Global burned-land estimation in Latin America using MODIS composite data

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.

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.

Datasets related to in-land water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates

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.

Land surface temperature retrieval from Sentinel 2 and 3 Missions

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.

The definition of potential infiltration areas in Guaratingueta watershed, Paraiba do Sul Basin, Southeastern Brazil: an integrated approach using physical and land-use elements

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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)

Use of synthetic aperture radar for recognition of Coastal Geomorphological Features, land-use assessment and shoreline changes in Bragança coast, Pará, Northern Brazil

Imagens de radar de abertura sintética (SAR) vem sendo bem mais utilizadas do que antes nas aplicações de geociências em regiões tropicais úmidas. Nesta investigação, uma imagem RADARSAT-1, na banda C, polarização HH adquirida em 1998 foi usada para o mapeamento costeiro e avaliação da cobertura da terra na área de Bragança, norte do Brasil. Imagem do radar aerotransportado GEMS-1000, na banda X, polarização HH, adquirida em 1972 durante o projeto RADAM foi também utilizada para avaliar as variações costeiras ocorridas nas últimas três décadas. A pesquisa tem confirmado a utilidade da imagem RADARSAT-1 para o mapeamento geomorfológico e avaliação da cobertura da terra, particularmente em costas de manguezal de macromaré. Além disso, um novo método para estimar as variações da linha de costa baseado na superposição de vetores extraídos de diferentes imagens SAR, com alta acurácia geométrica, tem mostrado que a planície costeira de Bragança tem estado sujeita a severa erosão responsável pelo recuo de aproximadamente 32 km² e acreção de 20 km², resultando em uma perda de área de manguezal de aproximadamente 12 km². Como perspectiva de aplicação, dados SAR orbitais e aerotransportados provaram ser uma importante fonte de informação tanto para o mapeamento geomorfológico, quando para o monitoramento de modificações costeiras em ambientes tropicais úmidos.

Why have land use change models for the Amazon failed to capture the amount of deforestation over the last decade?

Land cover change in the Neotropics represents one of the major drivers of global environmental change. Several models have been proposed to explore future trajectories of land use and cover change, particularly in the Amazon. Despite the remarkable development of these tools, model results are still surrounded by uncertainties. None of the model projections available in the literature plausibly captured the overall trajectory of land use and cover change that has been observed in the Amazon over the last decade. In this context, this study aims to review and analyze the general structure of the land use models that have most recently been used to explore land use change in the Amazon, seeking to investigate methodological factors that could explain the divergence between the observed and projected rates, paying special attention to the land demand calculations. Based on this review, the primary limitations inherent to this type of model and the extent to which these limitations can affect the consistency of the projections will also be analyzed. Finally, we discuss potential drivers that could have influenced the recent dynamic of the land use system in the Amazon and produced the unforeseen land cover change trajectory observed in this period. In a complementary way, the primary challenges of the new generation of land use models for the Amazon are synthesized. (c) 2014 Elsevier Ltd. All rights reserved.

Change detection as support for monitoring the dynamic of land around reservoir

The change detection technique was used in this study to provide preliminary information on the dynamics of land cover in the region over the western basin of the Tiete River. This area is characterized by sequence of reservoirs and intense agricultural activity, triggering series negative effects. One of the impacts is contamination and proliferation of aquatic organisms in these aquatics environments, increased by release of nutrients from human activities. This work was possible to observe a large switching classes and secondary vegetation bare land, probably related to agricultural activity.

Land Use, Freshwater Flows and Ecosystem Services in an Era of Global Change

The purpose of this thesis is to analyse interactions between freshwater flows, terrestrial ecosystems and human well-being. Freshwater management and policy has mainly focused on the liquid water part (surface and ground water run off) of the hydrological cycle including aquatic ecosystems. Although of great significance, this thesis shows that such a focus will not be sufficient for coping with freshwater related social-ecological vulnerability. The thesis illustrates that the terrestrial component of the hydrological cycle, reflected in vapour flows (or evapotranspiration), serves multiple functions in the human life-support system. A broader understanding of the interactions between terrestrial systems and freshwater flows is particularly important in light of present widespread land cover change in terrestrial ecosystems. The water vapour flows from continental ecosystems were quantified at a global scale in Paper I of the thesis. It was estimated that in order to sustain the majority of global terrestrial ecosystem services on which humanity depends, an annual water vapour flow of 63 000 km3/yr is needed, including 6800 km3/yr for crop production. In comparison, the annual human withdrawal of liquid water amounts to roughly 4000 km3/yr. A potential conflict between freshwater for future food production and for terrestrial ecosystem services was identified. Human redistribution of water vapour flows as a consequence of long-term land cover change was addressed at both continental (Australia) (Paper II) and global scales (Paper III). It was estimated that the annual vapour flow had decreased by 10% in Australia during the last 200 years. This is due to a decrease in woody vegetation for agricultural production. The reduction in vapour flows has caused severe problems with salinity of soils and rivers. The human-induced alteration of vapour flows was estimated at more than 15 times the volume of human-induced change in liquid water (Paper II).

Land use management in mountainous areas: combining ground-based and EO (Earth Observation) data to investigate the shallow landsliding susceptibility in the Duron valley (Trento, Italy).

