scholarly journals ASSESSING LAND COVER CHANGES CAUSED BY GRANITE QUARRYING USING REMOTE SENSING

2017 ◽  
Vol XLII-3/W2 ◽  
pp. 119-124 ◽  
Author(s):  
R. S. Moeletsi ◽  
S. G. Tesfamichael
Keyword(s):  
South Africa ◽  
Remote Sensing ◽  
Land Cover ◽  
Surface Mining ◽  
Google Earth ◽  
Land Cover Changes ◽  
Dimension Stone ◽  
Remotely Sensed Data ◽  
Landsat Images ◽  
Granite Quarries

Dimension stone quarrying in the area between Rustenburg and Brits in the North West Province of South Africa has been in existence for over 70 decades. The unique characteristics of the granite deposits in South Africa resulted in making the country a global producer of the granite rocks. This led to intensified quarrying activities between Rustenburg and Brits town. However, this surface mining method, has a potential to impact the environment in a negative way causing loss in vegetation, depletion of natural resources, loss of scenic beauty and contamination of surface water resources. To assess the land cover changes caused by granite quarrying activities, remotely sensed data in the form of Landsat images between 1998 and 2015 were used. Supervised classification was used to create maps. Accuracy assessment using Google Earth<sup>TM</sup> as a reference data yielded an overall accuracy of 78&amp;thinsp;%. The post classification change detection method was used to assess land cover changes within the granite quarries. Granite quarries increased by 1174.86 ha while formation of quarry lakes increased to 5.3 ha over the 17-year period. Vegetation cover decreased by 1308 ha in area while 18.3 ha bare land was lost during the same period. This study demonstrated the utility of remote sensing to detect changes in land cover within granite quarries.

scholarly journals Pattern Classification Technique to Assess Land Use/Cover Changes in Granite Quarry Area of Dharmapuri and Krishnagiri Districts of Tamilnadu

2019 ◽  
Vol 8 (12) ◽  
pp. 2947-2956
Keyword(s):  
Land Cover ◽  
Pattern Classification ◽  
Surface Mining ◽  
Land Cover Changes ◽  
Infrastructure Development ◽  
Remotely Sensed Data ◽  
Landsat Images ◽  
Rapid Phase ◽  
Temperature Loss ◽  
Granite Quarries

The rapid phase of urbanization and infrastructure development in Krishnagiri Distirct has been observed recently. The unique characteristics of the granite deposits in Krishnagiri and Dharmapuri Districts of Tamilnadu resulted in making the country a global producer of the granite rocks. This led to intensified quarrying activities between Dharmapuri and Krishnagiri. However, this surface mining method, has a potential to impact the environment in a negative way causing loss in vegetation, depletion of natural resources, increases the Temperature, loss of scenic beauty and contamination of surface water resources. To assess the land cover changes caused by granite quarrying activities, remotely sensed data in the form of Landsat images between 2000 and 2017 were used. Pattern classification was used to create maps. Accuracy assessment using Google EarthTM as a reference data yielded an overall accuracy of 88%. The post classification change detection method was used to value the land cover changes within the granite quarries. Granite quarries increased by 2562.78 ha while formation of quarry lakes increased to 5.3ha over the 18-year period. Vegetation cover decreased by 1521ha in area while 18.3ha bare land was lost during the same period. This study demonstrated the utility of remote sensing to detect changes in land cover within granite quarries.

Application of Remote Sensing and GIS to Detect Land Use and Land Cover Changes in Jos East Local Government Area, Plateau State, Nigeria.

2021 ◽  
Vol 1 (1) ◽  
pp. 1-8
Author(s):  
Solomon Wuyep zitta
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Digital Camera ◽  
Land Cover Changes ◽  
Remotely Sensed Data ◽  
Plateau State ◽  
Ground Truthing ◽  
Land Management System

This study examines the potentials of Remote Sensing techniques and GIS in land resources management with particular reference to detect land use and land cover changes in Jos East L.G.A, between 1995 to 2015. In this study, administrative maps, remotely sensed data (Landsat and Nigeriasat-1 satellite imageries) and GIS techniques were used in the image analysis. All these were done using Ilwis 3.3 Academic, ERDAS 9.3, IDIRISI 17.0 and ArcGIS 10.1. Digital camera was also used for ground truthing. The results were presented using classified imageries. Between the years 1995 to 2015, there was consistent change in the land use land cover of Jos east with different LULC categories. Throughout the study years, vegetation was observed to have the highest percentage of the total land coverage with 57544.28 ha (63%) in 1995, decreasing to 50322.96 ha (50%) in 2005, and 34969.95 (39%) in the year 2015. While agricultural/farm land was gradually increasing throughout the study period with 21271.05 ha (23%) in 1995, 27017.37 ha (27%) in 2005 and 25406.19 ha (28%) in 2015. Findings also showed that build-up-areas/settlement development increased consistently from 1451.97ha (2%) in 1995, 3290.49 ha (3%) in 2005 to 5817.96 (6%) in 2015. It was concluded that agriculture in the study area is increasing while large areas of vegetation is drastically reducing and being converted to farmlands and settlements. It is recommended that government should put up a reliable land management system in form of restrictions on premature conversion of agricultural land, there should be policies that control threat to the vegetation cover. Government should take cognizance of the land use and land cover at a regular interval to ascertain the changes that are taking place in the study area.

