Evaluation Of Land Cover Changes Research Articles

Analytical framework using remote sensing and water geochemistry to assess changes in landscapes with high ecological and social value

AbstractThe Brazilian Mata Atlântica coastal rainforest suffered a dramatic reduction in size due to agricultural and mining activities since the 1500s. Most relevant fragments are in mountainous areas assigned for environmental conservation, where there is increasing market pressure to open these areas for mining operations. In this study, we created a broader framework for water basin study on mountainous regions in tropical areas of high ecological importance. Remote sensing and hydrochemical analysis were used to create a more encompassing evaluation and a prognosis of environmental changes caused by mining operations. Our results showed that land use and land cover variations affect the physical and chemical behavior of rivers, and that seasonality plays a compounding role in their levels of particulate and chemical elements. Applying these combined techniques proved to be a good strategy in the evaluation of land cover change on the physical and chemical variations found in smaller watersheds.

Evaluation of Land Cover Changes in Karbala Governorate Using Remote Sensing and GIS Techniques

Evaluation of Land Cover Changes in Karbala Governorate Using Remote Sensing and GIS Techniques

The Evaluation of Land Cover Change of The Watershed Area Using ASTER Image

ASTER image is already widely used by various parties in various part of the world for the phenomena observation of the environmental changes. The image processing is supervised classification of maximum likelihood technique to produce land cover into 8 main classes. This study evaluate the changes in land cover in the Lesti’s sub-watershed where is a sub-watershed priority in the Brantas river’s watershed. The result of this study is the land cover change in the upstream area which approximately 1,314 km2 (4.65%) of forest area is converted to another type of land use and its dominated by dry-farm agricultural sector which is in particular farm and field. This is due to the large area of land cover for dry-land farming in 1999 which is approximately 78.198 km2 (31,77%) for the field and 61.844 km2 (25,13 %) for the farm while in 2009 is approximately 97.219 km2 (39,50%) for the fields and 49.421 km2 (20,08%) for the farm from the total land area. The dry-land farming is one of the most factor causing erotion and landslide.

Land Cover Changes in Selected Areas Next to Lagoons Located on the Southern Coast of the Baltic Sea, 1984–2021

The aim of the study is the evaluation of land cover changes in selected areas next to three lagoons (the Curonian Lagoon, the Vistula Lagoon and the Szczecin Lagoon) located on the southern coast of the Baltic Sea (in Lithuania, Russia, Poland and Germany) from 1984 to 2021. The changes are evaluated using multispectral (visible light—RGB and near infrared—NIR) satellite images from the Landsat 5 and Sentinel-2 sensors. Due to their high importance for ecosystem services, two main land cover types are evaluated, i.e., forest area and inland water reservoirs. The classification of the images is performed using a random forest algorithm. Areas of water bodies and forests are evaluated for the years 1984 and 2021. During period 1984–2021, positive changes in land cover are observed in all three regions included in the study. In almost all parts, with the exception of the Polish part of the area located next to the Szczecin Lagoon, of these regions, an increase in forest area is observed. The increase ranges from 0.1% (Poland, area next to the Vistula Lagoon) to 1.2% (Germany, area next to the Szczecin Lagoon). The area of inland water reservoirs has not changed significantly in the long term. Despite the global warming, no reduction in the area of these water reservoirs is observed, even new seminatural reservoirs have been created in some parts of the study area.

Evaluation of land cover changes and secondary ecological succession of typical agroforestry landscapes in Phu Yen Province

The study of land cover changes as well as landscape succession has theoretical and practical significance. Determining the characteristics, causes, and trends of the changes and succession of a landscape allows for assessing the natural and human characteristics of the territory. On this basis, appropriate solutions and policies in resource management, socioeconomic development, and environmental protection are available for each locality. Applying and integrating remote sensing data with field investigations and surveys improves the accuracy and reliability of research results. From the establishment of a land cover change map based on land cover map data collected in 2010, 2015, and 2020, variations in the land cover types of Phu Yen Province were observed. In the period 2010–2015, the area of natural forests and grasslands, shrubs, and bare lands decreased rapidly, whereas the covered areas of intentionally planted forests, industrial trees, and crops increased significantly. The secondary ecological succession of the agroforestry landscape of Phu Yen Province in the last 50–60 years occurred under the strong influence of human activities. Under the impact of chemical warfare and policies and farming practices of the local people, several evergreen broad-leaved tropical forest landscape units have undergone four to six stages of succession, with the interweaving of the economic development policy of Phu Yen Province and farming practices of the local people, making the structure and length of each period and succession very different.

