scholarly journals Conservation Measures for Improving Land Use and Land Cover in Dalvoy Lake Environs of Mysore City

2021 ◽  
Vol 10 (1) ◽  
pp. 173-177
Author(s):  
Akshatha N* ◽  
Shankar B
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Remote Sensing Data ◽  
Living Condition ◽  
Water Bodies ◽  
Large Cities ◽  
Small Water ◽  
The People ◽  
Erdas Imagine ◽  
The City

In recent years of Indian urbanization, the structure of large cities is undergoing rapid land use and land cover changes in lake environs, particularly in Mysore. Mysore is one of the fastest growing tier II cities, located in southern part of Karnataka. The city comprises of several large and small water bodies viz, Karanji Lake, Dalvoy Lake, Kukkarahalli Lake and Devanoor Lake. These lakes play an important role in recharging ground water, regulates microclimate, home for flora and fauna, recreational place for each neighborhood involving in community participation, improve aesthetic of the city and finally influence living condition of the people. Due to rapid transformation of land use and landcover in Mysore has resulted in degradation of water bodies. Dalvoy Lake is one of the major Lakes in Mysore City and it is deteriorating as a result of land use change, growth of industries and urbanization pressures. The total catchment area of Dalvoy Lake is 2165 acres. According to sixth sustainable development goals (clean water and sanitation) targets to protect and restore water-related ecosystems, including wetlands, rivers, and lakes. This paper deals with land use and landcover changes and its analyzing around Dalvoy Lake and its catchment using Remote sensing data and ERDAS imagine software and propose sustainable strategies for environmental improvement and management of the lake.

scholarly journals Assessment of Change in the Built-Up Index of Uyo Metropolis and Its Environs Using Remote Sensing

2019 ◽  
Vol 4 (6) ◽  
pp. 84-89 ◽  
Author(s):  
Aniekan Effiong Eyoh ◽  
Akwaowo Ekpa
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Quantitative Analysis ◽  
Land Cover ◽  
Agricultural Land ◽  
Remote Sensing Data ◽  
Land Use Land Cover ◽  
Positive Growth ◽  
Bare Land ◽  
Erdas Imagine

The research was aim at assessing the change in the Built-up Index of Uyo metropolis and its environs from 1986 to 2018, using remote sensing data. To achieve this, a quantitative analysis of changes in land use/land cover within the study area was undertaken using remote sensing dataset of Landsat TM, ETM+ and OLI sensor images of 1986, 2000 and 2018 respectively. Supervised classification, using the maximum likelihood algorithm, was used to classify the study area into four major land use/land cover types; built-up land, bare land/agricultural land, primary swamp vegetation and secondary vegetation. Image processing was carried out using ERDAS IMAGINE and ArcGIS software. The Normalised Difference Built-up Index (NDBI) was calculated to obtain the built-up index for the study area in 1986, 2000 and 2018 as -0.20 to +0.45, -0.13 to +0.55 and -0.19 to +0.63 respectively. The result of the quantitative analysis of changes in land use/land cover indicated that Built-up Land had been on a constant and steady positive growth from 6.76% in 1986 to 11.29% in 2000 and 44.04% in 2018.

scholarly journals Effect of Urbanization on Land use Land Cover in Gombe Metropolis

2019 ◽  
Vol 1 (1) ◽  
pp. 22-29
Author(s):  
L.A. Mbaya ◽  
G. O. Abu ◽  
Yila Caiaphas Makadi ◽  
D.M. Umar
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rock Outcrops ◽  
Policy Makers ◽  
Sparse Vegetation ◽  
Time Period ◽  
Land Cover Dynamics ◽  
Erdas Imagine ◽  
Arc Gis ◽  
The City

This study examined the integration of Remote Sensing and Geographic Information System (RS/GIS) for analyzing land use and land cover dynamics in Gombe Metropolitan, the Gombe State capital for the period 1976 to 2016. Land sat (TM) images of 1976, 1996and 2016 were used. The study employed supervised digital image classification method using Erdas Imagine 9.2 and Arc GIS 10.5 software and classified the land use into undisturbed vegetation, sparse vegetation, Settlements, Farmlands, Rock outcrops, Bare surfaces. The images were analyzed via georeferencing, image enhancement, image resampling and classification. The results obtained show an increasing settlements (from 0.36% - 4.01%) and farmlands (from 24.8% - 51.2%), over a decreasing of other LULC classes (bare surfaces, undisturbed and sparse vegetation, and rocky outcrops) for the time period of 1976 to 2016. These results could help city planners and policy makers to attain and sustain future urban development. It is therefore recommended that encouragement should be given to people to build towards the outskirts, like New mile 3 and Tumfure, etc through the provision of incentives and forces of attraction that is available at the city center in these areas to avoid the problem of overcrowdings.

