Large-scale Land Cover Change Research Articles

Modeling the impacts of oil palm plantations on water quantity and quality in the Kais River Watershed of Indonesia

Oil palm plantations can impact hydrological processes in many tropical watersheds. The rapid conversion of tropical rainforests for commercial operations in recent decades has been associated with water scarcity, flooding, and polluted rivers. However, this widespread and emerging issue is less studied and underreported due to limited data availability, modeling complexity, and the remote nature of these landscapes. Ecohydrologic modeling enables us to investigate changes in watershed conditions caused by large-scale land cover changes from plantations. This study examines the impact of oil plantations on water quantity and quality using the SWAT+ model in the Kais River Watershed, West Papua, Indonesia. The objective is to assess the hydrological changes concerning land cover conversion to oil palm plantations. Results show that establishing oil palm plantations increased surface runoff by 21 %, and sediment yields rose by 16.9 % compared to the baseline. There was also a significant increase of 78 % in mean annual total nitrogen and 144 % in total phosphorous after the plantations' establishment. The results show that forest conversion to oil palm plantations in the Kais River watershed is a primary driver of change in hydrological regimes, resulting in the deterioration of water quality. There is a need for conservation strategies to mitigate the impacts of significant landscape changes in watershed ecosystems.

The Spatiotemporal Change in Land Cover and Discrepancies within Different Countries on the Qinghai–Tibet Plateau over a Recent 30-Year Period

The Qinghai–Tibet Plateau is a unique global natural geographical unit with a high altitude and fragile ecology, where land cover change has been affecting its regional ecological security and sustainable development. The plateau covers nine countries with different variations in climate change and human activities, which cause significant spatial variations in its land cover change. This paper uses land cover data to reveal the spatiotemporal characteristics and multi-country differences in land cover change on the Qinghai–Tibet Plateau from 1992 to 2020 by applying spatiotemporal characteristic analysis and mapping methods. The results show that grassland (65.70%), bare land (15.56%), and woodland (10.25%) are the main types of land cover on the plateau, accounting for 91.51% of the total area. The interconversion of bare land and grassland was dominant in 1992–2020, with an area share of 67.83%. The turning point year of grassland change occurred in 2015. The grassland area increased by 6312 km2 in 1992–2015, while it decreased by 14,646 km2 in the plateau in 2015–2020. The areas of woodland, cropland, and water increased by 2.77%, 5.85%, and 7.57%, respectively, and the area of built-up land increased from 299.17 km2 to 1206.29 km2. Overall, a warming and wetting trend of the climate in the Qinghai–Tibet Plateau has driven the expansion of natural vegetation and water in the central plateau within China, with its natural vegetation area increasing by 0.11%. However, the development of regional warming and drying caused local grassland degradation, where Kyrgyzstan and India within the Qinghai–Tibet Plateau experienced the most prominent vegetation degradation. Human activities are relatively frequent in the Qinghai–Tibet Plateau within China and India, causing higher growth rates of built-up land and cropland than in other countries. The establishment of reserves and effective forest management policies have led to significant increases in woodland areas in China and Nepal within the plateau, while weak forest management and limited investment in forest conservation have led to high rates of deforestation in India and Myanmar. Accelerated temperature rises and regional differences in precipitation are the main drivers of large-scale land cover change on the plateau and differences in human activities and land use policies are responsible for the dramatic and diverse localized land cover change.

A Simple and Automatic Method for Detecting Large-Scale Land Cover Changes Without Training Data

A Simple and Automatic Method for Detecting Large-Scale Land Cover Changes Without Training Data

Dynamics of land cover transitions and agricultural abandonment in a mountainous agricultural landscape: Case of Ifugao rice terraces, Philippines

