Systematic processes of land use/land cover change to identify relevant driving forces: implications on water quality

Automated Mapping of Land Cover Type within International Heterogenous Landscapes Using Sentinel-2 Imagery with Ancillary Geospatial Data

A near-global framework for automated training data generation and land cover classification using shallow machine learning with low-density time series imagery does not exist. This study presents a methodology to map nine-class, six-class, and five-class land cover using two dates (winter and non-winter) of a Sentinel-2 granule across seven international sites. The approach uses a series of spectral, textural, and distance decision functions combined with modified ancillary layers (such as global impervious surface and global tree cover) to create binary masks from which to generate a balanced set of training data applied to a random forest classifier. For the land cover masks, stepwise threshold adjustments were applied to reflectance, spectral index values, and Euclidean distance layers, with 62 combinations evaluated. Global (all seven scenes) and regional (arid, tropics, and temperate) adaptive thresholds were computed. An annual 95th and 5th percentile NDVI composite was used to provide temporal corrections to the decision functions, and these corrections were compared against the original model. The accuracy assessment found that the regional adaptive thresholds for both the two-date land cover and the temporally corrected land cover could accurately map land cover type within nine-class (68.4% vs. 73.1%), six-class (79.8% vs. 82.8%), and five-class (80.1% vs. 85.1%) schemes. Lastly, the five-class and six-class models were compared with a manually labeled deep learning model (Esri), where they performed with similar accuracies (five classes: Esri 80.0 ± 3.4%, region corrected 85.1 ± 2.9%). The results highlight not only performance in line with an intensive deep learning approach, but also that reasonably accurate models can be created without a full annual time series of imagery.

Spatio-temporal dynamics of land use transitions associated with human activities over Eurasian Steppe: Evidence from improved residual analysis

We presented a framework to evaluate the land use transformations over the Eurasian Steppe (EUS) driven by human activities from 2000 to 2020. Framework involves three main components: (1) evaluate the spatial-temporal dynamics of land use transitions by utilizing the land change modeler (LCM) and remote sensing data; (2) quantifying the individual contributions of climate change and human activities using improved residual trend analysis (IRTA) and pixel-based partial correlation coefficient (PCC); and (3) quantifying the contributions of land use transitions to Leaf Area Index Intensity (LAII) by using the linear regression. Research findings indicate an increase in cropland (+1.17 % = 104,217 km2) over EUS, while a - 0.80 % reduction over Uzbekistan and - 0.16 % over Tajikistan. From 2000 to 2020 a slight increase in grassland was observed over the EUS region by 0.05 %. The detailed findings confirm an increase (0.24 % = 21,248.62 km2) of grassland over the 1st half (2000-2010) and a decrease (-0.19 % = -16,490.50 km2) in the 2nd period (2011-2020), with a notable decline over Kazakhstan (-0.54 % = 13,690 km2), Tajikistan (-0.18 % = 1483 km2), and Volgograd (-0.79 % = 4346 km2). Area of surface water bodies has declined with an alarming rate over Kazakhstan (-0.40 % = 10,261 km2) and Uzbekistan (-2.22 % = 8943 km2). Additionally, dominant contributions of human activities to induced LULC transitions were observed over the Chinese region, Mongolia, Uzbekistan, and Volgograd regions, with approximately 87 %, 83 %, 92 %, and 47 %, respectively, causing effective transitions to 12,997 km2 of cropland, 24,645 km2 of grassland, 16,763 km2 of sparse vegetation in China, and 12,731.2 km2 to grassland and 15,356.1 km2 to sparse vegetation in Mongolia. Kazakhstan had mixed climate-human impact with human-driven transitions of 48,568 km2 of bare land to sparse vegetation, 27,741 km2 to grassland, and 49,789 km2 to cropland on the eastern sides. Southern regions near Uzbekistan had climatic dominancy, and 8472 km2 of water bodies turned into bare soil. LAII shows an increasing trend rate of 0.63 year-1, particularly over human-dominant regions. This study can guide knowledge of oscillations and reduce adverse impacts on ecosystems and their supply services.

Comparison of machine learning algorithms to predict dissolved oxygen in an urban stream

Water quality monitoring for urban watersheds is critical to identify the negative urbanization impacts. This study sought to identify a successful predictive machine learning model with minimal parameters from easy-to-deploy, low-cost sensors to create a monitoring system for the urban stream network, Hunnicutt Creek, in Clemson, SC, USA. A multiple linear regression model was compared to machine learning algorithms k-nearest neighbor, decision tree, random forest, and gradient boosting. These algorithms were evaluated to understand which best predicted dissolved oxygen (DO) from water temperature, conductivity, turbidity, and water level change at four locations along the urban stream. The random forest algorithm had the highest performance in predicting DO for all four sites, with Nash-Sutcliffe model efficiency coefficient (NSE) scores > 0.9 at three sites and > 0.598 at the fourth site. The random forest model was further examined using explainable artificial intelligence (XAI) and found that temperature influenced the DO predictions for three of the four sites, but there were different water quality interactions depending on site location. Calculating the land cover type in each site's sub-watershed revealed that different amounts of impervious surface and vegetation influenced water quality and the resulting DO predictions. Overall, machine learning combined with land cover data helps decision-makers better understand the nuances of urban watersheds and the relationships between urban land cover and water quality.

Estimating the contribution of environmental variables to water quality in the postrestoration littoral zones of Taihu Lake using the APCS-MLR model

Water quality monitoring is one of the most important aspects of postrestoration assessments because it affects water pollution control and the development of sustainable management strategies. However, a comprehensive understanding of potential water pollution and source apportionment in restoration projects is still lacking. In this study, the water quality variables of three restored national wetland parks with different cofferdam systems (i.e., an eco-layered cofferdam, a fully enclosed cofferdam, and open water) in the littoral zone of Taihu Lake were monitored monthly for three years (2019-2021). Hydrochemical and meteorological variables were used as auxiliary parameters for multivariate statistics, including principal component analysis (PCA) and absolute principal component score-multiple linear regression (APCS-MLR), to accurately estimate the source apportionment of the potential factors influencing the water environment. PCA extracted three or four potential sources, accounting for 64.71 %, 65.40 %, and 63.85 % of the total variance. The APCS-MLR results showed that wind direction and volatile suspended solids were the primary sources affecting water quality in open water, with a sum of the mean source contributions of 40.7 %. In fully enclosed cofferdam systems, the dire state of endogenous pollution was the greatest potential source affecting water quality, with a mean contribution of 41.2 %. The eco-layered cofferdam alleviated the contributions of suspended solids (mean contribution of 23.7 %) and nutrients in the water column (mean contribution of 30.8 %); however, the contribution of organic matter in the cofferdam was relatively high (mean contribution of 13.4 %). Based on these results, eco-layered cofferdams play a positive role in eutrophication control and ecological restoration in the littoral zone of large shallow lakes. Meanwhile, adding meteorological variables to assist hydrochemical variables in multivariate statistics may improve the accuracy and certainty of pollution source apportionment and support decision-makers in developing water quality protection and management strategies for postrestoration projects in littoral zones.

