Land Use Cover Dynamics Research Articles

LAND USE/LAND COVER CHANGE PREDICTION USING MULTI-TEMPORAL SATELLITE IMAGERY AND MULTI-LAYER PERCEPTRON MARKOV MODEL

Abstract. This paper aims to predict the trend of land use land cover (LULC) changes in Dak Nong province over time. Data from Landsat images captured in 2009, 2015, and 2018 was employed to analyze and predict the spatial distributions of LULC categories. The Random Forest (RF) was adopted to classify the images into ten different LULC classes. Besides, integration of Multi-Layer Perceptron Markov Neural Network (MLP-NN) with Markov Chain (MC) was applied to predict the future LULC changes in the region based on the change detection over the previous years. For all classified images, overall accuracy (OA) ranged from 77.35% to 84.55% with kappa (K) coefficient index ranging from 0.75 to 0.8. The results revealed that the annual population growth together with social-economic development was regarded as major drives for land conversion in the area. The predicted map showed a significant decrease trend inthe forest classes by 2025, accounting for 23 thousand ha. However, residential areas, rubber, and agricultural land classes are predicted to rise to 460 ha, 3,000 ha, and 20,000 ha, respectively. The simulated model and calibrated area data may be a vital contribution to sustainable development efforts of the local based on the dynamics of LULC and future LULC change scenarios. Overall, ascertaining the complex interface related to changes in land use and its major drivers over time provides useful information predict to explore the future trend of LULC changes, establish alternative land-use schemes and serve as guidelines for urban planning policymakers.

Spatial modeling of land-use change in a rapidly urbanizing landscape in central Iran: integration of remote sensing, CA-Markov, and landscape metrics.

In the present paper, land use/land cover (LULC) change was predicted in the Greater Isfahan area (GIA), central Iran. The GIA has been growing rapidly in recent years, and attempts to simulate its spatial expansion would be essential to make appropriate decisions in LULC management plans and achieve sustainable development. Several modeling tools were employed to outline sustainable scenarios for future dynamics of LULCs in the region. Specifically, we explored past LULC changes in the study area from 1996 to 2018 and predicted its future changes for 2030 and 2050. For this purpose, we performed object-oriented and decision tree techniques on Landsat and Sentinel-2 satellite images. The CA-Markov hybrid model was utilized to analyze past trends and predict future LULC changes. LULC changes were quantitatively measured using landscape metrics. According to the results, the majority of changes were related to increasing residential areas and decreasing irrigated lands. The results indicated that residential lands would grow from 27,886.87ha to 67,093.62ha over1996-2050 while irrigated lands decrease from 99,799.4ha to 50,082.16ha during the same period of time. The confusion matrix of the 2018 LULC map was built using a total of 525 ground truth points and yielded a Kappa coefficient and overall accuracy of 78% and 82%, respectively. Moreover, the confusion matrix constructed base on the Sentinel-2 map, as a reference, to judge the predicted 2018 LULC map with a Kappa coefficient of 88%. The results of this study provide useful insights for sustainable land management. The results of this research also proved the promising capability of remote sensing algorithms, CA-Markov model and landscape metrics future LULC planning in the study area.

Geospatial Analyses for Assessing the Driving Forces of Land Use/Land Cover Dynamics Around the Nile Delta Branches, Egypt

