scholarly journals Watershed Health Changes based on Vegetated Land Cover in the Upper Citarum Watershed, West Java, Province, Indonesia

2021 ◽  
Vol 940 (1) ◽  
pp. 012045
Author(s):  
K Marko ◽  
D Sutjiningsih ◽  
E Kusratmoko
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Landsat Imagery ◽  
West Java ◽  
Health Changes ◽  
The North ◽  
Health Level ◽  
Watershed Health

Abstract The increase in built-up land and the decrease in vegetated land due to human activities have worsened watershed health from time to time. This study aims to assess the watershed’s health and changes every ten years based on the percentage of vegetated land cover except agricultural land in the Upper Citarum watershed, West Java. Land cover information was obtained from the processing of Landsat imagery in 1990, 2000, 2010, and 2020 based on remote sensing using the supervised classification method. The watershed health level is determined by calculating the percentage of vegetated land cover of 173 catchments. The results show that the area of the vegetated land cover decreased from 1990 to 2000, then increased from 2000 to 2010, and decreased again from 2010 to 2020. Changes in the area of vegetated land in each period of the year affect the health level of the watershed in a spatiotemporal manner. Although these changes occur in a fluctuating manner, the number of unhealthy catchments in the Upper Citarum watershed is increasing, especially in the Ci Kapundung sub-watershed in the north and Ci Sangkuy in the south.

scholarly journals Analysis of Spatiotemporal Land Use and Land Cover Changes using Remote Sensing and GIS: A Review

2018 ◽  
Vol 7 (4.34) ◽  
pp. 159
Author(s):  
Kabir Abdulkadir Gidado ◽  
Mohd Khairul Amri Kamarudin ◽  
Nik Ahmad Firdausaq ◽  
Aliyu Muhammad Nalado ◽  
Ahmad Shakir Mohd Saudi ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Accuracy Assessment ◽  
Geographical Information ◽  
Lulc Changes ◽  
Detection Analysis ◽  
Socio Economic Factors

The land-use and land-cover (LULC) pattern of an area is an outcome of natural and socio-economic factors and their use spatially by man; this LULC varies from the forest, water body, agricultural land and so on. Remote Sensing (RS) and Geographical Information System (GIS) studies have predominantly focused on providing the technical knowledge of, where, and the type of LULC change that has occurred and its impacts on man and the environment. Knowledge about LULC changes is essential for understanding the relationships and interfaces between humans and the natural environment. The purpose of this article is to review the previous studies of the spatiotemporal LULC changes. However, thirty (30) articles were reviewed from 2011 to 2017. However, these articles studied the LULC, classification, changes and change detection analysis, using different methods and software of RS and G.I.S. The finding shows that these articles have overall accuracy assessment ranges from 75% to 95% validations. Also, supervised classification in Maximum Likelihood Algorithm method was mostly employed for the LULC classification. Moreover, these reviewed articles confirmed that LULC changes are imminent as a result of both natural and human factors which lead to increase and decrease of one LULC cover to another. Therefore proper monitoring of LULC changes when applied help the relevant government bodies, agencies and environmental managers utilise the environment to the fullest.  

scholarly journals Land Use and Land Cover Detection by Different Classification Systems using Remotely Sensed Data of Kuala Tiga, Tanah Merah Kelantan, Malaysia

2017 ◽  
Vol 5 (3) ◽  
pp. 145-151
Author(s):  
Wani Sofia Udin ◽  
Zuhaira Nadhila Zahuri
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Classification System ◽  
Supervised Classification ◽  
Satellite Images ◽  
Agricultural Land ◽  
Unsupervised Classification ◽  
Land Cover Classification ◽  
Classification Systems

