903 resultados para Land cover classification
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mbikulam Tiger Reserve of Western Ghats using Geospatial technology. The major objectives of the study are Land use land cover mapping (LULC) and Phytodiversity analysis. Satellite data was used to map the land use / land cover using supervised classification techniques in Erdas imagine. The change for a period of 32 years was assessed using the multi-temporal satellite datasets from Landsat MSS (1973), Landsat TM (1990), and IRS P6 LISS III (2005). A geospatial approach was used for the land cover analysis. Digital elevation models, Satellite imageries and SOI topo sheets were the data sets used in the analysis. Vegetation sampling plots distributed over the different forest types were enumerated and studied for Phytodiversity analysis.
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Urbanization refers to the process in which an increasing proportion of a population lives in cities and suburbs. Urbanization fuels the alteration of the Land use/Land cover pattern of the region including increase in built-up area, leading to imperviousness of the ground surface. With increasing urbanization and population pressures; the impervious areas in the cities are increasing fast. An impervious surface refers to an anthropogenic ally modified surface that prevents water from infiltrating into the soil. Surface imperviousness mapping is important for the studies related to water cycling, water quality, soil erosion, flood water drainage, non-point source pollution, urban heat island effect and urban hydrology. The present study estimates the Total Impervious Area (TIA) of the city of Kochi using high resolution satellite image (LISS IV, 5m. resolution). Additionally the study maps the Effective Impervious Area (EIA) by coupling the capabilities of GIS and Remote Sensing. Land use/Land cover map of the study area was prepared from the LISS IV image acquired for the year 2012. The classes were merged to prepare a map showing pervious and impervious area. Supervised Maximum Likelihood Classification (Supervised MLC),which is a simple but accurate method for image classification, is used in calculating TIA and an overall classification accuracy of 86.33% was obtained. Water bodies are 100% pervious, whereas urban built up area are 100% impervious. Further based on percentage of imperviousness, the Total Impervious Area is categorized into various classes
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The 21st century has brought new challenges for forest management at a time when globalization in world trade is increasing and global climate change is becoming increasingly apparent. In addition to various goods and services like food, feed, timber or biofuels being provided to humans, forest ecosystems are a large store of terrestrial carbon and account for a major part of the carbon exchange between the atmosphere and the land surface. Depending on the stage of the ecosystems and/or management regimes, forests can be either sinks, or sources of carbon. At the global scale, rapid economic development and a growing world population have raised much concern over the use of natural resources, especially forest resources. The challenging question is how can the global demands for forest commodities be satisfied in an increasingly globalised economy, and where could they potentially be produced? For this purpose, wood demand estimates need to be integrated in a framework, which is able to adequately handle the competition for land between major land-use options such as residential land or agricultural land. This thesis is organised in accordance with the requirements to integrate the simulation of forest changes based on wood extraction in an existing framework for global land-use modelling called LandSHIFT. Accordingly, the following neuralgic points for research have been identified: (1) a review of existing global-scale economic forest sector models (2) simulation of global wood production under selected scenarios (3) simulation of global vegetation carbon yields and (4) the implementation of a land-use allocation procedure to simulate the impact of wood extraction on forest land-cover. Modelling the spatial dynamics of forests on the global scale requires two important inputs: (1) simulated long-term wood demand data to determine future roundwood harvests in each country and (2) the changes in the spatial distribution of woody biomass stocks to determine how much of the resource is available to satisfy the simulated wood demands. First, three global timber market models are reviewed and compared in order to select a suitable economic model to generate wood demand scenario data for the forest sector in LandSHIFT. The comparison indicates that the ‘Global Forest Products Model’ (GFPM) is most suitable for obtaining projections on future roundwood harvests for further study with the LandSHIFT forest sector. Accordingly, the GFPM is adapted and applied to simulate wood demands for the global forestry sector conditional on selected scenarios from the Millennium Ecosystem Assessment and the Global Environmental Outlook until 2050. Secondly, the Lund-Potsdam-Jena (LPJ) dynamic global vegetation model is utilized to simulate the change in potential vegetation carbon stocks for the forested locations in LandSHIFT. The LPJ data is used in collaboration with spatially explicit forest inventory data on aboveground biomass to allocate the demands for raw forest products and identify locations of deforestation. Using the previous results as an input, a methodology to simulate the spatial dynamics of forests based on wood extraction is developed within the LandSHIFT framework. The land-use allocation procedure specified in the module translates the country level demands for forest products into woody biomass requirements for forest areas, and allocates these on a five arc minute grid. In a first version, the model assumes only actual conditions through the entire study period and does not explicitly address forest age structure. Although the module is in a very preliminary stage of development, it already captures the effects of important drivers of land-use change like cropland and urban expansion. As a first plausibility test, the module performance is tested under three forest management scenarios. The module succeeds in responding to changing inputs in an expected and consistent manner. The entire methodology is applied in an exemplary scenario analysis for India. A couple of future research priorities need to be addressed, particularly the incorporation of plantation establishments; issue of age structure dynamics; as well as the implementation of a new technology change factor in the GFPM which can allow the specification of substituting raw wood products (especially fuelwood) by other non-wood products.
