scholarly journals Remote Sensing Application for Exploring Land Use and Land Cover Dynamics in and Around Chatra Wetland, English Bazar, West Bengal

2021 ◽  
Vol 9 (1) ◽  
pp. 15-27
Author(s):  
Saleha Jamal ◽  
Md Ashif Ali
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Changes ◽  
United States Geological Survey ◽  
Landsat 8 ◽  
Gis And Remote Sensing ◽  
Erdas Imagine ◽  
Landsat 7 ◽  
Vegetation Water

Wetlands are often called as biological “supermarket” and “kidneys of the landscape” due to their multiple functions, including water purification, water storage, processing of carbon and other nutrients, stabilization of shorelines and support of aquatic lives. Unfortunately, although being dynamic and productive ecosystem, these wetlands have been affected by human induced land use changes. India is losing wetlands at the rate of 2 to 3 per cent each year due to over-population, direct deforestation, urban encroachment, over fishing, irrigation and agriculture etc (Prasher, 2018). The present study tries to investigate the nature and degree of land use/land cover transformation, their causes and resultant effects on Chatra Wetland. To fulfil the purpose of the study, GIS and remote sensing techniques have been employed. Satellite imageries have been used from United States Geological Survey (USGS) Landsat 7 Enhanced Thematic Mapper plus and Landsat 8 Operational Land Imager for the year 2003 and 2018. Cloud free imageries of 2003 and 2018 have been downloaded from USGS (https://glovis.usgs.gov/) for the month of March and April respectively. Image processing, supervised classificationhas been done in ArcGis 10.5 and ERDAS IMAGINE 14. The study reveals that the settlement hasincreased by about 90.43 per cent in the last 15 years around the Chatra wetland within the bufferzone of 2 Sq km. Similarly agriculture, vegetation, water body, swamp and wasteland witnessed asignificant decrease by 5.94 per cent, 57.69 per cent, 26.64 per cent 4.52 per cent and 55.27 per centrespectively from 2003 to 2018.

scholarly journals Classification of Land Use/Land Cover Changes Using GIS and Remote Sensing Technique in Lake Kenyir Basin, Terengganu, Malaysia

2018 ◽  
Vol 7 (3.14) ◽  
pp. 12 ◽  
Author(s):  
Mohd Khairul Amri Kamarudin ◽  
Kabir Abdulkadir Gidado ◽  
Mohd Ekhwan Toriman ◽  
Hafizan Juahir ◽  
Roslan Umar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Body ◽  
Geographical Information ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technique ◽  
Multi Temporal ◽  
Vegetation Water

Geographical information system (GIS) techniques and Remote Sensing (RS) data are fundamental in the study of land use (LU) and land cover (LC) changes and classification. The aim of this study is to map and classify the LU and LC change of Lake Kenyir Basin within 40 years’ period (1976 to 2016). Multi-temporal Landsat images used are MSS 1976, 1989, ETM+ 2001 and OLI 8 2016. Supervised Classification on Maximum Likelihood Algorithm method was used in ArcGIS 10.3. The result shows three classes of LU and LC via vegetation, water body and built up area. Vegetation, which is the dominant LC found to be 100%, 88.83%, 86.15%, 81.91% in 1976, 1989, 2001 and 2016 respectively. While water body accounts for 0%, 11.17%, 12.36% and 13.62% in the years 1976, 1989, 2001 and 2016 respectively and built-up area 1.49% and 4.47 in 2001 and 2016 respectively. The predominant LC changes in the study are the water body and vegetation, the earlier increasing rapidly at the expense of the later. Therefore, proper monitoring, policies that integrate conservation of the environment are strongly recommended. 

scholarly journals LANDCOVER CHANGES IN COASTAL BUNGUS REGION OF KABUNG BAY, WEST SUMATRA FROM 200-2013 BASED ON GEOGRAPHIC INFORMATION SYSTEM APPLICATION

2015 ◽  
Vol 6 (2) ◽  
Author(s):  
Yulius Yulius ◽  
T A Tanto ◽  
M Ramdhan ◽  
A Putra ◽  
H L Salim
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Landsat Imagery ◽  
Land Use Changes ◽  
Population Increase ◽  
Landsat 8 ◽  
West Sumatra ◽  
Landsat 7 ◽  
Southern City ◽  
Growing Region