Major driving forces can alter Land use/Land cover (LULC) dynamics and affect landscape sustainability around the Nile Delta of Egypt. The present study aims at evaluating and mapping changes in LULC and assessing the dynamics of LULC and Land Surface Temperature (LST) around the two branches of the Nile Delta, Egypt using Landsat data and GIS. Calibrated Landsat images were acquired on 2000, 2014 and 2019 and processed to produce LULC, environmental indices and LST, respectively, using ENVI 5.3. ArcGIS 10.1 was used to extract a transition map from 2000 to 2019 around the two branches. The results displayed that five classes of LULC were extracted around Damietta and Rosetta branches; water, urban, bare, dense and spare vegetation. A continuous increase in water was recorded around Damietta branch; 13.66 km2 (197%), 14.21 km2 (2.04%) and 16.54 km2 (2.30%) in 2000, 2014 and 2019, respectively. Also, urban area was increased around Damietta and Rosetta branch as follows: 53.6 km2 (7.72%), 58.34 (8.37%) and 90.37 km2 (13.70%) in 2000, 2014 and 2019, 59.55 km2 (6.809%), 104.16 (11.90%) and 149.77 km2 (17.11%) in 2000, 2014 and 2019, respectively. Urban achieved the highest gain of 24.807 and 85.70 km2 at the expense of dense vegetation around Damietta and Rosetta branch, respectively. The results showed that the decrease in vegetation and the increase in urban density lead to increasing LST of the study area. The changes in LST can be monitored depending on the construction materials such as the presence of green areas and topography. Urban and bare lands have the highest LST while the water bodies and vegetation temperature showed a tendency to decrease. It can be concluded that urban areas increased with annual rate 0.27 and 0.54 km2 and vegetation decreased with annual rate −0.57 and−0.55 km2 around Damietta and Rosetta branches from 2000 to 2019. Results showed that comprehensive index was 321.14 and 330.03 around Damietta and Rosetta branch, the higher the degree of development and exploitation. There has been a significant land use change which was due to an increase in population. Overall, this research provides valuable data about changes in LU/LC around the Nile Delta branches, it is very important for decision maker and stockholders for proper management.

Modelling historic and future land use/land cover changes and their impact on wetland area in Shashe sub-catchment, Zimbabwe

The purpose of this study was to use current and historic land use/land cover (LULC) changes to predict future LULC using coupled Cellular Automata–Markov chain model. Landsat time series data for the month of June were used to determine LULC changes for the years 1984, 1995, 2005 and 2015 using random forest classification system in R. We then used Markov Chain algorithm with multiple perceptron in land change modeler to simulate future LULC dynamics for the years 2025, 2035 and 2045. Contingent valuation method was employed to estimate ecological value of wetlands. Results for the LULC analysis for the period between 1984 and 2015 show a decline in woodland and wetland area owing to natural and human factors. We noted a reduced net change for grassland, woodland and mountain vegetation covers losing by − 4%, − 5.2%, − 2% and − 4% change, respectively. While, riverine vegetation, crop field and rock outcrop gained by 0.5%, 4% and 10.2%, respectively. A notable dramatic decline in wetland area was recorded between 1995 and 2005 losing about 125.53 ha, which could be attributed to recurrent droughts of 1995, 1998, 2002 and 2005. Major conversions were from wetland cover to crop fields suggesting agricultural encroachment onto the wetland area. Wetland area, thus, significantly decreased by 6% (p < 0.05) amounting to 236.52 ha in the last 30 years. Coupled CA–Markov chain model results for the years 2025, 2035 and 2045 predicted a further increase in cropfield at the expense of woodland and wetland area. In particular, wetland area is expected to further shrink by 46% (72.67) by the year 2045. Contingent valuation results show that every respondent concurs that wetlands have deteriorated to a very bad state in comparison to their state in the twentieth century. The cited reduced wetland health, biodiversity of both flora and fauna, water quality and quantity and general wetland area. The present state is estimated to be far less than 10% of the total value of wetlands 20 years ago. Quantifying such future wetland area changes is important not only for pure-scientific purposes but also for appropriately developing locally relevant and sustainable management strategies for wetland conservation.

An Exploration into LULC Dynamics and Level of Urbanization: The Case of Wolaita Sodo City and its Peripheries

This study assessed current and historic land use, land cover (LULC) dynamics and the level of urbanization in Wolaita Sodo and its peripheries since 1985 up to 2016. Thus, it’s aimed to offer an increased understanding of the growing dynamics of land use changes in relation to the level of urbanization. The study primarily employed advanced technologies like GIS and RS to collect and analyze accurate and reliable information. In addition, survey questionnaire was used to gather quantitative and qualitative data from 200 respondents and then linear regression model and descriptive analysis was done by using SPSS v.21 software. The study showed that the area under forestland, bare land, grassland and cropland were declined while the area under built-up area was increased.

