Detection of land use-land cover changes in Anzali Wetland using a remote sensing-based approach

2021 ◽  
Author(s):  
Amirmoez Jamaat ◽  
Ammar Safaie
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Caspian Sea ◽  
Satellite Image ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Anzali Wetland ◽  
High Resolution Satellite Images

<p>Wetlands are valuable ecological resources which play an essential and important role in the ecosystem of the region. Hence, there is a crucial need for monitoring and characterization of wetland changes caused by natural and anthropogenic disturbance. In this study, we developed a remote sensing-based approach to investigate long term land use/land cover changes (LULC) of Anzali Lagoon located in the southern coast of the Caspian Sea. In recent years, Anzali Wetland has experienced severe threats by human- and climate-induced changes and is drying up at an alarming rate. Here, an enhanced LULC change detection method is presented using a seasonal harmonic analysis of satellite image based on Normalized Difference Vegetation Index (NDVI)   that combined with remotely-sensed thermal observations. Machine learning and object-oriented approaches were implemented on high-resolution satellite images to obtain a comprehensive land-use classification map of the study area. Then, wetland vegetation changes, such as marshes, were investigated during 2013 to 2020. Additionally, the long-term sea level trend in Caspian Sea was used, along with groundwater storage changes derived by GRACE satellite data, to study their impacts on wetland ecological changes. Results of the developed hybrid model indicate that the western and central parts of the wetland are more subjected to drought stress. Moreover, spatial and temporal changes in density of aquatic plants related to external stressors were identified in the wetland. The results of this study enhance a better understanding of long-term LULC changes in coastal wetlands in response to climate changes and anthropogenic activities.</p><p> </p><p> </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.

scholarly journals Land Use/Land Cover Changes of Ado-Ekiti LGA, Ekiti State, Nigeria Using Remote Sensing Techniques

2021 ◽  
pp. 32-42
Author(s):  
Ajagbe, Abeeb Babajide ◽  
Oguntade, Sodiq Solagbade ◽  
Abiade, Idunnu Temitope
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Local Government ◽  
Land Cover ◽  
Water Body ◽  
Local Government Area ◽  
Land Cover Changes ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
Bare Surface

Land use assessment and land cover transition need remote sensing (RS) and geographic information systems (GIS). Land use/land cover changes of Ado-Ekiti Local Government Area, Ekiti State, Nigeria, were examined in this research. Landsat 5 TM, Landsat 7 ETM+ and Landsat 8 OLI were acquired for 1985, 2000, and 2015 respectively. Image scene with path 190 and row 055 was used for the three Landsat Images. A supervised digital image classification approach was used in the study, which was carried out using the ArcMap 10.4 Software. Five land use/land cover categories were recognised and recorded as polygons, including Built-up Areas, Bare surface, water body, Dense Vegetation and Sparse Vegetation. The variations in the area covered by the various polygons were measured in hectares. This study revealed that between 1985 and 2015, there was a significant change in Built-up areas from 1694 hectares to 5656 hectares. However, there was a reduction in water body from 25 hectares in 1985 to 19 hectares in 2015; there was a severe reduction in the bare surface from 4641 hectares in 1985 to 2237 hectares in 2015. Generally, the findings show that the number of people building houses in the study area has grown over time, as many people reside in the outskirts of the Local Government Area, resulting in a decrease in the vegetation and bare surfaces. The maps created in this research will be useful to the Ekiti State Ministry of Land, Housing, Physical Planning, and Urban Development to develop strategies and government policies to benefit people living in the Ado-Ekiti Local Government Area of the State.

scholarly journals Land-use/Land-cover Changes and Deforestation in Effan Forest Reserve, Kwara State, Nigeria

2021 ◽  
Author(s):  
Adesoji Akinwumi Adeyemi ◽  
Farouq Maku Owolabi
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Tree Species ◽  
Land Cover Changes ◽  
Indigenous Species ◽  
Land Use Land Cover ◽  
Vitellaria Paradoxa ◽  
Forest Protection ◽  
Forest Reserve