Mountainous agricultural landscapes experienced large-scale land cover changes in the past decades due to traditional land modification practices and increasing permanent agricultural abandonment. However, there is lack of observation of short-period land cover transitions and paddy field dynamics of fallowing and recultivation. This study was implemented in the Philippines’ Ifugao rice terraces with three aims. The first aim is to analyze rapid land cover transitions by mapping land cover maps in consistent five-year intervals from 1990 to 2020. The second aim is to analyze paddy field dynamics that involve permanent abandonment, fallowing, first-time cultivations, and recultivation by developing an analysis framework involving time-series land cover maps. The third aim is to confirm the relationship between abundance of vegetation land covers and permanent abandonment of paddy fields by implementing regression analysis. Results show that a two-step process involving low vegetation as an intermediary land cover typically occurs in between agricultural abandonment and afforestation that was widely observed in mountainous agricultural landscapes. Observed temporal dynamics of paddy fields aligned with historical records such as high rates of permanent abandonment in the 1990s and recultivation (416% increase) in the 2000s. Regression analysis revealed that there is a significant correlation between low vegetation cover abundance and subsequent paddy field permanent abandonment (P = 0.0498), which confirms that afforestation in the landscape decreased the water yield and promoted agricultural abandonment. The findings suggest that planning of mountainous agricultural landscapes should address social and environmental driving factors to mitigate the land-transition feedback loop that further promotes agricultural abandonment.

Tracks of Death: Elephant Casualties along the Habaipur–Diphu Railway in Assam, India

Railway development is an important component of sustainable transportation systems but also affects wildlife habitats worldwide. Here, we assess spatiotemporal patterns of elephant–train collisions and mortalities within the state of Assam, India, and relate them to spatial and temporal land cover change (LCC) from 1988 to 2018. The results indicate that an extension of railways into forested landscapes is associated with large-scale LCC and increased elephant–train collisions and mortality. Prior to 1997, when the railway system used narrower gauge rails, elephant deaths from collisions occurred at a rate of one or two per year. After 1997, when the system was converted to larger gauge rails, elephant deaths increased starkly and now occur at a rate approaching ten per year. While the rail gauges were being converted, the landscape around the Habaipur–Diphu railway line saw a sevenfold increase in annual net loss of dense forest. The transition from forest to croplands was the most dominant process of deforestation and forest fragmentation during the postconversion period. Although elephant–train collisions are strongly associated with the land use transitions shown here, conservation and remediation measures can help to stem further declines in forest habitats and promote safe movement by elephants between resource patches.

Hydrological responses to large-scale changes in land cover of river watershed: Review

Hydrological responses to large-scale changes in land cover of river watershed: Review

Recent land cover changes in the Southwestern US lead to an increase in surface temperature

The increase in large-scale land cover change (LCC) in recent decades, particularly in response to climate-driven disturbances, has potential to impact local and regional changes in climate due to modification of carbon sources and sinks, albedo, surface roughness and energy fluxes. Using observational data, we predict the impact of two of the most extensive LCCs occurring in the Southwestern US: drought-induced tree mortality and shrub encroachment into grasslands, on surface temperature. We developed a new energy balance method that extracts the biophysical responses to environmental conditions, to predict how structural changes in albedo, surface roughness and canopy conductance following LCC will alter surface temperature. This method allows us not only to explain the observed differences in surface temperature between two non-adjacent study sites with different environmental conditions, but also to separate the contribution of biophysical and non-biophysical properties to surface temperature. Our results suggest that changes in biophysical properties due to shrub encroachment and tree mortality in the Southwestern US (independent of changes in other environmental properties) can potentially lead to an increase in midday surface temperature (11AM to 2PM) of 1 to 2 degrees Celsius, comparable to changes in surface temperature following deforestation. Although the average surface temperature increase in response to both shrub encroachment and tree mortality is similar, the biophysical properties driving the temperature change are different in each scenario. Change in aerodynamic conductance following tree mortality is the largest contributor to heating, while reduced albedo and canopy conductance drive the increase in surface temperature following shrub encroachment. We also show how this increase in daytime surface temperature could be further intensified with future climate, especially with the expected reduction in soil water availability in the Southwest.

Impacts of spatial heterogeneity patterns on long-term trends of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature time series