Linking land change model evaluation to model objective for the assessment of land cover change impacts on biodiversity

Evaluation of land cover change (LCC) is commonly done at the pixel level; however, the model’s purpose may be relevant at a different grain size. Thus, the same model may be good for one purpose but inappropriate for another. For conservation applications, it is crucial to assess land change simulations at the grain relevant for the assessment of biodiversity impacts. Our objective is to evaluate land cover change scenarios in Bolivia, at the pixel-level and grain relevant to biodiversity, to inform LCC models for biodiversity assessments. We created six deforestation simulations that varied deforestation allocation based on forest management units (national, province, and municipality), ecoregions, and carbon stocks. We evaluated the simulations at the pixel level, and the objective’s relevant grain size through stratified error decomposition. We assessed biodiversity impacts by comparing the quantity of reference and simulated deforestation within species ranges. The spatial allocation of deforestation differed across simulations; however, their pixel-level error were similar. The province and municipality land change simulations had the lowest allocation errors at the relevant grain despite their large pixel-level errors, and they showed the lowest biodiversity errors. The province simulation provided the best balance identifying both affected species composition and the area of impact. This work presents evidence of the importance of incorporating information regarding the purpose of the simulation during model evaluation and selection. Error decomposition allowed ignoring irrelevant errors, translating into meaningful assessments of biodiversity impacts. As opposed to pixel-level metrics, stratified errors identified models that characterized biodiversity impacts best.

Monitoring and evaluating the contribution of the rural development program to high nature value farmland dominated by traditional mosaic landscape in Slovakia

This paper focuses on designing an approach to monitor the effects of the Rural Development Program (RDP) on High Nature Value Farmland type 2 – farmland dominated by traditional mosaics of cultivated land and small-scale features (HNV2) – and its application to farmland in Slovakia. Based on the identification of HNV2 on the national level and selection of monitoring sites, we carried out monitoring for two periods: 1st monitoring of RDP 2007–2013 and 2nd monitoring of RDP 2014–2020. We developed a set of indicators for monitoring of HNV2, which were mapped in the field: management intensity, categories of land cover and type of management, share of semi-natural elements, management activities. The most significant changes were observed in the proportion of semi-natural vegetation and management intensity. We defined five categories of changes in management intensity: either positive – 1) improved, or 2) persistent regular management – or negative – 3) continued abandonment, 4) decrease in management intensity, or 5) intensification causing decrease of landscape diversity. The evaluation of land cover changes on the basis of landscape indices shows higher landscape diversity on sites without subsidies. This shows that subsidies are linked to farmland with less diverse landscape structure. Statistical analyses showed semi-natural vegetation to be dominant on both subsidised and unsubsidised sites. The total area of HNV2, which is one of the basic indicators evaluated under the RDP, is decreasing: partly due to updates and refinements of the Land Parcel Identification System (LPIS), and exclusion of HNV2 sites from LPIS due to a presence of woody elements, but also partly due to abandonment. The results of our study showed a slightly positive contribution of RDP to maintenance and sustainable management of HNV2.