Investigation of land cover (LC)/land use (LU) change affecting forest and seminatural ecosystems in Istanbul (Turkey) metropolitan area between 1990 and 2018

This study was conducted to examine the land cover (LC)/land use (LU) change affecting forest and seminatural ecosystems and the spatio-temporal development of urban expansion between 1990 and 2018 in the city of Istanbul, where urbanization is the most intense in Turkey. For this purpose, using Corine Land Cover (1990, 2000, 2006, 2012, and 2018) dataset, the land cover of the area was determined in 5 different classes (artificial surface, agriculture, forest, water bodies, water), maps were produced, and tabular data were created. The changes in LC/LU between 1990 and 2018 were determined according to the Puyravaud land cover change rate and hot spot analysis methods. According to our findings, we determined that urbanization in Istanbul expanded the most in the east-west direction, and the agricultural and forest areas gradually decreased by 3.02% and 6.66% respectively; urban areas increased at the same rate of 9.69%. It is predicted that this change will continue increasing until 2030 when the forecasting method is applied in the field. It has been determined that the most important reasons for this situation are local government policies, population growth, and economic development initiatives applied in the area. As a result, it has emerged that measures should be taken based on sustainability and naturalness approaches to design urban development plans and to protect natural areas on a large scale, in order to limit possible LC/LU conversion from natural structure to urbanization in the area.

The scale identification associated with priority zone management of the Yangtze River Estuary

Watershed and catchment area-based water quality management are important methods for comprehensive management of rivers and lakes. The impacts of land use/land cover (LULC) on river water quality vary with spatial scales, such as watersheds, catchments, and riparian zones. Achieving an effective spatial scale relationship between LULC and water quality, determining priority management areas, and reaching sustainable development of large estuarine deltas remain problematic. In this study, buffering analysis on the water quality data of the Yangtze River Estuary from 2009 to 2018 was conducted based on LULC, and the priority management areas of the basin were identified. Also, we infer that future river restoration or management efforts should focus on priority management area construction of a 1500 m riparian zone and a 150 km reach zone. Conclusively, establishing a priority management area within the effective buffer zone is key to watershed water quality management.

Determination of the Connectedness of Land Use, Land Cover Change to Water Quality Status of a Shallow Lake: A Case of Lake Kyoga Basin, Uganda

Catchments for aquatic ecosystems connect to the water quality of those waterbodies. Land use land cover change activities in the catchments, therefore, play a significant role in determining the water quality of the waterbodies. Research on the relationship between land use and land cover changes and water quality has gained global prominence. Therefore, this study aimed at determining land use, land cover changes in the catchments of L. Kyoga basin, and assessing their connectedness to the lake’s water quality. The GIS software was used to determine eight major land use and land cover changes for 2000, 2010, and 2020. Meanwhile, water quality data was obtained through both secondary and primary sources. Spearman correlation statistical tool in SPSS was used to correlate the land use, land cover changes, and water quality changes over the two-decade study period. The results showed that different land use and land cover activities strongly correlated with particular water quality parameters. For example, agriculture correlated strongly with nutrients like TP, TN, and nitrates and turbidity, TSS, BOD, and temp. The correlation with nitrates was statistically significant at 0.01 confidence limit. The findings of this study agreed with what other authors had found in different parts of the world. The results show that to manage the water quality of L. Kyoga, management of land use, land cover activities in the catchment should be prioritized. Therefore, the results are helpful to decision and policy makers and relevant stakeholders responsible for water management.

Characterization of the main land processes occurring in Europe (2000-2018) through a MODIS NDVI seasonal parameter-based procedure

The identification and recognition of the land processes are of vital importance for a proper management of the ecosystem functions and services. However, on-ground land uses/land covers (LULC) characterization is a time-consuming task, often limited to small land areas, which can be solved using remote sensing technologies. The objective of this work is to investigate how the different MODIS NDVI seasonal parameters responded to the main land processes observed in Europe in the 2000-2018 period; characterizing their temporal trend; and evaluating which one reflected better each specific land process. NDVI time-series were evaluated using TIMESAT software, which extracted eight seasonality parameters: amplitude, base value, length of season, maximum value, left and right derivative values and small and large integrated values. These parameters were correlated with the LULC changes derived from COoRdination of INformation on the Environment Land Cover (CLC) for assessing which parameter better characterized each land process. The temporal evolution of the maximum seasonal NDVI was the parameter that better characterized the occurrence of most of the land processes evaluated (afforestation, agriculturalization, degradation, land abandonment, land restoration, urbanization; R² from 0.67-0.97). Large integrated value also presented significant relationships but they were restricted to two of the three evaluated periods. On the contrary, land processes involving CLC categories with similar NDVI patterns were not well captured with the proposed methodology. These results evidenced that this methodology could be combined with other classification methods for improving LULC identification accuracy or for identifying LULC processes in locations where no LULC maps are available. Such information can be used by policy-makers to draw LULC management actions associated with sustainable development goals. This is especially relevant for areas where food security is at stake and where terrestrial ecosystems are threatened by severe biodiversity loss.

A multi-model approach to assessing the impacts of catchment characteristics on spatial water quality in the Great Barrier Reef catchments

Water quality monitoring programs often collect large amounts of data with limited attention given to the assessment of the dominant drivers of spatial and temporal water quality variations at the catchment scale. This study uses a multi-model approach: a) to identify the influential catchment characteristics affecting spatial variability in water quality; and b) to predict spatial variability in water quality more reliably and robustly. Tropical catchments in the Great Barrier Reef (GBR) area, Australia, were used as a case study. We developed statistical models using 58 catchment characteristics to predict the spatial variability in water quality in 32 GBR catchments. An exhaustive search method coupled with multi-model inference approaches were used to identify important catchment characteristics and predict the spatial variation in water quality across catchments. Bootstrapping and cross-validation approaches were used to assess the uncertainty in identified important factors and robustness of multi-model structure, respectively. The results indicate that water quality variables were generally most influenced by the natural characteristics of catchments (e.g., soil type and annual rainfall), while anthropogenic characteristics (i.e., land use) also showed significant influence on dissolved nutrient species (e.g., NO_X, NH₄ and FRP). The multi-model structures developed in this work were able to predict average event-mean concentration well, with Nash-Sutcliffe coefficient ranging from 0.68 to 0.96. This work provides data-driven evidence for catchment managers, which can help them develop effective water quality management strategies.

