Temporal Land Cover Changes Research Articles

Fragmentación de pastizales en el centro de la provincia de Buenos Aires, mediante imágenes LANDSAT

En el presente trabajo, se empleó una combinación de mapas dinámicos de cobertu- ras y métricas de paisaje basados en imágenes satelitales para cuantificar los cam- bios espacio-temporales de coberturas y los patrones de fragmentación en el centro de la provincia de Buenos Aires (Argentina), en el período 1974-2011. Esta área de estudio cubre dos zonas agroecológicas: la Pampa Deprimida y la Pampa Interior. A diferencia de otras regiones de Los Pastizales del Río de La Plata, el pastizal nativo ha sido reemplazado por una matriz de pastos cortos (más adaptada al pastoreo vacuno): durante todo el período de estudio, el pastizal nativo decreció 2762,1 Nm2 en un área de estudio de 21,911.4Nm2. El patrón de fragmentación en el paisaje presentó diferencias espaciales significativas entre las zonas agroecológicas anali- zadas, con un mejor estado de conservación de los pastizales en la Pampa Deprimi- da. La identificación de este patrón espacial debería promover políticas de conservación de la biodiversidad y manejo sustentable de este paisaje.

D-RUSLE: a dynamic model to estimate potential soil erosion with satellite time series in the Italian Alps

ABSTRACTSoil erosion is addressed as one of the main hydrogeological risks in the European Union. Since the average annual soil loss rate exceeds the annual average formation rate, soil is considered as a non-renewable resource. Besides, human activities, human-induced forces and climate change have further accelerated the erosion processes. Therefore, understanding soil erosion spatial and temporal trends could provide important information for supporting government land-use policies and strategies for its reduction. This paper describes the Dynamic Revised Universal Soil Loss Equation (D-RUSLE) model, a modified version of the well-known RUSLE model. The RUSLE model formulation was modified to include variations in rainfall erosivity and land-cover to provide more accurate estimates of the potential soil erosion in the Italian Alps. Specifically, the modelling of snow occurrence and the inclusion of Earth Observation data allow dynamic estimation of both spatial and temporal land-cover changes. Results obtained in Val Camonica (Italy) show that RUSLE model tends to overestimate erosion rates in Autumn/Winter because not considering snow cover and vegetation dynamics. The assimilation of satellite-derived information in D-RUSLE allows a better representation of soil erosion forcing, thus proving a more accurate erosion estimate for supporting government land-use policies and strategies for reducing this phenomenon.

Analyses of Time Series InSAR Signatures for Land Cover Classification: Case Studies over Dense Forestry Areas with L-Band SAR Images.

As demonstrated in prior studies, InSAR holds great potential for land cover classification, especially considering its wide coverage and transparency to climatic conditions. In addition to features such as backscattering coefficient and phase coherence, the temporal migration in InSAR signatures provides information that is capable of discriminating types of land cover in target area. The exploitation of InSAR signatures was expected to provide merits to trace land cover change in extensive areas; however, the extraction of suitable features from InSAR signatures was a challenging task. Combining time series amplitudes and phase coherences through linear and nonlinear compressions, we showed that the InSAR signatures could be extracted and transformed into reliable classification features for interpreting land cover types. The prototype was tested in mountainous areas that were covered with a dense vegetation canopy. It was demonstrated that InSAR time series signature analyses reliably identified land cover types and also recognized tracing of temporal land cover change. Based on the robustness of the developed scheme against the temporal noise components and the availability of advanced spatial and temporal resolution SAR data, classification of finer land cover types and identification of stable scatterers for InSAR time series techniques can be expected. The advanced spatial and temporal resolution of future SAR assets combining the scheme in this study can be applicable for various important applications including global land cover changes monitoring.

