Land Use Land Cover Analysis for Godavari Basin in Maharashtra Using Geographical Information System and Remote Sensing

The dynamic transformation of land use and land cover has emerged as a crucial aspect in the effective management of natural resources and the continual monitoring of environmental shifts. This study focused on the land use and land cover (LULC) changes within the catchment area of the Godavari River, assessing the repercussions of land and water resource exploitation. Utilizing LANDSAT satellite images from 2009, 2014, and 2019, this research employed supervised classification through the Quantum Geographic Information System (QGIS) software’s SCP plugin. Maximum likelihood classification algorithm was used for the assessment of supervised land use classification. Seven distinct LULC classes—forest, irrigated cropland, agricultural land (fallow), barren land, shrub land, water, and urban land—are delineated for classification purposes. The study revealed substantial changes in the Godavari basin’s land use patterns over the ten-year period from 2009 to 2019. Spatial and temporal dynamics of land use/cover changes (2009-2019) were quantified using three Satellite/Landsat images, a supervised classification algorithm and the post classification change detection technique in GIS. The total study area of the Godavari basin in Maharashtra encompasses 5138175.48 hectares. Notably, the built-up area increased from 0.14% in 2009 to 1.94% in 2019. The proportion of irrigated cropland, which was 62.32% in 2009, declined to 41.52% in 2019. Shrub land witnessed a noteworthy increase from 0.05% to 2.05% over the last decade. The key findings underscored significant declines in barren land, agricultural land, and irrigated cropland, juxtaposed with an expansion in forest land, shrub land, and urban land. The classification methodology achieved an overall accuracy of 80%, with a Kappa Statistic of 71.9% for the satellite images. The overall classification accuracy along with the Kappa value for 2009, 2014 and 2019 supervised land use land cover classification was good enough to detect the changing scenarios of Godavari River basin under study. These findings provide valuable insights for discerning land utilization across various categories, facilitating the adoption of appropriate strategies for sustainable land use in the region.

Assessment of Land Use Land Cover Change Detection Using Geospatial Techniques in Southeast Rajasthan

Change analysis acquires effective information in the form of maps and statistical data which becomes the central component in spatial planning, monitoring environmental changes, management and utilization of land. The present study makes an attempt to assess the changes in land use land cover using multi-temporal satellite data in south-east Rajasthan. These maps were derived from geocoded dia-positive False Color Composites (FCC’s) of IRS 1991, 2001, 2010 & 2018 using Arc GIS platform. The present study demonstrates the extension, approach and result of change analysis which might be helpful for decision making and sustainable growth. The landscape has been divided into 12 categories. Mining and its associated features were increased whereas forest and open scrub cover shows decreasing trend during the study period. The former increased by 23.82 km2 while the later shrunk by 26.08 km2. Most significant changes are also witnessed in settlement and industrial areas which shows increment by 8.8 km2 and 1.33 km2. Stone quarrying has destroyed arable land, natural vegetation cover, topsoil, subsoil and consequently the soil profile of the area. On the other hand cultivated land is increasing due to the conversion of uncultivated land and scrub cover with facilitation of irrigation and modern agricultural activities under different government schemes. The study shows that the area of 184.88 km2 has undergone significant spatial and temporal changes during the study period.

Land Use Land Cover Dynamics and Farmland Intensity Analysis at Ouahigouya Municipality of Burkina Faso,West Africa

Sahel zone has been reported as one of the most vulnerable regions to climate change, so serious attention must be paid to this zone by researchers and development actors who are interested in environmental-human dynamics and interactions. The aim of this study was to bring more insight into the impact of actions aiming at reducing land degradation, regreening the Sahel, stopping population migration and reducing the pressure on land in the Sahelian zone. The study focused on farmland dynamic in Ouahigouya municipality based on remote sensing data from 1986 to 2016 using intensity analysis. The annual time interval change was 0.77% and 2.46% for 1986-2001 and 2001-2016, respectively. Farmlands gained from mixt vegetation, water bodies and from bar lands. Mixed vegetation and water bodies were both active during both intervals while the other land use such as woodland and bar land were dormant. Combining land use land cover analysis and intensity analysis was found to be effective for assessing the differentiated impact of the various land restoration actions.