Spatio-seasonal variation of water quality influenced by land use and land cover in Lake Muhazi

Understanding the influence of land use/land cover (LULC) on water quality is pertinent to sustainable water management. This study aimed at assessing the spatio-seasonal variation of water quality in relation to land use types in Lake Muhazi, Rwanda. The National Sanitation Foundation Water Quality Index (NSF-WQI) was used to evaluate the anthropogenically-induced water quality changes. In addition to Principal Components Analysis (PCA), a Cluster Analysis (CA) was applied on 12-clustered sampling sites and the obtained NSF-WQI. Lastly, the Partial Least Squares Path Modelling (PLS-PM) was used to estimate the nexus between LULC, water quality parameters, and the obtained NSF-WQI. The results revealed a poor water quality status at the Mugorore and Butimba sites in the rainy season, then at Mugorore and Bwimiyange sites in the dry season. Furthermore, PCA displayed a sample dispersion based on seasonality while NSF-WQI's CA hierarchy grouped the samples corresponding to LULC types. Finally, the PLS-PM returned a strong positive correlation (+ 0.831) between LULCs and water quality parameters in the rainy season but a negative correlation coefficient (- 0.542) in the dry season, with great influences of cropland on the water quality parameters. Overall, this study concludes that the lake is seasonally influenced by anthropogenic activities, suggesting sustainable land-use management decisions, such as the establishment and safeguarding protection belts in the lake vicinity.

The Drivers-Pressures-State-Impact-Response Model to Structure Cause−Effect Relationships between Agriculture and Aquatic Ecosystems

Different segments of society have shown interest in understanding the effects of human activities on ecosystems. To this end, the aim of this article is to analyze the scientific literature on the application of the Drivers-Pressures-State-Impact-Response (DPSIR) conceptual model to identify the parameters used to describe the causal interactions that occur between agriculture and aquatic ecosystems at the watershed scale. In this way, descriptive indicators were established for the data of 63 publications collected through Scopus, Web of Science, and Science Direct. The results confirm the great heterogeneity in the interpretation of the pressure, state, and impacts components. Part of this discrepancy can be attributed to the use of different indicators, as the model is flexible and generic. Overall, the DPSIR is a tool used not only in the scientific field, but also has demonstrated its potential to guide public policy formulation, planning, and decision-making in water resource management.

Random and systematic change analysis in land use change at the category level-A case study on Mu Us area of China

Random and systematic change analysis is gradually becoming a common method for effectively detecting land use change signals from land transition matrix, but most researches focus only on the change characteristics at the transition level. This paper attempted to distinguish random and systematic changes at the category level, and to clarify the meanings of these two types of changes, as well as their indicative significances of change causes. This paper first calculated the random expected value of change area at the category level, and the deviation of the actual change area from the expected value. Then we proposed a method for setting a threshold of the deviation to clearly distinguish random and systematic changes. This method could eliminate the influence of land use classification errors on the distinction. Through analyzing the mathematical formulas of random expected area, this paper further clarified the meanings of random and systematic changes as well as their indicative significances to change causes. Land use change in Mu Us area of China was used as a case study. Practice showed that detecting and analyzing the random and systematic signals at the category level could accurately determine the change trend of land use, which could help to explore the relationship between land use change and external influences, especially human activities.

Analysis of the Spatiotemporal Changes in Watershed Landscape Pattern and Its Influencing Factors in Rapidly Urbanizing Areas Using Satellite Data

Analyzing the spatiotemporal characteristics and causes of landscape pattern changes in watersheds around big cities is essential for understanding the ecological consequence of urbanization and provides a basic reference for the watershed management. This study used a land-use transition matrix and landscape indices to explore the spatiotemporal change of land use and landscape pattern over Liuxihe River basin of Guangzhou in the southeast of China from 1980 to 2015 with multitemporal Landsat satellite data in response to the rapid urbanization process. Primary temporal and spatial influencing factors were first quantitatively identified through grey relation analysis (calculating correlation degree between land use changes and influencing factors) and Geodetector (detecting landscape spatial heterogeneity and its driving factors), respectively. Considerable spatial and temporal differences in land use and landscape pattern changes were observed herein, thus determining the influencing factors of these differences in the Liuxihe River basin. These changes were characterized by a large increase in construction land converted from cropland, particularly in the middle and lower reaches of the basin from 2000 to 2010, causing dramatic fragmentation and homogenization of the landscape pattern there. Meanwhile, the landscape pattern gradually transitioned from an agricultural land use dominant landscape to a construction land use dominant landscape in these regions. Furthermore, the rapid growth of a nonagricultural population and the transformation of industry primarily caused the temporal changes of landscape pattern, and the landscape spatial heterogeneity was mainly caused by the interaction of complicated geomorphology and anthropogenic activities in different spatial locations, particularly after 2000. This study not only provides an improved approach to quantifying the main spatiotemporal influencing factors of landscape pattern changes during different time periods, but also offers a reference for decision-makers to formulate optimal strategies on ecological protection and urban sustainable development of different regions in this study area.

Qualifying Land Use and Land Cover Dynamics and Their Impacts on Ecosystem Service in Central Himalaya Transboundary Landscape Based on Google Earth Engine

Land use and land cover (LULC) changes are regarded as one of the key drivers of ecosystem services degradation, especially in mountain regions where they may provide various ecosystem services to local livelihoods and surrounding areas. Additionally, ecosystems and habitats extend across political boundaries, causing more difficulties for ecosystem conservation. LULC in the Kailash Sacred Landscape (KSL) has undergone obvious changes over the past four decades; however, the spatiotemporal changes of the LULC across the whole of the KSL are still unclear, as well as the effects of LULC changes on ecosystem service values (ESVs). Thus, in this study we analyzed LULC changes across the whole of the KSL between 2000 and 2015 using Google Earth Engine (GEE) and quantified their impacts on ESVs. The greatest loss in LULC was found in forest cover, which decreased from 5443.20 km2 in 2000 to 5003.37 km2 in 2015 and which mainly occurred in KSL-Nepal. Meanwhile, the largest growth was observed in grassland (increased by 548.46 km2), followed by cropland (increased by 346.90 km2), both of which mainly occurred in KSL-Nepal. Further analysis showed that the expansions of cropland were the major drivers of the forest cover change in the KSL. Furthermore, the conversion of cropland to shrub land indicated that farmland abandonment existed in the KSL during the study period. The observed forest degradation directly influenced the ESV changes in the KSL. The total ESVs in the KSL decreased from 36.53 × 108 USD y−1 in 2000 to 35.35 × 108 USD y−1 in 2015. Meanwhile, the ESVs of the forestry areas decreased by 1.34 × 108 USD y−1. This shows that the decrease of ESVs in forestry was the primary cause to the loss of total ESVs and also of the high elasticity. Our findings show that even small changes to the LULC, especially in forestry areas, are noteworthy as they could induce a strong ESV response.