Analysing Temporal and Spatial Changes in Land Cover: the Case of Drahna Forest Subdistrict Directorate

Aim of study: In this study, changes in land cover and land use from designing forest management plans within a plan unit up until today in the field of study are analysed under various categories.Field of study: Drahna Forest Subdistrict Directorate (FSD) under Ulus Forest Operation Directorate (FOD) of Zonguldak Regional Directorate of Forestry (RDF) was selected as the field of this study.Material and Method: Forest management plans and forest cover type maps for the related plan unit were utilized in the study. Forest cover type maps for the years 1967-1986 and 1986-2005 were digitized by using Geographical Information System tool ArcGIS version 10.4, whereas forest cover type map for the years 2006-2024 was obtained digitized from the relevant authority.Results: It was found that there was an increase of 227.6 ha in forest land in addition to a decrease of 227.6 ha in non-forest land between 1967 and 2006. It was also determined that there was a decrease of 2,295.33 ha in sparse forest land (with less than 10% canopy closure) whereas an increase of 2,523 ha in productive forest land (canopy closure above 11%). Further, a decrease of 369.91 ha in agricultural land in contrast with an increase of 36.69 ha in treeless forest land (TFL) and of 105.62 ha in settlement land were observed as well in non-forest lands.Emphasis of study: Within a period of 40 years between 1967 and 2006, immigration led to decreases in agricultural land and increases in forest land within the field of this study.

Monitoring and mapping rural urbanization and land use changes using Landsat data in the northeast subtropical region of Vietnam

Rapid land use change has taken place in many neighboring provinces of the capital of Vietnam such as Thai Nguyen province over the past 2 decades due to urbanization and industrialization. Deriving accurate and updated land cover and land-use change information is essential for the environmental monitoring, evaluation and management. In this study, a robust classification algorithm, Random Forest (RF) was employed in R programming to map and monitor temporal and spatial characteristics of urban expansion and land-use change in Thai Nguyen province, Vietnam. The results showed that there has been a substantial and uneven urban growth and a significant loss of forest and cropland between 2000 and 2016. Most of the conversion of agriculture and forest into built-up and mining uses were largely detected in rural regions and suburbs of Thai Nguyen. Further GIS analysis revealed that rapid urban and industrial expansion was spatially occurred in the southern rural portions and central area of the province. This study also demonstrates the potential of Landsat data and combination of R programming language and GIS to provide a timely, accurate and economical means to map and analyze temporal land cover and land use changes for future national and local land development planning.

EFFECTS OF URBAN SPRAWL ON FOREST CONSERVATION IN A METROPOLITAN WATER SOURCE AREA

ABSTRACT The clearing of native vegetation in water source areas and its effects on water supply availability have become a major concern in large metropolises. This study examined the spatial and temporal changes in land use and cover and their effects on the conservation of Atlantic Forest in a water source area in the Metropolitan Region of São Paulo that is the second most densely populated territory in Brazil, the municipality of Diadema. Historical maps and trend scenarios were developed by applying the Markov chain in association with cellular automata. Forest conservation was assessed based on a set of landscape metrics of resource availability, fragment isolation, and trends of forest fragmentation. Our findings revealed an increase in urban growth of 37% in the last five decades directly associated to the clearing of 50% of forests in intermediate/advanced stages and 40% in early stages. The main drivers of landscape change were human-modified fields (41%) and net roads (54%). Optimal resource availability was drastically reduced (75%) while isolation increased (361.5%) among existing forest fragments. Therefore, future trends indicate that, without changes in the management of the area, deforestation may occur rapidly and continuously until 10% of forest remains, leading to potential adverse effects on water availability and quality of the Billings Reservoir and the local biodiversity.

Proposing an agricultural belt to protect a city’s semi-rural characteristics: The example of Bartın, Turkey

Urban sprawl, a type of urban expansion, is perceived as a global problem due to changes in land conversions and landscape patterns. Farms, forests and shores have been converted into urban areas; this transformation affects energy flow, biochemical cycles and climatic conditions. To follow and evaluate the physical, social and ecological results of urban sprawl, we identified and measured temporal changes in land use and land cover. This is especially important for urban planning policies. In this study, temporal change is identified in the city of Bartın using remote sensing and landscape metrics. An analysis of land cover and land transformation was done with LANDSAT5 TM/ETM satellite images from 1985 and 2015. These images were used to identify agricultural areas as land that has most commonly undergone drastic changes. Bartın is a small semi-rural city that has undergone significant changes. Among the most important reasons for these changes were uncontrolled urban sprawl due to political and administrative decisions that lacked long-term planning and a comprehensive city plan. This study examined the risk factors for loss of semi-rural characteristics using the example of Bartın city. To protect semi-rural city characteristics and control urban sprawl, we propose an agricultural belt based on spatial suitability and an evaluation of landscape metrics.