Land Use Land Cover Changes and Encroachment Issues in Kapkatet Wetland, Kenya

Kapkatet Wetland is a vital ecosystem in Kenya that supports rural livelihoods through the provision of various ecological goods and services. However, this ecosystem has been undergoing rapid degradation arising from competing land uses. It’s important to document these changes to obtain insights that can aid decision-making for effective restoration and conservation. This study, therefore, sought to assess the extent and patterns of land use and land cover changes in Kapkatet Wetland between 1986 and 2019, and their driving forces. The study followed a mixed-method research approach involving a combination of remote sensing and descriptive surveys. To quantify the wetland changes, remotely sensed imageries for 1986, 2000, and 2019 were utilized in classifying land use and land cover maps through the Maximum Likelihood algorithm. Household questionnaires and focus group discussions were used to obtain information about peoples’ perceptions of the driving forces of landscape change within the wetland. Results generally showed that Kapkatet wetland declined by 24.77% over the past years (1986-2019). Wetland vegetation declined drastically as open grounds increased while tree cover and disturbed reeds showed a fluctuating trend. These changes were majorly driven by land conversion activities within the wetland. The study recommends a community-based enforcement approach to existing laws and policies by both National and Local governments to curb the continuous loss of this wetland.

Spatiotemporal characteristics and driving mechanisms of land use/land cover(LULC)changes in the Jinghe River Basin,China

Understanding the trajectories and driving mechanisms behind land use/land cover(LULC)changes is essential for effective watershed planning and management.This study quantified the net change,exchange,total change,and transfer rate of LULC in the Jinghe River Basin(JRB),China using LULC data from 2000 to 2020.Through trajectory analysis,knowledge maps,chord diagrams,and standard deviation ellipse method,we examined the spatiotemporal characteristics of LULC changes.We further established an index system encompassing natural factors(digital elevation model(DEM),slope,aspect,and curvature),socio-economic factors(gross domestic product(GDP)and population),and accessibility factors(distance from railways,distance from highways,distance from water,and distance from residents)to investigate the driving mechanisms of LULC changes using factor detector and interaction detector in the geographical detector(Geodetector).The key findings indicate that from 2000 to 2020,the JRB experienced significant LULC changes,particularly for farmland,forest,and grassland.During the study period,LULC change trajectories were categorized into stable,early-stage,late-stage,repeated,and continuous change types.Besides the stable change type,the late-stage change type predominated the LULC change trajectories,comprising 83.31% of the total change area.The period 2010-2020 witnessed more active LULC changes compared to the period 2000-2010.The LULC changes exhibited a discrete spatial expansion trend during 2000-2020,predominantly extending from southeast to northwest of the JRB.Influential driving factors on LULC changes included slope,GDP,and distance from highways.The interaction detection results imply either bilinear or nonlinear enhancement for any two driving factors impacting the LULC changes from 2000 to 2020.This comprehensive understanding of the spatiotemporal characteristics and driving mechanisms of LULC changes offers valuable insights for the planning and sustainable management of LULC in the JRB.