Impact of Land Management on Water Resources, a South African Context

Globally, the changes exerted on the land cover have shown greater impacts on the quality and quantity of water resources and thus affecting catchment’s hydrological response (i.e., runoff, evapotranspiration, infiltration, amongst others). South Africa is a water-scarce country faced with domestic water supply challenges. A systematic review was conducted on the overview impacts of land use/land cover changes on water resources. Despite the country’s best efforts in ensuring the protection and sustainable use of water resources, the review indicated that water quality has been compromised in most parts of the country thus affecting water availability. The increase in water demand with development presents the need for better integrated strategic approaches and a change in behaviour towards water resource and land management. Thus, the review suggested a few possible solutions that will promote sustainable development, while protecting and preserving the integrity of South African water resources.

Variation of soil organic carbon and physical properties in relation to land uses in the Yellow River Delta, China

Soil physical properties and soil organic carbon (SOC) are considered as important factors of soil quality. Arable land, grassland, and forest land coexist in the saline-alkali reclamation area of the Yellow River Delta (YRD), China. Such different land uses strongly influence the services of ecosystem to induce soil degradation and carbon loss. The objective of this study is to evaluate the variation of soil texture, aggregates stability, and soil carbon affected by land uses. For each land use unit, we collected soil samples from five replicated plots from "S" shape soil profiles to the depth of 50 cm (0-5, 5-10, 10-20, 20-30, and 30-50 cm). The results showed that the grassland had the lowest overall sand content of 39.98-59.34% in the top 50 cm soil profile. The content of soil aggregates > 0.25 mm (R_0.25), mean weight diameter and geometric mean diameter were significantly higher in grassland than those of the arable and forest land. R_0.25, aggregate stability in arable land in the top 30 cm were higher than that of forest land, but lower in the soil profile below 20 cm, likely due to different root distribution and agricultural practices. The carbon management index (CMI) was considered as the most effective indicator of soil quality. The overall SOC content and CMI in arable land were almost the lowest among three land use types. In combination with SOC, CMI and soil physical properties, we argued that alfalfa grassland had the advantage to promote soil quality compared with arable land and forest land. This result shed light on the variations of soil properties influenced by land uses and the importance to conduct proper land use for the long-term sustainability of the saline-alkali reclamation region.

Spatiotemporal scale and integrative methods matter for quantifying the driving forces of land cover change

Land cover change (LCC) is a major part of environmental change. Exploring the spatiotemporal differences in LCC and the driving factors is the basis for comprehensive research on landscape planning, and it is of great significance for future effective and sustainable landscape management. In this respect, cross-scale research with integrated methods is worthy of more attention, although some studies have discussed the driving forces of LCCs at either regional or local scale. We combined a structural equation model and a mixed-effects model for quantifying the driving forces of LCCs across different scales in the Loess Plateau (China), which is a typical region that has experienced significant LCCs over recent decades. The impacts of biophysical and socioeconomic factors on different change trajectories (agricultural intensification, urbanization and ecological restoration) were found to be inconsistent at different temporal and spatial scales. We found that topography had a negative effect on agricultural intensification during 1990-2010 and on urbanization during 1990-2000, but it had a positive effect on ecological restoration during 2000-2015 at the regional scale. Moreover, although there was no significant impact from economic development on any type of LCCs at the regional scale, its important influence could be seen in some of the township categories. Therefore, the path and scale dependence of driving forces is an important consideration in landscape planning and management to accommodate local conditions and fine-tuned analysis as decision-making supports.

Evaluation of Driving Forces of Land Use and Land Cover Change in New England Area by a Mixed Method

Understanding the driving forces of land use/cover change (LUCC) is a requisite to mitigate and manage effects and consequences of LUCC. This study aims to analyze drivers of LUCC in New England, USA. It combines meta-study, GIS, and machine learning to identify the important factors of LUCC in the area. Firstly, we conducted a meta-study of the research on LUCC in the New England area and specifically focused on the driving forces analysis. The meta-analysis revealed that the LUCC studies in the research area were highly related with many other research topics, and population and economic factors were the most mentioned drivers of the LUCC. The drivers of LUCC in this study area for the past several decades were relatively well analyzed. However, the study of the main driving forces of recent LUCC is lacking. Then, the determinants of LUCC for the recent years were quantitatively assessed using the random forests (RF) model along with geospatial data processing. Two planning regions in Connecticut and one planning region in Massachusetts were selected to serve as the case study areas. Investigated variables included environmental and biophysical variables, location measures of infrastructure and existing land use, political variables, and demographic and social variables. These drivers were examined for their relations with LUCC processes. Their importance as driving forces was ranked by the RF method. The results show both consistency and inconsistency between the meta-analysis and the RF method. We found that this mixed method can enhance our understanding of driving forces of LUCC and improve the selection quality of important drivers for modeling LUCC. With more solid information, better land management advices for sustainable development may also be provided.

