Luciana Soler

Population growth in urban areas drives people vulnerability to natural disasters, especially in emergent economies like Brazil. The existing automatic pluviometric network is insufficient to provide enough information to monitor and prevent deaths due to landslides and floods in 821 municipalities defined as priority ones in the Brazilian National Plan of Risk Management and Response to Natural Disasters, implemented in 2012. Therefore, aiming to support early warning and monitoring systems and make available near-real time rain data, the National Early Warning and Monitoring Centre of Natural Disasters (Cemaden) has carried out an integrative institutional project to acquire and identify optimal places to install 1400 automatic pluviometers in risk areas of landslides and/or floods, already mapped in more than 350 Brazilian municipalities where existing network is scarce. Using geo-information techniques, the methodology included a deficit analysis to estimate the needed number of pluviometers per municipality. These estimates were used in a cooperative action between Cemaden and institutions at state and municipality levels, especially municipality governments and their civil defenses. A number of technical meetings and fieldwork training were done in 14 from the 27 Brazilian Federal Units in several municipalities to promote the project. Cemaden developed a dedicated web database where the institutions' representatives were able to supply detailed information of suitable sites to install pluviometers inside or nearby risk areas, based on their empirical knowledge of local characteristics. The results so far are very promising as 1, 500 locations have been filled since March 2013, and around 600 were chosen as optimal installation sites using spatial analysis. As the pluviometers installations take place, we expect a significant improvement on the efficiency and confidence of early warnings of landslides and floods as well as more commitment of local governments and communities to respond to warnings.

The Amazon is the largest rainforest on the planet and was an important carbon sink. The carbon sink is declining, mainly due to an increase in tree mortality as a result of deforestation, degradation, and local, regional and global climate change. In addition, deforestation and forest degradation reduce the ability of the Amazon rainforest to act as a carbon sink. CO2 Vertical Profiles (VP) were performed from 2010 to 2021 (805), using small aircraft at 4 locations: SAN (2.86° S 54.95° W), ALF (8.80° S 56.75° W), RBA (9.38° S 67.62° W) and from 2010 to 2012 on TAB (5.96° S 70.06° W) and since 2013 at TEF (3.39° S 65.55° W). The question if Amazonia is a carbon source or sink is an important role in the global carbon budget. Amazonia vertical profile annual mean derived from CO2 annual mean vertical profiles (VP subtracted from the background concentration: ∆VP) from the 4 studied sites can help to clarify this important question. The sampling frequency was approximately 2 times per month in each location, from 4.4 km height (a.s.l.) until near surface 300 m (a.s.l.), and usually carried out between 12:00 and 13:00 local time. The CO2 samples were analyzed at INPE's LaGEE (Greenhouse Gas Laboratory), in São Jose dos Campos. This result is a direct indication of the regional source in the global carbon budget, indeed there are well-known discrepancies from many studies using different methodologies (bottom-up, top-down techniques, and a wide variety of global, regional, and inversion models). In this study, we will present Carbon flux from the time series for the 4 sites and Amazon Carbon balance using the column budget technique, and analyze the correlations with various parameters related to climate, vegetation, deforestation, and biomass burning.

A procura por reservas de petróleo ao longo de plataformas continentais tem sido realizada, ao longo dos anos, em águas cada vez mais profundas, sendo que o petróleo cru e seus derivados são transportados por um número crescente de navios e oleodutos submarinos através dos oceanos. Como resultado destas atividades, o derramamento de óleo se mostra como uma séria ameaça à preservação e manutenção da saúde dos oceanos. Em virtude das limitações de técnicas convencionais de fiscalização e monitoramento da poluição do mar, tem-se buscado as técnicas de sensoriamento remoto orbital, como as apresentadas neste trabalho. Foram utilizadas imagens do sistema RADARSAT-1/SAR nos modos Fine e ScanSAR Wide obtidas na região da Bacia de Campos-RJ. A estas imagens foram aplicados dois tipos de classificadores texturais: Texture e CTS. Para a determinação da verdade terrestre, foram utilizados dados de direção e intensidade do vento e ondas, devido ao intervalo de 3 a 8 m/s de velocidade do vento a...

PRODES and DETER project together turned 33 years-old with an undeniably contribution to the state-of-art in mapping and monitoring tropical deforestation in Brazil. Monitoring systems all over the world have taken advantage of big data repositories of remote sensing data as they are becoming freely available together with artificial intelligence. Thus, considering the advent of new generation remote sensing data hubs, online platforms of big data that can fill in spatial and temporal resolutions gaps in current deforestation mapping, this work aims to present recent innovations at INPE ́s deforestation monitoring systems in Brazil and how they are gauging new realms of technological levels. Recent innovations at INPE ́s monitoring systems are: 1) the development of TerraBrasilis platform of data access and analysis; 2) the adoption of new sensors and cloud detection strategies; 3) the complementary use of multi-sensor images; 4) the complementary adoption of SAR C-band images using...