Analysis of Land Use Change and Forestation in Response to Demographic Movement and Reduction of Forest Crime

The sustainable management of natural resources requires a thorough analysis of the land-use and forest cover dynamics and the effective factors in the changes occurring in them. This study investigated the roles played by social factors in the temporal changes in land cover and deforestation within the Torul State Forest Enterprise in northeastern Turkey. Between 2005 and 2016, this area was examined in terms of forest crime, demographic movement and forest dynamics using the Geographic Information System (GIS). Major changes were observed in the temporal dynamics of the forested areas and their parameters, with an overall net increase of 3.26%. There was a productive forest area increase of 16.459 ha. Regenerated-young stand areas had increased because of the regeneration activities carried out over the period. This was partially due to decreased forest crime, decreased rural population and increased gross national product (GNP), which had been below Turkey’s average.

A Feature-Based Approach of Decision Tree Classification to Map Time Series Urban Land Use and Land Cover with Landsat 5 TM and Landsat 8 OLI in a Coastal City, China

Accurate mapping of temporal changes in urban land use and land cover (LULC) is important for monitoring urban expansion and changes in LULC, urban planning, environmental management, and environmental modeling. In this study, we present a feature-based approach of the decision tree classification (FBA-DTC) method for mapping LULC based on spectral and topographic information. Landsat 5 TM and Land 8 OLI images were employed, and the technique was applied to the coastal city of Xiamen, China. The method integrates multi-spectral features such as SAVI (soil adjustment vegetation index), NDWI (normalized water index), MNDBaI (modified normalized difference barren index), BI (brightness index), and WI (wetness index), with topographic features including DEM and slope. In addition, the new approach distinguishes between fallow land and cropland, and separates high-rise buildings from beaches and water bodies. Several of the FBA-DTC parameters (or rules) from 1997 to 2015 remained constant (i.e., DEM and slope), whereas others changed slightly. WI was negatively related to percent area of beach land, and BI was negatively related to percent area of arable land. The FBA-DTC method had an average user’s accuracy (UA) of 91.36% for built-up land, an average overall accuracy (OA) of 92.13%, and a Kappa coefficient (KC) of 0.90 for the period from 2003 to 2015, representing respective increases of 15.87%, 10.17%, and 0.13, compared with values calculated using maximum likelihood classification (MLC). Over the past 12 years, built-up land increased from 23.67% to 43.17% owing to occupation of coastal reclamation, arable land, and forest land. The FBA-DTC method presented here is a valuable technique for evaluating urban growth and changes in LULC classification for coastal cities.

A crop phenology knowledge-based approach for monthly monitoring of construction land expansion using polarimetric synthetic aperture radar imagery

Synthetic aperture radar (SAR) remote sensing, which is independent of weather conditions, can monitor construction land expansion at short intervals for early prevention of unauthorized land use. However, seasonal crop growth creates land cover changes that are hardly distinguishable from land developments by using the traditional approach that employs two SAR images for detection. This study proposes a knowledge-based approach based on crop phenology to detect monthly construction land expansion by using consecutive polarimetric SAR imagery. The innovation of the proposed approach is the utilization of crop phenology knowledge to remove errors introduced by seasonal crop growth. In this approach, using crop phenology knowledge asa basis, a knowledge-based system is built to automatically determine when seasonal crop growth yields considerable errors. Monthly land developments are normally detected by comparing two consecutive images, but in the periods when the errors from crop growth are considerable, monthly detection results are calibrated using an additional third consecutive image, which is utilized to identify the errors based on the difference in temporal land cover change between land development and crop growth. A comparison was made between the proposed approach and the traditional approach for the monthly monitoring of construction land expansion. We found that seasonal paddy growth created many errors by using the traditional approach. The proposed approach substantially reduced these errors. Compared with the traditional approach, the proposed approach reduced errors by up to 87.33% with an average overall error rate of only 0.24%. The results indicated that the proposed approach outperforms the traditional approach in monitoring monthly construction land expansion and suppressing the disturbance from seasonal crop growth.

