Spatio-temporal land use/land cover changes analysis and monitoring in the Valencia Municipality, Spain

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Urban land use change analysis and modelling: a case study of Setubal-Sesimbra, Portugal

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Knowing the past to predict the future: land-use change and the distribution of invasive bullfrogs

Biological invasions and land-use changes are two major causes of the global modifications of biodiversity. Habitat suitability models are the tools of choice to predict potential distributions of invasive species. Although land-use is a key driver of alien species invasions, it is often assumed that land-use is constant in time. Here we combine historical and present day information, to evaluate whether land-use changes could explain the dynamic of invasion of the American bullfrog Rana catesbeiana (=Lithobathes catesbeianus) in Northern Italy, from the 1950s to present-day. We used maxent to build habitat suitability models, on the basis of past (1960s, 1980s) and present-day data on land-uses and species distribution. For example, we used models built using the 1960s data to predict distribution in the 1980s, and so on. Furthermore, we used land-use scenarios to project suitability in the future. Habitat suitability models predicted well the spread of bullfrogs in the subsequent temporal step. Models considering land-use changes predicted invasion dynamics better than models assuming constant land-use over the last 50 years. Scenarios of future land-use suggest that suitability will remain similar in the next years. Habitat suitability models can help to understand and predict the dynamics of invasions; however, land-use is not constant in time: land-use modifications can strongly affect invasions; furthermore, both land management and the suitability of a given land-use class may vary in time. An integration of land-use changes in studies of biological invasions can help to improve management strategies.

Modelling tree population dynamics at the alpine and boreal tree-line ecotones in response to climate and land-use change