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Land use has become a force of global importance, considering that 34% of the Earth’s ice-free surface was covered by croplands or pastures in 2000. The expected increase in global human population together with eminent climate change and associated search for energy sources other than fossil fuels can, through land-use and land-cover changes (LUCC), increase the pressure on nature’s resources, further degrade ecosystem services, and disrupt other planetary systems of key importance to humanity. This thesis presents four modeling studies on the interplay between LUCC, increased production of biofuels and climate change in four selected world regions. In the first study case two new crop types (sugarcane and jatropha) are parameterized in the LPJ for managed Lands dynamic global vegetation model for calculation of their potential productivity. Country-wide spatial variation in the yields of sugarcane and jatropha incurs into substantially different land requirements to meet the biofuel production targets for 2015 in Brazil and India, depending on the location of plantations. Particularly the average land requirements for jatropha in India are considerably higher than previously estimated. These findings indicate that crop zoning is important to avoid excessive LUCC. In the second study case the LandSHIFT model of land-use and land-cover changes is combined with life cycle assessments to investigate the occurrence and extent of biofuel-driven indirect land-use changes (ILUC) in Brazil by 2020. The results show that Brazilian biofuels can indeed cause considerable ILUC, especially by pushing the rangeland frontier into the Amazonian forests. The carbon debt caused by such ILUC would result in no carbon savings (from using plant-based ethanol and biodiesel instead of fossil fuels) before 44 years for sugarcane ethanol and 246 years for soybean biodiesel. The intensification of livestock grazing could avoid such ILUC. We argue that such an intensification of livestock should be supported by the Brazilian biofuel sector, based on the sector’s own interest in minimizing carbon emissions. In the third study there is the development of a new method for crop allocation in LandSHIFT, as influenced by the occurrence and capacity of specific infrastructure units. The method is exemplarily applied in a first assessment of the potential availability of land for biogas production in Germany. The results indicate that Germany has enough land to fulfill virtually all (90 to 98%) its current biogas plant capacity with only cultivated feedstocks. Biogas plants located in South and Southwestern (North and Northeastern) Germany might face more (less) difficulties to fulfill their capacities with cultivated feedstocks, considering that feedstock transport distance to plants is a crucial issue for biogas production. In the fourth study an adapted version of LandSHIFT is used to assess the impacts of contrasting scenarios of climate change and conservation targets on land use in the Brazilian Amazon. Model results show that severe climate change in some regions by 2050 can shift the deforestation frontier to areas that would experience low levels of human intervention under mild climate change (such as the western Amazon forests or parts of the Cerrado savannas). Halting deforestation of the Amazon and of the Brazilian Cerrado would require either a reduction in the production of meat or an intensification of livestock grazing in the region. Such findings point out the need for an integrated/multicisciplinary plan for adaptation to climate change in the Amazon. The overall conclusions of this thesis are that (i) biofuels must be analyzed and planned carefully in order to effectively reduce carbon emissions; (ii) climate change can have considerable impacts on the location and extent of LUCC; and (iii) intensification of grazing livestock represents a promising venue for minimizing the impacts of future land-use and land-cover changes in Brazil.
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En este trabajo se describe la utilización de herramientas de software libre, básicamente GRASS y R, para obtener una serie de mapas de coberturas del suelo (1976-2006) a partir de imágenes de satélite Landsat MSS y Landsat TM. Se trata de un proyecto concedido a un año, por lo que se requería una metodología que permitiera realizar el análisis de forma rápida y sencilla, aún tratando de aplicar técnicas de clasificación avanzadas. Dada la complejidad del trabajo y la premura de tiempo, se ha tratado de automatizar gran parte del trabajo mediante diversos scripts con BASH y R. (...)
