scholarly journals Remote Sensing and Gis Based Land Use and Land Cover Information of Medchal Mandalof Medchal District

2019 ◽  
Vol 9 (2) ◽  
pp. 4682-4685
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Large Scale ◽  
Town Planning ◽  
Environmental Study ◽  
Land Resources ◽  
Visual Interpretation ◽  
Gis And Remote Sensing ◽  
Digital Format

It is exceptionally significant to use GIS and remote sensing application for proficient need in daily life. Upcoming and contemporary technologies like data processing, earth observation geodata processing and investigation are necessary for the researcher for the development of the society on a large scale. Remote sensing information data both in digital format and image format is utilized for retrieving the information about land resources by using (DIP) digital Interpretation Techniques and (VIP) Visual interpretation techniques Techniques. The foremost objective of the given study area is to Setup land use and land cover information system to evaluate land resources by by means of GIS Remote Sensing at Arc GIS10.2.1 platform of MedchalMandal. GIS and Remote Sensing information is the ultimate solution for the coverage of large area. Different types of layers are created from Remote Sensing images data and ArcGIS 10.2.1 Software. In the present study analysis is carried out by primary information which was generated from remote sensing data. GIS is Decision support system which helps planners and Decision makers to take correct decision for sustainable development, it also helps developers, engineers in environmental study, town planning and resource management.

scholarly journals Landuse Pattern and Landcover of Akure Forest Reserve and Its Environs

2019 ◽  
pp. 852-861
Author(s):  
O. O. Ojo ◽  
A. A. Shittu ◽  
T. J. Adebolu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Forest Reserve ◽  
Gis And Remote Sensing ◽  
Forestry Management ◽  
Ondo State ◽  
Cover Class ◽  
Broad Objective

This study investigated the pattern of land use and land cover of forest reserve in Akure, Ondo State, Nigeria. Currently, deforestation constitutes one of the global development challenges. The broad objective of this study is to identify land use and land cover class within the study area using satellite imagery (ies) to determine the rate/trend of change of this Forest Reserve from 1988 to 2018. The research method includes the use of Geographical Positioning System, and processing of field data through GIS and Remote sensing tool (ILWIS). The research was able to identify various land use and land cover within the Akure forest reserve with the help of GIS and remote sensing tools, the boundary of Akure forest reserve and its environs was delineated, and further result of the classification of Landsat shows that as at 2018 the forest reserve is covered with majorly light vegetation with 51.79%. The study recommended that there Department of Forestry and Ministry of Physical Planning and Urban Development must ensure Policy that will encourage local people and institutional participation in forestry management and conservation along with safeguarding indigenous people’s traditional rights and tenure with rightful sharing of benefits.

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 Land Use/Land Cover Mapping Using Geospatial Technology for Environmental Management

2019 ◽  
Vol 8 (9) ◽  
pp. 168-172
Keyword(s):  
Environmental Management ◽  
Land Use ◽  
Land Cover ◽  
Spatial Information ◽  
Decision Makers ◽  
Land Use Land Cover ◽  
Land Resources ◽  
Visual Interpretation ◽  
Management Planning ◽  
Cropping Patterns

The aim of the attempt was to study the Land use/Land cover attributes for environmental management planning for socio economic growth of study area. Evaluation of Land Resources in given study area by Remote sensing and Geographic Information System (GIS) technologies help to generate the spatial information to study the current conditions deliberate to the past conditions data and estimate the future requirements. The IRS-P6 satellite Imagery and Survey of India toposheets data, visual interpretation technique, Arc/Info and Arc View GIS software’s are used to prepare the final Land use/Land cover information. This data is useful for environment and natural resources development management. This type of land information study helps to prepare the Land and water Resources Action plans for conservation of suitable cropping patterns, and improved productivity of the study area and to provide the primary requirements of farmers, to enhance their background conditions and help to develop or enhance decision makers for sustainable development

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 Use of GIS and Remote Sensing Data to Understand the Impacts of Land Use/Land Cover Changes (LULCC) on Snow Leopard (Panthera uncia) Habitat in Pakistan