An Analysis of Urban Land Use/Land Cover Changes in Blantyre City, Southern Malawi (1994–2018)

Rapid and unplanned urban growth has adverse environmental and social consequences. This is prominent in sub-Saharan Africa where the urbanisation rate is high and characterised by the proliferation of informal settlements. It is, therefore, crucial that urban land use/land cover (LULC) changes be investigated in order to enhance effective planning and sustainable growth. In this paper, the spatial and temporal LULC changes in Blantyre city were studied using the integration of remotely sensed Landsat imageries of 1994, 2007 and 2018, and a geographic information system (GIS). The supervised classification method using the support vector machine algorithm was applied to generate the LULC maps. The study also analysed the transition matrices derived from the classified map to identify prominent processes of changes for planning prioritisation. The results showed that the built-up class, which included urban structures such as residential, industrial, commercial and public installations, increased in the 24-year study period. On the contrary, bare land, which included vacant lands, open spaces with little or no vegetation, hilly clear-cut areas and other fallow land, declined over the study period. This was also the case with the vegetation class (i.e., forests, parks, permanent tree-covered areas and shrubs). The post-classification results revealed that the LULC changes during the second period (2007–2018) were faster compared to the first period (1994–2007). Furthermore, the results revealed that the increase in built-up areas systematically targeted the bare land and avoided the vegetated areas, and that the vegetated areas were systematically cleared to bare land during the study period (1994–2018). The findings of this study have revealed the pressure of human activities on the land and natural environment in Blantyre and provided the basis for sustainable urban planning and development in Blantyre city.

Surface Water Quality Analysis Using CORINE Data: An Application to Assess Reservoirs in Poland

Reservoirs are formed through the artificial damming of a river valley. Reservoirs, among others, capture polluted load transported by the tributaries in the form of suspended and dissolved sediments and substances. Therefore, reservoirs are treated in the European Union (EU) as “artificial” or “heavily modified” surface water bodies. The reservoirs’ pollutant load depends to a large extent on the degree of anthropogenic impact in the respective river catchment area. The purpose of this paper is to assess the mutual relation between the catchment area and the reservoirs. In particular, we focus on the effects of certain land use/land cover on reservoirs’ water quality. For this study, we selected twenty Polish reservoirs for an in-depth analysis using 2018 CORINE Land Cover data. This analysis allowed the identification of the main triggering factors in terms of water quality of the respective reservoirs. Moreover, our assessment clearly shows that water quality of the analysed dam reservoirs is directly affected by the composition of land use/land cover, both of the entire total reservoir catchment areas and the directly into the reservoir draining sub-catchment areas.

Land Use and Land Cover Change Modeling and Future Potential Landscape Risk Assessment Using Markov-CA Model and Analytical Hierarchy Process

Land use and land cover change (LULCC) has directly played an important role in the observed climate change. In this paper, we considered Dujiangyan City and its environs (DCEN) to study the future scenario in the years 2025, 2030, and 2040 based on the 2018 simulation results from 2007 and 2018 LULC maps. This study evaluates the spatial and temporal variations of future LULCC, including the future potential landscape risk (FPLR) area of the 2008 great (8.0 Mw) earthquake of south-west China. The Cellular automata–Markov chain (CA-Markov) model and multicriteria based analytical hierarchy process (MC-AHP) approach have been considered using the integration of remote sensing and GIS techniques. The analysis shows future LULC scenario in the years 2025, 2030, and 2040 along with the FPLR pattern. Based on the results of the future LULCC and FPLR scenarios, we have provided suggestions for the development in the close proximity of the fault lines for the future strong magnitude earthquakes. Our results suggest a better and safe planning approach in the Belt and Road Corridor (BRC) of China to control future Silk-Road Disaster, which will also be useful to urban planners for urban development in a safe and sustainable manner.

Effects of Landscape Development Intensity on River Water Quality in Urbanized Areas

Urban development and human activities have greatly changed the appearance of urban landscapes, and also affect urban river water environments. Rapidly urbanized regions in China face particularly severe pressures and challenges in alleviating degradation of river water quality. Information is needed on which indexes of landscape development intensity in rapidly-urbanized areas are the key factors affecting the quality of river water environments, and how these factors affect water quality. In order to answer these questions, this research selected six indexes belonging to three dimensions for landscape development intensity evaluation. Based on five water quality parameters of 20 rivers and the land use data of 20 small watersheds of Liangjiang New Area, Chongqing, China in 2014, this research explored the correlation between the landscape development intensity indexes and river water quality through redundancy analysis. We found that the impervious surface rate and the land average fixed asset investment are the key indexes to affect river water quality. Regulating the corresponding indexes at the urban planning and design level, as well as the decision making level, can effectively achieve the goal of improving urban river water quality. The conclusions inspire strategies in planning and design, and are helpful for government decision making to effectively protect river water environment in rapidly urbanized areas in the developing countries.

Changes in Soil Microbial Biomass, Community Composition, and Enzyme Activities After Half-Century Forest Restoration in Degraded Tropical Lands

Soil carbon (C) sequestration and stabilization are determined by not only the C input to the soil but also the decomposition rate of soil organic matter (SOM), which is mainly mediated by soil microbes. Afforestation, an effective practice to restore forests from degraded or bare lands, may alter soil microbial properties, and thus soil C and nitrogen (N) dynamics. The aim of this study was to investigate the impacts of different afforestation strategies on soil microbial compositions and activities after afforestation for half a century. Soil samples were collected from two afforested sites (i.e., a restored secondary forest (RSF) and a managed Eucalyptus forest (MEP)) and two reference sites (i.e., a nearby undisturbed forest (UF), representing the climax vegetation and a bare land (BL), representing the original state before restoration) in south China. We quantified the soil microbial biomass, microbial community compositions, and activities of nine extracellular enzymes at different soil depths and in different seasons. Results showed that the soil microbial biomass, all the main soil microbial groups, and the activities of all extracellular enzymes were significantly increased after afforestation compared to the BL sites, while the ratios of fungi/bacteria (F/B), specific enzyme activities, and the ecoenzymatic stoichiometry were significantly decreased regardless of the season and soil depth. Between the two afforested sites, these microbial properties were generally higher in the RSF than MEP. However, the microbial properties in the RSF were still lower than those in the UF, although the differences varied with different seasons, soil depths, and microbial groups or enzymes. Our findings demonstrated that afforestation might significantly improve microbial properties. Afforestation is more effective in mixed-species plantation than in the monoculture Eucalyptus plantation but needs a much longer time to approach an equivalent level to the primary forests.

