Investigating land use and land cover changes in Dublin, Ireland using Satellite Imagery: A comparative analysis

2020 ◽  
Author(s):  
Bidroha Basu ◽  
Arunima Sarkar Basu ◽  
Srikanta Sannigrahi ◽  
Francesco Pilla
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Population Growth ◽  
Satellite Imagery ◽  
Rainfall Runoff ◽  
Lulc Changes ◽  
The Past ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Over Time

<p>Over the past few decades, there has been over increasing pressure on land due to population growth, urbanization, agriculture expansion and industrialization. The change in land use and land cover (LULC) pattern are highly dependent on human intervention. Deforestation pattern has started due to growth of suburbs, cities, and industrial land. The alarming rate in change of LULC pattern was on a rising trend since 1990s and has been increasing over time. This study focuses on analyzing the changes in LULC pattern in Dublin, Ireland over the past two decades using remotely sensed LANDSAT satellite imagery data, and quantify the effect of LULC change in streamflow simulation in watershed at Dublin by using rainfall-runoff model. Benefit of using remotely sensed image to investigate LULC changes include availability of high-resolution spatial data at free of cost, images captured at high temporal resolution to monitor the changes in LULC during both seasonal and yearly timescale and readily availability of data. The potential classification of landforms has been done by performing both supervised as well as unsupervised classification. The results obtained from the classified images have been compared to google earth images to understand the accuracy of the image classification. The change in LULC can be characterized by changes in building density and urban/artificial area (build up areas increase due to population growth), changes in vegetation area as well as vegetation health, changes in waterbodies and barren land. Furthermore, a set of indices such as vegetation index, building index, water index and drought index were estimated, and their changes were monitored over time. Results of this analysis can be used to understand the driving factors affecting the changes in LULC and to develop mathematical models to predict future changes in landforms. Soil Water Assessment Tool (SWAT) based rainfall-runoff model were used to simulate the changes in runoff due to the LULC changes in watershed over two decades. The developed framework is highly replicable because of the used LANDSAT data and can be applied to generate essential information for conservation and management of green/forest lands, as well as changes in water availability and water stress in the assessed area.</p>

scholarly journals Impacts of Land Use and Land Cover Changes on Peak Discharge and Flow Volume in Kakia and Esamburmbur Sub-Catchments of Narok Town, Kenya

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 82
Author(s):  
Etienne Umukiza ◽  
James M. Raude ◽  
Simon M. Wandera ◽  
Andrea Petroselli ◽  
John M. Gathenya
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Curve Number ◽  
Peak Discharge ◽  
Land Use Land Cover ◽  
Flow Volume ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Event Based ◽  
Runoff Model

Due to population growth and an expanding economy, land use/land cover (LULC) change is continuously intensifying and its effects on floods in Kakia and Esamburmbur sub-catchments in Narok town, Kenya, are increasing. This study was carried out in order to evaluate the influence of LULC changes on peak discharge and flow volume in the aforementioned areas. The Event-Based Approach for Small and Ungauged Basins (EBA4SUB) rainfall–runoff model was used to evaluate the peak discharge and flow volume under different assumed scenarios of LULC that were projected starting from a diachronic analysis of satellite images of 1985 and 2019. EBA4SUB simulation demonstrated how the configuration and composition of LULC affect peak discharge and flow volume in the selected catchments. The results showed that the peak discharge and flow volume are affected by the variation of the Curve Number (CN) value that is dependent on the assumed LULC scenario. The evaluated peak discharge and flow volume for the assumed LULC scenarios can be used by local Municipal bodies to mitigate floods.

scholarly journals Geospatial assessment of land use and land cover dynamics in the mid-zone of Ghana

2020 ◽  
Vol 62 (4) ◽  
pp. 288-305
Author(s):  
Addo Koranteng ◽  
Isaac Adu-Poku ◽  
Emmanuel Donkor ◽  
Tomasz Zawiła-Niedźwiecki
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Forest Cover ◽  
Anthropogenic Activities ◽  
Arable Land ◽  
Rapid Urbanization ◽  
The Past ◽  
Open Forest

