Land use and land cover change dynamics and prediction scenario in the Mahananda River basin: insights into environmental transformations.

Land use land cover (LULC) changes resulting from copper exploration in Kitwe District, Copperbelt Province has adversely impacted the environment. To understand LULC change dynamics associated with mining activities, this study mapped LULC changes using the Google Earth Engine (GEE) from 1990 to 2020. In addition, the Zambian legal framework for mine closure was assessed in terms of adequacy and comprehensiveness. A remote sensing analysis using Landsat TM (1990, 2000, and 2010) and OLI (2020) images was performed and the GEE Random Forest classifier algorithm was employed to detect LULC changes. Then, transition matrices and overall changes were calculated for each LULC class. The LULC classification had an overall accuracy and kappa coefficient of 82.47% and 0.78, respectively. In total, 45.2% of the district area (360.92 km2) experienced LULC changes from 1990 to 2020. The overall change indicates that the areas of built-up area, bare land, and grassland/pasture/agricultural land gained 35.84, 14.67, and 43.53 km2, respectively, while forest lost 95.30 km2, with the major driver being the privatization of mining companies. Several concerns regarding the mine closure process practiced in Zambia have principally been raised to the government. Although the legislation generally conformed to international best practices, a gap involving various pieces of legislation, overlapping requirements, and different interpretations of the laws by different governmental departments makes the system complex and unmanageable. An area of concern is the government’s capability and competence to implement legislation. Ineffective law enforcement, that is, the inadequacy of the legislation, is to blame for LULC changes in mining areas, resulting in mining corporations not paying attention to the changes made, particularly regarding mine closures. This study provides decision-makers and land use planners with baseline knowledge on LULC changes that can be valuable for future mining legislation and how these legislations can be effectively executed to ensure sustainable mine closure.

Land Use Land Cover (LULC) changes analysis is one of the most useful methodologies to understand how the land was used in the past years, what types of detections are to be expected in the future, as well as the driving forces and processes behind these changes. In Ethiopia, Africa, the rapid variations of LULC observed in the last decades are mainly due to population pressure, resettlement programs, climate change, and other human- and nature-induced driving forces. Anthropogenic activities are the most significant factors adversely changing the natural status of the landscape and resources, which exerts unfavourable and adverse impacts on the environment and livelihood. The main goal of the present work is to review previous studies, discussing the spatiotemporal LULC changes in Ethiopian basins, to find out common points and gaps that exist in the current literature, to be eventually addressed in the future. A total of 25 articles, published from 2011 to 2020, were selected and reviewed, focusing on LULC classification using ArcGIS and ERDAS imagine software by unsupervised and maximum likelihood supervised classification methods. Key informant interview, focal group discussions, and collection of ground truth information using ground positioning systems for data validation were the major approaches applied in most of the studies. All the analysed research showed that, during the last decades, Ethiopian lands changed from natural to agricultural land use, waterbody, commercial farmland, and built-up/settlement. Some parts of forest land, grazing land, swamp/wetland, shrubland, rangeland, and bare/ rock out cropland cover class changed to other LULC class types, mainly as a consequence of the increasing anthropogenic pressure. In summary, these articles confirmed that LULC changes are a direct result of both natural and human influences, with anthropogenic pressure due to globalisation as the main driver. However, most of the studies provided details of LULC for the past decades within a specific spatial location, while they did not address the challenge of forecasting future LULC changes at the watershed scale, therefore reducing the opportunity to develop adequate basin-wide management strategies for the next years.