ABSTRACT Bungus district of Kabung Bay is a growing region located at coastal zone of southern city of Padang, west sumatra. As a growing region, the Bungus district brings some impacts on population increase and degradation of environment quality. Therefore, it is needed an effort to identify land use changes and the distribution of land use in this region from the year of 2003 until 2013. This research used landsat 7 imagery in 2003 and landsat 8 imagery in 2013. The data were analysed descriptively using geographical informastion system. The result showd that (1) swamp land cover experienced the smallest land use change between 2003 until 2013 (0.02 ha/yr), meanwhile forest land use had the biggest change of about 224.8 ha/yr. The biggest addition of land cover belong to settlement area about 47.59 hectare, and the other hand occur on bush about -31.68 hectare. Keywords: Bungus district, landcover changes, Landsat imagery, GIS

scholarly journals Analysis of Land Use and Land Cover Changes in Urban Areas Using Remote Sensing: Case of Blantyre City

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Jane Ferah Gondwe ◽  
Sun Li ◽  
Rodger Millar Munthali
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Areas ◽  
Agricultural Land ◽  
Landsat 8 ◽  
Lulc Changes ◽  
Wide Range ◽  
Landsat 7 ◽  
Artificial Neural Network Ann

Blantyre City has experienced a wide range of changes in land use and land cover (LULC). This study used Remote Sensing (RS) to detect and quantify LULC changes that occurred in the city throughout a twenty-year study period, using Landsat 7 Enhanced Thematic Mapper (ETM+) images from 1999 and 2010 and Landsat 8 Operational Land Imager (OLI) images from 2019. A supervised classification method using an Artificial Neural Network (ANN) was used to classify and map LULC types. The kappa coefficient and the overall accuracy were used to ascertain the classification accuracy. Using the classified images, a postclassification comparison approach was used to detect LULC changes between 1999 and 2019. The study revealed that built-up land and agricultural land increased in their respective areas by 28.54 km2 (194.81%) and 35.80 km2 (27.16%) with corresponding annual change rates of 1.43 km·year−1 and 1.79 km·year−1. The area of bare land, forest land, herbaceous land, and waterbody, respectively, decreased by 0.05%, 90.52%, 71.67%, and 6.90%. The LULC changes in the study area were attributed to urbanization, population growth, social-economic growth, and climate change. The findings of this study provide information on the changes in LULC and driving factors, which Blantyre City authorities can utilize to develop sustainable development plans.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios

2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Cover ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Kurdistan Region ◽  
The Past ◽  
Past Trend

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.

scholarly journals Land Use/Land Cover Changes in a Disturbed River Watershed Kenya

2019 ◽  
Vol 3 (2) ◽  
pp. 29
Author(s):  
Zachary Gichuru Mainuri ◽  
John M. Mironga ◽  
Samuel M. Mwonga
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing Image ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Human Needs ◽  
Observation Systems ◽  
Erdas Imagine ◽  
Remote Sensing Image Processing

Drivers of land use change were captured by the use of DPSIR model where Drivers (D) represented human needs, Pressures (P), human activities, State (S), the ecosystem, Impact (I) services from the ecosystem and Response (R), the decisions taken by land users. Land sat MSS and Land sat ETM+ (path 185, row 31) were used in this study. The Land sat ETM+ image (June 1987, May, 2000 and July, 2014) was downloaded from USGS Earth Resources Observation Systems data website. Remote sensing image processing was performed by using ERDAS Imagine 9.1. Two land use/land cover (LULC) classes were established as forest and shrub land. Severe land cover changes was found to have occurred from 1987-2000, where shrub land reduced by -19%, and forestry reduced by -72%. In 2000 – 2014 shrub land reduced by-45%, and forestry reduced by -64%. Forestry and shrub land were found to be consistently reducing.

scholarly journals Predicting Land use and land cover spatiotemporal changes utilizing CA-Markov model in Duhok district between 1999 and 2033

2020 ◽  
Author(s):  
shamal
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Cellular Automata ◽  
Land Cover ◽  
Markov Model ◽  
Markov Chain Model ◽  
United States Geological Survey ◽  
Chain Model ◽  
Lulc Changes ◽  
Spatiotemporal Changes