scholarly journals A LONG-TERM LAND COVER AND LAND USE MAPPING METHODOLOGY FOR THE ANDEAN AMAZON

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 373-378
Author(s):  
M. O. Borja ◽  
R. Camargo ◽  
N. Moreno ◽  
E. Turpo ◽  
S. Villacis
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Large Scale ◽  
Methodological Approach ◽  
Remote Sensing Data ◽  
The Novel ◽  
Water Index ◽  
Small Water ◽  
The Andes ◽  
Fractional Abundance

Abstract. The data developed by the MapBiomas Amazon initiative ( http://amazonia.mapbiomas.org/ ) led by the Amazon Geo-referenced Socio-environmental Information Network’s (RAISG) is of unprecedented spatial and temporal resolution for the Andes region. It’s comprised by a series of annual maps for the years 2000 to 2017 that allow to monitor the extent of transformation in this region using a single regional methodological approach. Several variables were included to solve Andes-specific methodological challenges and they represent adaptations of RAISG’s Amazonian methodology to the Andean region. Among such, is the use of the novel NDFIb index (Turpo, 2018), an adaptation of the NDFI index that aims at mapping Andean Wetlands. Glaciers identification was aided by the fractional abundance of snow (Turpo, 2018), as well as small water bodies identification with McFeeters (1996) NDWI water index. This experience unfolds promising accessibility to novel land cover and land use regional reconstructions and comparisons possible only by the use of large-scale cloud-computing data processing tools, open source technology, spatially and temporally comprehensive remote sensing data, along with RAISG’s standardized protocols and frameworks.

scholarly journals Approach of Remote Sensing and GIS Techniques of Land Use and Land Cover Mapping –Patna Municipal Corporation, (PMC) Patna, Bihar, India

2020 ◽  
pp. 371-377
Author(s):  
Mohammad Yasir Ahmad ◽  
Nikhat Hassan Munim
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Maximum Likelihood ◽  
Land Cover ◽  
Water Bodies ◽  
Fallow Land ◽  
Land Use Land Cover ◽  
Gis Techniques ◽  
Agriculture Land ◽  
The City

The approach of Remote Sensing (RS) and Geographical Information System (GIS) for the preparation of land use land cover (LULC) mapping is an essential aspect of planning and development activities for earth resource management. This paper investigates land use land cover (LULC) map of Patna Municipal Corporation (PMC), Patna, Bihar, India. The City Patna (PMC) is a fast developing city and emerging economic centre in Bihar. The population of the city (PMC) is growing day by day, and rapid migration from the different parts of the Bihar resulted from rapid urbanization. We offer RS and GIS techniques delineated different LULC of the PMC study area. LULC was done through False Color Composite (FCC) Satellite Image, Resourcesat-2A Linear Imaging Self Scanning Sensor IV (LISS-IV) with 5.8-meter spatial resolution data of the year 2018. The supervised classification and maximum likelihood classification were used to classified LISS IV images. The LULC map was created five different classes identified water bodies, agriculture land, fallow land, wasteland, built-up land, and vegetation of the study area. The advantages of MLC method in which a pixel with the maximum likelihood is classified into the corresponding class based on a probability function determines the variance and covariance of each theme. The LULC result showed that maximum area under PMC was covered with a built-up area of 70.80 Sq. Km. is higher than the others because of the rapidly growing population. Agriculture land, fallow land, and vegetation occupied area of 31.7 Sq.Km., while the wasteland constituted around 11.86 Sq. Km and water bodies covered around 5.8 Sq.Km. The accuracy was done through field verification and Satellite (Google) image.

scholarly journals Monitoring the Spatial Variation of Aerosol Optical Depth and Its Correlation with Land Use/Land Cover in Wuhan, China: A Perspective of Urban Planning

2021 ◽  
Vol 18 (3) ◽  
pp. 1132
Author(s):  
Qijiao Xie ◽  
Qi Sun
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Urban Planning ◽  
Land Cover ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Water Bodies ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
The Impact

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.

scholarly journals Estimation of Infiltration Volumes and Rates in Seasonally Water-Filled Topographic Depressions Based on Remote-Sensing Time Series

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7403
Author(s):  
Pavel P Fil ◽  
Alla Yu Yurova ◽  
Alexey Dobrokhotov ◽  
Daniil Kozlov
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Shallow Groundwater ◽  
Remote Sensing Data ◽  
Water Bodies ◽  
Water Infiltration ◽  
Temporary Ponds ◽  
Small Water ◽  
Negative Exponential ◽  
Topographic Depressions