Agricultural expansion and intensification enabled growth of food production but resulted in serious environmental changes. In light of that, debates concerning sustainability in agriculture arises on scientific literature. Land sharing and land sparing are two opposite models for framing agricultural sustainability. The first aims to integrate agricultural activities with biodiversity conservation by means of enhancing the quality of the agricultural matrix in the landscape towards a wildlife friendly matrix. The other model aims to spare natural habitats from agriculture for conservation. This work aimed to explore spatial evidences of land sharing/sparing and its relationship with rural population in the Brazilian Cerrado. A Land Sharing/Sparing Index based on TerraClass Cerrado map was proposed. Spatial analysis based on Global and Local Moran statistics and Geographically Weighted Regression were made in order to explore the influence of local rural population on the probabilit...

In Brazil, Human Rights to Adequate Food was institutionalized in January 2010, incorporating adequate feed within the Citizens Social Rights as part of Brazilian Federal Constitution. Access to adequate food that guarantees and promotes such rights has been limited due to socioeconomic issues and environmental local and global changes. Expansion of cities in size and number, as well as population growth concentrated in urban areas might directly affect land availability for agriculture, reducing viable spaces near cities to produce fresh food in order to respond to the rise on demand for food by urban consumers. Vegetables are vital for a healthy human diet, and long market chains represent a damaging step between production and consumption, resulting in great losses due to high perishability, raising prices and difficulting access to food. Thus, the identification of near consumers areas suitable for vegetables´ production, can subsidize public policies and be part of adaptation m...

The application of Interferometric Synthetic Aperture Radar (InSAR) for detecting terrain deformation in the Amazon region is an important research tool that allows high accuracy of geophysical models based on satellite data. Amazonian forest cover and climate regime make InSAR implementation very difficult, so literature about the subject in that region is still rare. In this paper, we apply the interferometric technique to a stack of 24 Radarsat-2 images acquired from 2008 to 2010 over Manaus city (Amazonas state, Brazil) aiming to understand the terrain movement in the urban area, which has been detected by previous studies using Radarsat-1 data. The observed subsidence is estimated to be about three centimeters and occurs in the vicinities of the international airport. The phenomena can be associated with the Amazonas river flooding system, and indicates a local response from the seasonal fluctuations and Earth́s elasticity.

ABSTRACT The increasing figures of natural disasters and related human and material losses represent a major challenge to be faced by the Brazilian government, the scientific community and civil society all together. Landslides and floods resulting from climatic extremes have been associated not only to global climatic changes, but mostly due to the increase of population vulnerability and the lack of effective mitigation actions. Core governmental responses to mitigate such losses include the creation of operational centers for disaster monitoring and management -- Cemaden (National Early Warning and Monitoring Centre of Natural Disasters) and CENAD (Centro Nacional de Gerenciamento de Riscos e Desastres). The establishment of these institutions associated with investments to map risky areas are key to implement landslides and floods monitoring systems. Despite significant investments, the implementation of such natural disaster monitoring systems depend much on cooperative actions among organizations and entities from different sectors of the society. The main objective of this work is to present the challenges and perspectives of innovative digital ecosystems designed to effectively monitor, warn and respond to natural disasters related to landslides and floods in Brazil. The several methodologies adopted make use of technical, scientific and empirical knowledge to establish a rain gauge network of 1400 automatic pluviometers and 1100 semiautomatic pluviometers, distributed in more than 800 municipalities defined as priority ones by the Brazilian National Plan of Risk Management and Response to Natural Disasters. Pilot projects of landslides monitoring systems are also included in the methodology in key municipalities where the number of human losses has been significant in recent disasters. In order to develop such challenging methodologies, Cemaden has worked together with the Center for Information Technology Renato Archer (CTI), CENAD, a number of research institutions, the private sector, local and regional governments and non-governmental organizations as well as the civil society. The combination of different types of knowledge, technological approaches and levels of interaction to population under risk of such a variety of organizations shall configure a collective intelligence able to improve the efficiency and confidence of early warnings of landslides and floods, as well as to promote further commitment of local governments and communities to respond to warnings.