Analysis of temporal changes in land cover and landscape metrics of a managed forest in the west Black Sea region of northern Turkey: 1970–2010

Forest structure changes continuously by natural and anthropogenic effects. Because the level of goods and services provided by forest ecosystems are related to this structure, some attributes have to be controlled while they are being managed. In this paper we describe the long-term temporal changes in land area and landscape metrics related to different land uses of a managed forest in Turkey. The study was carried out for the Daday Forest Planning Unit located in the west Black Sea region of northern Turkey. The total area is 16,813 ha and besides wood production, it is managed for erosion control, public health, aesthetics, and recreation. Stand type maps that were constructed in 1970, 1989, 1999, and 2010 were used in this analysis. Transition matrixes that illustrate area changes among cover types and temporal changes on some landscape metrics were obtained using Geographic Information Systems. Stands were separated into small patches, and thus the number of patches increased nearly two-fold between 1970 and 2010. The total forest edge increased and through the associated fragmentation, the amount of core forest area decreased at the landscape scale. Landscape metrics were applied to digitized versions of historical maps to assess how forest area changed. Human use of the land has changed, forest management practices have evolved, and these along with natural forest growth have contributed to interesting changes in landscape character.

Spatial and temporal analysis of lake sedimentation under reforestation

Spatial and temporal land cover changes can reduce or accelerate lake sedimentation. This study was conducted to examine morphometry and bathymetry, and the long-term changes (over 75 years) in sedimentation in the Lake Issaqueena reservoir, South Carolina. The watershed and catchment areas were delineated using Light Detection and Ranging (LiDAR) based data. Trends in lake surface area and riparian buffer condition (vegetated or unvegetated) were determined from historical aerial photography. From 1938 to 2009, the lake experienced a decrease in surface area of approximately 11.33 ha while catchment area increased by 6.99 ha, and lake volume decreased by 320,800.00 m3. Lake surface area decreased in years corresponding to equal coverage or largely unvegetated riparian buffers. Surface area and average annual precipitation were not correlated; therefore other factors such as soil type, riparian buffer condition and changes in land use likely contributed to sedimentation. Shift from agricultural land to forestland in this watershed resulted in a decrease in sedimentation rates by 88.28%.

Characterizing land disturbance in Atewa Range Forest Reserve and Buffer Zone

Changes in land cover of protected areas and their buffers have serious implications on the conservation of biodiversity within such biomes because land use has been recognized as one of the major drivers of biodiversity change. Atewa Range Forest Reserve is one of Ghana's Upper Guinea Forests declared as a Globally Significant Biodiversity Area (GSBA). But the reserve is under threat from several human disturbances which could impact on the land cover of the reserve.This study examined the spatial and temporal changes in land cover of Atewa Range Forest Reserve and it's buffer between 1986 and 2013 using remote sensing. Land use and land cover (LULC) classification and change detections were undertaken using one Landsat Multispectral Scanner (MSS) image of 1986 and Landsat ETM+ images of 2003 and 2013.The study also investigated the driving forces of LULC and the effectiveness of the Forest and Wildlife Policy of 1994 in the management of the reserve.Results of image classification showed that much of the peripheral closed and open vegetative covers have been converted to farms and bushes with little disturbance within the interior of the reserve. The study revealed that, the conservation management policies were yielding very little results due to a number of policy deficiencies including low staff strength, lack of logistics and low remuneration. Enforcement of legal instruments against illegal logging, small scale mining and farming activities within the reserve, improvement in the staff strength and their condition of service, intensification of public education on the value of forest and the need to protect it are some of the major recommendations that could curb encroachment on the reserve.

Different land management measures and climate change impacts on the runoff – A simple empirical method derived in a mesoscale catchment on the Loess Plateau

Large-scale vegetation restoration and climate change triggered a significant decline in runoff in the middle reaches of the Yellow River and its tributaries. This runoff decline intensifies inherent water shortage and results in more severe water use conflicts that are threatening sustainable development in the Loess Plateau. Innovative strategies for more water-efficient land management are essential. To this end, the factors controlling runoff were investigated using the upstream area of the Jing River as an example. Runoff was found to be mainly controlled by evaporative demand, precipitation, and land cover type. Budyko's frameworks were applied to predict the annual and long-term runoff; however, the effect of changes in land management (e.g., afforestation) on runoff cannot be assessed due to lack of vegetation factors. Therefore, an empirical analysis tool was derived based on an existing relationship for runoff estimation. This method was found to be more effective in reproducing the annual and long-term runoff than others. The incorporation of temporal changes in land cover and form in approach enables the estimation of the possible impact of soil conservation measures (e.g., afforestation or terracing). Our study highlights the importance of adaptive land management strategies for mitigating water shortage on the Loess Plateau.