Land surface temperature (LST) is a crucial parameter for global climate change studies. LST changes are also directly associated with the large-scale changes in land cover. Previous studies carried out a comparative analysis of satellite-derived LST response between periods before and after homogenous land cover changes. We present an alternative approach that quantifies long-term LST variability in response to various land use/land cover change (LULCC) patterns over Phuket Island, Thailand, from 2003 to 2017. First, four Moderate Resolution Imaging Spectroradiometer (MODIS) overpass times of LST time series were adjusted for seasonal effects using a cubic spline function to preserve the number of original data and enable estimates of LST dynamics and trends using the generalized least squared models. Second, LULCC patterns were classified according to land cover type conversion and spatial pattern transformations between the years 2000 and 2016. Spatial homogeneity and heterogeneity were quantified by the coverage percentage for each land use and land cover (LULC) type within a given location. Finally, the influence of LULCC patterns on the long-term spatiotemporal behavior of LST was assessed using the generalized estimating equation model. Results showed that different land cover transitions influence the dynamics of daytime LST but not the nighttime LST. The proportion of different land cover types within an LST pixel and transition amounts contributed to the quantity of increasing surface temperature, especially over impervious surface types. Diverse LULCC patterns with considerations of spatial heterogeneity improved our insight about a relatively strong effect of combined LULC types on LST responses. The climatic effect through the gradual conversion of heterogeneous land cover is necessary to be considered in climate research studies.

Linking nest microhabitat selection to nest survival within declining pheasant populations in the Central Valley of California

Abstract ContextThe ring-necked pheasant (Phasianus colchicus) has experienced considerable population declines in recent decades, especially in agricultural environments of the Central Valley of California. Although large-scale changes in land cover have been reported as an important driver of population dynamics, the effects of microhabitat conditions on specific demographic rates (e.g. nesting) are largely unknown. AimsOur goal was to identify the key microhabitat factors that contribute to wild pheasant fitness by linking individual-level selection of each microhabitat characteristic to the survival of their nests within the California Central Valley. MethodsWe radio- or GPS-marked 190 female ring-necked pheasants within five study areas and measured nest-site characteristics and nest fates during 2013–2017. Specifically, we modeled microhabitat selection using vegetation covariates measured at nest sites and random sites and then modeled nest survival as a function of selecting each microhabitat characteristic. Key resultsFemale pheasants tended to select nest sites with greater proportions of herbaceous cover and avoided areas with greater proportions of bare-ground. Specifically, perennial grass cover was the most explanatory factor with regard to nest survival, but selection for increasing visual obstruction alone was not shown to have a significant effect on survival. Further, we found strong evidence that pheasants selecting sites with greater perennial grass height were more likely to have successful nests. ConclusionsAlthough pheasants will select many types of vegetation available as cover, our models provided evidence that perennial grasses are more beneficial than other cover types to pheasants selecting nesting sites. ImplicationsFocusing management actions on promoting perennial grass cover and increased heights at the microsite level, in lieu of other vegetative modifications, may provide improved quality of habitat for nesting pheasants and, perhaps, result in increased productivity. This is especially important if cover is limited during specific times of the nesting period. Understanding how microhabitat selection influences fitness can help land managers develop strategies to increase the sustainability of hunted populations of this popular game-bird species.

Geo-visualization of landscape dynamics in the proposed mega industrial corridor.

Urbanization is associated with large-scale irreversible landscape changes in response to the demands of burgeoning population, etc. Lack of basic amenities, job, and infrastructures in rural areas often drives migration towards the urbanizing landscapes. Urbanization is resource centric, which involves, large-scale transformation of the landscape with the irreversible impacts on the regional ecology, hydrology, and environment, which is evident from large-scale land cover changes leading to deforestation, encroachment of lakes/water bodies, forest, and farmlands, conversion of agriculture landscapes, etc. damaging the environs. Visualization of urban growth based on the past spatial patterns would help in evolving appropriate policy framework towards the design of sustainable cites for the prudent management of natural resources. Current communication attempts to understand the landscape dynamics along the proposed Mumbai-Pune industrial corridor (with 10 km buffer) through (i) rule-based/non agent-based models (non-ABM) and (ii) agent-based models (ABM) with the evaluation of relative performance of ABM and non-ABM methods. Comparative assessment of the model performance through accuracy assessment and Kappa (relatively significant at p < 0.05) indicates the superior performance of the agent-based model approaches due to its interaction with factors and constraints that allow urban growth in the region. Non-ABM model predicted the growth of 49.69% by 2027 with the decline of vegetation to 9.63%. Compared to this, agent-based model predicted growth in urban landscape to 47.12% and the decline of vegetation to 11.10%. The current research was formulated based on the recommendations of the deliberation between academia and stakeholder industries that are likely to be benefitted by the implementation of the industrial corridor. The research outcome also helps local planning authorities in advance visualization of urban dynamics to design sustainable urban regions with the provision of appropriate infrastructure and basic amenities.