Summary Ecotones are sensitive to change because they contain high numbers of species living at the margin of their environmental tolerance. This is equally true of tree-lines, which are determined by attitudinal or latitudinal temperature gradients. In the current context of climate change, they are expected to undergo modifications in position, tree biomass and possibly species composition. Attitudinal and latitudinal tree-lines differ mainly in the steepness of the underlying temperature gradient: distances are larger at latitudinal tree-lines, which could have an impact on the ability of tree species to migrate in response to climate change. Aside from temperature, tree-lines are also affected on a more local level by pressure from human activities. These are also changing as a consequence of modifications in our societies and may interact with the effects of climate change. Forest dynamics models are often used for climate change simulations because of their mechanistic processes. The spatially-explicit model TreeMig was used as a base to develop a model specifically tuned for the northern European and Alpine tree-line ecotones. For the latter, a module for land-use change processes was also added. The temperature response parameters for the species in the model were first calibrated by means of tree-ring data from various species and sites at both tree-lines. This improved the growth response function in the model, but also lead to the conclusion that regeneration is probably more important than growth for controlling tree-line position and species' distributions. The second step was to implement the module for abandonment of agricultural land in the Alps, based on an existing spatial statistical model. The sensitivity of its most important variables was tested and the model's performance compared to other modelling approaches. The probability that agricultural land would be abandoned was strongly influenced by the distance from the nearest forest and the slope, bath of which are proxies for cultivation costs. When applied to a case study area, the resulting model, named TreeMig-LAb, gave the most realistic results. These were consistent with observed consequences of land-abandonment such as the expansion of the existing forest and closing up of gaps. This new model was then applied in two case study areas, one in the Swiss Alps and one in Finnish Lapland, under a variety of climate change scenarios. These were based on forecasts of temperature change over the next century by the IPCC and the HadCM3 climate model (ΔT: +1.3, +3.5 and +5.6 °C) and included a post-change stabilisation period of 300 years. The results showed radical disruptions at both tree-lines. With the most conservative climate change scenario, species' distributions simply shifted, but it took several centuries reach a new equilibrium. With the more extreme scenarios, some species disappeared from our study areas (e.g. Pinus cembra in the Alps) or dwindled to very low numbers, as they ran out of land into which they could migrate. The most striking result was the lag in the response of most species, independently from the climate change scenario or tree-line type considered. Finally, a statistical model of the effect of reindeer (Rangifer tarandus) browsing on the growth of Pinus sylvestris was developed, as a first step towards implementing human impacts at the boreal tree-line. The expected effect was an indirect one, as reindeer deplete the ground lichen cover, thought to protect the trees against adverse climate conditions. The model showed a small but significant effect of browsing, but as the link with the underlying climate variables was unclear and the model was not spatial, it was not usable as such. Developing the TreeMig-LAb model allowed to: a) establish a method for deriving species' parameters for the growth equation from tree-rings, b) highlight the importance of regeneration in determining tree-line position and species' distributions and c) improve the integration of social sciences into landscape modelling. Applying the model at the Alpine and northern European tree-lines under different climate change scenarios showed that with most forecasted levels of temperature increase, tree-lines would suffer major disruptions, with shifts in distributions and potential extinction of some tree-line species. However, these responses showed strong lags, so these effects would not become apparent before decades and could take centuries to stabilise. Résumé Les écotones son sensibles au changement en raison du nombre élevé d'espèces qui y vivent à la limite de leur tolérance environnementale. Ceci s'applique également aux limites des arbres définies par les gradients de température altitudinaux et latitudinaux. Dans le contexte actuel de changement climatique, on s'attend à ce qu'elles subissent des modifications de leur position, de la biomasse des arbres et éventuellement des essences qui les composent. Les limites altitudinales et latitudinales diffèrent essentiellement au niveau de la pente des gradients de température qui les sous-tendent les distance sont plus grandes pour les limites latitudinales, ce qui pourrait avoir un impact sur la capacité des espèces à migrer en réponse au changement climatique. En sus de la température, la limite des arbres est aussi influencée à un niveau plus local par les pressions dues aux activités humaines. Celles-ci sont aussi en mutation suite aux changements dans nos sociétés et peuvent interagir avec les effets du changement climatique. Les modèles de dynamique forestière sont souvent utilisés pour simuler les effets du changement climatique, car ils sont basés sur la modélisation de processus. Le modèle spatialement explicite TreeMig a été utilisé comme base pour développer un modèle spécialement adapté pour la limite des arbres en Europe du Nord et dans les Alpes. Pour cette dernière, un module servant à simuler des changements d'utilisation du sol a également été ajouté. Tout d'abord, les paramètres de la courbe de réponse à la température pour les espèces inclues dans le modèle ont été calibrées au moyen de données dendrochronologiques pour diverses espèces et divers sites des deux écotones. Ceci a permis d'améliorer la courbe de croissance du modèle, mais a également permis de conclure que la régénération est probablement plus déterminante que la croissance en ce qui concerne la position de la limite des arbres et la distribution des espèces. La seconde étape consistait à implémenter le module d'abandon du terrain agricole dans les Alpes, basé sur un modèle statistique spatial existant. La sensibilité des variables les plus importantes du modèle a été testée et la performance de ce dernier comparée à d'autres approches de modélisation. La probabilité qu'un terrain soit abandonné était fortement influencée par la distance à la forêt la plus proche et par la pente, qui sont tous deux des substituts pour les coûts liés à la mise en culture. Lors de l'application en situation réelle, le nouveau modèle, baptisé TreeMig-LAb, a donné les résultats les plus réalistes. Ceux-ci étaient comparables aux conséquences déjà observées de l'abandon de terrains agricoles, telles que l'expansion des forêts existantes et la fermeture des clairières. Ce nouveau modèle a ensuite été mis en application dans deux zones d'étude, l'une dans les Alpes suisses et l'autre en Laponie finlandaise, avec divers scénarios de changement climatique. Ces derniers étaient basés sur les prévisions de changement de température pour le siècle prochain établies par l'IPCC et le modèle climatique HadCM3 (ΔT: +1.3, +3.5 et +5.6 °C) et comprenaient une période de stabilisation post-changement climatique de 300 ans. Les résultats ont montré des perturbations majeures dans les deux types de limites de arbres. Avec le scénario de changement climatique le moins extrême, les distributions respectives des espèces ont subi un simple glissement, mais il a fallu plusieurs siècles pour qu'elles atteignent un nouvel équilibre. Avec les autres scénarios, certaines espèces ont disparu de la zone d'étude (p. ex. Pinus cembra dans les Alpes) ou ont vu leur population diminuer parce qu'il n'y avait plus assez de terrains disponibles dans lesquels elles puissent migrer. Le résultat le plus frappant a été le temps de latence dans la réponse de la plupart des espèces, indépendamment du scénario de changement climatique utilisé ou du type de limite des arbres. Finalement, un modèle statistique de l'effet de l'abroutissement par les rennes (Rangifer tarandus) sur la croissance de Pinus sylvestris a été développé, comme première étape en vue de l'implémentation des impacts humains sur la limite boréale des arbres. L'effet attendu était indirect, puisque les rennes réduisent la couverture de lichen sur le sol, dont on attend un effet protecteur contre les rigueurs climatiques. Le modèle a mis en évidence un effet modeste mais significatif, mais étant donné que le lien avec les variables climatiques sous jacentes était peu clair et que le modèle n'était pas appliqué dans l'espace, il n'était pas utilisable tel quel. Le développement du modèle TreeMig-LAb a permis : a) d'établir une méthode pour déduire les paramètres spécifiques de l'équation de croissance ä partir de données dendrochronologiques, b) de mettre en évidence l'importance de la régénération dans la position de la limite des arbres et la distribution des espèces et c) d'améliorer l'intégration des sciences sociales dans les modèles de paysage. L'application du modèle aux limites alpines et nord-européennes des arbres sous différents scénarios de changement climatique a montré qu'avec la plupart des niveaux d'augmentation de température prévus, la limite des arbres subirait des perturbations majeures, avec des glissements d'aires de répartition et l'extinction potentielle de certaines espèces. Cependant, ces réponses ont montré des temps de latence importants, si bien que ces effets ne seraient pas visibles avant des décennies et pourraient mettre plusieurs siècles à se stabiliser.

