Impacts of LULC and climate change on streamflow in Netravati basin, Karnataka, India

2020 ◽  
Author(s):  
Dinu Maria Jose ◽  
Gowdagere Siddaramaiah Dwarakish
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Agricultural Intensification ◽  
Swat Model ◽  
Land Use Land Cover ◽  
Climate Variables ◽  
Landsat Images ◽  
Alos Palsar ◽  
Barren Land ◽  
Lulc Changes

<p>Human activities and climate affect the hydrology of a basin. The effect of Land Use Land Cover (LULC) change and climate change on streamflow are basin specific. In this study, an attempt has been made to evaluate the effects of LULC and climate change on streamflow in the Netravathi basin, Karnataka, India. The SWAT model, which reasonably simulates the streamflow of a basin, is used for this study. The analysis was done from the year 1990 to 2018. The watershed is delineated by using ALOS PALSAR DEM. Rainfall and temperature obtained from IMD are used as the climate variables. LULC maps were prepared using Landsat images of 1990 and 2018 in order to assess the LULC changes in the basin. The results showed that the spatial extent of the LULC classes of built-up (3.82%–6.51%), water bodies (0.76%–0.99%), and agriculture (11.96%–17.89%) increased, whereas that of forest (66.56%–51.7%), fallow (3.82%–6.13%), and barren land (13.07%–16.76%) decreased from 1990 to 2018. The streamflow increased steadily (5.02%) with changes in LULC from 1990 to 2018. The results indicate that LULC changes in urbanisation and agricultural intensification have contributed to the increase in runoff, in the catchment during this period. Thus, hydrological modelling integrating climate change and LULC can be used as an effective tool in estimating streamflow of the basin.</p>

scholarly journals Land Use Land Cover Changes and Their Effects on Surface Air Temperature in Myanmar and Thailand

2021 ◽  
Vol 13 (19) ◽  
pp. 10942
Author(s):  
Khun La Yaung ◽  
Amnat Chidthaisong ◽  
Atsamon Limsakul ◽  
Pariwate Varnakovida ◽  
Can Trong Nguyen
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Cover ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Forest Conversion ◽  
Land Use Land Cover ◽  
Forest Land ◽  
Lulc Changes ◽  
Average Maximum

Land use land cover (LULC) change is one of the main drivers contributing to global climate change. It alters surface hydrology and energy balance between the land surface and atmosphere. However, its impacts on surface air temperature have not been well understood in a dynamic region of LULC changes like Southeast Asia (SEA). This study quantitatively examined the contribution of LULC changes to temperature trends in Myanmar and Thailand as the typical parts of SEA during 1990–2019 using the “observation minus reanalysis” (OMR) method. Overall, the average maximum, mean, and minimum temperatures obtained from OMR trends indicate significant warming trends of 0.17 °C/10a, 0.20 °C/10a, and 0.42 °C/10a, respectively. The rates of minimum temperature increase were larger than maximum and mean temperatures. The decreases of forest land and cropland, and the expansions of settlements land fractions were strongly correlated with the observed warming trends. It was found that the effects of forest land converted to settlement land on warming were higher than forest conversion to cropland. A comprehensive discussion on this study could provide scientific information for the future development of more sustainable land use planning to mitigate and adapt to climate change at the local and national levels.

scholarly journals Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

2021 ◽  
Vol 13 (16) ◽  
pp. 3337
Author(s):  
Shaker Ul Din ◽  
Hugo Wai Leung Mak
Keyword(s):  
Land Use ◽  
Support Vector Machine ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land