Land use and land cover change detection at Mirzapur Union of Gazipur District of Bangladesh using remote sensing and GIS technology

A study was conducted with a view to identify and quantify the changes in land use and land cover occurred during the last 20 years at Mirzapur Union of Gazipur district of Bangladesh using remote sensing and GIS technologies. Two LANDSAT TM images of 1989 and 2009 with 30mx30m spatial resolution were used to determine the temporal land cover changes. Subsequently, a ground verification was done in the study site. The study revealed that forest cover was decreased by 20.29 % and settlement area was found to increase by 28.64% and water bodies was decreased by 6.25 %. In the same period of time, bare land was found to increase by 20.91 % due to the effect of clearing of forest area which is not replanted again. A lot of new infrastructures has been built by this time. Population pressure becomes double enhancing the deforestation of Sal (Shorea robusta). Most prominent features are the emergence of brick fields and various industries. Thus, the above study demonstrated the usefulness of RS and GIS technology regarding resource management and urban planning.

Spatial–Temporal Analyses of Surface Coal Mining Dominated Land Degradation in Holingol, Inner Mongolia

Surface coal mining and urbanization, as well as crop-based agriculture, have resulted in accelerated degradation and desertification of grasslands in the Holingol region, Inner Mongolia Autonomous Region, over the last three decades. The purpose of this study was to investigate the spatial–temporal changes of land cover due to the surface coal-mining activities in the Holingol region from 1978 to 2011. In this study, we used the subspace method to apply land-cover classification schemes to Landsat archival images from 1978, 1988, 1999, and 2011. We then used the grid square method to investigate spatial–temporal land-cover changes during the period of 1978–2011. The results show that both surface coal mining and urban areas have increased dramatically. This expansion was accompanied by considerable loss of grassland and wetland. Grid-cell-based spatial–temporal analysis showed that urban/bare expansion had a strong negative correlation with grassland change ( $-{\bf 0.67}$ ), coal-mining area expansion had a negative correlation with grassland change ( $-{\bf 0.29}$ ), and coal-mining area expansion was positively correlated with urban/bare expansion (0.21). Furthermore, the correlation coefficients of land-cover categories for three time intervals between 1978 and 2011 (1978–1988, 1988–1999, and 1999–2011) showed that there was almost no correlation between grassland and coal-mining area in 1978–1988 and 1988–1999, but the correlation coefficient became negative ( $-{\bf 0.21}$ ) in 1999–2011.

Linking Spatio-Temporal Land Cover Change to Biodiversity Conservation in the Koshi Tappu Wildlife Reserve, Nepal

Land cover change has been one of the major drivers of change leading to an alteration of critical habitats for many of the threatened species worldwide. Species with a narrow range and specialized habitats such as wetland ecosystems are at higher risk. The present paper describes spatial and temporal land use and cover change over the period of last 34 years (1976–2010) in the Koshi Tappu Wildlife Reserve (KTWR), Nepal. High spatial resolution Indian Remote-Sensing Satellite (IRS) Linear Imaging and Self Scanning Sensor (LISS-4) from 2005 and medium spatial resolution Landsat Multispectral Scanner (MSS) from 1976; Thematic Mapper (TM) from 1989; Enhanced Thematic Mapper Plus (ETM+) from 1999 and TM from 2010 were used to generate a land use/land cover map and change analysis. Acquired IRS LISS-4 and Landsat image was orthorectified into Universal Transverse Mercator (UTM), Zone 45 based on generated digital terrain model (DTM) from a topographic map and Ground Control Point (GCP) from the field. After rectifying all the images, eCognition developer software was used for object-based image analysis (OBIA). The change in the land cover and land use types were compared with the potential habitat of twenty globally significant species present in the reserve. The habitat information was collected from the literature and a map was prepared based on ‘presence’ data, habits and habitats used to identify their distribution pattern. The analysis revealed that the KTWR has gone through significant changes in land cover and ecosystems over the last 34 years due to the change in river course and anthropogenic pressure leading to direct change in habitats of the species. Forests have been reduced by 94% from their original state whereas the grassland has increased by 79% from its original state. On the basis of total land cover, forests, river and stream, swamp and marshes decreased by 16%, 14% and 3% respectively over the last 34 years whereas the grassland has increased by 45%. These ecosystems are also an important habitat for the majority of the species, which is resulting in habitat loss. Notably, the wetland ecosystems (marshes/swamps and river/streams), being one of the most important habitat for many globally threatened species, have changed by more than 30% from their original state in 1976. Based on the analysis, recommendations for management interventions were made.