Remote sensing/GIS techniques are a versatile tool for x-raying serial forest structural changes in retrospect. It would be impossible to evaluate past occurrences and changes in forest extents in past decades at Effan Forest Reserve without non-conventional means. Therefore, we adopted remote sensing technology using Landsat images to evaluate land-use change and degradation rates in the area with a view to ascertaining causal factors for possible minimization of forest degradation in Effan Forest Reserve. Land-use/land-cover changes were analyzed using USGS-Landsat TM and ETM images of 1987, 2002, 2014 and 2019. Field-data were collected using handheld GPS receiver and spatial statistical analyses were conducted using the ground control points (GCPs). For inventory data, a systematic sampling technique was adopted using ten 1.05 km-transects at 500 m intervals. A total of 50 sample plots of 50 × 50 m were used. All tree species with Dbh ≥10 cm were enumerated. Nineteen tree species in ten families were encountered with Vitellaria paradoxa as the most-frequently occurring species in the area. IUCN-listed endangered Pterocarpus erinaceus, hitherto abundant in the area, was rarely encountered during the survey, while Vitellaria paradoxa is gradually shrinking, going the relative abundance in the area. The result further showed that primary and secondary forests decreased considerably by 258.03 ha (46.72%) and 9.18 ha (3.63%), respectively, with a total forest loss of 50.3% in 32 years (8.4 hayr-1, 1.6% per annum). While forest plantation size doubled by 369.72 ha within the period. This is worrisome as the remaining fragmented forests appeared to be on the decline, except the riparian vegetation, due to inaccessibility to the riparian by loggers. It thus appeared that forest protection approaches were ineffective. Increased protection efforts could save this forest reserve, and the concerned authority should consider a focused-enrichment planting involving indigenous species for ecosystem-repair.

ASSESSMENT OF LAND COVER CHANGES DUE TO ANTHROPOGENIC CAUSES IN THE MOUNTAINOUS AREA OF ISHKOMAN WATERSHED, GILGIT, PAKISTAN

2021 ◽  
Vol 14(63) (1) ◽  
pp. 25-46
Author(s):  
Komal NABI ◽  
Karamat ALI ◽  
Muhammad Irfan ASHRAF ◽  
Areeba Binte IMRAN ◽  
Naveed AHMAD
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Temporal Changes ◽  
Population Increase ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Community Perception ◽  
Land Type ◽  
Land Use Dynamics

Remote Sensing (RS) provides the best ways to monitor temporal changes and to understand land use dynamics. Remote sensing analysis can be further enhanced when community perception regarding major drivers of change is integrated. The present study was an attempt to assess the land use land cover changes in the Ishkoman watershed in the Ghizer district. The study explored Landsat-5 and Landsat-8 images to assess the LULC dynamics from 1998 to 2018, and also used questionnaires for community perception regarding LULC changes in the past two decades. Supervised classification was used to monitor changes between 1998 and 2018 and the maximum likelihood technique was used to categorize the pixels into six classes: vegetation/forest area, bare rocks, water bodies, glaciers/snow area, rivers, water, and agriculture. Regarding the questionnaires, the correlation matrix and regression models were developed between independent variables (population, land type cleared, and extra land required for new family members) and dependent variables (land use dynamics factors and socio-economic variables). The results showed that all six land cover classes have shown temporal changes between 1998-2018 and the most significant change was observed in forests and pastures (which decreased from 18.7% to 5.9 %). Similarly, glaciers, water, rivers, and agriculture have changed from 13.1, 6.5, 9.3, 1.5 to 15.8, 4.0, 11.32, 3.1, respectively between 1998-2018. The largest change was observed in bare rocks which increased from 50.2 % to 60.06%. Moreover, temporal NDVI analysis showed a decrease in vegetation cover (conversion to bare rocks) between 1998-2018. The questionnaire results revealed that the highest correlation was shown between population increase and decrease in crop production (R2 = -0.348), whereas the lowest correlation was found in population increase and population access to bus stops (R2 = -0.167). Similarly, the highest correlation was found between access to roads and markets (R2 = 0.349) and dependent variable (land type cleared), whereas the lowest correlobserved in access to water resources (R2 = -0.021). The study concluded that land use land cover has been significantly changed from 1998 to 2018 in the Ishkoman Watershed. The study suggested more in-depth research to examine land use land cover changes at finer scales by using high resolution satellite imagery, and conducting details surveys regarding the underlying anthropogenic causes of land use dynamics.

The dynamics of urban expansion and land use/land cover changes using remote sensing and spatial metrics: the case of Mekelle City of northern Ethiopia

2017 ◽  
Vol 38 (14) ◽  
pp. 4107-4129 ◽  
Author(s):  
Ayele Almaw Fenta ◽  
Hiroshi Yasuda ◽  
Nigussie Haregeweyn ◽  
Ashebir Sewale Belay ◽  
Zelalem Hadush ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Urban Expansion ◽  
Land Cover Changes ◽  
Northern Ethiopia ◽  
Land Use Land Cover ◽  
Spatial Metrics ◽  
Mekelle City
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