Comprehending drivers of land use land cover change from 1999 to 2021 in the Pithoragarh District,Kumaon Himalaya,Uttarakhand,India

The Himalayan region has been experiencing stark impacts of climate change,demographic and livelihood pattern changes.The analysis of land use and land cover(LULC)change provides insights into the shifts in spatial and temporal patterns of landscape.These changes are the combined effects of anthropogenic and natural/climatic factors.The present study attempts to monitor and comprehend the main drivers behind LULC changes(1999-2021)in the Himalayan region of Pithoragarh district,Uttarakhand.Pithoragarh district is a border district,remotely located in the north-east region of Uttarakhand,India.The study draws upon primary and secondary data sources.A total of 400 household surveys and five group discussions from 38 villages were conducted randomly to understand the climate perception of the local community and the drivers of change.Satellite imagery,CRU(Climatic Research Unit)climate data and climate perception data from the field have been used to comprehensively comprehend,analyze,and discuss the trends and reasons for LULC change.GIS and remote sensing techniques were used to construct LULC maps.This multifaceted approach ensures comprehensive and corroborated information.Five classes were identified and formed viz-cultivation,barren,settlement,snow,and vegetation.Results show that vegetation and builtup have increased whereas cultivation,barren land,and snow cover have decreased.The study further aims to elucidate the causes behind LULC changes in the spatially heterogeneous region,distinguishing between those attributed to human activities,climate shifts,and the interconnected impacts of both.The study provides a comprehensive picture of the study area and delivers a targeted understanding of local drivers and their potential remedies by offering a foundation for formulating sustainable adaptation policies in the region.

Spatiotemporal detection of land use/land cover changes and land surface temperature using Landsat and MODIS data across the coastal Kanyakumari district, India

This study assesses the changes in land use/land cover(LULC) and land surface temperature(LST) to identify their impacts from 2000 to 2020 along the coast of Kanyakumari district, India using remote sensing techniques. Landsat images are used to estimate the LULC changes and the MODIS data for LST.The Maximum Likelihood Classification(MLC) method is used, and the LULC is classified into six categories: Agriculture Land, Barren Land, Salt Pan, Sandy Beach, Settlement, and Waterbody. Within the two decades of the present change detection study, upheave in the Settlement area of 49.89% is noticed, and the Agriculture Land is exploited by 20.09%. Salt Pan emits a high LST of 31.57°C, and the Waterbodies are noticed with a low LST of 28.9°C. However, the overall rate of LST decreased by 0.56°C during this period. This study will help policymakers make appropriate planning and management to overcome the impact of LULC and LST in the forthcoming years.

Land Use/Cover Change and Its Policy Implications in Typical Agriculture-forest Ecotone of Central Jilin Province,China

During the 21st century,policies toward agriculture,forestry,and urbanization have emerged to ensure food security,ecological restoration,and human well-being by managing land in Northeast China.However,the integrated effects and relationships of various policies are still not well understood.This study observed the land use land cover changes in Central Jilin from 2000 to 2019 and,by considering policy involvement,aimed to understand the effects and trade-offs of policies.Results showed that the cropland,including dryland and rice paddy,and the forest,including coniferous forest and deciduous forest,are dominant land types in Central Jilin.During 2000–2019,the land changed diversely,of which the main changes were the expanded dryland(+0.43 million ha),the increased deciduous forest(+22 million ha),the decreased coniferous forest(–0.08 million ha),and the expanded urban settlement(+0.04 million ha).With these changes,despite the unit grain yield showing a rising trend,the yield contribution of Central Jilin to the national total decreased.The poor cultivating structure made for the cropland expansion and reduced the implementation space of environmental restoration projects such as the Grain to Green.Thus,in Central Jilin that transits from the agri-food production zone to the eco-regulation zone,environmental projects coexisted in a trade-off manner with agricultural policies that aim to liberate agricultural productivity.In the key urban agglomerations of Central Jilin,the increase in the proportion of green space improved the thermal environment and carbon balance.The gross domestic product of the large city and its local proportion also rose.These improvements benefited from the promotion of development policies and urbanization policies at key time points.In the future,it is necessary to coordinate agricultural policies and environmental projects and promote the progress of small-and medium-sized cities to ensure the equality of regional development.This study has implications for making decisions to revitalize Northeast China and researchers who inform decisions.

