Land Cover Change Detection Analysis Research Articles

Land use land cover change detection analysis in kodjai watershed using remote sensing and GIS

Land use land cover change detection analysis in kodjai watershed using remote sensing and GIS

Land use / land cover change detection analysis through geospatial technology in Jhansi district of Bundelkhand region

Land use / land cover change detection analysis through geospatial technology in Jhansi district of Bundelkhand region

Assessment of Thermal-induced Forest Stress: A case of Akure Forest Reserve, Ondo State, Nigeria

Forest stress or health has become a topic of serious interest to researchers in recent times. It reached a crescendo consequent upon the renewed interest in climate change’s effects, resilience and mitigation. Forest stress is majorly a climate-related occurrence that can only be managed but not totally eradicated. Therefore, this study is aimed at assessing thermal induced stress in Akure forest reserve in Ondo State, Nigeria, using the instrumentality of Remote Sensing and Geographic Information System (GIS). The temperature data used for this study was extracted from Landsat 8 (OLI) imagery obtained from United States Geological Survey (USGS) database between the years 2016 and 2020. A land use land cover change detection analysis of the study area revealed that between 2016 and 2020, forest and waterbody decreased from 4344.59 to 2971.71 ha and 187.28 to 178.23 ha respectively while shrubs and bare land increased from 1472.13 to 2533.05 ha and 578.16 to 899.34 ha respectively. Forest stress and health of the study area was assessed using vegetation indices and land surface temperature LST). The result reveals changes in mean LST across the four lands cover types during the study period. It ranges between 22.28 oC (water body) in 2016 to 28.99 oC (bare land) in 2018. The spatial trend of Vegetation Health Index (VHI) was used to delineate the health of the forest. The study reveals that the spectral changes in the biophysical characteristics of the forest could not be solely attributed to temperature variability. Other climatic parameters and soil related variables must have contributed to notice stress in the forest reserve. However, this study has brought to the fore the robustness of geospatial technologies on the study of forest stress, health and drought.

Impacts of Urbanization Rate and Land Cover Change on Urban Farm Land: A Case of Wolayta Zone Sodo Zuria Woreda

The effect of human intervention on the agricultural system has shown food insecurity with an increase in the cost of crop production in the local market due to the expansion of urbanization in the study area with 2.66% in 9 years for the demand of residential land. and also beyond this simulation result, the impact of deforestation on urban Agricultural and livelihoods was not scientifically studied in most of the southern Ethiopia high lands and their surrounding in particularly for Wolayta zone sodo zuria woreda has shown 0.295 % per year of forestland declined by 0.09 % for residential land and it has used for public service during the selected study period. This study has focused on the impact of urbanization rate and land use land cover change detection analysis using Primate and secondary data source with integration (GIS) Geographic Information System and Remote sensing Method for managing the negative impact on the geospatial environment in the context of Ethiopian Agricultural Transformation (ATP) goal of sustainable development. And evaluation of image classification accuracy can be defined as the process of comparing the classified image with geographic data considered to be accurate and referential typically, the data which is classified image is compared to are ground-truth based on supervised classification with (CR) Consistency Ratio 0.016 % of the pixel has resulted for accuracy assessment of 30m Land Sat 7 satellite image. In general, a set of reference shapefile has been overlaid as 7 major landuse class which are generated over the classified image by the AHP method of Computing Eigenvector Matrixes, which is an output of the pairwise comparison matrix to produce the best fit set based on the pixel value landuse area listed Keywords: Analytic Hierarchical Process (AHP), Geographic Information System (GIS), Land sat 7 (ETM+) and Eigenvector Matrixes DOI: 10.7176/CER/13-3-03 Publication date: May 31 st 2021

Unmanned Aerial Vehicles for Three‑dimensional Mapping and Change Detection Analysis