In semi-arid ecoregions of temperate zones, focused snowmelt water infiltration in topographic depressions is a key, but imperfectly understood, groundwater recharge mechanism. Routine monitoring is precluded by the abundance of depressions. We have used remote-sensing data to construct mass balances and estimate volumes of temporary ponds in the Tambov area of Russia. First, small water bodies were automatically recognized in each of a time series of high-resolution Planet Labs images taken in April and May 2021 by object-oriented supervised classification. A training set of water pixels defined in one of the latest images using a small unmanned aerial vehicle enabled high-confidence predictions of water pixels in the earlier images (Cohen’s Κ = 0.99). A digital elevation model was used to estimate the ponds’ water volumes, which decreased with time following a negative exponential equation. The power of the exponent did not systematically depend on the pond size. With adjustment for estimates of daily Penman evaporation, function-based interpolation of the water bodies’ areas and volumes allowed calculation of daily infiltration into the depression beds. The infiltration was maximal (5–40 mm/day) at onset of spring and decreased with time during the study period. Use of the spatially variable infiltration rates improved steady-state shallow groundwater simulations.

scholarly journals Impact of Changes in Land Use and Land Cover in the Contribution Basin of Doutor João Penido Water Supply Reservoir of Juiz de Fora, MG, Brazil

2021 ◽  
Vol 11 (1) ◽  
pp. 108
Author(s):  
Juliana Nazareth de Lana ◽  
Márcio de Oliveira ◽  
Vanessa Romario de Paula ◽  
Cézar Henrique Barra Rocha
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Cover ◽  
Water Supply ◽  
Quality Parameters ◽  
E Coli ◽  
The City ◽  
Water Supply Reservoirs ◽  
Limnological Parameters

Changes in the land use and land cover in areas adjacent to water reservoirs directly affect the quality of this water. This research presents a study on the water quality in the basin of one of the most important public water supply reservoirs in the city of Juiz de Fora, Minas Gerais. The main objective of this study was to analyze the behavior of limnological parameters and the correlation with land use and land cover in the contribution basin of the Doutor João Penido reservoir (CBJPR). The methodology was based on the analysis of water quality parameters, related to water samples collected from 2012 to 2015. Six sampling points were chosen from different locations: spring, medium course, main tributaries of the reservoir and the reservoir catchment. The parameters analyzed were turbidity, total solids (TS), oxygen consumed (OC), dissolved oxygen (DO), electrical conductivity, total nitrogen (TN), total phosphorus (TP), E. Coli, temperature, pH and total dissolved solids (TDS). The Kendall’s tau test was used to analyze the correlations between the parameters of water quality, land use and land cover in the CBJPR. In general, measured parameters showed better results in spring and in reservoir catchment, showing a worse quality of the water along the tributaries and the dilution power of the reservoir. The correlations pointed to the need for protection and preservation of forests in strategic locations to ensure good water quality.

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 Land Use/Land Cover Mapping of Sambar Watershed by Using Remote Sensing and GIS

2021 ◽  
Vol 10 (9) ◽  
pp. 578-585
Author(s):  
B. Varpe Shriniwas D. Payal Sandip
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing And Gis ◽  
Rapid Expansion ◽  
Water Bodies ◽  
Land Cover Mapping ◽  
Fallow Land ◽  
Land Use Land Cover ◽  
Barren Land

In the present study, an effort has been made to study in detail of Land Use/Land Cover Mapping for Sambar watershed by using Remote Sensing and GIS technique was carried out during the year of 2020-2021 in Parbhani district. In this research the Remote Sensing and Geographical Information system technique was used for identifying the land use/land cover classes with the help of ArcGIS 10.8 software. The Sambar watershed is located in 19º35ʹ78.78˝ N and 76º87ʹ88.44˝ E in the Parbhani district of Marathwada region in Maharashtra. It is covered a total area 97.01 km2. The land use/land cover map and its classes were identified by the Supervised Classification Method in ArcGIS 10.8 software by using the Landsat 8 satellite image. Total six classes are identified namely as Agricultural area, Forest area, Urban area, Barren land, Water bodies and Fallow land. The Agricultural lands are well distributed throughout the watershed area and it covers 4135 ha. (43 per cent). Forest occupies 502 ha area and sharing about 5 per cent of the total land use land cover of the study area. The Urban land occupies 390 ha. area (4 per cent) and there was a rapid expansion of settlement area. Barren land occupies 3392 ha. area (35 per cent). A water bodies occupy 630 ha. area (6 per cent) and the Fallow land occupies 650 ha (7 per cent) but well-developed dendritic drainage pattern and good water availability is in the Sambar watershed.

Sign in / Sign up

Export Citation Format

Share Document