Remotely sensing the spatial and temporal land cover changes in Eastern Mau forest reserve and Lake Nakuru drainage basin, Kenya

This study aimed at characterizing land cover dynamics for four decades in Eastern Mau forest and Lake Nakuru basin, Kenya. The specific objectives were to: (i) identify and map the major land cover types in 1973, 1985, 2000 and 2011; (ii) detect and determine the magnitude, rates and nature of the land cover changes that had occurred between these dates, and; (iii) establish the spatial and temporal distribution of these changes. Land cover types were discriminated through partitioning, hybrid classification and spatial reclassification of multi-temporal Landsat imagery. The land cover products were then validated and overlaid in post-classification comparison to detect the changes between 1973 and 2011. The accuracies of the land cover maps for 1973, 1985, 2000 and 2011 were 88%, 95%, 80% and 89% respectively. Six land cover classes, namely forests-shrublands, grasslands, croplands, built-up lands, bare lands and water bodies, were mapped. Forests-shrublands dominated in 1973, 1985 and 2000 covering about 1067 km2, 893 km2 and 797 km2 respectively, but were surpassed by croplands (953 km2) in 2011. Bare lands occupied the least area that varied between 2 km2 and 7 km2 during this period. Overall, forests-shrublands and grasslands decreased by 428 km2 and 258 km2 at the annual average rates of 1% each, whereas croplands and built-up lands expanded by 660 km2 and 24 km2 at the annual rates of 6% and 16% respectively. The key hotspots of these changes were distributed in all directions of the study area, but at different times. Therefore, policies that integrate restoration and conservation of natural ecosystems with enhancement of agricultural productivity are strongly recommended. This will ensure environmental sustainability and socio-economic well-being in the area. Future research needs to assess the impacts of the land cover changes on ecosystem services and to project the future patterns of land cover changes.

Monitoring urban land cover using satellite remote sensing techniques and field spectroradiometric measurements: case study of “Yialias” catchment area in Cyprus

This study highlights the need for digital mapping of sprawl phenomenon in catchment areas with the use of both satellite and ground remote-sensing techniques. The Yialias River, located in the central part of Cyprus, was selected as a case study area. In this catchment, devastating flash flood events took place in both 2003 and 2009, with catastrophic results. Initially, ground spectroradiometric measurements were applied to investigate the spectral similarity of different classes such as those of urban fabric and marl/chalk origin formations within the watershed. Temporal land cover changes were analyzed by using multitemporal satellite imagery (ASTER) and by incorporating both pixel- and object-oriented classification techniques. To create effective land use and land cover maps, a classification model was proposed based on spectral, texture, and shape characteristics. The pixel-based classification results were compared and evaluated with the object-based classification products. The optimum classification products were imported to geographical information systems and FRAGSTATS software and were used to visually and statistically detect landscape identifying trends based on spatial landscape metrics. The final results indicated considerable expansion within the study area during the last 10 years.

Spatial and Temporal Land Cover Changes in the Simen Mountains National Park, a World Heritage Site in Northwestern Ethiopia

The trend of land cover (LC) and land cover change (LCC), both in time and space, was investigated at the Simen Mountains National Park (SMNP), a World Heritage Site located in northern Ethiopia, between 1984 and 2003 using Geographical Information System (GIS) and remote sensing (RS). The objective of the study was to generate spatially and temporally quantified information on land cover dynamics, providing the basis for policy/decision makers and resource managers to facilitate biodiversity conservation, including wild animals. Two satellite images (Landsat TM of 1984 and Landsat ETM+ of 2003) were acquired and supervised classification was used to categorize LC types. Ground Control Points were obtained in field condition for georeferencing and accuracy assessment. The results showed an increase in the areas of pure forest (Erica species dominated) and shrubland but a decrease in the area of agricultural land over the 20 years. The overall accuracy and the Kappa value of classification results were 88 and 85%, respectively. The spatial setting of the LC classes was heterogeneous and resulted from the biophysical nature of SMNP and anthropogenic activities. Further studies are suggested to evaluate the existing LC and LCC in connection with wildlife habitat, conservation and management of SMNP.