scholarly journals Application of GIS and Remote Sensing Technique to Change Detection in Land Use/Land Cover Mapping of Igbokoda, Ondo State, Nigeria

1970 ◽  
Vol 3 (1) ◽  
Author(s):  
James R. Adewumi ◽  
James K. Akomolafe ◽  
Fidelis O. Ajibade ◽  
Blessing B. Fabeku
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Change Detection ◽  
Rapid Change ◽  
Land Use Land Cover ◽  
Remotely Sensed Data ◽  
Landsat Images ◽  
Annual Increment ◽  
Rapid Urbanization

This paper aims at establishing changes in land use and land cover in Igbokoda municipality using Geographic Information System and remote sensing techniques. Three satellite images for three different epochs 1986, 1999 and 2013 were used to produce a land use/land cover map classification for Igbokoda. In determining the extent of land use/land cover changes in the township from 1986 through 1999 to 2013, Landsat images of the town were downloaded from the United State Geological Survey online archive. The images were analyzed using change detection technique (NDVI differencing) along with SRTM 90m DEM of the study area to generate the extent of the changes that have occurred. Ground trotting was carried out to ascertain the accuracy of data and the major changes in the land use/land cover. Results show that vegetation has decreased from 75.04% in 1986 to 46.81% in 2013 which was due to increase in population and rapid urbanization. In 1996 the Built-up area covers 19.6321 km2 of the study area but has increased rapidly to 39.1505 km2 in the year 1999 with an average annual increment of 2.025Km2/year. By the year 2013, the built-up area has increased to 64.1520Km2. Also in the same vein, the bare surface area which was 13.28029km2 in 1986 was increased to 39.6053 and 50.240Km2 in 1999 and 2013 respectively. On the contrary, the vegetated area of Igbokoda reduced from 196.3046Km2 in 1999 to 122.4680Km2 in 2013. This study has demonstrated that remotely sensed data and GIS based approach is timely and cost effective than the conventional method of analysis, classification of land use pattern effective for planning and management. It further shows that If the rapid change in land use is not properly manage, the situation poses a serious threat to Igbokoda town by increasing surface runoff and susceptibility to flooding.

scholarly journals ANALYSIS OF LAND COVER CHANGES IN THE AREA OF THE TOWN OF GORAŽDE

2020 ◽  
Vol 43 ◽  
pp. 37-46
Keyword(s):  
Land Cover ◽  
Spatial Planning ◽  
Geographical Location ◽  
Research Area ◽  
Google Earth ◽  
Land Cover Changes ◽  
The Third ◽  
Complete Procedure ◽  
The Subject ◽  
The Town

The subject of the research is the analysis of the land cover changes in the area of the town of Goražde. In the period after 1995, throughout the entire Bosnia and Herzegovina, a visible spontaneous spatial planning contributed to significant changes in the land cover. The research aims to determine how many changes have taken place in the last few decades in the researched area when it comes to land cover. The analysis is based on topographic maps from 1980, Google Earth images, then Corina Land Cover images from 2000, 2006, 2012, and 2018. Research on the topic was conducted through several phases. The first part of the paper refers to determining the geographical location of the research area and defining all its components. The second part of the paper deals with a detailed analysis of all categories of land cover in the last twenty years. The third part of the paper involves a comparative analysis of quantitative and qualitative indicators of land cover in the town of Goražde. The complete procedure of the analysis was performed using GIS, where the corresponding databases were created and a cartographic visualization for the investigated area was performed.

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 THE SPATIAL AND TEMPORAL AVAILABILITY DIFFERENCES OF CLOUD-FREE LANDSAT IMAGES OVER THREE GORGES RESERVOIR AREA

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 1-8
Author(s):  
B. X. Bai ◽  
Y. M. Tan ◽  
P. Wu
Keyword(s):  
Remote Sensing ◽  
Three Gorges Reservoir ◽  
Google Earth ◽  
Optical Data ◽  
Three Gorges Reservoir Area ◽  
Three Gorges ◽  
Landsat Images ◽  
Reservoir Area ◽  
Availability Analysis ◽  
Sensing Applications

Abstract. Availability analysis of cloud-free optical remote sensing data is a prerequisite for remote sensing applications. In this study, spatio-temporal availability differences of cloud-free Landsat TM, ETM+, and OLI sensors images over Three Gorges Reservoir Area (TGRA) were analyzed from 1986 to 2019 based on the Google Earth Engine (GEE). The results show that: 1) in Summer, especially in August, the probabilities of obtaining Landsat images with no more than 30% cloud cover (CC) is higher. 2) the northeast of TGRA has higher probability of acquiring cloudless images than the southwest. 3) In TGRA, annual monitoring which require at least one cloud-free observation in a year largely unaffected by CC, but when considering seasonal monitoring, cloud contaminate will become a limitation, and monthly monitoring in this area is basically not feasible even if the three sensors data are combined. The results of this paper will provide important references for the research of using optical data in this area, and although the research area is relatively small, the analysis method and the program developed in this paper have no restrictions on the area.

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