Currently Amazon land use/cover changes are closely related to its impact on regional policies. These policies can be based on deforestation data resulting from land cover models, which may be based on on empirical analysis of potential factors determining its patterns and processes. However, when only data from total deforestation are shown, it can cause misinterpretation of the recently cleared areas, inducing poor decisionmaking. In the present study were constructed deforestation risk maps of Brazilian Amazon from the simulations results obtained by a regional scale model for the Brazilian Amazon called LuccME / BRAmazonia. This model was built using a modeling framework developed by CCST / INPE, which allows to build integrated models that combine different modules of demand, transition potential and land use/cover changes allocation. We made simulations with two different demand scenarios (Baseline and carbon Emission Reduction Target scenario) for 2020, and the second one was...

Radar images are presently being used in association with optical remote sensing data to characterize the different processes of land use in Brazilian Amazon region. Considering the current development in remote sensing techniques for estimating forest biomass, where L, X and C band images have their limitations, it was recently accomplished a scientific airborne mission with image polarimetric P-band imagery acquisition at lower Rio Tapajós region, Brazil. This study analyses the biomass variation of the primary forest and secondary succession and it's influence on the response of backscatter values in the P-band polarimetric images. The start of this study was the understanding of the behavior of the structural variables of the vegetation cover (measured during the field survey) and its'correlation with the backscatter data obtained from PHH -, PHV - and PVV - band data. A statistical regression model was used to verify the relationship between biomass (estimate by different allometric equations) and P-band polarimetric data. Based on the regression equation that best fits the data sets, a biomass map was elaborated. This was done through the segmentation of the backscatter image, using Caesar 3.0 rwseg algorithm (based on the successive edge detecting and region growing procedures), with the σ° of each resulting segment was converted into biomass values by the best fit function. The final goal of this P-band experiment is to improve the regional inventory and monitoring biomass dynamics, as well as landscape changes, due to human action in Amazon.

Abstract—In September 2000, an airborne synthetic aperture radar (SAR) mission acquired unprecedented full polarimetric P-band data over the Tapajós National Forest (Pará State), which is an area in the Brazilian Amazon which has been continuously monitored in the last three ...

Abstract—In September 2000, an airborne synthetic aperture radar (SAR) mission acquired unprecedented full polarimetric P-band data over the Tapajós National Forest (Pará State), which is an area in the Brazilian Amazon which has been continuously monitored in the last three ...

In this paper the potentiality of polarimetric P-band SAR data for Amazon tropical forest land cover mapping is assessed. The classifying approach is based on the Iterative Conditional Mode (ICM) algorithm, taking into account several specific distributions to SAR data. Distinct land cover classes are modeled considering different distributions. The results show that the P-band data is not capable to discriminate the nine classes initially used. However this capability improves significantly when classes having similar vegetation structure are grouped. The HV image is effective in differentiating primary and very old regeneration forest areas from other land cover classes, while W image increases the classification of bare soil and crop/pasture areas. The results show the importance of polarimetric information for the classification of several land use classes.

The aim of this work was to analyze the potentiality of polarimetric P-band data for land use and land cover mapping in a site of the Brazilian Amazonia. These data are the first P-band image set gathered in the Brazilian Amazonia, so they represent a unique opportunity of analyzing the potentiality of this frequency for classification purposes. The stratification of

This work focus on two municipalities established first as rural settlements in Rondonia State in 1982. These two municipalities consist on a unique land use change study due to the differences in settlements planning, but also because they are part of recent frontiers of deforestation. The main land use patterns in the study area are mainly related to small farmers. However, medium and big farms, mineral extraction and timber exploration are also expressive. To understand the land use and land change processes, we have investigated and connected these different patterns to their possible causes and driving forces. This was realized by the use of statistical analysis and spatial-temporal modeling. The simulation was useful as learning tool to explore previous feedbacks of deforestation observed during fieldwork campaigns in the area.

Land cover change in the Brazilian Amazon depends on the spatial variability of political, socioeconomic and biophysical factors, as well as on the land use history and its actors. A regional scale analysis was made in Rondônia State to identify possible differences in land cover change connected to spatial policies of land occupation, size and year of establishment of properties, accessibility measures and soil fertility. The analysis was made based on remote sensing data and household level data gathered with a questionnaire. Both types of analyses indicate that the highest level of total deforestation is found inside agrarian projects, especially in those established more than 20 years ago. Even though deforestation rates are similar inside and outside official settlements, inside agrarian projects forest depletion can exceed 50% at the property level within 10–14 years after establishment. The data indicate that both small-scale and medium to large-scale farmers contribute to deforestation processes in Rondônia State encouraged by spatial policies of land occupation, which provide better accessibility to forest fringes where soil fertility and forest resources are important determinants of location choice.