ANALYSIS OF LAND USE / LAND COVER AND CLIMATE IMPACTS ON KANGIMI STREAMFLOW AND SEDIMENT YIELD: KANGIMI CATCHMENT, KADUNA NIGERIA

The Kangimi reservoir is an important dam augmenting water supply and recreational activities in and around the Kangimi Watershed in Kaduna, Nigeria. However, the impending hydrological effect of land use / land cover (LULC) dynamics in relation to agricultural expansion has not been established. This study determines the LULC dynamics on hydrological parameters (streamflow and sediment yield) using the ArcGIS 10.2 interfaced with ArcSWAT 2009 and detailed LULC maps (1975, 2000 and 2013). The catchment was delineated into ten subbasins, and 39 hydrological response units (HRUs) were created according to multiple HRU development. Kangimi hydrology was simulated for three different LULC types. The model was verified through calibration and validation to determine its performance; the values were determined to be (R2=0.92, NS=0.93) for calibration and (R2=0.82, NS=0.86) for validation, respectively. The hydrological response was considered based on three conditions (climate of 1979-2014 &amp; 1975 LULC, the climate of 1979-2014 &amp; 2000 LULC, and climate of 1979-2014 &amp; 2013 LULC). Model results for the Kangimi catchment confirm that agricultural growth and bare surface increase led to an increase in annual streamflow and sediment yield. Thehydrology streamflow increased 28.23% (from 345.2 m3/s to 387.37 m3/s) as well as 33.31% (from 60.03 to 90.02 t/ha) of sediment yield due to LULC and climate dynamics. The results confirm the prominence of incorporating physical hydrologic models through the use of GIS for estimating catchment characteristics and the relative effect of LULC dynamics on hydrologic response. A well-parameterized model can be equally used to estimate the impact of LULC dynamics on water quality, pesticide loading, nutrients and land management practice.Keywords: Hydrological parameters, Climate changes, SWAT, GIS

Tracking conservation effectiveness in the Vhembe Biosphere Reserve in South Africa using Landsat imagery.

Biosphere reserves (BRs) seek to reconcile a sustainable relationship between human welfare and environmental integrity by adopting a landscape model that distinguishes between three interdependent management zones (core, buffer, transition). Considering the increasing human influence on landscapes in BRs, the tracking land use-land cover (LULC) dynamics is crucial for the development and planning of efficient management strategies for specific management zone. This study aimed at (i) assessing biodiversity protection around the core zones to highlight the threats facing the core zones and (ii) tracking the effect of the proclamation of the Vhembe Biosphere Reserve (VBR) on the LULC dynamics in the management zones through spatio-temporal analysis using Landsat imagery acquired from1999 to 2018. Six LULC categories (water body, forest/bush, shrubs/grass, agricultural land, bare soil, and built-up/mines) were identified and mapped using the support vector machine (SVM) classification to address both objectives. Assessment of threats around the core zones using artificial buffers (0-5, 10-15, and 15-20km radius) created around them showed agricultural activities in the most immediate buffers (0-5km radius). The LULC dynamics showed vegetation increase in all the management zones evidenced by the reduction of bare soil as well shrub/grass lands, and by the corresponding increase in foliage-richer forest/bush lands since the proclamation of the reserve in 2009. The findings might signify a positive outcome of vegetation increase as a consequence of the proclamation of the VBR. However, firmer conservation measures must be adopted and priority must be given to the arrangement of the management zones to strengthen biodiversity protection in the core zone.

Assessing Anthropogenic Dynamics in Megacities from the Characterization of Land Use/Land Cover Changes: The Bogotá Study Case

Usually, megacities expand without proper planning in a context of demographic growth and are increasingly dependent on the natural resources related to the occupied area. This is a major challenge for the sustainable management of these territories, justifying the need for a better knowledge of land use/land cover (LULC) distribution and characteristics to observe spatial anthropogenic dynamics. In this study, the Bogotá river basin and the Bogotá megacity were analyzed as a case study. The main objective of this work was to analyze the historical LULC dynamics from 1985 to 2014. Reliable forecasting scenarios were developed using the Land Change Modeler to support sustainable management and planning. Results show an expansion of the Bogotá megacity toward the Northeast and an increase of urban areas within the basin. These changes implied a loss of 58% of forest surface, a strategic ecosystem, from 1985 to 2014. This dynamic is expected to continue, with a 50% increase of urban areas between 2012 to 2050, thus the megacity and neighbor cities potentially become an “urban continuum”. A replacement of crop and pasture lands near the city is expected, even though Bogotá lands are among the best agricultural lands in the Andean region of Colombia.