Assessing the Impact of Land Use and Land Cover Change on Air Quality in East Baton Rouge—Louisiana Using Earth Observation Techniques

There has been significant research in recent decades on Land use Land cover (LULC) changes and their influence on biodiversity but little to no research on its impact on air quality. This research seeks to demonstrate how geospatial technologies such as geographic information system (GIS) and remote sensing can be used to assess the effects of LULC changes on particulate matter emissions and their impact on air quality in the East Baton Rouge area. In pursuit of these objectives, this study uses LANDSAT imageries from the past 30 years specifically Landsat Thematic Mapper (TM C2L2) and Landsat 8 Operational Land Imager/Thermal Infrared (OLI/TIRS C2L2) covering 1991, 2001, 2011 and 2021 were collected, processed, and analyzed for the LULC change analysis using QGIS software. Additionally, Sentinel 5P and the Air quality index from the U.S. Environmental Protection Agency (EPA) were used to assess the air quality trend over the years to establish the correlation between LULC and air quality. Results showed an increasing trend in air quality over the past 3 decades with concentrations of CO, NO2, and PM2.5 abruptly falling however, urbanization and the population expanded throughout the time. The paper concludes by outlining a policy recommendation in the form of encouraging Louisiana residents to use alternative renewable energies rather than the over-dependence on coal-fired electric generating plants that have an impact on the environment.

Inconsistent increasing of climate potential productivity resulting from global warming and land use transitions in the Dongting Lake Basin,from 2000 to 2020

In the face of global warming and increasing impervious surfaces,quantifying the change of climate potential productivity(CPP)is of great significance for the food production planning.Targeting the Dongting Lake Basin,which is a key area for food production in China,this paper uses meteorological data,as well as Climate Change Initiative Land Cover,and Shuttle Radar Topography Mission digital elevation model to investigate the CPP and its changes from 2000 to 2020.The suitability of land for cultivation(SLC),and the land use/land cover change(LUCC)are also considered.The results showed that the CPP varied from 9,825 to 20,895 kg ha^(-1).Even though the newly added impervious surfaces indirectly resulted in the decrease of CPP by of 9.81×10~8 kg,overall,the CPP increased at an average rate of 83.7 kg ha^(-1)a^(-1).Global warming is the strongest driver behind CPP increase,and CPP has played an important role in the conversions between cultivated land and other land types.The structure of land types tends to be optimized against this challenge.

Hydrological response to land use and land cover changes in a sub-watershed of West Liaohe River Basin,China

In recent years, the streamflow of the Laohahe Basin in China showed a dramatic decrease during the rainy season as a result of climate change and/or human activities. The objective of this work was to document significant streamflow changes caused by land use and land cover （LULC） changes and to quantify the impacts of the observed changes in Laohahe Basin. in the study area, the observed streamflow has been influenced by LULC changes, dams, and irrigation from rivers, industry, livestock and human consumption. Most importantly, the growth of population and gross domestic product （GDP） accompanied by the growth in industrial and agricultural activities, which led to LULC changes with increased residential land and cropland and decreased grassland since 2000s. Statistical methods and Variable Infiltration Capacity （VIC） hydrological model were used to estimate the effects of climate change and LULC changes on streamflow and evaportranspiration lET）. First, the streamflow data of the study area were divided into three sub-periods according to the Pettitt test. The hydrological process was then simulated by VIC model from 1964 to 2009. Furthermore, we compared the simulated results based on land use scenarios in 1989, 1999 and 2007, respectively for exploring the effect of LULC changes on the spatio-temporal distribution of streamflow and ET in the Laohahe Basin. The results suggest that, accompanied with climate change, the LULC changes and human water consumption appeared to be the most likely factors contributing to the sig- nificant reduction in streamflow in the Laohahe Basin by 64% from1999 to 2009.