AbstractLand use and land cover (LULC) terrain in Ghana has undergone profound changes over the past years emanating mainly from anthropogenic activities, which have impacted countrywide and sub-regional environment. This study is a comprehensive analysis via integrated approach of geospatial procedures such as Remote Sensing (RS) and Geographic Information System (GIS) of past, present and future LULC from satellite imagery covering Ghana’s Ashanti regional capital (Kumasi) and surrounding districts. Multi-temporal satellite imagery data sets of four different years, 1990 (Landsat TM), 2000 (Landsat ETM+), 2010 (Alos and Disaster Monitoring Constellation-DMC) and 2020 (SENTINEL), spanning over a 30-year period were mapped. Five major LULC categories – Closed Forest, Open Forest, Agriculture, Built-up and Water – were delineated premised on the prevailing geographical settings, field study and remote sensing data. Markov Cellular Automata modelling was applied to predict the probable LULC change consequence for the next 20 years (2040). The study revealed that both Open Forest and Agriculture class categories decreased 51.98 to 38.82 and 27.48 to 20.11, respectively. Meanwhile, Built-up class increased from 4.8% to 24.8% (over 500% increment from 1990 to 2020). Rapid urbanization caused the depletion of forest cover and conversion of farmlands into human settlements. The 2040 forecast map showed an upward increment in the Built-up area up to 35.2% at the expense of other LULC class categories. This trend from the past to the forecasted future would demand that judicious LULC resolutions have to be made to keep Ghana’s forest cover, provide arable land for farming activities and alleviate the effects of climate change.

scholarly journals Formulation of Parsimonious Urban Flash Flood Predictive Model with Inferential Statistics

Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 175
Author(s):  
Lloyd Ling ◽  
Sai Hin Lai ◽  
Zulkifli Yusop ◽  
Ren Jie Chin ◽  
Joan Lucille Ling
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Flash Flood ◽  
Curve Number ◽  
Runoff Coefficient ◽  
Rainfall Runoff ◽  
Inferential Statistics ◽  
Moisture Condition ◽  
Antecedent Moisture ◽  
Runoff Model

The curve number (CN) rainfall–runoff model is widely adopted. However, it had been reported to repeatedly fail in consistently predicting runoff results worldwide. Unlike the existing antecedent moisture condition concept, this study preserved its parsimonious model structure for calibration according to different ground saturation conditions under guidance from inferential statistics. The existing CN model was not statistically significant without calibration. The calibrated model did not rely on the return period data and included rainfall depths less than 25.4 mm to formulate statistically significant urban runoff predictive models, and it derived CN directly. Contrarily, the linear regression runoff model and the asymptotic fitting method failed to model hydrological conditions when runoff coefficient was greater than 50%. Although the land-use and land cover remained the same throughout this study, the calculated CN value of this urban watershed increased from 93.35 to 96.50 as the watershed became more saturated. On average, a 3.4% increase in CN value would affect runoff by 44% (178,000 m3). This proves that the CN value cannot be selected according to the land-use and land cover of the watershed only. Urban flash flood modelling should be formulated with rainfall–runoff data pairs with a runoff coefficient > 50%.

scholarly journals Land-Use and Land-Cover (LULC) Change Detection in Wami River Basin, Tanzania

Land ◽  
2019 ◽  
Vol 8 (9) ◽  
pp. 136 ◽  
Author(s):  
Sekela Twisa ◽  
Manfred F. Buchroithner
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Population Growth ◽  
Change Detection ◽  
River Basin ◽  
Land Use Planning ◽  
Management Practice ◽  
Cultivated Land ◽  
Lulc Change ◽  
Lulc Changes

Anthropogenic activities have substantially changed natural landscapes, especially in regions which are extremely affected by population growth and climate change such as East African countries. Understanding the patterns of land-use and land-cover (LULC) change is important for efficient environmental management, including effective water management practice. Using remote sensing techniques and geographic information systems (GIS), this study focused on changes in LULC patterns of the upstream and downstream Wami River Basin over 16 years. Multitemporal satellite imagery of the Landsat series was used to map LULC changes and was divided into three stages (2000–2006, 2006–2011, and 2011–2016). The results for the change-detection analysis and the change matrix table from 2000 to 2016 show the extent of LULC changes occurring in different LULC classes, while most of the grassland, bushland, and woodland were intensively changed to cultivated land both upstream and downstream. These changes indicate that the increase of cultivated land was the result of population growth, especially downstream, while the primary socioeconomic activity remains agriculture both upstream and downstream. In general, net gain and net loss were observed downstream, which indicate that it was more affected compared to upstream. Hence, proper management of the basin, including land use planning, is required to avoid resources-use conflict between upstream and downstream users.