Tracking changes in soil organic carbon across the heterogeneous agricultural landscape of the Lower Fraser Valley of British Columbia

Increasing soil organic carbon (SOC) can improve the capacity of agricultural systems to both adapt to and mitigate climate change. Despite its importance, the current understanding of the magnitude or even the direction of SOC change in agricultural landscapes is limited. While changes in land use/land cover (LULC) and climate are among the main drivers of changes in SOC, their relative importance for the spatiotemporal assessment of SOC is unclear. This study evaluated LULC and SOC dynamics using archived and recent soil samples, remote sensing, and digital soil mapping in the Lower Fraser Valley of British Columbia, Canada. We combined both pixel- and object-based analysis of Landsat satellite imagery to assess LULC changes from 1984 to 2018. We achieved an overall accuracy of 81% and kappa coefficient of 0.77 for LULC classification using a random forest model. For predicting SOC for the same time period, we applied soil and vegetation indices derived from Landsat images, topographic indices, historic soil survey variables, and climate data in a random forest model. The SOC prediction of 2018 resulted in a coefficient of determination (R2) of 0.67, concordance correlation coefficient (CCC) of 0.76, and normalized root mean square error (nRMSE) of 0.12. For 1984, the SOC prediction accuracies were 0.46, 0.58, and 0.18 for R2, CCC, and nRMSE, respectively. We detected SOC loss in 61%, gain in 12%, while 27% remained unchanged across the study area. Although we detected large losses of SOC due to LULC change, the majority of the SOC losses across the landscape were attributed to areas that were remained in the same type of agricultural production since 1984. Climate variability did not, however, have a strong effect on SOC changes. These results can inform decision making in the study area to support sustainable LULC management for enhancing SOC sequestration.

Land use Land Cover Monitoring and Change Detection of Tinsukia, India

This study is driven towards land use land cover (LULC) mapping and LULC change detection in Tinsukia district, India. LULC mapping and change detection provides land planner and environmental scientists a better understanding of the land surface processes occurring in a given landscape so that they can come up with a strategy for sustainable development keeping degradation of natural environment from anthropogenic activities at bay. This study utilized remote sensing data products and software’s for LULC mapping and LULC change. Landsat data has been utilized in ENVI for the classification of LULC and LULC change detection during the period 1991-2020. The LULC classification was achieved through Maximum Likelihood Classification (MLC) which is a widely preferred classificatory method. Image change detection was achieved through ENVI thematic change workflow. On top of that ArcGIS version 10.2 was used for preparing all map layouts. Results reveal that the study area has undergone significant changes in its LULC pattern. Substantial increases were recorded in agricultural area (862.4 sq. km to 1186 sq. km), built up area (473.4 sq. km to 699.5 sq. km) and waterbodies (81 sq. km to 146.7 sq. km). A declining trend was evident in degraded vegetation (772.2 sq. km to 274.3 sq. km) and barren land (798.8 sq. km to 641 sq. km). In the short study period, the study area already seems to be changing in its LULC pattern due to anthropogenic activities. The steady increases to the agricultural land and built up area (BUA) is a potential threat to the LULC balance and it may have manifold impacts to LULC dynamics in the future if proper land utilization policy is not adopted.