Climatic impacts of land-use change due to crop yield increases and a universal carbon tax from a scenario model*

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.

The role of CO2 and dynamic vegetation on the impact of temperate land use change in the HadCM3 coupled climate model

Human induced land-use change (LUC) alters the biogeophysical characteristics of the land surface influencing the surface energy balance. The level of atmospheric CO2 is expected to increase in the coming century and beyond, modifying temperature and precipitation patterns and altering the distribution and physiology of natural vegetation. It is important to constrain how CO2-induced climate and vegetation change may influence the regional extent to which LUC alters climate. This sensitivity study uses the HadCM3 coupled climate model under a range of equilibrium forcings to show that the impact of LUC declines under increasing atmospheric CO2, specifically in temperate and boreal regions. A surface energy balance analysis is used to diagnose how these changes occur. In Northern Hemisphere winter this pattern is attributed in part to the decline in winter snow cover and in the summer due to a reduction in latent cooling with higher levels of CO2. The CO2-induced change in natural vegetation distribution is also shown to play a significant role. Simulations run at elevated CO2 yet present day vegetation show a significantly increased sensitivity to LUC, driven in part by an increase in latent cooling. This study shows that modelling the impact of LUC needs to accurately simulate CO2 driven changes in precipitation and snowfall, and incorporate accurate, dynamic vegetation distribution.

Impacts of Climate Change and the End of Deforestation on Land Use in the Brazilian Legal Amazon

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Land cover dynamics and climate change implications on water resources in South Pacific Costa Rica