This paper discusses results of a Gulf of Mexico Application Pilot project conducted in 2008 to quantify and assess land use land cover (LULC) change from 1974 to 2008. Led by NASA Stennis Space Center, this project involved multiple Gulf of Mexico Alliance (GOMA) partners, including the Mobile Bay National Estuary Program (NEP), the U.S. Army Corps of Engineers, the National Oceanic and Atmospheric Administration's (NOAA's) National Coastal Data Development Center (NCDDC), and the NOAA Coastal Services Center. The Mobile Bay region provides great economic and ecologie benefits to the Nation, including important coastal habitat for a broad diversity of fisheries and wildlife. The Mobile Bay region has experienced considerable LULC change since the latter half of the 20th century. Accompanying this change has been urban expansion and a reduction of rural land uses. Much of this LULC change (largely urbanization) has reportedly occurred since the landfall of Hurricane Frederic in 1979. Regional urbanization threatens the estuary's water quality and aquatic-habitat dependent biota, including commercial fisheries and avian wildlife. Coastal conservation and urban land use planners require additional information on historical LULC change to support coastal habitat restoration and resiliency management efforts. This project quantified and assessed LULC change across the 34-year time frame and at decadal and mid-decadal scales. Nine Landsat images were employed to compute LULC products because of their availability and suitability for the application. The project also used Landsat-based national LULC products, including coastal LULC products from NOAA's Coastal Change & Analysis Program (C-CAP), available at 5-year intervals since 1995. Our study was initiated in part because C-CAP LULC products were not available to assess the region's urbanization prior to 1995 and subsequent to post-Hurricane Katrina in 2006. The study area included the majority of Mobile and Baldwin counties that encompass Mobile Bay. Each date of Landsat data was classified using an end-user defined modified Anderson level 1 classification scheme. LULC classifications were refined using a decision rule approach in conjunction with available C-CAP products. Individual dates of LULC classifications were validated by image interpretation of stratified random locations on raw Landsat color composite imagery in combination with higher resolution remote sensing and in situ reference data. Overall classification accuracies for five separate single-date products ranged from 83% to 89%. The results of the LULC change analysis indicate that during the 34-year study period, urban areas increased from 96,688 to 150,227 acres, representing a 55.37% increase, or 1.63% per annum. Most of the identified urban expansion regarded the conversion of rural forest and agriculture to urban cover types. Final LULC mapping and metadata products were produced for the entire study area as well as for multiple watersheds of concern within the study area. The final project products, including LULC trend information, were incorporated into the Mobile Bay NEP State of the Bay report. Products and metadata were also transferred to NOAA NCDDC to allow free online accessibility and use by GOMA partners and by the public.


 
 
 Floods are one of the most common natural disasters worldwide. Apart from rainfall, Land Use Land Cover (LULC) changes too are a main contributory factor for floods. This study attempted to understand the link between floods and LULC changes in Kalu river basin, which is the second largest river basin and an area that experiences recurrent floods in Sri Lanka. We studied peak water levels, number of flood events, changes in land use types and impacts in rapidly urbanizing two districts, Rathnapura (upper basin) and Kalutara (lower basin) during 2001-2020. The satellite images (LANDSAT) were obtained for 2001, 2009, 2015 and 2020 and land use classification was done using ArcGIS and Remote Sensing Tools. Main land use types and their transformations were investigated and ground-truthing was carried out. Accordingly, the main types of land uses identified were Natural Vegetation and forests (NV), Settlements (ST- housing and industrial lands), Cultivated Lands (CL), Water Bodies (WB) and Bare Lands (BL). The results indicated that the most drastic change was found in the natural areas (NV) and they have diminished while the lands with anthropogenic impacts (ST, CL and BL) have increased across years. The NV had occupied the highest land area in 2001 (42.4%) and has reduced by 14.2% by 2020. The ST and CL have increased by 8.6 % and 5.2% respectively. The monthly rainfall of Rathnapura and Kalutara (Source: Department of Meteorology, Sri Lanka) has increased with time, which is a main reason for the increasing peak water levels of these areas (Source: Department of Irrigation, Sri Lanka). However, a significant correlation also exists between the change of the settlement area with the peak river water levels in the lower basin (p=0.03, R2=99%; regression analysis). Rathnapura has experienced 3 major floods (floods above the high water alert level) from 2001-2020, while 16 major floods have occurred in Kalutara. During the major flood in 2017, the number of child deaths in Rathnapura was 14 while in Kalutara it was 24. Accordingly, the LULC changes of the whole basin along with rainfall seem to influence on the severity of floods in Kalutara more, as it is located in the lowest elevation level. When natural lands are transformed to anthropogenic- impacted areas with disturbances to the water cycle, increased impervious surfaces, reduced water storage capacities and loss of natural drainage, the flood risk tends to increase. Proactive approaches including proper land use planning and rainwater storage are urgently needed as the climate change too would trigger more floods. Thus, the flood mitigatory actions, especially, in the lower river basin should be a priority to ensure resilience and sustainability.
 Keywords: Kalu river basin, Land Use Land Cover (LULC) changes, Floods
 