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Entre el 14 i el 18 de març de 1998 es va celebrar a Barcelona la conferència Earth’s Changing Land sota la tutela dels programes internacionals Global Change in Terrestrial Ecosystems (GCTE) i Land Use and Land Cover Change (LUCC). L’objectiu principal de la trobada era presentar les darreres aportacions científiques sobre els efectes presents i previsibles del canvi global sobre els ecosistemes terrestres i la societat. Al mateix temps, es volia afavorir l’establiment de ponts de diàleg entre els professionals implicats en el canvi global
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Within this paper modern techniques such as satellite image analysis and tools provided by geographic information systems (GIS.) are exploited in order to extend and improve existing techniques for mapping the spatial distribution of sediment transport processes. The processes of interest comprise mass movements such as solifluction, slope wash, dirty avalanches and rock- and boulder falls. They differ considerably in nature and therefore different approaches for the derivation of their spatial extent are required. A major challenge is addressing the differences between the comparably coarse resolution of the available satellite data (Landsat TM/ETM+, 30 in x 30 m) and the actual scale of sediment transport in this environment. A three-stepped approach has been developed which is based on the concept of Geomorphic Process Units (GPUs): parameterization, process area delineation and combination. Parameters include land cover from satellite data and digital elevation model derivatives. Process areas are identified using a hierarchical classification scheme utilizing thresholds and definition of topology. The approach has been developed for the Karkevagge in Sweden and could be successfully transferred to the Rabotsbekken catchment at Okstindan, Norway using similar input data. Copyright (C) 2008 John Wiley & Sons, Ltd.
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Land use and land cover changes in the Brazilian Amazon have major implications for regional and global carbon (C) cycling. Cattle pasture represents the largest single use (about 70%) of this once-forested land in most of the region. The main objective of this study was to evaluate the accuracy of the RothC and Century models at estimating soil organic C (SOC) changes under forest-to-pasture conditions in the Brazilian Amazon. We used data from 11 site-specific 'forest to pasture' chronosequences with the Century Ecosystem Model (Century 4.0) and the Rothamsted C Model (RothC 26.3). The models predicted that forest clearance and conversion to well managed pasture would cause an initial decline in soil C stocks (0-20 cm depth), followed in the majority of cases by a slow rise to levels exceeding those under native forest. One exception to this pattern was a chronosequence in Suia-Missu, which is under degraded pasture. In three other chronosequences the recovery of soil C under pasture appeared to be only to about the same level as under the previous forest. Statistical tests were applied to determine levels of agreement between simulated SOC stocks and observed stocks for all the sites within the 11 chronosequences. The models also provided reasonable estimates (coefficient of correlation = 0.8) of the microbial biomass C in the 0-10 cm soil layer for three chronosequences, when compared with available measured data. The Century model adequately predicted the magnitude and the overall trend in delta C-13 for the six chronosequences where measured 813 C data were available. This study gave independent tests of model performance, as no adjustments were made to the models to generate outputs. Our results suggest that modelling techniques can be successfully used for monitoring soil C stocks and changes, allowing both the identification of current patterns in the soil and the projection of future conditions. Results were used and discussed not only to evaluate soil C dynamics but also to indicate soil C sequestration opportunities for the Brazilian Amazon region. Moreover, modelling studies in these 'forest to pasture' systems have important applications, for example, the calculation of CO, emissions from land use change in national greenhouse gas inventories. (0 2007 Elsevier B.V. All rights reserved.
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A mesoscale meteorological model (FOOT3DK) is coupled with a gas exchange model to simulate surface fluxes of CO2 and H2O under field conditions. The gas exchange model consists of a C3 single leaf photosynthesis sub-model and an extended big leaf (sun/shade) sub-model that divides the canopy into sunlit and shaded fractions. Simulated CO2 fluxes of the stand-alone version of the gas exchange model correspond well to eddy-covariance measurements at a test site in a rural area in the west of Germany. The coupled FOOT3DK/gas exchange model is validated for the diurnal cycle at singular grid points, and delivers realistic fluxes with respect to their order of magnitude and to the general daily course. Compared to the Jarvis-based big leaf scheme, simulations of latent heat fluxes with a photosynthesis-based scheme for stomatal conductance are more realistic. As expected, flux averages are strongly influenced by the underlying land cover. While the simulated net ecosystem exchange is highly correlated with leaf area index, this correlation is much weaker for the latent heat flux. Photosynthetic CO2 uptake is associated with transpirational water loss via the stomata, and the resulting opposing surface fluxes of CO2 and H2O are reproduced with the model approach. Over vegetated surfaces it is shown that the coupling of a photosynthesis-based gas exchange model with the land-surface scheme of a mesoscale model results in more realistic simulated latent heat fluxes.