Assessing long-term land cover changes in watershed by spatiotemporal fusion of classifications based on probability propagation: The case of Dniester river basin

Broad-scale land cover classifications created by using satellite imagery are recognized as important and necessary input to land cover mapping. Evaluation of land cover changes is essential for sustainable watershed management. In this research, a framework for quantitative assessment of long-term land cover changes over large areas is developed. A key feature of the framework is a spatiotemporal fusion of classifications. Herein, a method to resolve the inconsistency of land cover classes at overlapped multi-segment and multi-temporal classifications by considering their probability propagation is proposed. The framework was applied in assessing long-term land cover changes in the Dniester river basin. Two land cover maps, for 2002 and 2018, were obtained with overall accuracy of 81.42% and 81.30%, respectively. The subsequent analysis and quantitative assessment of sixteen-year land cover changes by T. Saaty's analytic hierarchy procedure resulted in a map of the significance of these long-term land cover changes for the Dniester river basin. The major part of the basin (81.6%) exhibits no changes. Land cover changes maintaining favorable conditions for watershed appear over 10.5% of the area, while harmful changes occur over 7.9% of the territory.

Interactive classification and spatial modeling of land cover changes in the Slovak Republic in the period 1990 to 2018

Abstract. The current country is the result of changes from the original country, mainly due to human influence. The external appearance of the landscape is represented by landscape cover. Within the EU, the Copernicus program, coordinated by the European Environment Agency (EEA), is dedicated to Earth and environmental monitoring. The outputs of the program are information services based on satellite observations of the Earth and ground-based collection of spatial data - implemented in cooperation with individual Member States of the EU. The Copernicus Land Monitoring Service (CLMS) and the collection of geographical information about land cover and land cover changes, land use, vegetation status, water cycles and the energy of the Earth's surface are provided.The Slovak Republic has been involved in the program since 1990. Corine Land Cover (CLC) data are freely available for 1990, 2000, 2006, 2012 and 2018. The CLC legend is a mutual combination of land cover and land use, the highest - third hierarchical level of the CLC classification identifies 44 classes. Data are available in the form of vectors and rasters, with a scale of 1 : 100 000, coordinate system: ETRS89, minimum mapping unit of 25 ha was selected.In this paper, we focus on the identification of the condition and spatial modeling of landscape changes with emphasis on forests. Forests as important carbon sinks are an environmental factor that influences the impact of emissions on the development of greenhouse gases and climate change. According to the Intergovernmental Panel on Climate Change (IPCC), member countries report changes in land cover categories according to the AFOLU (Agriculture, Forestry and Other Land Use) classification. For the purposes of estimating greenhouse gas emissions, the AFOLU methodology distinguishes six categories: forest land; cropland; grassland; wetlands; settlements; other areas.The main goal of the paper is the development and presentation of an integrated geographical database of land cover data of the Slovak Republic from CLC datasets (in the period 1990 to 2018), a tool for reclassification of the third hierarchical level CLC and creation of data structures of land use categories according to AFOLU.The specific goal is the development and presentation of an interactive tool - a web application for retrospective assessment of land cover changes from the integrated geographical database according to the CLC classification and interactive assessment of land cover changes according to the AFOLU classification. The outputs of the interactive evaluation of land cover changes will focus on the forest land cover category, evaluation of changes according to adjustable time intervals in CLC and AFOLU and the statistical evaluation of changes.The output is a freely available web application with interactive functionality for datasets, database modeling of land cover changes, statistical evaluation of changes and creation of map outputs. A case study of data processing for the area of the Bratislava region (205 270 ha) in the years 1990 to 2018 (five CLC datasets) is presented. The datasets are suitable for continuously identifying the state of land cover, modeling its changes over time and interpreting land cover change processes over time.

Evaluation of Land Cover Changes in Southwestern Lithuania from 1984 to 2018 Using Medium Spatial Resolution Satellite Imagery

Evaluation of Land Cover Changes in Southwestern Lithuania from 1984 to 2018 Using Medium Spatial Resolution Satellite Imagery

A Statistical Approach to Detect Land Cover Changes in Mediterranean Ecosystems Using Multi-Temporal Landsat Data: The Case Study of Pianosa Island, Italy