 

Land use land cover (LULC) changes are inherently spatial and dynamic with high spatiotemporal variability resulted from complex human-environmental interactions. Current extents, rates and intensities of LULC changes are driving unprecedented changes in ecosystems functions and environmental processes at local, regional and global scales. The study was conducted to assess LULC changes and its drivers using remote sensing (RS) and geographic information system (GIS) in Gojeb River Catchment, Ethiopia. The satellite images at different reference years (1978, 1987, 2001 and 2015) were obtained from Landsat images. Supervised classification with maximum likelihood algorithm was applied for image processing and change analysis. The LULC classes identified were cropland, forestland, shrubland, swamp, and woodland. The study found that the catchment has undergone significant LULC changes. The major changes were expansion of cropland at the expense of other LULC classes at the rate of 29.56% in 1978, 38.91% in 1987, 46.62% in 2001 and 52.74% in 2015. It has gained about 160,736.08 ha with an annual average increment of 4,344.22 ha. Conversely, forestland has undergone reductions at an annual rate of 9,030.0 ha between 1978 and 1987. The conversions of other classes to cropland are mainly associated with more demand for crop production. On the other hand, the conversion of relevant part of forest land to other classes could be due to vegetation degradation. Hence, the conversion of forestland to other land use classes could be attributed to the highly demand of agricultural land, firewood, charcoal, timbers and housing materials. The major driving forces which should be considered in sustainable watershed management were population growth and government induced settlements. Provision of modern alternative sources of energy, agricultural inputs and promoting non-agricultural sectors are also other considerations for the community sustainable livelihood. It is critical to follow holistic view and management of the catchment for successful integrated watershed management endeavours.

The process of spatiotemporal changes in land use land cover (LULC) and predicting their future changes are highly important for LULC managers. one of the most important challenges in LULC studies is considered to be the creation of simulation of future change in LULC that involve spatial modeling. the purpose of this study is to use GIS and remote sensing to classify LULC classes in Duhok district between 1999 and 2018, and their results calculated using an integrated cellular automaton and ca-markov chain model to simulate LULC changes in 2033. in this study, satellite images from landsat7 ETM and landsat8 oli used for Duhok district which is located in the northern part of Iraq obtained from united states geological survey (USGS) for the periods (1999 and 2018) analyzed using remote sensing and GIS techniques in addition to the ground control points, for each class 60 ground points have taken. to simulate future LULC changes for 2033, integrated approaches of cellular automata and ca-markov models utilized in Idrisi selva software. the outcomes demonstrate that Duhok district has experienced a total of 184.91km changes during the period (table 4). the prediction also indicates that the changes will equal to 235.4 km by 2033 (table 8). soil and grass constitute the majority of changes among LULC classes and are increasing continuously. the achieved kappa values for the model accuracy assessment higher than 0.93 and 0.85 for 1999 and 2018 respectively showed the model’s capability to forecast future LULC changes in Duhok district. thus, analyzing trends of LULC changes from past to now and predict future applying ca-markov model can play an important role in land use planning, policy making, and managing randomly utilized LULC classes in the proposed study area.