Unmanned Aerial Vehicles (UAVs), commonly known as drones are increasingly being used for three‑dimensional (3D) mapping of the environment. This study utilised UAV technology to produce a revised 3D map of the University of Lagos as well as land cover change detection analysis. A DJI Phantom 4 UAV was used to collect digital images at a flying height of 90 m, and 75% fore and 65% side overlaps. Ground control points (GCPs) for orthophoto rectification were coordinated with a Trimble R8 Global Navigation Satellite System. Pix4D Mapper was used to produce a digital terrain model and an orthophoto at a ground sampling distance of 4.36 cm. The change detection analysis, using the 2015 base map as reference, revealed a significant change in the land cover such as an increase of 16,306.7 m2 in buildings between 2015 and 2019. The root mean square error analysis performed using 7 GCPs showed a horizontal and vertical accuracy of 0.183 m and 0.157 m respectively. This suggests a high level of accuracy, which is adequate for 3D mapping and change detection analysis at a sustainable cost.

Application of GIS and Remote Sensing to Analyse Land Use Land Cover Change Detection and Vegetation Dynamics Using Multi-temporal Satellite Images; The Case of Mariamdehan Kebele, Tigray Region, Northern Ethiopia

Detecting Land use and land cover change and vegetation condition has become a central component in current strategies for managing and monitoring of environmental changes caused by anthropogenic activities. To come up with such decisions, geoinformatics technology is providing new tools to conduct vegetation and land use land cover change detection analysis for managing and wise utilisation of natural resources as well as to provide information for policymakers in a given study area. This study examines the use of geoinformatics technology to analyse land use land cover (LULC) change and vegetation dynamics using multi-temporal satellite images for the maryamdehan kebele in the years 1984, 2005 and 2015. Both primary and secondary data were used from different sources. Satellite images of the year 1984, 2005 and 2015 were downloaded from the govis.usgs.gov website and ground control points (GCP) data were collected by handheld GPS for supervised image classification in Erdas imagine and ArcGIS environment. The findings show that six main land use land cover classes were detected and vegetation values were also computed in each period. As a result, the total area of the kebele was 3646.49 hectare, from which in 1984 forest area (40.691%), grassland (26.15%) and farmland (10.81%) were dominant classes and in 2005 settlement (52.41%), forest area (25.04%) & farmland (11.71%) and in 2015, 35.14% was covered by forest land, 30.04% by Settlement, and 14.74% by farmland. Water resource decreases from 9.3% to 0.64% in 2015 and the bare land also changes from 3.18% to 0.903% because of urban expansion and agricultural activities in the kebele. In addition, the vegetation condition looks like a sinusoidal trend from the year 1984 up to 2015 because of climate change and human interventions in the kebele. To conclude that detecting LULC change and analysis of vegetation dynamics plays a great role in land use management and wise utilisation of natural resources by applying Geoinformatics tools in the kebele and it provides information for the policymakers to prepared future plan and for sustainable development.

Change Detection Analysis of Vamsadhara - Nagavali River Fluvial System, using Multi-Temporal Remote Sensing Data and GIS Techniques

Land use & Land cover change detection analysis has been carried out in the present study covering the Nagavali and Vamsadhara Fluvial system (18°40′N to 18°09′N latitude and 84°10′ E to 83°39′E longitude). Satellite images of Landsat-7 ETM+ (2000) Landsat ETM+ (2010) Landsat OLV-TIRS (2016) and 1975 SI Toposheets have been used to study the temporal changes in the land use and land cover by onscreen digitisation techniques in ARC GIS 10.1 software followed by image processing to obtain changes in various classes of land use during study period from 1975 to 2016. The classes include plantation, settlements, water bodies, coastal area, wetlands, agriculture land and area under river course of both rivers. The classes, which have shown an increased area from 1975 to 2016, include Agriculture (from 56.93 % to 63.95%) and Settlements (from 1.40% to 3.43%). The classes that have shown the decreasing trend of Land Use are Plantation (from 19.76% to 13.14%), water bodies (from 2.29% to 0.77%), Wetlands (from 0.72% to 0.57%). The area under river course of both the rivers has shown a decreasing trend. The analysis reveals that due to increased irrigation facility plantation, wetlands and water bodies have brought under agricultural use and this trend need to be arrested. The Plantation area for natural resource management furthermore declines the soil erosion in between the Vamsadhara and Nagavali river area.