Four decades' dynamics of coastal blue carbon storage driven by land use/land cover transformation under natural and anthropogenic processes in the Yellow River Delta, China

Land reclamation can impact a variety of ecosystem services provided by coastal wetlands. The dynamics of coastal blue carbon storage (CBCS) altered by land use/land cover (LULC) transformation and its linkage with natural and anthropogenic driving processes was analyzed in the Yellow River Delta (YRD), China. Using LULC data in the YRD during 1970-2010, the LULC transformation in four periods (i.e., 1970-1980, 1980-1990, 1990-2000 and 2000-2010) and their cumulative conversions within coastal wetlands were tracked to investigate the flow of LULC transformation. The spatiotemporal dynamics of the CBCS were then modeled and investigated by InVEST based on the LULC transformation in relation to their driving processes. The results indicated that the CBCS in the YRD has been substantially altered by continuous LULC transformation driven by the natural and anthropogenic processes, totally decreased by 10.2% (1.63 × 10⁶ Mg) during 1970-2010 followed the loss of 2028 km² natural wetlands converted to socioeconomic land use. The 78% of increased CBCS were contributed by single natural (e.g., succession) or anthropogenic (e.g., restoration) driving process at the seaward edge within tidal area, whereas 71% of decreased CBCS was linked with multiple driving processes in inland areas. In addition, the anthropogenic driving processes caused much greater loss (-5.97 × 10⁵ Mg) than gain (6.81 × 10⁴ Mg) in CBCS, compared with a net gain of CBCS (1.04 × 10⁴ Mg) brought by the natural driving processes. The study can facilitate to develop coastal management strategy to balance and mitigate the conflicted LULC between socioeconomic development and maintenance of multiple ecosystem services incorporating CBCS.

Land Use and Land Cover Changes, and Environment and Risk Evaluation of Dujiangyan City (SW China) Using Remote Sensing and GIS Techniques

Understanding of the Land Use and Land Cover (LULC) change, its transitions and Landscape risk (LR) evaluation in earthquake-affected areas is important for planning and urban sustainability. In the present study, we have considered Dujiangyan City and its Environs (DCEN), a seismic-prone area close to the 2008 Wenchuan earthquake (8.0 Mw) during 2007–2018. Five different multi-temporal data sets for the years 2007, 2008, 2010, 2015, and 2018 were considered for LULC mapping, followed by the maximum likelihood supervised classification technique. The individual LULC maps were further used in four time periods, i.e., 2007–2018, 2008–2018, 2010–2018, and 2015–2018, to evaluate the Land Use and Land Cover Transitions (LULCT) using combined remote sensing and GIS (Geographical Information System). Furthermore, multi-criteria evaluation (MCE) techniques were applied for LR mapping. The results of the LULC change data indicate that built-up, agricultural area, and forest cover are the prime categories that had been changed by the natural and anthropogenic activities. LULCT, along with multi-parameters, are suggested to avoid development in fault-existing areas that are seismically vulnerable for future landscape planning in a sustainable manner.

The Effects of Land Use and Land Cover Geoinformation Raster Generalization in the Analysis of LUCC in Portugal

Multiple land use and land cover (LUC) datasets are available for the analysis of LUC changes (LUCC) in distinct territories. Sometimes, different LUCC results are produced to characterize these changes for the same territory and the same period. These differences reflect: (1) The different properties of LUC geoinformation (GI) used in the LUCC assessment, and (2) different criteria used for vector-to-raster conversion, namely, those deriving from outputs with different spatial resolutions. In this research, we analyze LUCC in mainland Portugal using two LUC datasets with different properties: Corine Land Cover (CLC 2006 and 2012) and LUC official maps of Portugal (Carta de Ocupação do Solo, COS 2007 and 2010) provided by the European Environment Agency (EEA) and the General Directorate for Territorial Development (DGT). Each LUC dataset has undergone vector-to-raster conversion, with different resolutions (10, 25, 50, 100, and 200 m). LUCC were analyzed based on the vector GI of each LUC dataset, and with LUC raster outputs using different resolutions. Initially, it was observed that the areas with different LUC types in two LUC datasets in vector format were not similar—a fact explained by the different properties of this type of GI. When using raster GI to perform the analysis of LUCC, it was observed that at high resolutions, the results are identical to the results obtained when using vector GI, but this ratio decreases with increased cell size. In the analysis of LUCC results obtained with raster LUC GI, the outputs with pixel size greater than 100 m do not follow the same trend of LUCC obtained with high raster resolutions or using LUCC obtained with vector GI. These results point out the importance of the factor form and the area of the polygons, and different effects of amalgamation and dilation in the vector-to-raster conversion process, more evident at low resolutions. These findings are important for future evaluations of LUCC that integrate raster GI and vector/raster conversions, because the different LUC GI resolution in line with accuracy can explain the different results obtained in the evaluation of LUCC. The present work demonstrates this fact, i.e., the effects of vector-to-raster conversions using various resolutions culminated in different results of LUCC.

The Impacts of Land Use Patterns on Water Quality in a Trans-Boundary River Basin in Northeast China Based on Eco-Functional Regionalization

The relationships between land use patterns and water quality in trans-boundary watersheds remain elusive due to the heterogeneous natural environment. We assess the impact of land use patterns on water quality at different eco-functional regions in the Songhua River basin during two hydrological seasons in 2016. The partial least square regression indicated that agricultural activities associated with most water quality pollutants in the region with a relative higher runoff depth and lower altitude. Intensive grazing had negative impacts on water quality in plain areas with low runoff depth. Forest was related negatively with degraded water quality in mountainous high flow region. Patch density and edge density had major impacts on water quality contaminants especially in mountainous high flow region; Contagion was related with non-point source pollutants in mountainous normal flow region; landscape shape index was an effective indicator for anions in some eco-regions in high flow season; Shannon’s diversity index contributed to degraded water quality in each eco-region, indicating the variation of landscape heterogeneity influenced water quality regardless of natural environment. The results provide a regional based approach of identifying the impact of land use patterns on water quality in order to improve water pollution control and land use management.

Peri-Urbanization and Rurbanization in Leiria City: the Importance of a Planning Framework

The objective of this study is to evaluate the spatial and temporal dynamics of land use in the city of Leiria, which is located in central Portugal, and its relation to the planning framework. The analysis is based on land-use change recognition in the period 1958–2011, calculation of the stability grade indicator, the losses and gains between classes, and the rate of artificialization. The results show an increase of the artificial areas, namely in continuous and discontinuous urban fabric, contrasting with a continuous decrease of the agricultural land-use classes, giving origin to peri-urbanization and rurbanization processes. We can also observe a large fragmentation of the landscape in the city of Leiria, representing rapid urban expansion that is fundamentally related to the increase of residential and industrial areas, and afterwards, tertiary growth. This study also demonstrated the relation of a land-use and planning framework that works as a driving force for land-use changes. This underlines the importance of strategic regional planning instruments in managing urban sprawl and the artificialization processes of medium-sized cities.