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.

Extensive land cover change across Arctic-Boreal Northwestern North America from disturbance and climate forcing.

A multitude of disturbance agents, such as wildfires, land use, and climate-driven expansion of woody shrubs, is transforming the distribution of plant functional types across Arctic-Boreal ecosystems, which has significant implications for interactions and feedbacks between terrestrial ecosystems and climate in the northern high-latitude. However, because the spatial resolution of existing land cover datasets is too coarse, large-scale land cover changes in the Arctic-Boreal region (ABR) have been poorly characterized. Here, we use 31years (1984-2014) of moderate spatial resolution (30m) satellite imagery over a region spanning 4.7×106 km2 in Alaska and northwestern Canada to characterize regional-scale ABR land cover changes. We find that 13.6±1.3% of the domain has changed, primarily via two major modes of transformation: (a) simultaneous disturbance-driven decreases in Evergreen Forest area (-14.7±3.0% relative to 1984) and increases in Deciduous Forest area (+14.8±5.2%) in the Boreal biome; and (b) climate-driven expansion of Herbaceous and Shrub vegetation (+7.4±2.0%) in the Arctic biome. By using time series of 30m imagery, we characterize dynamics in forest and shrub cover occurring at relatively short spatial scales (hundreds of meters) due to fires, harvest, and climate-induced growth that are not observable in coarse spatial resolution (e.g., 500m or greater pixel size) imagery. Wildfires caused most of Evergreen Forest Loss and Evergreen Forest Gain and substantial areas of Deciduous Forest Gain. Extensive shifts in the distribution of plant functional types at multiple spatial scales are consistent with observations of increased atmospheric CO2 seasonality and ecosystem productivity at northern high-latitudes and signal continental-scale shifts in the structure and function of northern high-latitude ecosystems in response to climate change.

Global climate forcing driven by altered BVOC fluxes from 1990 to 2010 land cover change in maritime Southeast Asia

Abstract. Over the period of 1990–2010, maritime Southeast Asia experienced large-scale land cover changes, including expansion of high-isoprene-emitting oil palm plantations and contraction of low-isoprene-emitting natural forests. The ModelE2-Yale Interactive terrestrial Biosphere global chemistry–climate model is used to quantify the atmospheric composition changes, and for the first time, the associated radiative forcing induced by the land-cover-change-driven biogenic volatile organic compound (BVOC) emission changes (+6.5 TgC y−1 isoprene, −0.5 TgC y−1 monoterpenes). Regionally, surface-level ozone concentrations largely decreased (−3.8 to +0.8 ppbv). The tropical land cover changes occurred in a region of strong convective transport, providing a mechanism for the BVOC perturbations to affect the composition of the upper troposphere. Enhanced concentrations of isoprene and its degradation products are simulated in the upper troposphere, and, on a global-mean basis, land cover change had a stronger impact on ozone in the upper troposphere (+0.5 ppbv) than in the lower troposphere (&lt;0.1 ppbv increase). The positive climate forcing from ozone changes (+9.2 mW m−2) was partially offset by a negative forcing (−0.8 mW m−2) associated with an enhancement in secondary organic aerosol (SOA). The sign of the net forcing is sensitive to uncertainty in the SOA yield from BVOCs. The global-mean ozone forcing per unit of regional oil palm expansion is +1 mW m−2 Mha−1. In light of expected continued expansion of oil palm plantations, regional land cover changes may play an increasingly important role in driving future global ozone radiative forcing.