The normalized difference vegetation index (NDVI) is commonly used to detect spatiotemporal changes of vegetation cover. This study modeled the spatiotemporal changes of land cover on Pianosa Island, Italy, in the period 1999–2015, using the multi-temporal Landsat images. Since the end of the 1990s, the natural vegetation has been re-colonizing an area of abandoned agricultural land and the island is undergoing a process of re-naturalization in harsh (drought and hot) environmental conditions. Hence, it is an ideal test site to monitor the effects of anthropogenic and climatic stressors on vegetation dynamics under Mediterranean climate. In this work, we proposed a new statistical approach based on a pixel-by-pixel analysis of multi-temporal Landsat images. Mean (µ) and standard deviation (σ) values of the NDVI images taken in 2015 were used for the determination of the pixel thresholds (µ ± 3σ). The evaluation of land cover change was carried out by comparing the µ value of a single NDVI pixel for 2015 with the same pixel of different years of the study period. The results indicate that surface reflectance (SR) Landsat images are more suitable in detecting the vegetation dynamics on the island than the top of atmosphere (TOA) ones and highlight an increasing trend of vegetation cover on Pianosa Island, mainly during the early seven years following the land abandonment in all the main land cover classes: abandoned crops and pastures, Mediterranean macchia, and woodland. However, the abandoned agricultural and pasture areas showed a higher increase in the vegetation cover and a shift in the shape of the normalized frequency distribution of the SR NDVI data during the study period, suggesting that a colonization process from other vegetation classes is occurring (i.e., Mediterranean macchia and trees are colonizing the abandoned land, partly replacing herbaceous species). Our data highlight that the statistical approach applied in this study is suitable for detecting vegetation cover changes associated with anthropogenic and climatic drivers in a typical Mediterranean environment and could be proposed as a new methodological approach in several other land monitoring studies.

Evaluation of Land Cover Change and Agricultural Protection Sites: A GIS and Remote Sensing Approach for Ho Chi Minh City, Vietnam

Ho Chi Minh City (HCMC), economic center and most populous city of Vietnam faces a strong structural change since its market liberalization in the late 1980s. Big challenges occur in the form of uncontrolled urban sprawl due to rapid population growth with encroachment of agricultural land, which leads to environmental and climatic issues like urban heat island effects, air pollution and flooding events. Remote Sensing and Geographic Information Systems (GIS) provide new computer-based technologies for urban planners which can greatly ease the monitoring of agricultural loss as well as improve decision making for future land management. In the first part of this study, land cover change dynamics are thoroughly assessed using moderate and high spatial resolution satellite imagery (Landsat and SPOT) over the period 2010–2017 in 22 districts of HCMC. In the second part, the land cover classification results of 2017 provide the initial map for a GIS-based Multi-Criteria-Decision-Analysis (MCDA) of potential agricultural protection sites. Therefore, criteria of climate adaptation and ecological service are established and embedded in the GIS-compatible Compromise Programming Model (CP). With the use of Analytic Hierarchy Process (AHP) by Thomas L. Saaty and additional expert knowledge, appropriate weighting factors have been affiliated. The results show that agricultural land decreased by more than two thirds in the period considered. However, particularly the western rural districts Bình Chánh and Hóc Môn still offer a great amount of valuable agricultural land suitable for protection. The proposed method can serve as a scientific framework for planning departments of fast growing cities to zone agricultural land for protection on an early planning stage in order to ensure sustainable land use development in the future.

An insight into land-cover changes and their impacts on ecosystem services before and after the implementation of a comprehensive experimental zone plan in Pingtan island, China