Land use and land cover classification system has been used widely in many applications such as for baseline mapping for Geographic Information System (GIS) input and also target identification for identification of roads, clearings and also land and water interface. The research was conducted in Kuala Tiga, Tanah Merah, Kelantan and the study area covering about 25 km2. The main purpose of this research is to access the possibilities of using remote sensing for the detection of regional land-use change by developing a land cover classification system. Another goal is to compare the accuracy of supervised and unsupervised classification systems by using remote sensing. In this research, both supervised and unsupervised classifications were tested on satellite images of Landsat 7 and 8 in the years 2001 and 2016. As for supervised classification, the satellite images are combined and classified. Information and data from the field and land cover classification are utilized to identify training areas that represent land cover classes. Then, for unsupervised classification, the satellite images are combined and classified by means of unsupervised classification by using an Iterative Self- Organizing Data Analysis Techniques (ISODATA) algorithm. Information and data from the field and land cover classification are utilized to assign the resulting spectral classes to the land cover classes. This research was then comparing the accuracy of two classification systems at dividing the landscape into five classes; built-up land, agricultural land, bare soil, forest land, water bodies. Overall accuracies for unsupervised classification are 36.34 % for 2016 and 51.76% for 2001 while for supervised classification, accuracy assessments are 95.59 % for 2016 and 96.29 % for 2001.

scholarly journals Land Use - Land Cover Change Analysis of Karur Town - A GIS Approach

2021 ◽  
pp. 360-366
Author(s):  
S. Ravichandran ◽  
I. K. Manonmani
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Geographical Information ◽  
Land Use Land Cover ◽  
Change Analysis ◽  
Barren Land

Land use / Land cover change is one of the most sensitive factors that show the interactions between human activities and the ecological environment. This research study demonstrated the importance of geographical information system and remote sensing technologies in spatial temporal data analysis and also this paper shows a GIS and remote sensing approach for modeling of spatial - temporal pattern of land use and land cover change (LULC) in a fastest growing towns / industrial region of Karur town. QGIS 3.10 version and Arc GIS 10.2 software platforms were utilized in the study for Image processing, LULC mapping and change detection analysis. USGS Earth explorer Landsat series satellite imageries were acquired and LULC maps were prepared for the years 1991, 2000, 2010 and 2020. Supervised classification with maximum likelihood algorithm is adopted for LULC classification. The LULC classes are Built upland, Agricultural land, Barren land and Water body based on NRSA Level – I supervised classification. The Built-up area has drastically increased from 1991 to 2020. It has increased more than double. It was 17 percent in 1991 and increased to 40 percent in 2020. This clearly shows Karur town is the becoming more and more urbanized.

scholarly journals MAPPING OF LAND-COVER CHANGE ANALYSIS IN MA’RIB AT YEMEN USING REMOTE SENSING AND GIS TECHNIQUES

2019 ◽  
Vol XLII-4/W12 ◽  
pp. 1-10
Author(s):  
S. Al-Akad ◽  
Y. Akensous ◽  
M. Hakdaoui ◽  
F. Al-Nahmi ◽  
S. Mahyoub ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Supervised Classification ◽  
Satellite Images ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Rate Of Change ◽  
Change Analysis ◽  
Remote Sensing Techniques

<p><strong>Abstract.</strong> Studies on the change in occupation and land-use are of great importance in order to understand landscape dynamics in the process of agricultural land degradation, urbanization, desertification, deforestation and all change in the landscape global of a region. The most effective procedure to measure the degree of land-cover and land-use changes is the multi-date study. For this purpose, the aim of this work is to analyze the current evolution of land-use and land-cover (LULC) using remote sensing techniques, in order to better understand this evolution. For this purpose, a diachronic approach is applied to satellite images acquired in 1987 to 2018 of Ma’rib city Yemen. The LULC maps we obtained were produced from different image analysis procedures (non-supervised classification and recode technique) to map the land-use and land-cover. The objective of this study is to apply reproducibly and generalizable a predefined nomenclature to different scenes of satellite images. The first step consists in interpreting the radiometric classes obtained by non-supervised classification so as to form the classes of the thematic nomenclature. An improvement of the classification is then obtained by using the recode technique which makes it possible to correctly reassign the previously badly classified pixels of the satellite images classification. Land-cover maps obtained from remote sensing were used to quantify the rate of change (Tc) and (Tg) of area occupied by each class. The results will indicate the most changeable period and the percentage of overall change in the study area (Ma’rib Yemen), and helped to identify and characterize the spatial and temporal evolution of land use in the district over a period of thirty-one years (1987 to 2018). They reveal that annual average rates of decline for the water body is &amp;minus;83.5% and &amp;minus;9.96% for the sandy land. However, it was observed an increase in built-up area 365.52% and farm land 324.52% classes.</p>