Partitioning the impacts of land use/land cover change and climate variability on water supply over the source region of the Blue Nile Basin

AbstractWater plays a vital role in sustaining the natural functioning of the entire ecosystem that supports life on Earth. It plays key roles in the well‐being of society in numerous ways. However, climate variability and land use land cover (LULC) change have caused spatiotemporal water supply variation. Disentangling the effects of climate variability from LULC change on water supply is crucial for sustainable water resource management. The main purpose of this study is, therefore, to disentangle the relative contribution of LULC change and climate variability to the overall average annual water supply variation. Residual trends analysis combined with Integrated Valuation of Environmental Services and Tradeoffs (InVEST) annual water yield model was adopted to perform simulations and disentangle the relative impacts of climate variability and LULC change. Ground and satellite data were used in this study. The study area has experienced a significant increasing wetness trend and significant LULC dynamics between 2003 and 2017. As a result, an increasing water supply was observed due to the joint effects of climate variability and LULC change in the watershed (203 mm). The contribution of climate variability was 94%, whereas LULC contributes only 6% from 2003 to 2017. Climate variability negatively led to water supply variation while LULC change contributed positively from 2010 to 2017. Although the ongoing soil and water conservation (SWC) practices improved vegetation cover and water retention of the watershed, climate variability is the main driver of water supply variation. Therefore, SWC practices should incorporate ecosystem‐based climate change adaptation strategies and scale up to community‐based integrated watershed management to sustain water supply.

Impact analysis of land use dynamics on coastal features of Deshapran block, Purba East Medinipur, West Bengal

Coastal tract of India endorses diverse land cover features such as mangroves, mudflats, sand dunes, beaches, spits, sand bars and barrier islands. Land use pattern portrays the interaction between human and the environment. Increased anthropogenic activities in the form of urbanization and transformation of landscape into commercial activities like aquaculture would endanger the coastal land cover pattern. Multi temporal time series data facilitate in analyzing the Land use/Land cover (LULC) change dynamics using Remote Sensing and GIS techniques. Present study evaluates the changes in coastal features due to alteration of human intervened land uses in Deshapran block of Purba East Medinipur district of West Bengal. The study was attempted to assess the LULC changes in the past 4.5 decades and its impacts on the coastal features. The changes were detailed in different scenarios of definite time intervals. The study was further up scaled to predict the expected changes in the land cover for the next two decades using CA-MARKOV prediction model. The forecast study indicated that the haphazard expansion of aquaculture would impose severe stress to the crop lands and coastal features as well as menacing the coastline dynamics of Deshapran block. The outcome of the LULC dynamics provide changes in LULC at different period due to increasing human interventions and the forecast study will serve as a key information for policy makers for coastal sustainability of Deshapran.

Influence of Land Use Land Cover Change on Groundwater Recharge in the Continental Terminal Area of Abidjan, Ivory Coast

The process by which rainfall reaches the aquifer in a sedimentary area is infiltration. This process could be affected quantitatively or qualitatively by the changes in the land use land cover (LULC) as a result of anthropogenic activities which could affect groundwater reserves. This study focuses on the influence of LULC change on groundwater recharge in the context of urbanization and population growth. Four weather stations data and satellite image data were used in order to evaluate water infiltration which is the amount of water that reaches the piezometric surface from 1990 to 2016. The spatial-temporal LULC change in relation to urbanization sprawl was assessed based on a series of Landsat images for 1990, 2000 and 2016. The maximum likelihood pixel-based on classification method was used to analyze the spatial-temporal LULC dynamics. The Thiessen polygon method was used for the mean area precipitation computation. The recharge was determined using water balance method after determining the runoff based on the Soil Conservation Service curve number method. The results show an increase in built-up and agricultural land, while the forest and shrub areas declined with water body remaining unchanged over the period 1990-2016. The decline in forest could be imputed to the demographic and socio-economic growth as expressed by the expansion of agriculture and urbanization. Groundwater recharge and runoff results are respectively 34%, 20% in 1999; 21%, 46% in 2000 and 26%, 14% in 2016 of rainfall and show their strong dependence on precipitation and LULC change.