Water is fundamental to human life and the availability of freshwater is often a constraint on human welfare and economic development. Consequently, the potential effects of global changes on hydrology and water resources are considered among the most severe and vital ones. Water scarcity is one of the main problems in the rural communities of Central America, as a result of an important degradation of catchment areas and the over-exploitation of aquifers. The present Thesis is focused on two critical aspects of global changes over water resources: (1) the potential effects of climate change on water quantity and (2) the impacts of land cover and land use changes on the hydrological processes and water cycle. Costa Rica is among the few developing countries that have recently achieved a land use transition with a net increase in forest cover. Osa Region in South Pacific Costa Rica is an appealing study site to assess water supply management plans and to measure the effects of deforestation, forest transitions and climate change projections reported in the region. Rural Community Water Supply systems (ASADAS) in Osa are dealing with an increasing demand of freshwater due to the growing population and the change in the way of life in the rural livelihoods. Land cover mosaics which have resulted from the above mentioned processes are characterized by the abandonment of marginal farmland with the spread over these former grasslands of high return crops and the expansion of secondary forests due to reforestation initiatives. These land use changes have a significant impact on runoff generation in priority water-supply catchments in the humid tropics, as evidenced by the analysis of the Tinoco Experimental Catchment in the Southern Pacific area of Costa Rica. The monitoring system assesses the effects of the different land uses on the runoff responses and on the general water cycle of the basin. Runoff responses at plot scale are analyzed for secondary forests, oil palm plantations, forest plantations and grasslands. The Oil palm plantation plot presented the highest runoff coefficient (mean RC=32.6%), twice that measured under grasslands (mean RC=15.3%) and 20-fold greater than in secondary forest (mean RC=1.7%). A Thornthwaite-type water balance is proposed to assess the impact of land cover and climate change scenarios over water availability for rural communities in Osa Region. Climate change projections were obtained by the downscaling of BCM2, CNCM3 and ECHAM5 models. Precipitation and temperature were averaged and conveyed by the A1B, A2 and B1 IPCC climate scenario for 2030, 2060 and 2080. Precipitation simulations exhibit a positive increase during the dry season for the three scenarios and a decrease during the rainy season, with the highest magnitude (up to 25%) by the end of the 21st century under scenario B1. Monthly mean temperature simulations increase for the three scenarios throughout the year with a maximum increase during the dry season of 5% under A1B and A2 scenarios and 4% under B1 scenario. The Thornthwaite-type Water Balance model indicates important decreases of water surplus for the three climate scenarios during the rainy season, with a maximum decrease on May, which under A1B scenario drop up to 20%, under A2 up to 40% and under B1 scenario drop up to almost 60%. Land cover scenarios were created taking into account current land cover dynamics of the region. Land cover scenario 1 projects a deforestation situation, with forests decreasing up to 15% due to urbanization of the upper catchment areas; land cover scenario 2 projects a forest recovery situation where forested areas increase due to grassland abandonment on areas with more than 30% of slope. Deforestation scenario projects an annual water surplus decrease of 15% while the reforestation scenario projects a water surplus increase of almost 25%. This water balance analysis indicates that climate scenarios are equal contributors as land cover scenarios to future water resource estimations.

Hydro-Meteorology and Water Budget of the Mara River Basin Under Land Use Change Scenarios

Mara is a transboundary river located in Kenya and Tanzania and considered to be an important life line to the inhabitants of the Mara-Serengeti ecosystem. It is also a source of water for domestic water supply, irrigation, livestock and wildlife. The alarming increase of water demand as well as the decline in the river flow in recent years has been a major challenge for water resource managers and stakeholders. This has necessitated the knowledge of the available water resources in the basin at different times of the year. Historical rainfall, minimum and maximum stream flows were analyzed. Inter and intra-annual variability of trends in streamflow are discussed. Landsat imagery was utilized in order to analyze the land use land cover in the upper Mara River basin. The semi-distributed hydrological model, Soil and Water Assessment Tool (SWAT) was used to model the basin water balance and understand the hydrologic effect of the recent land use changes from forest-to-agriculture. The results of this study provided the potential hydrological impacts of three land use change scenarios in the upper Mara River basin. It also adds to the existing literature and knowledge base with a view of promoting better land use management practices in the basin.

Estimates of global sources and sinks of carbon from land cover and land use changes