Land-use/land cover change (LUCC) is an important problem in developing and under-developing countries with regard to global climatic changes and urban morphological distribution. Since the 1900s, urbanization has become an underlying cause of LUCC, and more than 55% of the world’s population resides in cities. The speedy growth, development and expansion of urban centers, rapid inhabitant’s growth, land insufficiency, the necessity for more manufacture, advancement of technologies remain among the several drivers of LUCC around the globe at present. In this study, the urban expansion or sprawl, together with spatial dynamics of Hyderabad, Pakistan over the last four decades were investigated and reviewed, based on remotely sensed Landsat images from 1979 to 2020. In particular, radiometric and atmospheric corrections were applied to these raw images, then the Gaussian-based Radial Basis Function (RBF) kernel was used for training, within the 10-fold support vector machine (SVM) supervised classification framework. After spatial LUCC maps were retrieved, different metrics like Producer’s Accuracy (PA), User’s Accuracy (UA) and KAPPA coefficient (KC) were adopted for spatial accuracy assessment to ensure the reliability of the proposed satellite-based retrieval mechanism. Landsat-derived results showed that there was an increase in the amount of built-up area and a decrease in vegetation and agricultural lands. Built-up area in 1979 only covered 30.69% of the total area, while it has increased and reached 65.04% after four decades. In contrast, continuous reduction of agricultural land, vegetation, waterbody, and barren land was observed. Overall, throughout the four-decade period, the portions of agricultural land, vegetation, waterbody, and barren land have decreased by 13.74%, 46.41%, 49.64% and 85.27%, respectively. These remotely observed changes highlight and symbolize the spatial characteristics of “rural to urban transition” and socioeconomic development within a modernized city, Hyderabad, which open new windows for detecting potential land-use changes and laying down feasible future urban development and planning strategies.

A novel toolkit to streamline Land Use Land Cover change assessment in the SWAT+ model to enhance flood management and infrastructure decisions

2021 ◽  
Author(s):  
Alex Rigby ◽  
Sopan Patil ◽  
Panagiotis Ritsos
Keyword(s):  
Land Use ◽  
Decision Support ◽  
Swat Model ◽  
Decision Support Tool ◽  
Flood Management ◽  
Land Use Land Cover ◽  
End User ◽  
Support Tool ◽  
Lulc Changes ◽  
Hydrological Impacts

<p>Land Use Land Cover (LULC) change is widely recognised as one of the most important factors impacting river basin hydrology.  It is therefore imperative that the hydrological impacts of various LULC changes are considered for effective flood management strategies and future infrastructure decisions within a catchment.  The Soil and Water assessment Tool (SWAT) has been used extensively to assess the hydrological impacts of LULC change.  Areas with assumed homogeneous hydrologic properties, based on their LULC, soil type and slope, make up the basic computational units of SWAT known as the Hydrologic Response Units (HRUs).  LULC changes in a catchment are typically modelled by SWAT through alterations to the input files that define the properties of these HRUs.  However, to our knowledge at least, the process of making such changes to the SWAT input files is often cumbersome and non-intuitive.  This affects the useability of SWAT as a decision support tool amongst a wider pool of applied users (e.g., engineering teams in environmental regulatory agencies and local authorities).  In this study, we seek to address this issue by developing a user-friendly toolkit that will: (1) allow the end user to specify, through a Graphical User Interface (GUI), various types of LULC changes at multiple locations within their study catchment, (2) run the SWAT+ model (the latest version of SWAT) with the specified LULC changes, and (3) enable interactive visualisation of the different SWAT+ output variables to quantify the hydrological impacts of these scenarios.  Importantly, our toolkit does not require the end user to have any operational knowledge of the SWAT+ model to use it as a decision support tool.  Our toolkit will be trialled at 15 catchments in Gwynedd county, Wales, which has experienced multiple occurrences of high flood events, and consequent economic damage, in the recent past.  We anticipate this toolkit to be a valuable addition to the decision-making processes of Gwynedd County Council for the planning and development of future flood alleviation schemes as well as other infrastructure projects.</p>

scholarly journals Land use/land cover change assessment of Mohana watershed (Far-Western Nepal) using GIS and remote sensing

2021 ◽  
Vol 6 (3) ◽  
pp. 320-328
Author(s):  
Suraj Prasad Bist ◽  
Rabindra Adhikari ◽  
Raju Raj Regmi ◽  
Rajan Subedi
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Change ◽  
Forest Cover ◽  
Agricultural Land ◽  
Water Bodies ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Barren Land ◽  
Gis And Remote Sensing