Land use and land cover change within the Koshi River Basin of the central Himalayas since 1990

Land change is a cause and consequence of global environmental change.Land use and land cover have changed considerably due to increasing human activities and climate change,which has become the core issue of major international research projects.This study interprets land use and land cover status and the changes within the Koshi River Basin(KRB)using Landsat remote sensing(RS)image data,and employs logistic regression model to analyze the influence of natural and socioeconomic driving forces on major land cover changes.The results showed that the areas of built-up land,bare land and forest in KRB increased from 1990 to 2015,including the largest increases in forest and the highest growth rate in construction land.Areas of glacier,grassland,sparse vegetation,shrub land,cropland,and wetland all decreased over the study period.From the perspective of driving analysis,the role of human activities in land use and land cover change is significant than climate factors.Cropland expansion is the reclamation of cropland by farmers,mainly from early deforestation.However,labor force separation,geological disasters and drought are the main factors of cropland shrinkage.The increase of forest area in India and Nepal was attributed to the government’s forest protection policies,such as Nepal’s community forestry has achieved remarkable results.The expansion and contraction of grassland were both dominated by climatic factors.The probability of grassland expansion increases with temperature and precipitation,while the probability of grassland contraction decreases with temperature and precipitation.

A Modified Self-adaptive Method for Mapping Annual 30-m Land Use/Land Cover Using Google Earth Engine:A Case Study of Yangtze River Delta

Annual Land Use/Land Cover(LULC)change information at medium spatial resolution(i.e.,at 30 m)is used in applications ranging from land management to achieving sustainable development goals related to food security.However,obtaining annual LULC information over large areas and long periods is challenging due to limitations on computational capabilities,training data,and workflow design.Using the Google Earth Engine(GEE),which provides a catalog of multi-source data and a cloud-based environment,we developed a novel methodology to generate a high accuracy 30-m LULC cover map collection of the Yangtze River Delta by integrating free and public LULC products with Landsat imagery.Our major contribution is a hybrid approach that includes three major components:1)a high-quality training dataset derived from multi-source LULC products,filtered by k-means clustering analysis;2)a yearly 39-band stack feature space,utilizing all available Landsat data and DEM data;and 3)a self-adaptive Random Forest(RF)method,introduced for LULC classification.Experimental results show that our proposed workflow achieves an average classification accuracy of 86.33%in the entire Delta.The results demonstrate the great potential of integrating multi-source LULC products for producing LULC maps of increased reliability.In addition,as the proposed workflow is based on open source data and the GEE cloud platform,it can be used anywhere by anyone in the world.

Assessment of ecological quality in Northwest China(2000-2020)using the Google Earth Engine platform:Climate factors and land use/land cover contribute to ecological quality

The ecological quality of inland areas is an important aspect of the United Nations Sustainable Development Goals(UN SDGs).The ecological environment of Northwest China is vulnerable to changes in climate and land use/land cover,and the changes in ecological quality in this arid region over the last two decades are not well understood.This makes it more difficult to advance the UN SDGs and develop appropriate measures at the regional level.In this study,we used the Moderate Resolution Imaging Spectroradiometer(MODIS)products to generate remote sensing ecological index(RSEI)on the Google Earth Engine(GEE)platform to examine the relationship between ecological quality and environment in Xinjiang during the last two decades(from 2000 to 2020).We analyzed a 21-year time series of the trends and spatial characteristics of ecological quality.We further assessed the importance of different environmental factors affecting ecological quality through the random forest algorithm using data from statistical yearbooks and land use products.Our results show that the RSEI constructed using the GEE platform can accurately reflect the ecological quality information in Xinjiang because the contribution of the first principal component was higher than 90.00%.The ecological quality in Xinjiang has increased significantly over the last two decades,with the northern part of this region having a better ecological quality than the southern part.The areas with slightly improved ecological quality accounted for 31.26%of the total land area of Xinjiang,whereas only 3.55%of the land area was classified as having a slightly worsen(3.16%)or worsen(0.39%)ecological quality.The vast majority of the deterioration in ecological quality mainly occurred in the barren areas Temperature,precipitation,closed shrublands,grasslands and savannas were the top five environmental factors affecting the changes in RSEI.Environmental factors were allocated different weights for different RSEI categories.In general,the recovery of ecological quality in Xinjiang has been controlled by climate and land use/land cover during the last two decades and policy-driven ecological restoration is therefore crucial.Rapid monitoring of inland ecological quality using the GEE platform is projected to aid in the advancement of the comprehensive assessment of the UN SDGs.