Global land-water nexus: Agricultural land and freshwater use embodied in worldwide supply chains

As agricultural land and freshwater inextricably interrelate and interact with each other, the conventional water and land policy in "silos" should give way to nexus thinking when formulating the land and water management strategies. This study constructs a systems multi-regional input-output (MRIO) model to expound global land-water nexus by simultaneously tracking agricultural land and freshwater use flows along the global supply chains. Furthermore, land productivity and irrigation water requirements of 160 crops in different regions are investigated to reflect the land-water linkage. Results show that developed economies (e.g., USA and Japan) and major large developing economies (e.g., mainland China and India) are the overriding drivers of agricultural land and freshwater use globally. In general, significant net transfers of these two resources are identified from resource-rich and less-developed economies to resource-poor and more-developed economies. For some crops, blue water productivity is inversely related to land productivity, indicating that irrigation water consumption is sometimes at odds with land use. The results could stimulus international cooperation for sustainable land and freshwater management targeting on original suppliers and final consumers along the global supply chains. Moreover, crop-specific land-water linkage could provide insights for trade-off decisions on minimizing the environmental impacts on local land and water resources.

Spatial scale and seasonal dependence of land use impacts on riverine water quality in the Huai River basin, China

Land use pattern is an effective reflection of anthropic activities, which are primarily responsible for water quality deterioration. A detailed understanding of relationship between water quality and land use is critical for effective land use management to improve water quality. Linear mixed effects and multiple regression models were applied to water quality data collected from 2003 to 2010 from 36 stations in the Huai River basin together with topography and climate data, to characterize the land use impacts on water quality and their spatial scale and seasonal dependence. The results indicated that the influence of land use categories on specific water quality parameter was multiple and varied with spatial scales and seasons. Land use exhibited strongest association with dissolved oxygen (DO) and ammonia nitrogen (NH₃-N) concentrations at entire watershed scale and with total phosphorus (TP) and fluoride concentrations at finer scales. However, the spatial scale, at which land use exerted strongest influence on instream chemical oxygen demand (COD) and biochemical oxygen demand (BOD) levels, varied with seasons. In addition, land use composition was responsible for the seasonal pattern observed in contaminant concentrations. COD, NH₃-N, and fluoride generally peaked during dry seasons in highly urbanized regions and during rainy seasons in less urbanized regions. High proportion of agricultural and rural areas was associated with high nutrient contamination risk during spring. The results highlight the spatial scale and seasonal dependence of land use impacts on water quality and can provide scientific basis for scale-specific land management and seasonal contamination control.

Understanding the relationship of land uses and water quality in Twenty First Century: A review

Rising food, housing and energy demand of increasing population creates an immense pressure on water resources, especially on water quality. The water quality around the globe is degrading primarily due to intense agricultural activities associated with rapid urbanization. This study attributes to cause of water quality problem, indices to measure water quality, methods to identify proper explanatory variables to water quality and it's processing to capture the special effect, and finally modeling of water quality using identified explanatory variables to provide insights. This would help policymakers and watershed managers to take necessary steps to protect water quality for the future as well as current generation. Finally, some knowledge gaps are also discussed which need to be addressed in the future studies.

Water Quality Index (WQI) of Jaguari and Atibaia Rivers in the region of Paulínia, São Paulo, Brazil

Due to the concern with the quality of hydric resources, the monitoring is essential to evaluate and identify the anthropogenic and environmental interferences in a quantitative and qualitative level. In order to assist the interpretation of the water status of hydric bodies, the gathering of analytical data often considers the Water Quality Index (WQI). This index transforms technical information in description of the water quality status, highlighting the effectiveness of its use and guiding the decision-making process when necessary. The aim of this research is to assess the water quality of a region in São Paulo State, Brazil, by means of the WQI of Jaguari and Atibaia Rivers. The period of intense drought, which affected the Brazilian southeast in 2014, was evaluated and compared to the mean values recorded from October 2009 to March 2015, correlating the values of Escherichia coli and the biochemical oxygen demand (BOD). One hundred nine samples were collected, being 53 from dry seasons, between October and March, and 56 from rainy seasons, between April and September. The WQIs in Jaguari and Atibaia Rivers, during dry season, were of 42.2 (medium) and 36.7 (bad), respectively. The same pattern was registered for the dry season, for both rivers, with indices values of 40.1 for Jaguari River (medium) and 34.9 for Atibaia River (bad). This research presented the need of an effective evaluation of the environmental quality and preservation by competent organs for both rivers. Due to the detected conditions, special attention should be given to the Atibaia River.

Spatial driving forces of dominant land use/land cover transformations in the Dongjiang River watershed, Southern China

Information about changes in, and causes of, land use/land cover (LULC) is crucial for land use resource planning. We investigated the processes involved in LULC change (LUCC) in the Dongjiang Watershed, in Southern China, over a 15-year period to gain a better understanding of the causes of the main types of LUCC. Using a depth transition matrix and redundancy analysis (RDA), the major types and causes of LUCC for each LULC type over the past 15 years were identified. LUCC exhibited obvious net change, relatively low persistence, and high swap change. The swap changes in most LULC types were considered as a strong signal of LULC transformations. The driving forces behind swap changes were quantified and identified through RDA. The results showed that all driving forces played important roles in explaining swap changes of LULC, although the relative effects of these drivers varied widely with both LULC type and time period. Swap changes of the LULC types were generally classified into two categories. Some, e.g., built-up land and wetland, were affected mostly by landform and/or distance factors, while others, e.g., grassland and woodland, were modulated mostly by climate and/or socioeconomic factors. Selected spatial driving forces and local land use policies played important roles in explaining the dominant LUCC types, but on different timescales. These findings may improve understanding of the detailed processes involved in LUCC, landscape transformation, and the causes of LUCC in other areas with extensive LUCC and could help managers plan, design, and implement land resource management.

Soil microbial community and its interaction with soil carbon and nitrogen dynamics following afforestation in central China

Afforestation may alter soil microbial community structure and function, and further affect soil carbon (C) and nitrogen (N) dynamics. Here we investigated soil microbial carbon and nitrogen (MBC and MBN) and microbial community [e.g. bacteria (B), fungi (F)] derived from phospholipid fatty acids (PLFAs) analysis in afforested (implementing woodland and shrubland plantations) and adjacent croplands in central China. Relationships of microbial properties with biotic factors [litter, fine root, soil organic carbon (SOC), total nitrogen (TN) and inorganic N], abiotic factors (soil temperature, moisture and pH), and major biological processes [basal microbial respiration, microbial metabolic quotient (qCO2), net N mineralization and nitrification] were developed. Afforested soils had higher mean MBC, MBN and MBN:TN ratios than the croplands due to an increase in litter input, but had lower MBC:SOC ratio resulting from low-quality (higher C:N ratio) litter. Afforested soils also had higher F:B ratio, which was probably attributed to higher C:N ratios in litter and soil, and shifts of soil inorganic N forms, water, pH and disturbance. Alterations in soil microbial biomass and community structure following afforestation were associated with declines in basal microbial respiration, qCO2, net N mineralization and nitrification, which likely maintained higher soil carbon and nitrogen storage and stability.