The distribution of sources and sinks of carbon over the land surface is dominated by changes in land use such as deforestation, reforestation, and agricultural management. Despite, the importance of land-use change in dominating long-term net terrestrial fluxes of carbon, estimates of the annual flux are uncertain relative to other terms in the global carbon budget. The interaction of the nitrogen cycle via atmospheric N inputs and N limitation with the carbon cycle contributes to the uncertain effect of land use change on terrestrial carbon uptake. This study uses two different land use datasets to force the geographically explicit terrestrial carbon-nitrogen coupled component of the Integrated Science Assessment Model (ISAM) to examine the response of terrestrial carbon stocks to historical LCLUC (cropland, pastureland and wood harvest) while accounting for changes in N deposition, atmospheric CO2 and climate. One of the land use datasets is based on satellite data (SAGE) while the other uses population density maps (HYDE), which allows this study to investigate how global LCLUC data construction can affect model estimated emissions. The timeline chosen for this study starts before the Industrial Revolution in 1765 to the year 2000 because of the influence of rising population and economic development on regional LCLUC. Additionally, this study evaluates the impact that resulting secondary forests may have on terrestrial carbon uptake. The ISAM model simulations indicate that uncertainties in net terrestrial carbon fluxes during the 1990s are largely due to uncertainties in regional LCLUC data. Also results show that secondary forests increase the terrestrial carbon sink but secondary tropical forests carbon uptake are constrained due to nutrient limitation.

FLOOD RISK ASSESSMENT UNDER HISTORICAL AND PREDICTED LAND USE CHANGE USING CONTINUOUS HYDROLOGIC MODELING

Current procedures for flood risk estimation assume flood distributions are stationary over time, meaning annual maximum flood (AMF) series are not affected by climatic variation, land use/land cover (LULC) change, or management practices. Thus, changes in LULC and climate are generally not accounted for in policy and design related to flood risk/control, and historical flood events are deemed representative of future flood risk. These assumptions need to be re-evaluated, however, as climate change and anthropogenic activities have been observed to have large impacts on flood risk in many areas. In particular, understanding the effects of LULC change is essential to the study and understanding of global environmental change and the consequent hydrologic responses. The research presented herein provides possible causation for observed nonstationarity in AMF series with respect to changes in LULC, as well as a means to assess the degree to which future LULC change will impact flood risk. Four watersheds in the Midwest, Northeastern, and Central United States were studied to determine flood risk associated with historical and future projected LULC change. Historical single framed aerial images dating back to the mid-1950s were used along with Geographic Information Systems (GIS) and remote sensing models (SPRING and ERDAS) to create historical land use maps. The Forecasting Scenarios of Future Land Use Change (FORE-SCE) model was applied to generate future LULC maps annually from 2006 to 2100 for the conterminous U.S. based on the four IPCC-SRES future emission scenario conditions. These land use maps were input into previously calibrated Soil and Water Assessment Tool (SWAT) models for two case study watersheds. In order to isolate effects of LULC change, the only variable parameter was the Runoff Curve Number associated with the land use layer. All simulations were run with daily climate data from 1978-1999, consistent with the 'base' model which employed the 1992 NLCD to represent 'current' conditions. Output daily maximum flows were converted to instantaneous AMF series and were subsequently modeled using a Log-Pearson Type 3 (LP3) distribution to evaluate flood risk. Analysis of the progression of LULC change over the historic period and associated SWAT outputs revealed that AMF magnitudes tend to increase over time in response to increasing degrees of urbanization. This is consistent with positive trends in the AMF series identified in previous studies, although there are difficulties identifying correlations between LULC change and identified change points due to large time gaps in the generated historical LULC maps, mainly caused by unavailability of sufficient quality historic aerial imagery. Similarly, increases in the mean and median AMF magnitude were observed in response to future LULC change projections, with the tails of the distributions remaining reasonably constant. FORE-SCE scenario A2 was found to have the most dramatic impact on AMF series, consistent with more extreme projections of population growth, demands for growing energy sources, agricultural land, and urban expansion, while AMF outputs based on scenario B2 showed little changes for the future as the focus is on environmental conservation and regional solutions to environmental issues.

Implications of long-term land-use change for the hydrology and solute budgets of small catchments in Amazonia