Recent land cover change after the Kyrill windstorm in the Šumava NP

Mountain forests in Central Europe are mostly disturbed by windstorms and subsequently by insect outbreaks. Disturbances play a key role in forest composition, structure, ecosystem functioning or species richness and consequently in general land cover changes. The Šumava National Park was affected by a windstorm known as Kyrill in January 2007. This event initiated dynamic period of large scale land cover changes from 2006 to 2012. The main goal of this study is to analyse and quantify the development of land cover changes caused by the disturbance with the use of detailed airborne data. We recorded a spatial-temporal classification of changes by so-called land cover flows, which detect changes among defined land cover types.Layers of land cover for each year were collected in GIS software (ArcGIS 10.3) and they were used as inputs for the Land Change Modeler for ArcGIS software. The results show relatively small direct effects of the Kyrill windstorm, windfalls subsequently (in the year 2007) increased their proportion by 4.73 km2, e.g. 0.69% of the Šumava National Park area in 2007. Area of coniferous forest decreased from 56.55% to 48.27% (between 2006 and 2012) of the National Park area and from 2008 this decrease was the dominant change. In neighbourhood of windfalls, new dead-standing forest in 2008 originated. Differences in management in particular zones of the national park resulted in an increase of clear-cuts and clear-cuts with dead wood in the intervention zone. Coniferous forest was widely changed into dead-standing forest in non-intervention areas. This pattern of change was the most intensive between 2008 and 2011. Changes were spatially clustered and dead-standing forest work as a main driver of subsequent dynamics. During the bark beetle infestation period (2008–2011), more than 80% of new dead-standing forest occur within 100 m distance from patches of dead-standing forest from previous year. During the last period (2011–2012) these processes slowed down and large-scale regeneration took place within the focus area.

Modelling the forest transition in Central Western Ghats, India

The Western Ghats forms an important watershed for the entire peninsular India, being the source of 37 west flowing rivers and three major east flowing rivers and their numerous tributaries. However, deforestation due to large scale land cover changes has affected the water sustenance in the region evident from the quantity and duration of water availability during post monsoon period. Land use Land cover changes accelerated by unplanned anthropogenic activities have been the prime mover of global warming and consequent changes in the climate. This necessitates appropriate resource management with an understanding of drivers. Geo-visualization of landscape transitions considering the influential agents will aid in formulating strategies to mitigate global warming. Uttara Kannada district in the Central Western Ghats has the distinction of having highest forest cover in the country and this region is now experiencing rapid forest cover changes. Factors inducing changes in the land cover are normalized through fuzzyfication, considered for Multi criteria Evaluation using Analytical Hierarchy Process (AHP) under high protection and low protection scenarios. Likely land use transitions by 2022 across zones based on transitions during 2004–2007, 2007–2010, 2010–2013 was done through cellular automata and Markov chain process (MC). The analyses highlight the loss of forest cover by 66.55–56.76% by 2022 in the coastal zone with escalating population density. Similar situation of 65.98–55.62% decline in Sahyadri region is noticed with execution of dams, hydroelectric projects and monoculture plantations. Lower transitions as compared with the second scenario highlights regulatory framework’s role in protection. However, forests in plain region show loss of 27.38–11.09% in both scenarios due to population pressure and market induced land cover changes. This necessitates policy interventions by the federal government to mitigate forest loss towards sustainable development.

Environmental Flow Assessment in a Lotic Ecosystem of Central Western Ghats, India