The present study was conducted in the Mohana watershed of Far-western Nepal to assess land use land cover change. The study has used ArcGIS and three Landsat images - Landsat TM (1999), Landsat ETM+ (2009), and Landsat OLI (2019) – to analyze land use the land cover change of the watershed. The change matrix technique was used for change detection analysis. The study area was classified into five classes; forest, agriculture, built-up, water bodies, and barren lands. The study has found that among the five identified classes forest and build-up increased positively from 45.40 % to 51.51 % - forest cover and 11.26 % to 19. 85 % - build-up respectively. Similarly, agricultural land and water bodies initially increased but after 2009 both land cover areas decreased to 23.79 % and 0.73 % from 31.38 % and 0.97 % in 2009 respectively. Barren land decreased from 15.37% to 4.12% over the last 20 years. This study might support land-use planners and policymakers to adopt the best suitable land use management option for the Mohana watershed.

scholarly journals Land Use Land Cover Change Analysis in Fagge Local Government, Kano State from 1991-2019

2020 ◽  
Author(s):  
Al-amin Abbas Ahmad
Keyword(s):  
Land Use ◽  
Local Government ◽  
Land Cover ◽  
Driving Forces ◽  
Urban Expansion ◽  
Land Use Land Cover ◽  
Economic Activities ◽  
Landsat Images ◽  
Change Analysis ◽  
Barren Land

Abstract Land Use and Land Cover (LULC) are important components of the environmental system and changes in it mirror the impacts of human activities on the environment. These impacts needed to be determined in order to get a clear picture of the extent at which different land use practices change over time. This study focused on the Land use and land cover changes of Fagge local government Kano state between 1991 and 2019 and also identify the driving forces of such changes. The data for the study two 30m x 30m Landsat images (Landsat 4&8) of the two years i.e. 2019 and 1991. The two images undergo series of image analysis and classification using ArcGIS 10.7 and ENVI 5.1 and the result where presented in form of maps, charts and tables. The result also shows that the changes that occurred from 1991 to 2019 in Fagge local government to be positive and negative changes. There happen to be a positive in the size of built-up areas in Fagge from 1991 – 2019 with a change of +4.678km2. The vegetation cover experienced a negative change of -8.87km2 while the barren land also had an increase in size with a positive change of +4.199. The data collected from previous studies indicated that the main driving behind the various changes may include; urban expansion, population growth, commercial and economic activities, security, and Government law and policies. It was recommended that Sufficient land use/land cover information should be acquired, Sensitization programs on land use / land cover, Geospatial techniques should be adopted by Government and NGO’s and lastly Government policies should geared to ensuring that there is balance in the utilization of the available land in the country

scholarly journals LAND USE/LAND COVER CHANGE PREDICTION USING MULTI-TEMPORAL SATELLITE IMAGERY AND MULTI-LAYER PERCEPTRON MARKOV MODEL

2020 ◽  
Vol XLIV-3/W1-2020 ◽  
pp. 99-105
Author(s):  
H. T. T. Nguyen ◽  
T. A. Pham ◽  
M. T. Doan ◽  
P. T. X. Tran
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Agricultural Land ◽  
Land Use Land Cover ◽  
Multi Layer Perceptron ◽  
Time Data ◽  
Landsat Images ◽  
Lulc Changes ◽  
The Future ◽  
Over Time