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We present a simple theoretical land-surface classification that can be used to determine the location and temporal behavior of preferential sources of terrestrial dust emissions. The classification also provides information about the likely nature of the sediments, their erodibility and the likelihood that they will generate emissions under given conditions. The scheme is based on the dual notions of geomorphic type and connectivity between geomorphic units. We demonstrate that the scheme can be used to map potential modern-day dust sources in the Chihuahuan Desert, the Lake Eyre Basin and the Taklamakan. Through comparison with observed dust emissions, we show that the scheme provides a reasonable prediction of areas of emission in the Chihuahuan Desert and in the Lake Eyre Basin. The classification is also applied to point source data from the Western Sahara to enable comparison of the relative importance of different land surfaces for dust emissions. We indicate how the scheme could be used to provide an improved characterization of preferential dust sources in global dust-cycle models.
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This paper presents results of the AQL2004 project, which has been develope within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLatif). The project intended to obtain monthly burned-land maps of the entire region, from Mexico to Patagonia, using MODIS (moderate-resolution imaging spectroradiometer) reflectance data. The project has been organized in three different phases: acquisition and preprocessing of satellite data; discrimination of burned pixels; and validation of results. In the first phase, input data consisting of 32-day composites of MODIS 500-m reflectance data generated by the Global Land Cover Facility (GLCF) of the University of Maryland (College Park, Maryland, U.S.A.) were collected and processed. The discrimination of burned areas was addressed in two steps: searching for "burned core" pixels using postfire spectral indices and multitemporal change detection and mapping of burned scars using contextual techniques. The validation phase was based on visual analysis of Landsat and CBERS (China-Brazil Earth Resources Satellite) images. Validation of the burned-land category showed an agreement ranging from 30% to 60%, depending on the ecosystem and vegetation species present. The total burned area for the entire year was estimated to be 153 215 km2. The most affected countries in relation to their territory were Cuba, Colombia, Bolivia, and Venezuela. Burned areas were found in most land covers; herbaceous vegetation (savannas and grasslands) presented the highest proportions of burned area, while perennial forest had the lowest proportions. The importance of croplands in the total burned area should be taken with reserve, since this cover presented the highest commission errors. The importance of generating systematic products of burned land areas for different ecological processes is emphasized.
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Future land cover will have a significant impact on climate and is strongly influenced by the extent of agricultural land use. Differing assumptions of crop yield increase and carbon pricing mitigation strategies affect projected expansion of agricultural land in future scenarios. In the representative concentration pathway 4.5 (RCP4.5) from phase 5 of the Coupled Model Intercomparison Project (CMIP5), the carbon effects of these land cover changes are included, although the biogeophysical effects are not. The afforestation in RCP4.5 has important biogeophysical impacts on climate, in addition to the land carbon changes, which are directly related to the assumption of crop yield increase and the universal carbon tax. To investigate the biogeophysical climatic impact of combinations of agricultural crop yield increases and carbon pricing mitigation, five scenarios of land-use change based on RCP4.5 are used as inputs to an earth system model [Hadley Centre Global Environment Model, version 2-Earth System (HadGEM2-ES)]. In the scenario with the greatest increase in agricultural land (as a result of no increase in crop yield and no climate mitigation) there is a significant -0.49 K worldwide cooling by 2100 compared to a control scenario with no land-use change. Regional cooling is up to -2.2 K annually in northeastern Asia. Including carbon feedbacks from the land-use change gives a small global cooling of -0.067 K. This work shows that there are significant impacts from biogeophysical land-use changes caused by assumptions of crop yield and carbon mitigation, which mean that land carbon is not the whole story. It also elucidates the potential conflict between cooling from biogeophysical climate effects of land-use change and wider environmental aims.