Environmental/Ecological flow refers to the minimum flow of water to be maintained in a water body (river, lake, etc.) to sustain ecosystem services. Understanding environmental flow is important to ensure the local ecological and social (people, agriculture and horticulture, etc.) needs in a sustained and balanced way, while designing large scale projects (such as hydro-electric, river diversion, etc.). Western Ghats are the mountain ranges extending from southern tip of India (Tamil Nadu-Kanyakumari) to Gujarat. These mountain ranges are rich in biodiversity with diverse and endemic flora and fauna, and is birth place to numerous perennial rivers namely Netravathi, Sita, Sharavathi, Aghanashini, Krishna, Cauvery, etc. Western Ghats is often referred as water tower of peninsular India, due to the water and food security provided by the ecosystem through array of services. The region is also one among 35 global biodiversity hotspots. However, deforestation due to large scale land cover changes has affected the water sustenance in the region evident from the quantity and duration of water availability during post monsoon period. Forests in the Western Ghats along with the soil characteristics and precipitation plays a major role in storing water in sub-surface (vadoze and groundwater) zones during monsoon, and releases to the streams during post monsoon periods catering to the needs of the dependent biota including humans. Some of these undisturbed/ unaltered natural flow conditions in rivers and streams have proved their worth with the presence of rich and diverse species and array of ecosystem services, which also has helped in sustaining the livelihood of dependent populations. The undisturbed flow conditions guarantees the natural flow as well as minimum flow in streams to sustain the ecosystem services, which helps in meeting the social and ecological needs. Growing demand to cater the demands of burgeoning human population coupled with accelerated pace of deforestation due to unplanned and senseless developmental projects in the ecologically fragile regions have led the water scarcity even in regions receiving high amount of rainfall. In the current communication an attempt is made to understand the linkages between the hydrological dynamics across varied landscape with the anthropogenic and ecological water needs. If the available water resource meets the societal and environmental demands across seasons, the catchment is said to achieve the minimum flow requirements. The federal government has plans to divert the water from rivers in Western Ghats region to the dry arid regions in Karnataka. In this regard, environmental flow assessment of Yettinahole river in Central Western Ghats is carried out to understand the feasibility of river diversion through the assessment of hydrologic regime with the analysis of land use dynamics (using remote sensing data), meteorological data (rainfall, temperature, etc. from IMD, Pune), hydrological data (from gauged streams) apart from field investigations in the catchment. The catchments receive annual rainfall of 3000-5000 mm (Department of Statistics, Government of Karnataka). Land use analyses reveal that Major portion of the catchment is covered with evergreen forest (45.08%) followed by agriculture plantations (29.05%) and grass lands (24.06%). Water yield in the catchment computed for each of sub-catchments based on the current land use and other related hydrological parameters using empirical method. The total runoff yield from the catchments is estimated to be 9.55 TMC. About 5.84 TMC is required for domestic purposes including agriculture, horticulture and livestock rearing. The quantum of water required to sustain fish life in the streams is about 2 TMC, computed based on hydrological discharge monitoring and fish diversity in streams during 18 months (covering all seasons) in select streams in Western Ghats. Considering the available water is sufficient only to meet the anthropogenic and ecological needs in the region, the sustainable option to meet the water requirements in dry arid regions would be through (i) decentralized water harvesting (through tanks, ponds, lakes, etc.), (ii) rejuvenation or restoration of existing lakes/ponds, (iii) reuse of waste water, (iv) recharging groundwater resources, (v) planting native species of grasses and tree species in the catchment (to enhance percolation of water in the catchment), (vi) implementation of soil and water conservation through micro-watershed approaches. Implementation of these location specific approaches in arid regions would cost much less compared to the river diversion projects, which if implemented would help the section of the society involved in decision making, construction and implementation of the project.

Mapping CORINE Land Cover from Sentinel-1A SAR and SRTM Digital Elevation Model Data using Random Forests

The European CORINE land cover mapping scheme is a standardized classification system with 44 land cover and land use classes. It is used by the European Environment Agency to report large-scale land cover change with a minimum mapping unit of 5 ha every six years and operationally mapped by its member states. The most commonly applied method to map CORINE land cover change is by visual interpretation of optical/near-infrared satellite imagery. The Sentinel-1A satellite carries a C-band Synthetic Aperture Radar (SAR) and was launched in 2014 by the European Space Agency as the first operational Copernicus mission. This study is the first investigation of Sentinel-1A for CORINE land cover mapping. Two of the first Sentinel-1A images acquired during its ramp-up phase in May and December 2014 over Thuringia in Germany are analysed. 27 hybrid level 2/3 CORINE classes are defined. 17 of these were present at the study site and classified based on a stratified random sample of training pixels from the polygon-eroded CORINE 2006 map. Sentinel-1A logarithmic radar backscatter at HH and HV polarisation (May acquisition), VV and VH polarisation (December acquisition), and the HH image texture are used as input bands to the classification. In addition, a Digital Terrain Model (DTM), a Canopy Height Model (CHM) and slope and aspect maps from the Shuttle Radar Topography Mission (SRTM) are used as input bands to account for geomorphological features of the landscape. In future, elevation data will be delivered for areas with sufficiently high coherence from the Sentinel-1A Interferometric Wide-Swath Mode itself. When augmented by elevation data from radar interferometry, Sentinel-1A is able to discriminate several CORINE land cover classes, making it useful for monitoring of cloud-covered regions. A bistatic Sentinel-1 Convoy mission would enable single-pass interferometric acquisitions without temporal decorrelation.