Abstract. This paper aims to predict the trend of land use land cover (LULC) changes in Dak Nong province over time. Data from Landsat images captured in 2009, 2015, and 2018 was employed to analyze and predict the spatial distributions of LULC categories. The Random Forest (RF) was adopted to classify the images into ten different LULC classes. Besides, integration of Multi-Layer Perceptron Markov Neural Network (MLP-NN) with Markov Chain (MC) was applied to predict the future LULC changes in the region based on the change detection over the previous years. For all classified images, overall accuracy (OA) ranged from 77.35% to 84.55% with kappa (K) coefficient index ranging from 0.75 to 0.8. The results revealed that the annual population growth together with social-economic development was regarded as major drives for land conversion in the area. The predicted map showed a significant decrease trend inthe forest classes by 2025, accounting for 23 thousand ha. However, residential areas, rubber, and agricultural land classes are predicted to rise to 460 ha, 3,000 ha, and 20,000 ha, respectively. The simulated model and calibrated area data may be a vital contribution to sustainable development efforts of the local based on the dynamics of LULC and future LULC change scenarios. Overall, ascertaining the complex interface related to changes in land use and its major drivers over time provides useful information predict to explore the future trend of LULC changes, establish alternative land-use schemes and serve as guidelines for urban planning policymakers.

scholarly journals Land Use/Land Cover Changes Impact on Groundwater Level and Quality in the Northern Part of the United Arab Emirates

2020 ◽  
Vol 12 (11) ◽  
pp. 1715 ◽  
Author(s):  
Samy Elmahdy ◽  
Mohamed Mohamed ◽  
Tarig Ali
Keyword(s):  
Land Use ◽  
Land Cover ◽  
United Arab Emirates ◽  
Groundwater Level ◽  
Integrated Approach ◽  
Support Vector ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Lulc Changes ◽  
Gis Environment

This study aims to develop an integrated approach for mapping and monitoring land use/land cover (LULC) changes and to investigate the impacts of LULC changes and population growth on groundwater level and quality using Landsat images and hydrological information in a Geographic information system (GIS) environment. All Landsat images (1990, 2000, 2010, and 2018) were classified using a support vector machine (SVM) and spectral analysis mapper (SAM) classifiers. The result of validation metrics, including precision, recall, and F1, indicated that the SVM classier has a better performance than SAM. The obtained LULC maps have an overall accuracy of more than 90%. Each pair of enhanced LULC maps (1990–2000, 2000–2010, 2010–2018, and 1990–2018) were used as input data for an image difference algorithm to monitor LULC changes. Maps of change detection were then imported into a GIS environment and spatially correlated against the spatiotemporal maps of groundwater level and groundwater quality. The results also show that the approximate built-up area increased from 227.26 km2 (1.39%) to 869.77 km2 (7.41%), while vegetated areas (farmlands, parks and gardens) increased from about 76.70 km2 (0.65%) to 290.70 km2 (2.47%). The observed changes in LULC are highly linked to the depletion in groundwater level and quality across the study area from the Oman Mountains to the coastal areas.

scholarly journals Land Use/Land Cover Changes and Their Driving Factors in the Northeastern Tibetan Plateau Based on Geographical Detectors and Google Earth Engine: A Case Study in Gannan Prefecture

2020 ◽  
Vol 12 (19) ◽  
pp. 3139
Author(s):  
Chenli Liu ◽  
Wenlong Li ◽  
Gaofeng Zhu ◽  
Huakun Zhou ◽  
Hepiao Yan ◽  
...  
Keyword(s):  
Land Use ◽  
Tibetan Plateau ◽  
Land Cover ◽  
Google Earth ◽  
Driving Factors ◽  
Optical Remote Sensing ◽  
Land Use Land Cover ◽  
Landsat Images ◽  
Lulc Changes ◽  
Google Earth Engine