Do abandoned farmlands promote spread of invasive alien plants? Change detection analysis of black wattle in montane grasslands of the Eastern Cape

ABSTRACTInvasive alien plants (IAPs) pose a threat to ecosystem integrity and generally provide more disservices than services. Acacia mearnsii (black wattle) was introduced to South Africa for its provisioning and economic potential. Since then, it has colonized large areas and it is a high priority taxon by the Working for Water (WfW) programme. This study establishes the nature of the spread of A. mearnsii in grasslands in the Eastern Cape Province of South Africa, with the aim of providing feedback to the WfW programme on IAP expansion and focal areas of concern. Land cover change detection analysis using historical aerial photographs showed that A. mearnsii has spread more extensively into disturbed (abandoned cultivation and overgrazed) grasslands compared to undisturbed natural grasslands from the initial plantings prior to 1958. Using the point-centred quarter method to determine density, and an allometric equation to determine above-ground biomass, a growth model for A. mearnsii was prepared. The incremental annual increase in the standing biomass of A. mearnsii using the model, validated against MODIS Net Primary Productivity data, was estimated to be ~10.5 ton DM ha−1 yr−1. The spread rate of wattle maybe up to 10% and several alternative control strategies need to be considered.

Spatial analysis of the impact of shrimp culture on the coastal wetlands on the Northern coast of Sinaloa, Mexico

In the Mexican coasts, as in many tropical and subtropical coastal areas, shrimp culture grew exponentially over the last three decades. This process has produced an intense debate on the economic benefits but also about the extent and intensity of the impact of this activity on the coastal ecosystems, particularly the effects of pond construction on mangrove areas and other coastal wetlands. For the Northern coast of Sinaloa (Northwest Mexico), a region where shrimp culture is actively practiced and reproduces most of the shrimp controlled production model in Mexico, a land cover change-detection analysis, with Landsat images, outputs that 75% of the shrimp farming in this region has been built on saltmarshes while less than 1% was constructed on mangrove areas. Through the estimation of landscape metrics for different scenarios (with and without shrimp culture infrastructure), we find that in addition to direct removal of saltmarshes, shrimp aquaculture has significantly modified the spatial patterns of coastal wetlands, retreating wetland borders and fragmenting their patches. These last impacts are mainly related with the development of the linear infrastructure associated with shrimp culture (drainage channels and roads), rather than the construction of the ponds. Present findings and other from similar studies done in Northwest Mexico; allow us to estimate that 60% of shrimp farming in Mexico impacted directly on saltmarshes, contrasting with the 3% of shrimp farms built on mangroves.

Application of Remote Sensing in Water Resource Management: The Case Study of Lake Trasimeno, Italy

Satellite multi-sensor data were used to investigate the evolution in time and space of Lake Trasimeno, a shallow and turbid lake in central Italy. Large-swath MERIS and MODIS sensors were proposed for regular broad scale monitoring of water quality, having compared the retrieved chlorophyll-a (Chl-a) concentration, Secchi disk (SD) depth and surface water temperature with the 2005–2008 time-series of the in situ data. Although, in a shorter time span, also the MERIS-derived total suspended matter (TSM) matched the in situ data. MERIS-derived water quality products confirmed the meso-eutrophic conditions of Lake Trasimeno (average Chl-a = 8.5 mg/m3) and the low levels of transparency (average SD = 1 m). A negative correlation found between water levels and Chl-a suggest the importance of maintaining water levels as close as possible to the hydrometric zero. A spatial analysis of TSM also reveals how small tributaries may affect the load of suspended solids in the southern part of the lake. Higher spatial resolution satellite images were exploited both to describe land use/cover transformation from 1978 to 2008 and to assess the recent changes in macrophyte colonisation patterns. Land cover change detection analysis results showed a decrease in cultivated areas starting from the early Nineties and the subsequent increase in unproductive terrain (bare land and pastures) and natural woods as well as the changing fragmentation of agricultural areas through time. A reduction in macrophyte beds from 2003 to 2008 was also observed. We expect the results of this study to support local water authorities in redrawing the management plan of Lake Trasimeno.