Goal and products of PAGES LandCover6k 2018-2020: Past Global Land Cover and Land Use for Climate Modelling

2020 ◽  
Author(s):  
Marie-Jose Gaillard ◽  
Andria Dawson ◽  
Ralph Fyfe ◽  
Esther Githumbi ◽  
Emily Hammer ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Carbon Cycle ◽  
Climate Model ◽  
Climate Modelling ◽  
Model Simulations ◽  
Lulc Changes ◽  
The Past ◽  
Per Capita ◽  
Past Land Use

<p>The question of whether prehistoric human impacts on land cover (i.e. anthropogenic land cover change due to land use, LULC) were sufficiently large to have a major impact on regional cli-mates is still a matter of debate. Climate model simulations have shown that LULC datasets can have large regional impacts on climate in recent and prehistoric time<sup> (1)</sup>. But there are major differences between the available LULC scenarios/datasets such as HYDE (History Database of the Global En-vironment) and Kaplan’s KK10 <sup>(2)</sup>, and diagnoses of inferred carbon-cycle impacts show that none of the scenarios are realistic <sup>(3)</sup>. The only way to provide a useful assessment of the potential for LULC changes to affect climate in the past, is to provide more realistic LULC data based on palaeovegetation and archaeological evidence to improve the LULC datasets used in climate modelling<sup>(4)</sup>. We use the REVEALS model to reconstruct LC from pollen data at a regional scale, and archaeological data to map LU types and distribution, and estimate per capita LU. The archaeology-based LU maps and per-capita LU estimates are used to improve LULC datasets. Pollen-based REVEALS LC estimates are then used to evaluate/validate the new, improved LULC datasets. These new datasets will be used to implement past land use in palaeoclimate and carbon cycle model simulations. Such simulations are necessary to assess the impact of LULC changes in the past and understand the effect of ecosys-tem management on future climate. We present results from five years of PAGES LandCover6k activities. </p><p>(1) Strandberg G, Kjellström E, Poska A, Wagner S, Gaillard M-J et al. (2014) Regional climate model sim-ulations for Europe at 6 and 0.2 k BP: sensitivity to changes in anthropogenic deforestation. Clim. Past 10, 661–680.<br>(2) Gaillard M-J, Sugita S, Mazier F et al (2010) Holocene land-cover reconstructions for studies on land cover-climate feedbacks. Clim. Past 6, 483-499.<br>(3) Stocker B, Yud Z, Massae C, Joos F (2017) Holocene peatland and ice-core data constraints on the tim-ing and magnitude of CO2 emissions from past land use. www.pnas.org/cgi/doi/10.1073/ pnas.1613889114.<br>(4) Harrison S P, Gaillard M-J, Stocker B D, Vander Linden M, Klein Goldewijk K, Boles O, Braconnot P, Dawson A, Fluet-Chouinard E, Kaplan J O, Kastner T, Pausata F S R, Robinson E, Whitehouse N J, Madella M, and Morrison K D (2019) Development and testing of scenarios for implementing Holocene LULC in Earth Sys-tem Model Experiments, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-125, in review, 2019.</p><p><sup> </sup></p><p> </p><p> </p>

scholarly journals Use of the KINFIL rainfall-runoff model on the Hukava catchment

2009 ◽  
Vol 4 (No. 1) ◽  
pp. 1-9
Author(s):  
P. Kovář ◽  
V. Kadlec
Keyword(s):  
Land Use ◽  
Land Use Changes ◽  
Practical Implementation ◽  
Rainfall Runoff ◽  
Flood Events ◽  
Event Duration ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Runoff Events ◽  
Small Catchments

The paper reports on the flood events on the forested Hukava catchment. It describes practical implementation of the KINFIL rainfall-runoff model. This model has been used for the reconstruction of the rainfall-runoff events and thus for the calibration of its parameters. The model was subsequently used to simulate the design discharges with an event duration of t<sub>d</sub> = 30, 60, and 300 min in the period of recurrence of 100 years, and during the scenario simulations of the land use change when 40% and 80% of the forest in the catchment had been cleared out and then replaced by permanent grasslands. The implementation of the KINFIL model supported by GIS proved to be a proper method for the flood runoff assessment on small catchments, during which different scenarios of the land use changes were tested.

scholarly journals The role of land use and morphology representation in the setup and calibration of the conceptual TUW model

2021 ◽  
Vol 906 (1) ◽  
pp. 012050
Author(s):  
Martiň Kubáň ◽  
Adam Brziak ◽  
Silvia Kohnová
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Type Model ◽  
Hydrological Models ◽  
Percentage Cover ◽  
Model Efficiency ◽  
Model Setup ◽  
Rainfall Runoff Model ◽  
Runoff Model

