scholarly journals Analysis of Land Use and Land Cover Changes in the Wetland Ecosystem of Port-Harcourt Metropolis, Nigeria

2019 ◽  
Vol 8 (2) ◽  
pp. 54
Author(s):  
Wali Elekwachi ◽  
Phil-Eze P. O. ◽  
Nwankwoala Hycienth O. ◽  
Bosco-Abiahu Lilian C. ◽  
Emelu Victoria O.
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Rate Of Change ◽  
Freshwater Wetland ◽  
Total Percentage ◽  
Port Harcourt ◽  
Erdas Imagine ◽  
The Government ◽  
Remote Sensing Techniques

The study analyzed changes in land use and land cover overtime in Port-Harcourt metropolis using remote sensing techniques from 1984-2013.The Geo-referencing properties of 1984, 1999, 2003 and 2013 include; universal Transverse Mercator (UTM) projection, and datum WGS 84, zone 32, ERDAS Imagine (2014).These were used for displaying processing, enhancement, classification of the imageries and also used for the delineation of the study area imagery. IDRIS SELVA was used for the development of land use land cover classes. ArcGIS 10.1was used in developing, display and processing of the location maps. Total percentage change and total rate of change for the entire trend after conversion are thus: Saltwater Wetland 23.44%, to- 2.17, Freshwater Wetland - 26.44%to- 11.49 Fallow land- 47.13%to- 5.41 Built-up Area 43.33% to 7.41Water bodies 43.36% to 3.06.The study recommended that activities shrinking wetlands size should be thoroughly put to check by the government and better efforts should be focused on those activities that inspire wetland conservation.

scholarly journals Land use and land cover mapping and identification of misuse in the permanent preservation areas in the Tailândia Municipality - PA

2017 ◽  
Vol 38 (3) ◽  
pp. 1145 ◽  
Author(s):  
Rosana Sumiya Gurgel ◽  
Paulo Roberto Silva Farias ◽  
Sandro Nunes de Oliveira
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Palm Oil ◽  
Regulatory Agencies ◽  
Visual Interpretation ◽  
Livestock Farming ◽  
Land Cover Data ◽  
The Government ◽  
Remote Sensing Techniques ◽  
Bodies Of Water

The objective of this study is to expand the mapping of land use and land cover, as well as of the permanent preservation areas (PPAs), and identify land misuse areas in the PPAs in the Tailândia municipality in the state of Pará, which is part of the Amazon biome. Remote sensing techniques and geographic information systems (GIS) were used to achieve these goals. Mapping and classification for the year 2012 were made by visual interpretation of images obtained from the RapidEye satellite, which has a 5 m spatial resolution. In this work, we identified nine classes of land use and land cover. From the hydrography vectors it was possible to determinate the Permanent Preservation Areas of the bodies of water according to the environmental legislation. Analysis of misuse in the PPAs was made by crossing-checking the land use and land cover data with that of the PPAs. The results show that 53 % of the municipality (2,347.64 km²) is occupied by human activities. Livestock farming is the activity that has most increased the use of area (30 %), followed by altered vegetation (14.6 %) and palm oil (7.2 %). The PPAs have a high percentage of misuse (47.12 %), with livestock being the largest contributor, occupying 26.65 % of the PPAs, followed by altered vegetation (12.64 %) and palm oil (4.29 %). Therefore, the main objective in Tailândia is to reconcile economic activity with sustainable development. It is important to emphasize the partnerships between the government, research institutions, regulatory agencies, states departments and local communities, else it would be impossible to monitor or control an area as vast as the Amazon.

scholarly journals Spatial change detections and inventory of wetlands in Yenagoa Urban Area: Bayelsa State, Nigeria

2021 ◽  
Vol 6 (6) ◽  
pp. 230-240
Author(s):  
Eze Promise I ◽  
Elemuwa IC ◽  
Lawrence Hart
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Area ◽  
Urban Expansion ◽  
Rate Of Change ◽  
Percentage Change ◽  
Annual Rate ◽  
Land Use Land Cover ◽  
Total Percentage

Yenegoa Town has in recent years witnessed rapid City growth and Urban development and much of these developments are unplanned and unregulated. This has seriously impacted on wetlands in several locations of the town as persistent Wetlands reclamations are being witnessed in study area. This prompted the need for the study which is aimed to map wetlands location in Yenagoa’s urban area using GIS and Remote Sensing approach. The study analyzes land use/land cover changes (LULC) using LANDSAT(5) TM, LANDSAT(5) ETM and LANDSAT(7) OLI satellite imageries of 1990, 2000, 2010 and 2020 respectively. Through this study, the pattern of urban expansion for Thirty years were been studied. The satellite imageries covering the area were acquired and analyzed using ArcGIS 10.1 and ENVI 5.0 software. The supervised image classification method was adopted and the classification results were validated using the Kappa Index of Agreement (KIA) yielding an accuracy of 0.69m for year 1990, 0.62m for year 2000, 0.58m for year 2010 and 0.73m for 2020. A total area of 13,741.4 hectares was delineated in the study area which is identified as Yenagoa’s urban area. After processing the imageries, four land use/land cover (LULC) classes where considered, and the results shows that Built-up area continuously increased in land area from 1990 -2020 with total percentage change of 273.31% (4,178.7ha) and total annual rate of change of 25.33. Vegetation have total percentage change of 38.55% (974.34Ha) and total annual rate of change of 3.85, wetland cover loss with total percentage Change of 61.96% (-51,44.99ha) and total annual rate of change of -6.19ha, and the water body have loss of total percentage of -2.16% (-8.05Ha) and total annual rate of change of -0.22ha wetland at Yenegwe loss by Total %change of -29.918% ( -197.95ha), and wetland at Igbogene loss by total percentage change of -36.028% (-358.7ha). The research findings also revealed that the wetlands in Anyama, Swali, Kpansia and Opolo Towns were completely lost from the third Epoch of 2010, this may be as a result of persistence reclamation of wetland in this parts of the study area. The Markov Chain predicted model were utilized for predicting the likely changes in land use land cover for a period of thirty years. The predicted results also indicates that wetland size of 32.47,%, 30.68% and 28.99% may likely be lost by the year 2030, 2040 and 2050 respectively in study area if no action is taking by concerned authorities to forestall the factors responsible for the lost in wetland. The study justified the dynamics of remote sensing and GIS techniques in modeling wetlands changees over these periods, wise use of wetland resources and improvement of institutional arrangement were recommended so that wetland policies can be fully integrated into the planning process across all disciplines.

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 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.

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