The replacement of undisturbed tropical forest with cattle pasture has the potential to greatly modify the hydrology of small watersheds and the fluxes of solutes. We examined the fluxes of water, Cl(-), NO(3)(-)-N: SO(4)(2--)-S, NH(4)(+)-N, Na(+), K(+), Mg(2+) and Ca(2+) in different flow paths in similar to 1 ha catchments of undisturbed open tropical rainforest and a 20 year-old pasture established from forest in the southwestern Brazilian Amazon state of Rondonia. Storm flow discharge was 18% of incident rainfall in pasture, but only 1% in forest. Quickflow predominated over baseflow in both catchments and in both wet and dry seasons. In the pasture, groundwater and quickflow were important flow paths for the export of all solutes. In the forest, quickflow was important for NO(3)(-)-N export, but all other solutes were exported primarily by groundwater outflow. Both catchments were sinks for SO(4)(2-)-S and Ca(2+), and sources of Na(+). The pasture catchment also lost K(+) and Mg(2+) because of higher overland flow frequency and volume and to cattle excrement. These results show that forest clearing dramatically influences small watershed hydrology by increasing quickflow and water export to streams. They also indicate that tropical forest watersheds are highly conservative for most solutes but that pastures continue to lose important cations even decades after deforestation and pasture establishment. (c) 2008 Elsevier B.V. All rights reserved.

Runoff sources and land cover change in the Amazon: an end-member mixing analysis from small watersheds

The flowpaths by which water moves from watersheds to streams has important consequences for the runoff dynamics and biogeochemistry of surface waters in the Amazon Basin. The clearing of Amazon forest to cattle pasture has the potential to change runoff sources to streams by shifting runoff to more surficial flow pathways. We applied end-member mixing analysis (EMMA) to 10 small watersheds throughout the Amazon in which solute composition of streamwater and groundwater, overland flow, soil solution, throughfall and rainwater were measured, largely as part of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia. We found a range in the extent to which streamwater samples fell within the mixing space determined by potential flowpath end-members, suggesting that some water sources to streams were not sampled. The contribution of overland flow as a source of stream flow was greater in pasture watersheds than in forest watersheds of comparable size. Increases in overland flow contribution to pasture streams ranged in some cases from 0% in forest to 27-28% in pasture and were broadly consistent with results from hydrometric sampling of Amazon forest and pasture watersheds that indicate 17- to 18-fold increase in the overland flow contribution to stream flow in pastures. In forest, overland flow was an important contribution to stream flow (45-57%) in ephemeral streams where flows were dominated by stormflow. Overland flow contribution to stream flow decreased in importance with increasing watershed area, from 21 to 57% in forest and 60-89% in pasture watersheds of less than 10 ha to 0% in forest and 27-28% in pastures in watersheds greater than 100 ha. Soil solution contributions to stream flow were similar across watershed area and groundwater inputs generally increased in proportion to decreases in overland flow. Application of EMMA across multiple watersheds indicated patterns across gradients of stream size and land cover that were consistent with patterns determined by detailed hydrometric sampling.

Using indicators of deforestation and land-use dynamics to support conservation strategies: A case study of central Rondonia, Brazil

In Rondonia State, Brazil, settlement processes have cleared 68,000 km 2 of tropical forests since the 1970s. The intensity of deforestation has differed by region depending on driving factors like roads and economic activities. Different histories of land-use activities and rates of change have resulted in mosaics of forest patches embedded in an agricultural matrix. Yet, most assessments of deforestation and its effects on vegetation, soil and water typically focus on landscape patterns of current conditions, yet historical deforestation dynamics can influence current conditions strongly. Here, we develop and describe the use of four land-use dynamic indicators to capture historical land-use changes of catchments and to measure the rate of deforestation (annual deforestation rate), forest regeneration level (secondary forest mean proportion), time since disturbance (mean time since deforestation) and deforestation profile (deforestation profile curvature). We used the proposed indices to analyze a watershed located in central Rondonia. Landsat TM and ETM+ images were used to produce historical land-use maps of the last 18 years, each even year from 1984 to 2002 for 20 catchments. We found that the land-use dynamics indicators are able to distinguish catchments with different land-use change profiles. Four categories of historical land-use were identified: old and dominant pasture cover on small properties, recent deforestation and dominance of secondary growth, old extensive pastures and large forest remnants and, recent deforestation, pasture and large forest remnants. Knowing historical deforestation processes is important to develop appropriate conservation strategies and define priorities and actions for conserving forests currently under deforestation. (C) 2009 Elsevier B.V. All rights reserved.

Urban land cover change detection analysis and modeling spatio-temporal Growth dynamics using Remote Sensing and GIS Techniques: A case study of Dhaka, Bangladesh

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.