Spatio-temporal sensitivity of MODIS land surface temperature anomalies indicates high potential for large-scale land cover change detection in Arctic permafrost landscapes

The accelerated warming of the Arctic climate may alter the local and regional surface energy balances, for which changing land surface temperatures (LSTs) are a key indicator. Modeling current and anticipated changes in the surface energy balance requires an understanding of the spatio-temporal interactions between LSTs and land cover, both of which can be monitored globally by measurements from space. This paper investigates the accuracy of the MODIS LST/Emissivity Daily L3 Global 1km V005 product and its spatio-temporal sensitivity to land surface properties in a Canadian High Arctic permafrost landscape. The land cover ranged from fully vegetated wet sedge tundra to barren rock. MODIS LSTs were compared with in situ radiometer measurements from wet tundra areas collected over a 2-year period from July 2008 to July 2010 including both summer and winter conditions. The accuracy of the MODIS LSTs was −1.1°C with a root mean square error of 3.9°C over the entire observation period. Agreement was lowest during the freeze-back periods where MODIS LST showed a cold bias likely due to the overrepresentation of clear-sky conditions. A multi-year analysis of LST spatial anomalies, i.e., the difference between MODIS LSTs and the MODIS LST regional mean, revealed a robust spatio-temporal pattern. Highest variability in LST anomalies was found during freeze-up and thaw periods as well as for open water surface in early summer due to the presence or absence of snow or ice. The summer anomaly pattern was similar for all three years despite strong differences in precipitation, air temperature and net radiation. Summer periods with regional mean LSTs above 5.0°C showed the greatest spatial diversity with four distinct 2.0°C classes. Summer anomalies ranged from −4.5°C to 2.6°C with an average standard deviation of 1.8°C. Dry ridge areas heated up the most, while wetland areas and dry areas of sparsely vegetated bedrock with a high albedo remained coolest. The observed summer LST anomalies can be used as a baseline against which to evaluate both past and future changes in land surface properties that relate to the surface energy balance. Summer anomaly classes mainly reflected a combination of albedo and surface wetness. The potential to use this tool to monitor surface drying and wetting in the Arctic should therefore be further explored. A multi-sensor approach combining thermal satellite measurements with optical and radar imagery promises to be an effective tool for a dynamic, process-based ecosystem monitoring scheme.

Approach to the analysis of land cover dynamics using change detection and spatial stochastic modeling

The important problem of land cover dynamics analysis is considered. We propose a multi-step approach using methods of land cover change detection and an original method for evaluating the scale of changes is proposed. Applying this approach to a large archive of multi-temporal aerospace monitoring data makes it possible to choose only large-scale changes in land cover that deserve a more careful expert examination, and as a consequence, to perform a more rapid and comprehensive aerospace monitoring. The approach has been tested on problems of analyzing the land cover dynamics in Portugal under the LANDYN international research project. This paper presents some estimates of the scale of changes in the study area and results of long-term modeling of the development of the area, including alternative conditional scenarios.

Assessment of Large Scale Land Cover Change Classifications and Drivers of Deforestation in Indonesia

Abstract. Indonesia possesses the third largest tropical forests coverage following Brazilian Amazon and Congo Basin regions. This country, however, suffered from the highest deforestation rate surpassing deforestation in the Brazilian Amazon in 2012. National capacity for forest change assessment and monitoring has been well-established in Indonesia and the availability of national forest inventory data could largely assist the country to report their forest carbon stocks and change over more than two decades. This work focuses for refining forest cover change mapping and deforestation estimate at national scale applying over 10,000 scenes of Landsat scenes, acquired in 1990, 1996, 2000, 2003, 2006, 2009, 2011 and 2012. Pre-processing of the data includes, geometric corrections and image mosaicking. The classification of mosaic Landsat data used multi-stage visual observation approaches, verified using ground observations and comparison with other published materials. There are 23 land cover classes identified from land cover data, presenting spatial information of forests, agriculture, plantations, non-vegetated lands and other land use categories. We estimated the magnitude of forest cover change and assessed drivers of forest cover change over time. Forest change trajectories analysis was also conducted to observe dynamics of forest cover across time. This study found that careful interpretations of satellite data can provide reliable information on forest cover and change. Deforestation trend in Indonesia was lower in 2000-2012 compared to 1990-2000 periods. We also found that over 50% of forests loss in 1990 remains unproductive in 2012. Major drivers of forest conversion in Indonesia range from shrubs/open land, subsistence agriculture, oil palm expansion, plantation forest and mining. The results were compared with other available datasets and we obtained that the MOF data yields reliable estimate of deforestation.