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Datasets containing information to locate and identify water bodies have been generated from data locating static-water-bodies with resolution of about 300 m (1/360 deg) recently released by the Land Cover Climate Change Initiative (LC CCI) of the European Space Agency. The LC CCI water-bodies dataset has been obtained from multi-temporal metrics based on time series of the backscattered intensity recorded by ASAR on Envisat between 2005 and 2010. The new derived datasets provide coherently: distance to land, distance to water, water-body identifiers and lake-centre locations. The water-body identifier dataset locates the water bodies assigning the identifiers of the Global Lakes and Wetlands Database (GLWD), and lake centres are defined for in-land waters for which GLWD IDs were determined. The new datasets therefore link recent lake/reservoir/wetlands extent to the GLWD, together with a set of coordinates which locates unambiguously the water bodies in the database. Information on distance-to-land for each water cell and the distance-to-water for each land cell has many potential applications in remote sensing, where the applicability of geophysical retrieval algorithms may be affected by the presence of water or land within a satellite field of view (image pixel). During the generation and validation of the datasets some limitations of the GLWD database and of the LC CCI water-bodies mask have been found. Some examples of the inaccuracies/limitations are presented and discussed. Temporal change in water-body extent is common. Future versions of the LC CCI dataset are planned to represent temporal variation, and this will permit these derived datasets to be updated.
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In this work we explore the synergistic use of future MSI instrument on board Sentinel-2 platform and OLCI/SLSTR instruments on board Sentinel-3 platform in order to improve LST products currently derived from the single AATSR instrument on board the ENVI- SAT satellite. For this purpose, the high spatial resolu- tion data from Setinel2/MSI will be used for a good characterization of the land surface sub-pixel heteroge- neity, in particular for a precise parameterization of surface emissivity using a land cover map and spectral mixture techniques. On the other hand, the high spectral resolution of OLCI instrument, suitable for a better characterization of the atmosphere, along with the dual- view available in the SLTSR instrument, will allow a better atmospheric correction through improved aero- sol/water vapor content retrievals and the implementa- tion of novel cloud screening procedures. Effective emissivity and atmospheric corrections will allow accu- rate LST retrievals using the SLSTR thermal bands by developing a synergistic split-window/dual-angle algo- rithm. ENVISAT MERIS and AATSR instruments and different high spatial resolution data (Landsat/TM, Proba/CHRIS, Terra/ASTER) will be used as bench- mark for the future OLCI, SLSTR and MSI instruments. Results will be validated using ground data collected in the framework of different field campaigns organized by ESA.
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The first agricultural societies were established around 10 ka BP and had spread across much of Europe and southern Asia by 5.5 ka BP with resultant anthropogenic deforestation for crop and pasture land. Various studies (e.g. Joos et al., 2004; Kaplan et al., 2011; Mitchell et al., 2013) have attempted to assess the biogeochemical implications for Holocene climate in terms of increased carbon dioxide and methane emissions. However, less work has been done to examine the biogeophysical impacts of this early land use change. In this study, global climate model simulations with Hadley Centre Coupled Model version 3 (HadCM3) were used to examine the biogeophysical effects of Holocene land cover change on climate, both globally and regionally, from the early Holocene (8 ka BP) to the early industrial era (1850 CE). Two experiments were performed with alternative descriptions of past vegetation: (i) one in which potential natural vegetation was simulated by Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) but without land use changes and (ii) one where the anthropogenic land use model Kaplan and Krumhardt 2010 (KK10; Kaplan et al., 2009, 2011) was used to set the HadCM3 crop regions. Snapshot simulations were run at 1000-year intervals to examine when the first signature of anthropogenic climate change can be detected both regionally, in the areas of land use change, and globally. Results from our model simulations indicate that in regions of early land disturbance such as Europe and south-east Asia detectable temperature changes, outside the normal range of variability, are encountered in the model as early as 7 ka BP in the June–July–August (JJA) season and throughout the entire annual cycle by 2–3 ka BP. Areas outside the regions of land disturbance are also affected, with virtually the whole globe experiencing significant temperature changes (predominantly cooling) by the early industrial period. The global annual mean temperature anomalies found in our single model simulations were −0.22 at 1850 CE, −0.11 at 2 ka BP, and −0.03 °C at 7 ka BP. Regionally, the largest temperature changes were in Europe with anomalies of −0.83 at 1850 CE, −0.58 at 2 ka BP, and −0.24 °C at 7 ka BP. Large-scale precipitation features such as the Indian monsoon, the Intertropical Convergence Zone (ITCZ), and the North Atlantic storm track are also impacted by local land use and remote teleconnections. We investigated how advection by surface winds, mean sea level pressure (MSLP) anomalies, and tropospheric stationary wave train disturbances in the mid- to high latitudes led to remote teleconnections.