2021 ◽  
Vol 13 (7) ◽  
pp. 3590
Author(s):  
Tauheed Ullah Khan ◽  
Abdul Mannan ◽  
Charlotte E. Hacker ◽  
Shahid Ahmad ◽  
Muhammad Amir Siddique ◽  
...  
Keyword(s):  
Remote Sensing ◽  
At Risk ◽  
Land Use ◽  
Land Cover ◽  
Human Population ◽  
Land Cover Changes ◽  
Snow Leopard ◽  
Land Use Land Cover ◽  
Gis And Remote Sensing ◽  
Panthera Uncia

Habitat degradation and species range contraction due to land use/land cover changes (LULCC) is a major threat to global biodiversity. The ever-growing human population has trespassed deep into the natural habitat of many species via the expansion of agricultural lands and infrastructural development. Carnivore species are particularly at risk, as they demand conserved and well-connected habitat with minimum to no anthropogenic disturbance. In Pakistan, the snow leopard (Panthera uncia) is found in three mountain ranges—the Himalayas, Hindukush, and Karakoram. Despite this being one of the harshest environments on the planet, a large population of humans reside here and exploit surrounding natural resources to meet their needs. Keeping in view this exponentially growing population and its potential impacts on at-risk species like the snow leopard, we used geographic information systems (GIS) and remote sensing with the aim of identifying and quantifying LULCC across snow leopard range in Pakistan for the years 2000, 2010, and 2020. A massive expansion of 1804.13 km2 (163%) was observed in the built-up area during the study period. Similarly, an increase of 3177.74 km2 (153%) was observed in agricultural land. Barren mountain land increased by 12,368.39 km2 (28%) while forest land decreased by 2478.43 km2 (28%) and area with snow cover decreased by 14,799.83 km2 (52%). Drivers of these large-scale changes are likely the expanding human population and climate change. The overall quality and quantity of snow leopard habitat in Pakistan has drastically changed in the last 20 years and could be compromised. Swift and direct conservation actions to monitor LULCC are recommended to reduce any associated negative impacts on species preservation efforts. In the future, a series of extensive field surveys and studies should be carried out to monitor key drivers of LULCC across the observed area.

scholarly journals Land Use Land Cover Analysis using Geospatial Techniques

2021 ◽  
Vol 9 (8) ◽  
pp. 2561-2566
Author(s):  
Babita Singh
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Images ◽  
Anthropogenic Activities ◽  
Google Earth ◽  
Landscape Configuration ◽  
Landsat 8 ◽  
Visual Interpretation ◽  
Open Forest

Abstract: Remote sensing and Geographic information system (GIS) techniques can be used for the changing pattern of landscape. The study was conducted in Dehradun, Haridwar and Pauri Garhwal Districts of Uttarakhand State, India. In order to understand dynamics of landscape and to examine changes in the land use/cover due to anthropogenic activities, two satellite images (Landsat 5 and Landsat 8) for 1998 and 2020 were used. Google Earth Engine was used to perform supervised classification. Spectral indices (NDVI, MNDWI, SAVI, NDBI) were calculated in order to identify land cover classes. Both 1998 and 2020 satellite images were classified broadly into six classes namely agriculture, built-up, dense forest, open forest, scrub and waterbody. Using high resolution google earth satellite images and visual interpretation, overall accuracy assessment was performed. For land cover/use change analysis, these images were imported to GIS platform. Landscape configuration was observed by calculating various landscape metrices Images. It was observed that scrub land area had increased from 11 % to 14 % but a decrease in agriculture by 4.65 %. The increased value of NP, PD, PLAND, LPI and decrease in AI landscape indices shows that land fragmentation had increased since 1998. The most fragmented classes were scrub (PD - 3.32 to 5.18) and open forest (PD - 3.57 to 5.07). Decrease in AI for open forest, agriculture, built-up indicated that more fragmented patches of these classes were present. The result confirmed increase in the fragmentation of landscape from 1998 onwards. Keywords: GIS, LULC, landscape metrics, Remote Sensing

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