Satellite remote sensing and geographic information system (GIS) have revolutionalized the mapping, quantifying, and assessing the land surface processes, particularly analyzing the past and future land use-land cover (LULC) change patterns. Worldwide river basins have observed enormous changes in the land system dynamics as a result of anthropogenic factors such as population, urbanization, development, and agriculture. As is the scenario of various other river basins, the Brahmaputra basin, which falls in China, Bhutan, India, and Bangladesh, is also witnessing the same environmental issues. The present study has been conducted on the Brahmaputra Valley in Assam, India (a sub-basin of the larger Brahmaputra basin) and assessed its LULC changes using a maximum likelihood classification algorithm. The study also simulated the changing LULC pattern for the years 2030, 2040, and 2050 using the GIS-based cellular automata Markov model (CA-Markov) to understand the implications of the ongoing trends in the LULC change for future land system dynamics. The current rate of change of the LULC in the region was assessed using the 48years of earth observation satellite data from 1973 to 2021. It was observed that from 1973 to 2021, the area under vegetation cover and water body decreased by 19.48 and 47.13%, respectively. In contrast, cultivated land, barren land, and built-up area increased by 7.60, 20.28, and 384.99%, respectively. It was found that the area covered by vegetation and water body has largely been transitioned to cultivated land and built-up classes. The research predicted that, by the end of 2050, the area covered by vegetation, cultivated land, and water would remain at 39.75, 32.31, and 4.91%, respectively, while the area covered by built-up areas will increase by up to 18.09%. Using the kappa index (ki) as an accuracy indicator of the simulated future LULCs, the predicted LULC of 2021 was validated against the observed LULC of 2021, and the very high ki observed validated the generated simulation LULC products. The research concludes that significant LULC changes are taking place in the study area with a decrease in vegetation cover and water body and an increase of area under built-up. Such trends will continue in the future and shall have disastrous environmental consequences unless necessary land resource management strategies are not implemented. The main factors responsible for the changing dynamics of LULC in the study area are urbanization, population growth, climate change, river bank erosion and sedimentation, and intensive agriculture. This study is aimed at providing the policy and decision-makers of the region with the necessary what-if scenarios for better decision-making. It shall also be useful in other countries of the Brahmaputra basin for transboundary integrated river basin management of the whole region.

Quantification of Land Use Land Cover (LULC) change influence river basin on hydrology will enable local government and policy makers to formulate and implement effective and appropriate strategies to minimize the effect of future LULC change. In this research Soil and Water Assessment Tool (SWAT) with Sequential Uncertainty Fitting Intervals (SUFI-2) was used for analyzing the LULC changes on the Water balance of Katar and Meki River Basins, in the Rift Valley of Ethiopia. LULC map of 1996 and 2014 was used for the change analysis and the results revealed that the reduction of Forest and expansion of Agriculture and Built-up areas have an influence on the surface water spatial distribution and the water balance components. During the land use change periods, the increment of annual surface runoff from 67.54 mm to 129.14 mm has resulted from Katar river basin and 40.64 mm to 59.56 mm has resulted from Meki river basins. This result has revealed that the above land use changes are the main contributors to the increment of surface runoff on both river basins. With this regard, major changes from the Forested region on both river basins have resulted in runoff depth increment. Forexample, runoff depth increment of 4-53 mm to 10-65 mm on Katar river basin and 2-34 mm to 23-60 mm range from Meki river basin mainly from forested regions resulted. Therefore, LULC change is becoming a serious threat to Katar and Meki river basin, hence appropriate measures should have to be taken for the stabilization of the land cover change with the regional development plan. Furthermore, the outcome of this study serves for policymakers as a valuable information for the planning of best land management strategies and priorities for the region.

Climate change and land use land cover (LULC) changes are recognised as two of the most significant causes of environmental change. Climate change and LULC changes are related to one another. Land use change may drive climate change, and a changing climate may result in land cover changes. Climate change and LULC changes are believed to influence soil erosion. This chapter analyses the impacts of climate and LULC changes on soil erosion. The causes and effects of climate change on precipitation, temperature, solar radiation, atmospheric CO2 concentrations, and radiative forcing are discussed. The chapter includes the impacts of climate change on soil characteristics, vegetation cover, runoff, floods, and droughts and extends the impacts of these changes on water and wind erosion. The chapter explores the human alterations of LULC changes in terms of changes in the forest cover, alterations in agricultural lands, increase in urban areas, and decrease in wetland areas. The influence of the LULC changes on soil erosion and sediment production processes is discussed. Also, the combined impact of climate and LULC changes on soil erosion is explored, and mitigation strategies like sustainable land management practices and appropriate policy incentives to conserve soil are discussed.