AbstractTHE PROCESS OF SPATIOTEMPORAL CHANGES IN LAND USE LAND COVER (LULC) AND PREDICTING THEIR FUTURE CHANGES ARE HIGHLY IMPORTANT FOR LULC MANAGERS. ONE OF THE MOST IMPORTANT CHALLENGES IN LULC STUDIES IS CONSIDERED TO BE THE CREATION OF SIMULATION OF FUTURE CHANGE IN LULC THAT INVOLVE SPATIAL MODELING. THE PURPOSE OF THIS STUDY IS TO USE GIS AND REMOTE SENSING TO CLASSIFY LULC CLASSES IN DUHOK DISTRICT BETWEEN 1999 AND 2018, AND THEIR RESULTS CALCULATED USING AN INTEGRATED CELLULAR AUTOMATA AND CA-MARKOV CHAIN MODEL TO SIMULATE LULC CHANGES IN 2033. IN THIS STUDY, SATELLITE IMAGES FROM LANDSAT7 ETM AND LANDSAT8 OLI USED FOR DUHOK DISTRICT WHICH IS LOCATED IN THE NORTHERN PART OF IRAQ OBTAINED FROM UNITED STATES GEOLOGICAL SURVEY (USGS) FOR THE PERIODS (1999 AND 2018) ANALYZED USING REMOTE SENSING AND GIS TECHNIQUES IN ADDITION TO THE GROUND CONTROL POINTS, FOR EACH CLASS 60 GROUND POINTS HAVE TAKEN. TO SIMULATE FUTURE LULC CHANGES FOR 2033, INTEGRATED APPROACHES OF CELLULAR AUTOMATA AND CA-MARKOV MODELS UTILIZED IN IDRISI SELVA SOFTWARE. THE OUTCOMES DEMONSTRATE THAT DUHOK DISTRICT HAS EXPERIENCED A TOTAL OF 184.91KM CHANGES DURING THE PERIOD (TABLE 4). THE PREDICTION ALSO INDICATES THAT THE CHANGES WILL EQUAL TO 235.4 KM BY 2033 (TABLE 8). SOIL AND GRASS CONSTITUTES THE MAJORITY OF CHANGES AMONG LULC CLASSES AND ARE INCREASING CONTINUOUSLY. THE ACHIEVED KAPPA VALUES FOR THE MODEL ACCURACY ASSESSMENT HIGHER THAN 0.93 AND 0.85 FOR 1999 AND 2018 RESPECTIVELY SHOWED THE MODEL’S CAPABILITY TO FORECAST FUTURE LULC CHANGES IN DUHOK DISTRICT. THUS, ANALYZING TRENDS OF LULC CHANGES FROM PAST TO NOW AND PREDICT FUTURE APPLYING CA-MARKOV MODEL CAN PLAY AN IMPORTANT ROLE IN LAND USE PLANNING, POLICY MAKING, AND MANAGING RANDOMLY UTILIZED LULC CLASSES IN THE PROPOSED STUDY AREA

scholarly journals Assessment of Land Use and Vegetative Cover in Kano Metropolis (from 1975-2015) Employing GIS and Remote Sensing Technology

2020 ◽  
Vol 27 (2) ◽  
pp. 1-7
Author(s):  
M. Haruna ◽  
M.K. Ibrahim ◽  
U.M. Shaibu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Agricultural Land ◽  
Landsat 8 ◽  
Vegetative Cover ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Agricultural Planning ◽  
Bare Land

This study applied GIS and remote sensing technology to assess agricultural land use and vegetative cover in Kano Metropolis. It specifically examined the intensity of land use for agricultural and non agricultural purpose from 1975 – 2015. Images (1975, 1995 and 2015), landsat MSS/TM, landsat 8, scene of path 188 and 052 were downloaded for the study. Bonds for these imported scenes were processed using ENVI 5.0 version. The result indicated five classified features-settlement, farmland, water body, vegetation and bare land. The finding revealed an increase in settlement, vegetation and bare land between 1995 and 2015, however, farmland decreased in 2015. Indicatively, higher percentage of land use for non agricultural purposes was observed in recent time. Conclusively, there is need to accord surveying the rightful place and priority in agricultural planning and development if Nigeria is to be self food sufficient. Keywords: Geographic Information System, Agriculture, Remote sensing, Land use, Land cover

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