Water quality changes in response to urban expansion: spatially varying relations and determinants

Urban expansion is an important stressor to water bodies, and the spatial variations of their relations are increasingly highlighted by recent studies. What remain unclear, however, are the underlying drivers to the spatial variability. The paper was not limited to modeling spatially varying linkages but also drew attention to the local anthropogenic influential factors that shape land-water relations. We employed geographically weighted regression to examine the relationships between urban expansion (measured by land use change intensity) and water quality changes (focusing on six water quality indicators) in a recently fast-growing Chinese city, Lianyungang. Specifically, we analyzed how the local characteristics including urbanization level, environmental management, industrial zone expansion, and land use composition, attributed to the varying responses of water quality changes. Results showed that urbanization level significantly affects land-water linkages. Remarkable water quality improvement was accompanied by urbanization in highly developed watersheds, primarily due to strong influence from extensive water management practices (particularly for COD, BOD, NH3-N, and TP). By contrast, water qualities of less-urbanized watersheds were more sensitive and negatively responsive to land use changes. Clustering industrial activities acted as distinct contributor to Hg contamination, while boosted organic pollution control in highly urbanized areas. The approach proposed in the study can locate and further zoom into the hot-spots of human-water interactions, thereby contributing to better solutions for mitigating undesirable impacts of urbanization on water environment.

Land use and land cover changes in Zêzere watershed (Portugal)--Water quality implications

To understand the relations between land use allocation and water quality preservation within a watershed is essential to assure sustainable development. The land use and land cover (LUC) within Zêzere River watershed registered relevant changes in the last decades. These land use and land cover changes (LUCCs) have impacts in water quality, mainly in surface water degradation caused by surface runoff from artificial and agricultural areas, forest fires and burnt areas, and caused by sewage discharges from agroindustry and urban sprawl. In this context, the impact of LUCCs in the quality of surface water of the Zêzere watershed is evaluated, considering the changes for different types of LUC and establishing their possible correlations to the most relevant water quality changes. The results indicate that the loss of coniferous forest and the increase of transitional woodland-shrub are related to increased water's pH; while the growth in artificial surfaces and pastures leads mainly to the increase of soluble salts and fecal coliform concentration. These particular findings within the Zêzere watershed, show the relevance of addressing water quality impact driven from land use and should therefore be taken into account within the planning process in order to prevent water stress, namely within watersheds integrating drinking water catchments.

Effects of logging activities on ecological water quality indicators in the Berasau River, Johor, Malaysia

Influence of deforestation on biodiversity of aquatic organisms was investigated in a stream in the Ulu Sedili Forest Reserve. The stream was monitored five (5) times from December 2011 until December 2012 with 2-month intervals. Sampling of benthic communities was carried out using rectangular dip net while water quality study using a YSI ProPlus meter and the rest were done in the laboratory. Physicochemical parameters and water quality index (WQI) calculation showed no significant difference among the investigated events. WQI classified the Berasau River between Class II (good) to III (moderate) of river water quality. In total, 603 individuals representing 25 taxa that were recorded with Decapods from genus Macrobrabchium were widely distributed. Several intolerant taxa, especially Ephemeroptera and Odonata, were also observed in this river. According to Pearson's correlation analysis, the richness and diversity indices were generally influenced by water quality parameters represented by WQI (P < 0.01). In conclusion, logging activities have strong attributes for variation in benthic macroinvertebrate assemblage.

Agro-forest landscape and the 'fringe' city: a multivariate assessment of land-use changes in a sprawling region and implications for planning

The present study evaluates the impact of urban expansion on landscape transformations in Rome's metropolitan area (1500 km(2)) during the last sixty years. Landscape composition, structure and dynamics were assessed for 1949 and 2008 by analyzing the distribution of 26 metrics for nine land-use classes. Changes in landscape structure are analysed by way of a multivariate statistical approach providing a summary measure of rapidity-to-change for each metric and class. Land fragmentation increased during the study period due to urban expansion. Poorly protected or medium-low value added classes (vineyards, arable land, olive groves and pastures) experienced fragmentation processes compared with protected or high-value added classes (e.g. forests, olive groves) showing larger 'core' areas and lower fragmentation. The relationship observed between class area and mean patch size indicates increased fragmentation for all uses of land (both expanding and declining) except for urban areas and forests. Reducing the impact of urban expansion for specific land-use classes is an effective planning strategy to contrast the simplification of Mediterranean landscape in peri-urban areas.

Monitoring land use/land cover transformations from 1945 to 2007 in two peri-urban mountainous areas of Athens metropolitan area, Greece

The aims of this study were to map and analyze land use/land cover transitions and landscape changes in the Parnitha and Penteli mountains, which surround the Athens metropolitan area of Attica, Greece over a period of 62 years. In order to quantify the changes between land categories through time, we computed the transition matrices for three distinct periods (1945-1960, 1960-1996, and 1996-2007), on the basis of available aerial photographs used to create multi-temporal maps. We identified systematic and stationary transitions with multi-level intensity analysis. Forest areas in Parnitha remained the dominant class of land cover throughout the 62 years studied, while transitional woodlands and shrublands were the main classes involved in LULC transitions. Conversely, in Penteli, transitional woodlands, along with shrublands, dominated the study site. The annual rate of change was faster in the first and third time intervals, compared to the second (1960-1996) time interval, in both study areas. The category level analysis results indicated that in both sites annual crops avoided to gain while discontinuous urban fabric avoided to lose areas. At the transition level of analysis, similarities as well as distinct differences existed between the two areas. In both sites the gaining pattern of permanent crops with respect to annual crops and the gain of forest with respect to transitional woodland/shrublands were stationary across the three time intervals. Overall, we identified more systematic transitions and stationary processes in Penteli. We discussed these LULC changes and associated them with human interference (activity) and other major socio-economic developments that were simultaneously occurring in the area. The different patterns of change of the areas, despite their geographical proximity, throughout the period of analysis imply that site-specific studies are needed in order to comprehensively assess the driving forces and develop models of landscape transformation in Mediterranean areas.