Monitoring land use and land cover changes in the mountainous cities of Oman using GIS and CA-Markov modelling techniques

As a result of the socioeconomic transformation, the rapid urban expansion of cities and towns in the Gulf Cooperation Council (GCC) states has predominately led to tremendous pressure on the limited natural resources and loss of productive lands. Indeed, the spatial patterns of urbanisation and their impacts on mountain resources and environment have received little attention, particularly in Oman. Predicting urban growth in the mountainous cities has the potential to better understand the interaction between the spatial growth patterns and the mountain topography. This study aims to analyse spatiotemporal dynamics of land use/land cover (LULC) (2008–2018) and simulate urban expansion (2008–2038) in Nizwa city, Al Dakhliyah governorate, Oman. Cellular Automata (CA)-Markov and geospatial techniques were utilised to assess and project urban growth and land cover changes. The analysis was based on three maps of LULC at equal intervals derived from satellite imageries: Landsat TM for 1998, 2008 and 2018, along with topographic spatial layers (elevation, aspects, and terrain slopes) derived from the ASTER digital elevation model. In addition, other spatial parameters (population density, proximity to urban centres, and proximity to major roads,) were incorporated in the simulation process. The findings revealed that the actual LULC change during 2008–2018 was 12,014 ha of net urban growth (418.5 % change), while the simulated change was expected to be 14,985 ha by 2028, with a total of 37,465 ha increase in the built-up area and urban growth by 2038. Although the topographic variability will control LULC changes, the urban expansion overly will occupy the arable land across the valleys along with the flat areas. During the next two decades, the built-up areas will dominant, with a large percentage of vacant land (net loss 12,813 ha) and vegetation cover (net loss 35 ha) will be gradually converted into residential land use. The output of the simulations in this research could serve not only as spatial guidelines for monitoring future trends of LULC dynamics, but also address the threats and deteriorates of urban sustainability in the Omani mountainous cities. Furthermore, identifying bare soils and vegetation areas that are susceptible to urbanisation is of value for the national strategy of future urban planning in Oman.

Impact of Land Use/Land Cover Change on Hydrological Components in Chongwe River Catchment

Chongwe River Catchment, a sub-catchment of the Zambezi River Basin, has been experiencing changes in land use/land cover (LULC) and in its hydrology. This study aims to assess the impact of LULC changes on the catchment’s hydrological components such as streamflow, evapotranspiration and water abstractions. LULC change data, detected from the 1984, 1994, 2014 and 2017 USGS Landsat imagery using a maximum likelihood supervised classifier, were integrated into the WEAP Model along with soil, slope and hydro–climate data. The results showed that between 1984 and 2017 built-up area increased by 382.77% at 6.97 km2/year, irrigated agriculture increased by 745.62% at 1.70 km2/year, rainfed farms/ranch/grassland increased by 14.67% at 14.53 km2/year, forest land decreased by 41.11% at 22.33 km2/year and waterbodies decreased by 73.95% at 0.87 km2/year. Streamflow increased at a rate of 0.13 Mm3 per annum in the wet seasons and showed a high variation with flow volume of 79.68 Mm3 in February and 1.01 Mm3 in September. Annual actual evapotranspiration decreased from 840.6 mm to 796.3 mm while annual water abstraction increased from 8.94 mm to 23.2 mm from the year 1984 to 2017. The pattern of LULC change between 1984 and 2017 has negatively impacted the hydrology of the Chongwe River Catchment. From these findings, an integrated catchment management and protection approach is proposed to mitigate the negative impacts of LULC dynamics on hydrological components in the Chongwe River Catchment.

Carbon Sequestration Potential of the Forest Ecosystems in the Western Ghats, a Global Biodiversity Hotspot

