this current study. Remote Sensing and Geographical Information System has been demonstrated as successful apparatus in the demarcation of drainages and sub-watersheds boundary and morphometric investigations of sub-watersheds. The current study integrates a morphometric study of 68 sub-watersheds of Karur District, Tamil Nadu, India. Common morphometric parameters are measured for analysis. The following morphometric features such as drainage density, bifurcation ratio, drainage texture, circularity ratio, stream frequency, and form factor has a straight connection by runoff, i.e., superior these values, then, more is the runoff. For the recognition of runoff prone sub-watersheds, the uppermost values of above limits were rated as rank 5, the subsequent uppermost values were rated as rank 4 and so on, and the least values of these factors were charged last in rank 1. The factor such as elongation ratio and length of overland flow has an opposite connection with runoff, i.e., lesser these values; supplementary is the runoff. Therefore the lowly values of these factors were rated as level 5, subsequently, lower values were rated as rank 4 and so on and the maximum values of these parameters were rated last in rank 1. The above-weighted maps were in ArcGIS software to identify the runoff prone sub-watersheds. The current study will improve the systematic understanding of watershed characteristics and its runoff proneness of the study area since there is no prior information is accessible in this study region. The results of the current research will support the development of further hydrological improvement actions in the study area watersheds. Keywords: GIS, morphometric analysis, remote Sensing, sub-watershed-runoff prone modeling Cite this Article J. Muralitharan, K. Palanivel. Sub-watershed wise Runoff Modeling using Drainage Morphometric Analysis in Karur District, Tamil Nadu, India through Remote Sensing and GIS Techniques. Journal of Remote Sensing & GIS. 2019; 10(2): 52–65p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129134282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prioritization of Micro/Mini Watersheds and Identification of Locations to Construct Rainwater Harvesting Structures using Morphometric Parameters and Geoinformatics","authors":"V. Anantharama, K. Gajalakshmi","doi":"10.37591/.V7I2.546","DOIUrl":"https://doi.org/10.37591/.V7I2.546","url":null,"abstract":"Nalluru Amani Kere Watershed (NAKW) is constituent of Caveri river basin, Karnataka state, covering 415.68 km 2 area, representing arid climate. The NAKW has been divided into thirty one micro/mini watersheds (MWS) of 3rd order, designated as MWS-1 to MWS-31, for the purpose of prioritization. For this purpose, morphometric parameters were calculated under linear and shape aspects. Linear aspects such as; drainage density (D d ), bifurcation ratio (Rb), stream frequency (Fu), length of overland flow (Lg), texture ratio (T), and the shape parameter such as; shape factor (B s ), form factor (R f ), compactness constant (C c ), elongation ratio (R e ), and circularity ratio (Rc) are utilized for prioritization of MWS. Above morphometric parameter was determined for each MWS and assigned rank on the basis of value and relationship with erodibility so as to arrive at a compound value for final ranking based on which sub-watersheds were prioritized. Soil map, slope map and land use maps with stream numbers are used in spatial analysis tool of ArcGIS 9.2 platform to identify the best feasible locations to construct different types of engineering structures (water harvesting/soil conservation) in the sub-watersheds. Keywords: Drainage density, Geographic Information System, Rain water harvesting structures, spatial analysis, Slope","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132673835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Role of Geographic Information System and Remote Sensing in Monitoring and Management of Urban and Watershed Environment: Overview","authors":"Avinash Kumar Ranjan, S. Vallisree, R. Singh","doi":"10.37591/.V7I2.553","DOIUrl":"https://doi.org/10.37591/.V7I2.553","url":null,"abstract":"Geoinformatics technology is basically comprises of 3S component, Remote Sensing (RS), Geographic Information System (GIS) and Global Positioning System (GPS). Nowadays Geographic Information System and Remote Sensing are playing a crucial role in our environmental development, raw materials assessment, urbanization, study of watershed, survey and management of cultivable land, study of forestry, geological structure, disaster management and supervision, etc. GIS and RS have emerged as key instruments for retrieving data and information on the earth during the last 30 years. These days, spatial, temporal and spectral resolve satellite data are accessible and using GIS environment their applications have multiplied for the purpose of research work. The objective of the present paper is to present an overview of the state-of-the-art technology behind GIS and RS. This study also highlights the importance of GIS and RS in managing, monitoring and analysing of contemporary issues, such as, urbanization and watershed management, etc. Keywords: Geographic information system, remote sensing, urbanization, watershed monitoring, environment","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114882574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of