As an important production base for livestock and a unique ecological zone in China, the northeast Tibetan Plateau has experienced dramatic land use/land cover (LULC) changes with increasing human activities and continuous climate change. However, extensive cloud cover limits the ability of optical remote sensing satellites to monitor accurately LULC changes in this area. To overcome this problem in LULC mapping in the Ganan Prefecture, 2000–2018, we used the dense time stacking of multi-temporal Landsat images and random forest algorithm based on the Google Earth Engine (GEE) platform. The dynamic trends of LULC changes were analyzed, and geographical detectors quantitatively evaluated the key driving factors of these changes. The results showed that (1) the overall classification accuracy varied between 89.14% and 91.41%, and the kappa values were greater than 86.55%, indicating that the classification results were reliably accurate. (2) The major LULC types in the study area were grassland and forest, and their area accounted for 50% and 25%, respectively. During the study period, the grassland area decreased, while the area of forest land and construction land increased to varying degrees. The land-use intensity presents multi-level intensity, and it was higher in the northeast than that in the southwest. (3) Elevation and population density were the major driving factors of LULC changes, and economic development has also significantly affected LULC. These findings revealed the main factors driving LULC changes in Gannan Prefecture and provided a reference for assisting in the development of sustainable land management and ecological protection policy decisions.

Analysis of Land Use Land Cover in Annapurna Conservation Area in Gandaki Province, Nepal using Vegetation Index and Land Use Land Cover Datasets

2019 ◽  
Vol 2 (2) ◽  
pp. 87-99
Author(s):  
Shiva Pokhrel ◽  
Chungla Sherpa
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Index ◽  
National Level ◽  
Climate Mitigation ◽  
Land Use Land Cover ◽  
Conservation Area ◽  
Barren Land ◽  
Wide Range ◽  
Annapurna Conservation Area

Conservation areas are originally well-known for protecting landscape features and wildlife. They are playing key role in conserving and providing a wide range of ecosystem services, social, economic and cultural benefits as well as vital places for climate mitigation and adaptation. We have analyzed decadal changes in land cover and status of vegetation cover in the conservation area using both national level available data on land use land cover (LULC) changes (1990-2010) and normalized difference vegetation index (NDVI) (2010-2018) in Annapurna conservation area. LULC showed the barren land as the most dominant land cover types in all three different time series 1990, 2000 and 2010 with followed by snow cover, grassland, forest, agriculture and water body. The highest NDVI values were observed at Southern, Southwestern and Southeastern part of conservation area consisting of forest area, shrub land and grassland while toward low to negative in the upper middle to the Northern part of the conservation area.

scholarly journals Investigating impact of land-use and land cover changes on hydro-ecological balance using GIS: insights from IIT Bombay, India

2021 ◽  
Vol 3 (3) ◽  
Author(s):  
Aman Srivastava ◽  
Pennan Chinnasamy
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Runoff ◽  
Forest Cover ◽  
Google Earth ◽  
Negative Consequences ◽  
Ecological Stability ◽  
Barren Land ◽  
Ecological Balance ◽  
Lulc Changes

AbstractThe present study, for the first time, examined land-use land cover (LULC), changes using GIS, between 2000 and 2018 for the IIT Bombay campus, India. Objective was to evaluate hydro-ecological balance inside campus by determining spatio-temporal disparity between hydrological parameters (rainfall-runoff processes), ecological components (forest, vegetation, lake, barren land), and anthropogenic stressors (urbanization and encroachments). High-resolution satellite imageries were generated for the campus using Google Earth Pro, by manual supervised classification method. Rainfall patterns were studied using secondary data sources, and surface runoff was estimated using SCS-CN method. Additionally, reconnaissance surveys, ground-truthing, and qualitative investigations were conducted to validate LULC changes and hydro-ecological stability. LULC of 2018 showed forest, having an area cover of 52%, as the most dominating land use followed by built-up (43%). Results indicated that the area under built-up increased by 40% and playground by 7%. Despite rapid construction activities, forest cover and Powai lake remained unaffected. This anomaly was attributed to the drastically declining barren land area (up to ~ 98%) encompassing additional construction activities. Sustainability of the campus was demonstrated with appropriate measures undertaken to mitigate negative consequences of unwarranted floods owing to the rise of 6% in the forest cover and a decline of 21% in water hyacinth cover over Powai lake. Due to this, surface runoff (~ 61% of the rainfall) was observed approximately consistent and being managed appropriately despite major alterations in the LULC. Study concluded that systematic campus design with effective implementation of green initiatives can maintain a hydro-ecological balance without distressing the environmental services.

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