Global warming with the burgeoning anthropogenic greenhouse gas (GHG) emissions (400 parts per million from 280 ppm CO2 emissions of pre-industrial era) has altered climate, eroding the ecosystem productivity and sustenance of water, affecting the livelihood of people. The anthropogenic activities such as burning fossil fuel, power generation, agriculture, industry, polluting water bodies and urban activities are responsible for increasing GHG footprint of which 72% constitute CO2. GHG footprint needs to be in balance with sequestration of carbon to sustain ecosystem functions. Forests are the major carbon sinks (about 45%) that aid in mitigating global warming. The current research focusses on the carbon budgeting through quantification of emissions and sinks in the forest ecosystems and changes in climatic conditions of Western Ghats. This would help in evolving appropriate mitigation strategies toward sustainable management of forests and mitigate impacts of global warming. The land-use land-cover (LULC) dynamics are the prime driver of climate change due to the loss of carbon sequestration potential as well as emissions. The Western Ghats are one among 36 global biodiversity hotspots and forests in this region sequester atmospheric carbon, which aid in moderating the global climate and sustaining water to ensure water and food security in the peninsular India. Assessment of LULC dynamics using temporal remote sensing data shows the decline of evergreen forest by 5% with an increase in agriculture, plantations and built-up area. The interior or intact forests have declined by 10%, and they are now confined to protected areas. The simulation of likely changes indicates that the region will have only 10% evergreen cover and 17% agriculture, 40% plantations and 5% built-up. Quantification of carbon reveals that the WG forest ecosystem holds 1.23 MGg (million gigagrams or Gt) in vegetation and soils. The annual incremental carbon is about 37,507.3 Gg, (or 37.5 million tons, Mt) and the highest in the forests of Karnataka part of WG. Simulation of the likely changes in carbon content indicates the loss of 0.23 MGg (2018–2031) carbon sequestration potential under business as usual scenario. The conservation scenario depicts an increase in carbon sequestration potential of WG forests with the protection. Sequestered carbon in WG is about INR 100 billion ($1.4 billion) at carbon trading of INR 2142 ($30) per tonne. Large-scale land-cover changes leading to deforestation has contributed to an increase in mean temperature by 0.5°C and decline in rainy days, which necessitates evolving prudent landscape management strategies involving all stakeholders for conservation of ecologically fragile WG. This will enhance the ability of forests to sequester atmospheric carbon and climate moderation, with the sustenance of ecosystem goods and services.

Land use/land cover dynamics and soil erosion in the Umzintlava catchment (T32E), Eastern Cape, South Africa

Land use/land cover (LULC) change is often recognised as one of the most sensitive indicators of the interaction between humans and the natural environment contributing to soil erosion. Assessing the impact of LULC dynamics on soil erosion is imperative for soil conservation planning. Against this background, the primary aim of this paper is to assess the impact of LULC change on soil erosion in the Umzintlava catchment during the period 1989–2017. To achieve this, multi-temporal Landsat data, together with the Revised Universal Soil Loss Equation (RUSLE) were used. Six LULC classes – water bodies, badlands, bare soil and built-up area, agriculture, grassland, and forest – were derived for the years 1989, 2001, and 2017, based on the Normalised Difference Vegetation Index (NDVI) classification. A post-classification change detection analysis showed that water bodies, agriculture, and grassland decreased by 0.038%, 1.796%, and 13.417%, respectively, whereas the areas covered by forest, badlands, and bare soil and built-up area increased by 9.741%, 3.7338%, and 1.778%, respectively. Results further showed that all other LULC classes, except badlands, experienced increased rates of soil loss. The proportion of the catchment area experiencing moderate (12–25t ha-1year-1) to extremely high (>150t ha-1year-1) erosion risk consistently increased. This study provides relevant information on the relationship between LULC dynamics and soil erosion risk, highlighting the necessity and importance of integrating remote sensing and empirical erosion models in spatio-temporal soil erosion assessment at the catchment level.

Exploring land use/land cover changes, drivers and their implications in contrasting agro-ecological environments of Ethiopia