Land use and land cover change processes in China's eastern Loess Plateau

Using Landsat remote sensing images, we analyzed changes in each land use type and transitions among different land use types during land use and land cover change （LUCC） in Ningwu County, located in the eastern Loess Plateau of China, from 1990 to 2010. We found that grassland, woodland, and farmland were the main land use types in the study area, and the area of each type changed slightly from 1990 to 2010, whereas the area of water, construction land, and unused land increased greatly. For the whole area, the net change and total change were insignificant due to weak human activity intensity in most of the study area, and the LUCC was dominated by quasi-balanced two-way transitions from 1990 to 2010. The insignificant overall amount of LUCC appears to have resulted from offsetting of rapid increases in population, economic growth, and the im- plementation of a program to return farmland to woodland and grassland in 2000. This program converted more farmland into woodland and grassland from 2000 to 2010 than from 1990 to 2000, but reclamation of woodland and grassland for use as farmland continued from 2000 to 2010, and is a cause for concern to the local government.

Land Use/Land Cover and Forest Canopy Density Monitoring of Wafi-Golpu Project Area, Papua New Guinea

This study aims to examine the use of Remote Sensing and Geographical Information System (GIS) technology in land use/land cover mapping to aide sustainable planning and development in the Wafi-Golpu project area. At the same time, this study examines an existing method of Forest Canopy Density (FCD) model to estimate forest canopy density of the proposed deforestation site, which is known as the Advanced Exploration Feasibility Study Activities (AEFSA) area within the Wafi-Golpu Project site. The FCD model calculates the forest canopy density using the three (3) indices of vegetation, soil and shadow from the Landsat-8 Operational Land Imager (OLI) satellite image of year 2013. In this study an attempt has been made to monitor the forest loss or degradation during deforestation in a natural forest stand of the Wafi-Golpu project area using forest FCD mapping and monitoring model and the findings of the study will assist the project planners and developers with their work on forest rehabilitation and reforestation for the purposes of sustainable forest management. The result of the work shows that a considerable amount of forest loss will be undertaken during the AEFSA deforestation exercise and also the findings show that a reliable land use/land cover map will greatly assist sustainable development in a resource project development period.

Land Use and Land Cover Dynamics in the Urban Watershed of Kimemi River (Butembo/D.R.C)

Changes in land use and land cover (LULC) influence hydrological processes in a watershed. This study analyses the dynamics of LULC in the Kimemi watershed from 1987 to 2021. GIS and remote sensing tools as well as landscape pattern analysis were used to achieve this purpose. The results reveal that the LULC change is globally marked by an increase in the bare land and building at the expense of the low vegetation (grassland). Between 1987 and 2011, the bare land and buildings (Tg = 61.33%) and the woodland (Tg = 34.2%) classes increased, whereas the grassland class decreased (Tg = -39.5%). On the other hand, between 2011 and 2015, the bare land and building class still increased (Tg = 29.9%) while that of grassland and woodland decreased with Tg = -37.3% and Tg = -4.9%, respectively. Finally, the dynamics observed from 2015 to 2021 is marked by small changes between classes with Tg values of 2.1%, 1.9% and -8.9%, respectively, for the bare land and building, grassland and woodland classes, respectively. The main spatial transformation processes observed are creation and dissection for the bare land and building class, and the grassland class respectively. In particular, the woodland class underwent the creation process between 1987 and 2011 before undergoing attrition (2011-2015-2021). Reduced vegetated areas give rise to new planning decisions to mitigate the hydrological risks that could result from this situation.