Pingtan Island has undergone changes in socio-economic and policy environment with significant effect on land cover change (LCC) and ecosystem service values (ESV). The most notable changes in both land cover and ESV were linked to Pingtan Comprehensive Experimental Zone (PCEZ) plan, economic development plan with the aim of making Pingtan an international tourism island and free trade zone. However, evaluation of LCC and its impact on ESV is not yet attempted in the area. Using multispectral Landsat images, value transfer method and socioeconomic data, this study aims to quantify and track LCC, landscape pattern and ESV (2003–2017). The results showed that farmland, forest land and urban land covered >74% of the total area in the years considered. The class-to-class transition was also substantial among them. During the period 2003–2010, LCC was slow with stable areas of 73.52%. In the second period (2010–2017), it showed remarkable differences with the highest change in water bodies (9.76% less than its initial proportion), urban land (9.47% higher), farmland (8.67% less) and the stable areas reduced to 63.87%. Regardless of class-level variations, landscape fragmentation generally increased but shape irregularity among patches decreased during the study period. The total ESV was 32 million US$ in 2003. It changed slowly in the first period (1.61%/year) and rapidly in the second period (–2.869%/year) that caused the overall net loss of 4.35 million US$ (13.594%). Partial least square regression model also showed the highest variance of ESV (85%) due to the variance of LCC (92%), whereas it exhibited less variance owing to the variance of landscape pattern. Following PCEZ plan, the policy reforms accelerated construction land and economic development that negatively affected ecosystem services. Our results could help understand the relationship between LCC and ESV along with socioeconomic and policy factors to make sustainable land management interventions.

Assessing land cover/use changes in Karbala city (Iraq) using GIS techniques and remote sensing data

In this research, land cover changes between 2000 to 2017 were studied in Karbala city (Iraq) using geographic information system techniques and remote sensing data. Satellite imagery data -Landsat7 (2000) and Landsat 8 (2017) - were processed using the supervised maximum likelihood algorithm, and the post-classification comparison method in QGIS 2.14. Four land cover categories, namely, built-up, vegetation, water, and soil have been specified to produce land cover maps for each acquisition date. The overall accuracies were 99.99% (2000), and 99.98% (2017) with Kappa statistics of 0.99, and 0.99. The evaluation of land cover changes shows that built-up, vegetation and soil have been increased by 1.9% (93.5 km2), 0.4% (20.8 km2) and 4.4% (221.3 km2) while water land has a shrink by 6.7% (335.6 km2) respectively. These changes conclude a serious threat to water land which it effects on population growth, human activities and agricultural activities in the study area.

Evaluation of land cover changes and Black locust occurrence in agricultural landscape. Case study: Podolie and Častkovce cadastral areas, Slovakia

This study presents spatial analysis of agricultural landscape changes in the Podolie and Castkovce cadastral areas since 1949. Data for analysis was obtained from historical aerial photographs (from 1949, 1986 and 2006), detailed field mapping and Black locust ( Robinia pseudoacacia L.) monitoring. Land cover changes were assessed from the aerial photographs based on the CORINE land cover legend, environmental variables were derived from digital elevation model (DEM) and detailed geological and soil maps. Data was spatially compared and assessed by regression analysis for interpretation of Black locust occurrence. The most significant land cover changes occurred between 1949 and 1986 when agricultural areas were replaced by forest and semi-natural areas. One of the aspects of landscape changes is abandonment of agricultural landscape and occupancy this new transformed surfaces by invasive plant taxons (e. i. Robinia pseudoacacia L.). Black locust occurrence was mainly influenced by landscape management changes and subsequent land cover changes (afforestation from 1949 to 1986), especially in regions of dispersed settlements (Podolske and Korytnianske kopanice) after agricultural collectivisation. Environmental variables had little effect on Black locust expansion in these areas.

The assessment of land cover in the Nowy Targ commune with particular focus on the area of Natura 2000

Summary The rural landscape in Poland has been changing for the past several dozen years. The changes are visible in the land use and land cover. Technological progress, changes in people’s outlook and a low profitability of agriculture resulted in transformations of rural landscapes, especially in the areas of high level of land fragmentation, as it is the case in the south part of Poland. These changes are accompanied by growing awareness of environmental or cultural landscape protection related issues. Recent years have also brought new forms of environmental protection, for example the programme Natura 2000, being the result of agreements with European Union. The network of Natura 2000 cover the areas of special protection of birds, habitats, and according to the Act on Nature Conservation – areas of special interest for the Community. The goal of this form of protection is a preservation of valuable or engendered elements of biodiversity. The question arises then whether in the era of landscape transformations and changes of land cover qualifying a particular area as part of Natura 2000 network has any influence on the way of land use. The aim of the article is an analysis and evaluation of land cover changes, also in the areas covered by Natura 2000 programme, within the piedmont commune of Nowy Targ in Malopolskie Voivodeship. Moreover, a thesis is proposed that submontane lands, specifically used, due to large terrain height differences, are faced with less intense urbanization pressures and land transformations. Is it also the case of the Nowy Targ commune, covered in more than 22% by the Natura 2000 areas?