Abstract The processes of the transformation of rainfall to runoff are highly complicated, and the proper characterisation of these processes with conceptual hydrological models is a very challenging task. Morphology and land cover have a significant influence on a river basin’s hydrologic response. Thus, catchment characteristics of the topography and land use play an essential role in parametrising the runoff concentration processes in hydrological models. In the study, our goal was to detect which characteristics and their spatial distribution influence the efficiency of a conceptual rainfall-runoff model efficiency most. The spatially lumped and semi-distributed versions of the TUW conceptual rainfall model, which is an HBV type model, were compared. Both models use the concept of lumped storages associated with the surface and subsurface, interconnected by thresholds and links to simulate the runoff transformation. We focused on two land-use characteristics, the percentage cover of the agricultural land and percentage cover of the forests, and the mean slope of the terrain as a topography characteristic. The differences between runoff model efficiencies both in the calibration and validation periods were evaluated. Based on which version of the model was more effective in the simulation of the runoff, it was detected which types of catchment land use, and morphology were better represented by using the lumped or semi-distributed version of the TUW model, respectively. The analysis aimed to improve the understanding of the influence of spatial representation morphology and land cover in conceptual models on model efficiency and may help to improve model setup and calibration.

scholarly journals Understanding the effect of changing land use on floods and soil erosion in the Cagayan de Oro catchment

2021 ◽  
Author(s):  
◽  
Rubianca Benavidez
Keyword(s):  
Decision Making ◽  
Soil Erosion ◽  
Land Cover ◽  
The Philippines ◽  
Flood Mitigation ◽  
Baseline Scenario ◽  
Rainfall Runoff ◽  
Sediment Delivery ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>The destructive capability of typhoons affects lives and infrastructure around the world. Spatial analysis of historical typhoon records reveal an area of intense storm activity within the Southeast Asian (SEA) region. Within SEA is the Philippines, an archipelagic tropical country regularly struck by storms that often cause severe landslides, erosion and floods. Annually, ˜20 cyclones enter the Philippine Area of Responsibility, with about nine making landfall, causing high winds and intense rainfall. Thus, significant research in the Philippines has focused on increasing the resilience of ecosystems and communities through real-time disaster forecasting, structural protections, and programmes for sustainable watershed management (e.g. rehabilitation and conservation agriculture). This dissertation focused on the third aspect through computer modelling and scenario analysis.  The study area is the Cagayan de Oro (CDO) catchment (˜1400km²) located in the Southern Philippines. The catchment experienced heavy flooding in 2012 from Typhoon Bopha and has major erosion problems due to mountainous slopes and heavy rainfall. Communities derive ecosystem services (ES) including agricultural production, water supply, recreation, mining resources, flood mitigation, etc. Since changes to the supply or distribution of these ES affects livelihoods and the hydrological response of the catchment to typhoon events, this research used the Land Utilisation and Capability Indicator (LUCI) model to understand the baseline ES and potential changes associated with basin management plans.  This was the first detailed tropical application of LUCI, including parameterising it for Philippine soil and land cover datasets in CDO and extending its capability to be applied in future tropical areas. Aside from applying LUCI in a new geoclimatic region, this research contributed to the general development of LUCI through testing and improving its sediment delivery and inundation modelling. The sediment delivery was enhanced using the Revised Universal Soil Loss Equation (RUSLE) model that allows LUCI for the first time to account for impacts of specific land management such as agroforestry and contour cropping on erosion and sediment delivery. Progress was made in updating a flatwater inundation model for use with LUCI, including converting it to Python but this requires further development and testing before it is suitable for application in the Philippines.  The development and rehabilitation scenarios showed improved flood mitigation, lower surficial soil erosion rates, and lower loads of nutrients compared to the baseline scenario. Additionally, ES mapping under different land cover scenarios has not been previously accomplished in CDO, and this research provides useful information to guide local decision-making and management planning.   The rainfall-runoff model of LUCI was tested against the Hydrologic Engineering Center’s Hydrological Modelling System (HEC-HMS), showing good agreement with observed flow. Since the rainfall-runoff model of LUCI has been minimally utilised in past applications, this CDO application elucidated directions for future work around further testing under extreme rainfall events and climate change.  Overall, this novel application of LUCI creates a framework to assist decision-making around land cover changes in the CDO, provides guidance around data requirements and parameterisation procedures to guide future international applications, and has significantly contributed to development and improvement of the LUCI framework to extend its modelling capabilities in the future.</p>

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