Throughout the alpine domain, shallow landslides represent a serious geologic hazard, often causing severe damages to infrastructures, private properties, natural resources and in the most catastrophic events, threatening human lives. Landslides are a major factor of landscape evolution in mountainous and hilly regions and represent a critical issue for mountainous land management, since they cause loss of pastoral lands. In several alpine contexts, shallow landsliding distribution is strictly connected to the presence and condition of vegetation on the slopes. With the aid of high-resolution satellite images, it's possible to divide automatically the mountainous territory in land cover classes, which contribute with different magnitude to the stability of the slopes. The aim of this research is to combine EO (Earth Observation) land cover maps with ground-based measurements of the land cover properties. In order to achieve this goal, a new procedure has been developed to automatically detect grass mantle degradation patterns from satellite images. Moreover, innovative surveying techniques and instruments are tested to measure in situ the shear strength of grass mantle and the geomechanical and geotechnical properties of these alpine soils. Shallow landsliding distribution is assessed with the aid of physically based models, which use the EO-based map to distribute the resistance parameters across the landscape.

The Dynamics of Secondary Forest Landscapes in the Lower Mekong Basin: A Regional-Scale Analysis

Secondary forests in the Lower Mekong Basin (LMB) are increasingly recognized as a valuable component of land cover, providing ecosystem services and benefits for local users. A large proportion of secondary forests in the LMB, especially in the uplands, are maintained by swidden cultivation. In order to assess the regional-scale status and dynamic trends of secondary forests in the LMB, an analysis of existing regional land cover data for 1993 and 1997 was carried out and forms the basis of this paper. To gain insight into the full range of dynamics affecting secondary forests beyond net-change rates, cross-tabulation matrix analyses were performed. The investigations revealed that secondary forests make up the largest share of forest cover in the LMB, with over 80% located in Laos and Cambodia. The deforestation rates for secondary forests are 3 times higher than the rates for other forest categories and account for two-thirds of the total deforestation. These dynamics are particularly pronounced in the less advanced countries of the LMB, especially in Laos, where national policies and the opening up of national economies seem to be the main drivers of further degradation and loss of secondary forests.

The geography of large-scale land acquisitions: Analysing socio-ecological patterns of target contexts in the global South

This paper analyses local geographical contexts targeted by transnational large-scale land acquisitions (>200 ha per deal) in order to understand how emerging patterns of socio-ecological characteristics can be related to processes of large-scale foreign investment in land. Using a sample of 139 land deals georeferenced with high spatial accuracy, we first analyse their target contexts in terms of land cover, population density, accessibility, and indicators for agricultural potential. Three distinct patterns emerge from the analysis: densely populated and easily accessible croplands (35% of land deals); remote forestlands with lower population densities (34% of land deals); and moderately populated and moderately accessible shrub- or grasslands (26% of land deals). These patterns are consistent with processes described in the relevant case study literature, and they each involve distinct types of stakeholders and associated competition over land. We then repeat the often-cited analysis that postulates a link between land investments and target countries with abundant so-called “idle” or “marginal” lands as measured by yield gap and available suitable but uncultivated land; our methods differ from the earlier approach, however, in that we examine local context (10-km radius) rather than countries as a whole. The results show that earlier findings are disputable in terms of concepts, methods, and contents. Further, we reflect on methodologies for exploring linkages between socioecological patterns and land investment processes. Improving and enhancing large datasets of georeferenced land deals is an important next step; at the same time, careful choice of the spatial scale of analysis is crucial for ensuring compatibility between the spatial accuracy of land deal locations and the resolution of available geospatial data layers. Finally, we argue that new approaches and methods must be developed to empirically link socio-ecological patterns in target contexts to key determinants of land investment processes. This would help to improve the validity and the reach of our findings as an input for evidence-informed policy debates.

Linking livelihood strategies with a regional level landscape mosaic to explore trade-offs between forest conservation and human wellbeing in a Madagascar biodiversity hotspot

The north-eastern escarpment of Madagascar contains the island’s last remaining large-scale humid forest massifs surrounded by diverse small-scale agricultural mosaics. There is high deforestation mainly caused by shifting cultivation practiced by local land users to produce upland rice for subsistence. Today, large protected areas restrict land users’ access to forests to collect wood and other forest products. Moreover, they are no more able to expand their cultivated land, which leads to shorter shifting cultivation cycles and decreasing plot sizes for irrigated rice and cash crop cultivation. Cash crop production of clove and vanilla is exposed to risks such as extreme inter-annual price fluctuations, pests and cyclones. In the absence of work opportunities, agricultural extension services and micro-finance schemes people are stuck in a poverty trap. New development strategies are needed to mitigate the trade-offs between forest conservation and human well-being. As landscape composition and livelihood strategies vary across the region, these strategies need to be spatially differentiated to avoid implementing generic solutions, which do not fit the local context. However, up to date, little is known about the spatial patterns of shifting cultivation and other land use systems at the regional level. This is mainly due to the high spatial and temporal dynamics inherent to shifting cultivation, which makes it difficult to monitor the dynamics of this land use system with remote sensing methods. Furthermore, knowledge about land users’ livelihood strategies and the risks and opportunities they face stems from very few local case studies. To overcome this challenge, firstly, we used remote sensing data and a landscape mosaic approach to delineate the main landscape types at the regional level. Secondly, we developed a land user typology based on socio-ecological data from household surveys in 45 villages spread throughout the region. Combining the land user typology with the landscape mosaic map allowed us to reveal spatial patterns of the interaction between landscapes and people and to better understand the trade-offs between forest conservation and local wellbeing. While shifting cultivation systems are being transformed into more intensive permanent agricultural systems in many countries around the globe, Madagascar seems to be an exception to this trend. Linking land cover information to human-environmental interactions over large areas is crucial to designing policies and to inform decision making for a more sustainable development of this resource-rich but poverty-prone context.

Contextualizing local-scale point sample data using global-scale spatial datasets: Lessons learnt from the analysis of large-scale land acquisitions

This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.