This study examined the trends, driving factors, and implications of land use/land cover (LULC) dynamics over the past 35 years (1982–2017) in three watersheds of the drought-prone areas that represent different agro-ecologies of Upper Blue Nile basin, Ethiopia: Guder (highland), Aba Gerima (midland), and Debatie (lowland). The changes in LULC were analyzed by integrating field observations, remote-sensing data (aerial photographs [1: 50,000 scale] and very high resolution [0.5–3.2 m] satellite images), and geographic information systems. The drivers of LULC were explored using key informant interviews and relevant literature reviews. The implications of LULC change on soil erosion and surface runoff responses were also evaluated. A minimum of four and maximum of six LULC classes were identified in each watershed over the study period. The study revealed that forest land was the dominant LULC class accounting for 40.9% and 32.0% in Guder and Aba Gerima, respectively in 1982. While in the same period, bush land (36.6%) was the dominant LULC class in Debatie watershed. From 1982 to 2016/2017, forest land, bush land, and grazing land respectively decreased by about 70%, 50%, and 27% in Guder; 65%, 49%, and 63% in Aba Gerima; and 63%, 59%, and 38% in Debatie. During the same period, cultivated land increased by approximately 40%, 129%, and 704% in Guder, Aba Gerima and Debatie, respectively. In contrast, between 2012 and 2017, plantation cover increased by about 400% in the Guder, mainly at the expense of cultivated land, which decreased by 40% for the same period. Population growth and associated changes in the farming practices were the major driving forces for the observed LULC changes in the study watersheds. The traditionally deleterious impacts of human activities on the environment have been recently reversed at an unprecedented rate, particularly at Guder and to a lesser extent at Aba Gerima, following the shift from the traditional annual cropping to more economically attractive tree-based farming practices such as Acacia decurrens plantation in Guder and khat (Catha edulis) cultivation in Aba Gerima. The continued expansion of cultivated land combined with population growth positively linked to the increase of gully erosion and surface runoff potential in the study watersheds particularly, in Aba Gerima and Debatie watersheds. The Upper Blue Nile basin is currently experiencing both positive and negative socio-economic and environmental consequences of LULC dynamics. Hence, the present study can help form a basis for the appropriate development of land management policies and strategies in this and other basins experiencing similar problems.

Land Use/Land Cover changes dynamics and their effects on Surface Urban Heat Island in Bucharest, Romania

The aim of the paper is to examine and analyze the long-term spatial dynamics of LULC (Land Use/Land Cover) and the impact of their changes on the SUHI (Surface Urban Heat Island). The study covered the area of Bucharest Municipality, the capital of Romania and its neighboring areas, and involved a series of Landsat images, taken in the summer, and ranging from 1984 to 2016. To achieve the goal the following were accomplished: (i) a supervised image classification, done with good accuracy and (ii) a post classification change detection approach was used to assess the LULC changes; (iii) the thermal signature for each land use category was determined using LST (Land Surface Temperature); also, iv) NDVI (Normalized Difference Vegetation Index) has been used to determine a relationship between the thermal behavior and the characteristics of each land use category. The results have revealed that by 2016 there has been an increase in the built-up areas and the fallow land areas and a decrease in the croplands and forested areas. Also, there were observed the increase in surface temperature and a decrease for the difference between the average temperature of the urban area and the surrounding areas of the city indicating the extension of the area where the phenomenon of the Urban Heat Island of Bucharest occurs.

Implications of land use/land cover dynamics and Prosopis invasion on ecosystem service values in Afar Region, Ethiopia

Land use/land cover (LULC) dynamics and the resulting changes in ecosystems, as well as the services they provide, are a consequence of human activities and environmental drivers, such as invasive alien plant species. This study assessed the changes in LULC and ecosystem service values (ESVs) in the Afar National Regional State, Ethiopia, which experiences a rapid invasion by the alien tree Prosopis juliflora (Swartz DC). Landsat satellite data of 1986, 2000 and 2017 were used in Random Forest algorithm to assess LULC changes in the last 31 years, to calculate net changes for different LULC types and the associated changes in ESVs. Kappa accuracies of 88% and higher were obtained for the three LULC classifications. Post-classification change analyses for the period between 1986 and 2017 revealed a positive net change for Prosopis invaded areas, cropland, salt flats, settlements and waterbodies. The rate of Prosopis invasion was estimated at 31,127 ha per year. Negative net changes were found for grassland, bareland, bush-shrub-woodland, and natural forests. According to the local community representatives, the four most important drivers of LULC dynamics were climate change, frequent droughts, invasive species and weak traditional law. Based on two different ESVs estimations, the ecosystem changes caused by LULC changes resulted in an average loss of ESVs in the study area of about US$ 602 million (range US$ 112 to 1091 million) over the last 31 years. With an increase in area by 965,000 ha, Prosopis-invaded land was the highest net change during the study period, followed by grassland (−599,000 ha), bareland (−329,000 ha) and bush-shrub-woodland (−327,000 ha). Our study provides evidence that LULC changes in the Afar Region have led to a significant loss in ESVs, with serious consequences for the livelihoods of the rural people.