Evaluation of Land Cover Changes at the Coast of Sindh through Successive Landsat Imageries

Satellite remote sensing is the most readily available and updated data source for detection, quantification, and mapping of Land-use/Land Cover (LULC) patterns and changes because of its repetitive data acquisition, digital format suitable for computer processing, and accurate geo-referencing procedures. The objective of the study is to analyze the land cover changes and to examine the Land Surface Temperature (LST) with other climatic effects on the Sindh coastal region. Satellite images of Landsat-7 ETM+, Landsat-5 TM and Landsat-8 OLI/TIRS were used in the study, acquired on March 08, 2000, November 20, 2009 and April 08, 2014 respectively. The land cover classes selected for the study are vegetation, mudflat, built-up/vacant land, shallow water and deep water. Maximum likelihood supervised classification and LST techniques were used in the study. The results of the classification mainly consist of land cover classes for 2000, 2009 and 2014, respectively. The land cover in the study area is under the serious threat of climate change. The major cause of ecological, environmental and land use degradation of Indus delta is reduction in fresh water flow, sea water intrusion and natural disasters. Sindh coastline is widely exposed to the disasters like heavy rains, floods, frequent storms and cyclones. This coast faces cyclones approximately every year. Eastern part of Sindh Province is at high risk of tropical cyclones. It is a huge threat to the land covers, biodiversity and human population.

The Analysis and Evaluation of Land Cover Change in Xining City Based on CA-Markov Model

Cellular automata model is a dynamic evolution model with discrete space and time, it is powerful in spatial modeling and parallel computing, so it can take advantage of workstation to simulate the transformation process of complex spatial system. Using a model based on cellular automata to forecast the development of Xining has a great benefit for the urban development. Markov Chain model is widely used in forecasting a system which is changing smoothly, the Markov Chain would provide transition rules for the cellular automata. The main task is predicting the land cover of Xining in 2020 based on CA-Markov. and analyzing the characteristics of change of Xining between 1996 and 2020. Finally, some useful advices are provided for the current urban planning by analyzing the driving factors.

Evaluation of land cover changes after extraordinary windstorm by using the land cover metrics: a case study on the high Tatras foothill

On the 19th November 2004, a wind disaster caused extensive damages, especially in the forests of the Tatra National Park. Despite that windstorm consequences of natural processes impact the spatial structure of landscape excessively, their studies have been subject only to a minor interest so far. The aim of this paper is to characterize the land cover changes in the Štrbské Pleso – Tatranská Lesná area, before the wind disaster and after its impacts have been processed. We also analyze the relationship between wind-caused damages to the vegetation and the natural landscape structure, using various landscape metrics.

Extending post-classification change detection using semantic similarity metrics to overcome class heterogeneity: A study of 1992 and 2001 U.S. National Land Cover Database changes

The use of post-classification change methods for the analysis of land cover change provides intuitive and potentially reliable results. A recurring problem is the difference in land cover nomenclature that can occur over time or across space when multiple data sources are required. Building on work that uses category semantics as a foundation for reasoning with land cover classes, this paper uses a fuzzy sets based approach to develop attribute based prototype definitions of land cover classes. These formalized category descriptions are used to look at land cover changes as a semantic change evaluated through semantic similarity metrics. The methodology is illustrated on the U.S. National Land Cover Data from 1992 to 2001 over Chester County, PA. The results demonstrate that the proposed method is more versatile than the standard post-classification method in that it can both provide an overall, spatially explicit evaluation of land cover change, as well as nuanced assessments of graded changes for heterogeneous land cover types.