Precipitation Data from Advanced Microwave Scanning Radiometer 2 in the Forecasting of Floods in Assam","authors":"Banira Thapa, Nitumoni Deka, Ripranchi Ch. Marak, Bikramjit Goswami, Manoranjan Kalita","doi":"10.37591/.V6I1.508","DOIUrl":"https://doi.org/10.37591/.V6I1.508","url":null,"abstract":"Flood occurs most commonly from heavy rainfall but it can also result from storm surge associated with a tropical cyclone, a tsunami or a high tide coinciding with higher than normal river levels. Rainfall in the upstream of a river can also cause inundation in the downstream side of a river. Reliable and timely information is essential for appropriate flood management system. This paper explains the use of precipitation data obtained from Advanced Microwave Scanning Radiometer (AMSR) 2 for the detection of flood. The data obtained, if timely utilized helps in the mitigation of floods and aids to decrease the mortality rate. (AMSR) 2 is a passive microwave sensor and it can record microwave energy emitted by the atmosphere, reflected from the surface, emitted from the surface or transmitted from the subsurface. Algorithms were developed to assess the precipitation values of southern part of Assam and along the upstream and downstream side of river Brahmaputra for the month of August and September, 2014. The assessment and consequent analysis led to possibility of forecasting the flood occurrences in many places in Assam. Keywords : AMSR 2, microwave remote sensors, precipitation, flood","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"15 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114041813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vegetation Area Monitoring Through NDVI Technique: A Case Study of Dengei Pahad Micro Watershed, Khurda District, Odisha","authors":"A. Ojha, R. N. Samal, G. Rajesh, A. Pattnaik","doi":"10.37591/.V6I1.503","DOIUrl":"https://doi.org/10.37591/.V6I1.503","url":null,"abstract":"Watershed treatment includes implementation of participatory micro-watershed-based soil and moisture conservation programs and income generation through proper natural resource management areas. This has led to increased productivity and income. Training and holistic management along with aforestation programs has led to reduction of silt flow to the lake. The assessment revealed that land degradation in the drainage basin not only leads to enhanced silt flow into the lagoon but also causes poverty, due to low productivity in the drainage basin. The drainage basin management program is conceived as a long-term participatory process to achieve an environmentally, economically and socially sustainable management of water resources. The present study deals with periodic assessment and monitoring the vegetation cover of the Dengei pahad micro watershed, Khurda District, Odisha, using NDVI techniques. NDVI is the traditional vegetation index used by researchers for extracting vegetation abundance from remotely sensed data. In essence, the algorithm isolates the dramatic increase in reflectance over the visible red to near infrared wavelengths, and normalized it by dividing by the overall brightness of each pixel in those wavelengths. Satellite data of IRS series from 1999 to 2010 and Resources at series from 2011 to 2014 along with other spatial and non-spatial data were used to find out the changes that occurred in vegetation and other land cover categories during the last 16 years. It was analyzed that dense vegetation cover has decreased up to 20.24 Ha in the year 2010 and after the awareness to the local people by CDA, has taken active role to sustain the natural resource and it has shown positive impact after the analysis through Remote Sensing data. Keywords: Micro-watershed, participatory, degradation, sustainable, NDVI, satellite, remote sensing","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115088956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil Moisture Retrieval from Brightness Temperature using Passive Microwave Remote Sensing","authors":"Bikramjit Goswami, Rittika Bezbaruah, Lige Kato, P. Kalita, Sukanya Dutta, Manoranjan Kalita","doi":"10.37591/.V5I3.498","DOIUrl":"https://doi.org/10.37591/.V5I3.498","url":null,"abstract":"Soil Moisture (SM) data are often a derived product of Microwave Remote Sensing (MRS) satellites. The brightness temperature (T b ) however, is a basic quantity associated with the satellites in the Microwave range and is available as a common data product from all MRS satellites. In this paper an attempt has been made to develop an algorithm to retrieve SM information directly from the T b values obtained from the Advanced Microwave Scanning Radiometer on Earth Observing (AMSR-E) System. Analysis of T b and SM data is done to find the most suitable frequency band and polarization at which the conversion from T b to SM is possible. Out of all the frequencies from the satellite, the T b values at 6 GHz frequency with horizontal polarization have been found to be most suitable for SM retrieval. The algorithm designed is found to be applicable for T b to SM conversion for any season. Keywords : Microwave remote sensing, soil moisture, AMSR-E, brightness temperature, passive sensors.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134313103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}