Change Detection of Land Use and Land Cover over a Period of 20 Years in Papua New Guinea

People have an inherent tenacity to throng coastal regions in pursuit of better living conditions. As such the brisk dynamism of land use/land cover activities in a coastal region becomes obvious. The former keeps changing rapidly due to burgeoning population. A digital change detection analysis is performed with the help of Geographic Information System (GIS) on the Remote Sensing data spanning over last 20 years, complemented by in-situ data and ground truth information. This current research briefly endeavours to find out the nature of change happening in the major three coastal cities of Papua New Guinea (PNG), namely Alotau, capital of Milnebay province;Lae, capital of Morobe province and Port Moresby, capital of Papua New Guinea. Changes in land use and land cover that took place over 20 years have been recorded using Landsat 5 thematic mapper (TM) data of 1992 and Landsat 8 operational land imager (OLI) data. Land use and land cover maps of 1992, and 2013/14, and change detection matrix of 1992-2013/14 are derived. Results show an immensely sprawling urban landscape, evincing about five times growth during 1992 to 2014. At the same time “natural forests” dwindled by 444.96 hectares in Alotau, 6977.25 hectares in Lae and “mangrove” and “grass/shrub land” decreased by 127.78 and 4859.39 hectares respectively around Port Moresby. The above changes owe to ever increasing population pressure, land tenure shift, agriculture and industrial development.

An Appraisal of Land Use/Land Cover Change Scenario of Tummalapalle, Cuddapah Region, India—A Remote Sensing and GIS Perspective

The study was aimed at appraising the changing land use/land cover scenario of Tummalapalle region in Cuddapah district of Andhra Pradesh using Remote sensing data and GIS technology. The region is considered as it has rich uranium reserves and is experiencing a remarkable expansion in recent times. The land use/land cover change analysis was carried out using IRS P6 LISS-III and LANDSAT-8 OLI multitemporal data pertaining to the years 2006 and 2016. The image classification resulted in five major land use/land cover classes namely built-up, agricultural, forest, wasteland and water bodies. The study noticed that the areas under built-up and agricultural classes are found increased from 0.94 km2 (0.84%) to 2.75 km2 (2.44%) and 61.68 km2 (54.84%) to 63.91 km2 (56.82%), respectively during 2006-2016. Area under forest, wasteland and water bodies are found decreased considerably from 3.09 km2 (2.75%) to 0.86 km2 (0.76%), 43.71 km2 (38.56%) to 42.60 km2 (37.88%) and 3.05 km2 (2.71%) to 2.35 km2 (2.09%), respectively. The study recommends development of industrial based economy by optimally utilizing the existing land resource (scrub and wasteland classes) and simultaneously extending the agricultural practices to other possible areas to make them more productive.

Simulation of the Dynamics of Land Cover and Land Use in the Lobo River Watershed Upstream of Nibéhibé(Center-West of Côte d’Ivoire)

From medium-resolution satellite images (Landsat TM, ETM+ and OLI), the spatial dynamics of land cover and land use are highlighted. The objective of this study is to quantify the evolution of land use in the watershed of the Lobo River upstream of Nibéhibé between 1986 and 2019 in order to analyze the impacts of human activities on the landscape. The study method was based, on the one hand, on the processing of satellite images, for the analysis of the dynamics of land use and, on the other hand, on the CA-Markov model, for the prediction of land use by 2050. It emerged from this study that the land use maps produced made it possible to highlight the spatio-temporal dynamics of land use on the basin. For the period from 1986 to 2019, there is a decrease in the area of forests in favor of built-bare ground and crops and fallows. A land use scenario for the years 2019 and 2050 was simulated with an accuracy of 87.11%. The regressive trend in forests seems to continue in the future with current land use practices.