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 REMOTE SENSING AND GIS FOR LAND COVER CLASSIFICATION AND CHANGE DETECTION IN GAZIPUR SADAR, BANGLADESH DURING 1973-2017

2018 ◽  
Vol 5 (2) ◽  
pp. 215
Author(s):  
Md Arafat Hassan ◽  
Rakibul Islam ◽  
Rehnuma Mahjabin
Keyword(s):  
Remote Sensing ◽  
Supervised Classification ◽  
Agricultural Land ◽  
Satellite Image ◽  
Remote Sensing Data ◽  
Remote Sensing And Gis ◽  
Vegetation Coverage ◽  
Accurate Information ◽  
Sal Forest ◽  
Shed Light

This paper has been developed to capture the land coverage change in Gazipur Sadar Upazila with the help of remote sensing data of 44 years from 1973 to 2017. After acquiring the study area image of 1973, 1991, 2006 and 2017 supervised classification method has been used to get the accurate information from the satellite image and the whole outcome has been transformed into measurable unit (sq km) and graphs. The accuracy of land coverage was ranged from 85% to 89%. The outcome says that the acceleration of economic growth and pressure of huge population took a heavy toll on the vegetation coverage which decreased -199.7%. People are destroying vegetation coverage for building up settlements and infrastructure. In the year 2017, the map shows that the built-up area increased 312.9% for industry, settlement and agricultural purpose. Moreover agricultural land also drops down from 42% to 32%.  The rapid rate of decreasing vegetation coverage and small amount of existing vegetation coverage only 57 sq km (in 2017) is a red alert for the region. The Sal forest and other special flora species of that region is valuable resource for environment. This paper shed light on the fact that it is urgent to protect vegetation coverage so it will help the authority to make good policies and use other techniques to save vegetation coverage.

scholarly journals Remote Sensing in Predicting Development Patterns of Built-up Land

2021 ◽  
Vol 2 (2) ◽  
pp. 56-64
Author(s):  
Iqbal Eko Noviandi ◽  
Ramadhan Alvien Hanif ◽  
Hasanah Rahma Nur ◽  
Nandi
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Population Growth Rate ◽  
Landsat Imagery ◽  
Temporal Analysis ◽  
West Java ◽  
Development Patterns ◽  
Human Needs ◽  
Multi Temporal ◽  
Total Growth

Indonesia is a developing country whose construction and development are centered on the island of Java, especially in West Java Province. Sukabumi City is one of the areas in West Java. The development of urban areas is expanding due to various human needs to carry out the construction of buildings. Remote sensing that can be used to store developments with multi-temporal analysis with materials is Landsat imagery from 2001 to 2020. The method used is the Normalized Difference Built-up Index (NDBI). The purpose of this study is to map the development of the built-up land from year to year and predict the following years. The results of the research on the significant changes in built-up land occurred between 2013-2020, while from 2001 to 2013 there was not much change. Based on the research results, the total growth of built-up land was 1.539% per year with a population growth rate of 1.4% per year. The results of the analysis show that the area of ​​land built in Sukabumi City in 2028 is 186,7194 km2 or has increased by 21,2808 km2 since 2020.

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