<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>

In developing countries, examining land use land cover (LULC) change pattern is crucial to understanding the land surface temperature (LST) effect as urban development lacks coherent policy planning. The variability in LST is often determined by continuously changing LULC patterns. In this study, LULC change effect analysis on LST has been carried out using geometric and radiometric corrected thermal bands of multi-spectral Landsat 7 ETM + and 8 TIRS/OLI satellite imagery over Gandhinagar, Gujarat, in the years 2001 and 2022, respectively. Maximum likelihood classification (MLC) was applied to assess LULC change while an NDVI-based single-channel algorithm was used to retrieve LST using Google Earth Engine (GEE). Results showed a substantial change in built-up (+ 347.08%), barren land (- 50.74%), and vegetation (- 31.66%). With the change in LULC and impervious surfaces, the mean LST has increased by 5.47 ℃. The impact of sparse built-up was seen on vegetation and agriculture as a maximum temperature of > 47 ℃ was noticed in all LULC classes except agriculture, where the temperature reached as high as > 49 ℃ in 2022. Since Gandhinagar is developing a twin-city plan with Ahmedabad, this study could be used as a scientific basis for sustainable urban planning to overcome dynamic LULC change and LST impacts.

Understanding trends of land use land cover (LULC) changes is important for biodiversity monitoring and conservation planning, and identifying the areas affected by change and designing sustainable solutions to reduce the changes. The study aims to evaluate and quantify the historical changes in land use and land cover in Mukumbura (Ward 2), Mt Darwin, Zimbabwe, from 2002 to 2022. The objective of the study was to analyse the LULC changes in Ward 2 (Mukumbura), Mt Darwin, Northern Zimbabwe, for a period of 20 years using geospatial techniques. Landsat satellite images were processed using Google Earth Engine (GEE) and the supervised classification with maximum likelihood algorithm was employed to generate LULC maps between 2002 and 2022 with a five (5) year interval, investigating the following variables, forest cover, barren land, water cover and the fields. Findings revealed a substantial reduction in forest cover by 38.8%, water bodies (wetlands, ponds, and rivers) declined by 55.6%, whilst fields (crop/agricultural fields) increased by 93.3% and the barren land cover increased by 26.3% from 2002 to 2022. These findings point to substantial changes in LULC over the observed years. LULC changes have resulted in habitat fragmentation, reduced biodiversity, and the disruption of ecosystem functions. The study concludes that if these deforestation trends, cultivation, and settlement land expansion continue, the ward will have limited indigenous fruit trees. Therefore, the causes for LULC changes must be controlled, sustainable forest resources use practiced, hence the need to domesticate the indigenous fruit trees in arborloo toilets.

Ethiopia is a growing country which is in need of scientific ground for land use planning and agricultural-based economy. Evaluation of land use/land cover (LULC) changes helps for proper scheduling and use of natural resources with safe administration in accordance with time and dynamic population growth of the country, specifically in the study area. One of the detailed and useful ways to develop land use evaluation and classification maps is the use of geospatial techniques such as remote sensing and geographic information systems (GIS). The main focus of this study is to evaluate the dynamics of land use and land cover (LULC) changes in the Abelti Watershed, Omo-Gibe River basin, Ethiopia. Maximum likelihood algorithm approach supervised classification method was used for identifying the LULC changes using satellite data to know LULC changes in the watershed. Quantifications of spatial and temporal dynamics of land use/cover changes were accomplished by using three satellite images of 2000, 2010, and 2017 and classifying them via a supervised classification algorithm by using Earth Resources and Development System (ERDAS) software and finally applying the postclassification change detection technique was performed by using ArcGIS 10.3. From the LULC analysis, the increase was observed in the agricultural area and settlement area from 2000 to 2017. On the other hand, shrub land followed a declining trend during the study period. However, forest and bare land followed variable trends during the study period in which forest declined from 2000 to 2010 but increased from 2010 to 2017 and bare land increased from 2000 to 2010 and declined from 2010 to 2017. Generally, the driving force behind this change was population growth, rapid urbanization, and deforestation which resulted in a wide range of environmental impacts, including degraded habitat quality in the watershed.

Analysis of land use land cover change dynamics in Habru District, Amhara Region, Ethiopia

Quantifying smallholder farmers’ managed land use/land cover dynamics and its drivers in contrasting agro-ecological zones of the East African Rift