PALSAR-2/ALOS-2 AND OLI/LANDSAT-8 DATA INTEGRATION FOR LAND USE AND LAND COVER MAPPING IN NORTHERN BRAZILIAN AMAZON

In northern Brazilian Amazon, the crops, savannahs and rainforests form a complex landscape where land use and land cover (LULC) mapping is difficult. Here, data from the Operational Land Imager (OLI)/Landsat-8 and Phased Array type L-band Synthetic Aperture Radar (PALSAR-2)/ALOS-2 were combined for mapping 17 LULC classes using Random Forest (RF) during the dry season. The potential thematic accuracy of each dataset was assessed and compared with results of the hybrid classification from both datasets. The results showed that the combination of PALSAR-2 HH/HV amplitudes with the reflectance of the six OLI bands produced an overall accuracy of 83% and a Kappa of 0.81, which represented an improvement of 6% in relation to the RF classification derived solely from OLI data. The RF models using OLI multispectral metrics performed better than RF models using PALSAR-2 L-band dual polarization attributes. However, the major contribution of PALSAR-2 in the savannahs was to discriminate low biomass classes such as savannah grassland and wooded savannah

Drought-induced Amazonian wildfires instigate a decadal-scale disruption of forest carbon dynamics

Drought-induced wildfires have increased in frequency and extent over the tropics. Yet, the long-term (greater than 10 years) responses of Amazonian lowland forests to fire disturbance are poorly known. To understand post-fire forest biomass dynamics, and to assess the time required for fire-affected forests to recover to pre-disturbance levels, we combined 16 single with 182 multiple forest census into a unique large-scale and long-term dataset across the Brazilian Amazonia. We quantified biomass, mortality and wood productivity of burned plots along a chronosequence of up to 31 years post-fire and compared to surrounding unburned plots measured simultaneously. Stem mortality and growth were assessed among functional groups. At the plot level, we found that fire-affected forests have biomass levels 24.8 ± 6.9% below the biomass value of unburned control plots after 31 years. This lower biomass state results from the elevated levels of biomass loss through mortality, which is not sufficiently compensated for by wood productivity (incremental growth + recruitment). At the stem level, we found major changes in mortality and growth rates up to 11 years post-fire. The post-fire stem mortality rates exceeded unburned control plots by 680% (i.e. greater than 40 cm diameter at breast height (DBH); 5–8 years since last fire) and 315% (i.e. greater than 0.7 g cm−3 wood density; 0.75–4 years since last fire). Our findings indicate that wildfires in humid tropical forests can significantly reduce forest biomass for decades by enhancing mortality rates of all trees, including large and high wood density trees, which store the largest amount of biomass in old-growth forests. This assessment of stem dynamics, therefore, demonstrates that wildfires slow down or stall the post-fire recovery of Amazonian forests. This article is part of a discussion meeting issue ‘The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’

Taking the pulse of Earth's tropical forests using networks of highly distributed plots

Tropical forests are the most diverse and productive ecosystems on Earth. While better understanding of these forests is critical for our collective future, until quite recently efforts to measure and monitor them have been largely disconnected. Networking is essential to discover the answers to questions that transcend borders and the horizons of funding agencies. Here we show how a global community is responding to the challenges of tropical ecosystem research with diverse teams measuring forests tree-by-tree in thousands of long-term plots. We review the major scientific discoveries of this work and show how this process is changing tropical forest science. Our core approach involves linking long-term grassroots initiatives with standardized protocols and data management to generate robust scaled-up results. By connecting tropical researchers and elevating their status, our Social Research Network model recognises the key role of the data originator in scientific discovery. Conceived in 1999 with RAINFOR (South America), our permanent plot networks have been adapted to Africa (AfriTRON) and Southeast Asia (T-FORCES) and widely emulated worldwide. Now these multiple initiatives are integrated via ForestPlots.net cyber-infrastructure, linking colleagues from 54 countries across 24 plot networks. Collectively these are transforming understanding of tropical forests and their biospheric role. Together we have discovered how, where and why forest carbon and biodiversity are responding to climate change, and how they feedback on it. This long-term pan-tropical collaboration has revealed a large long-term carbon sink and its trends, as well as making clear which drivers are most important, which forest processes are affected, where they are changing, what the lags are, and the likely future responses of tropical forests as the climate continues to change. By leveraging a remarkably old technology, plot networks are sparking a very modern revolution in tropical forest science. In the future, humanity can benefit greatly by nurturing the grassroots communities now collectively capable of generating unique, long-term understanding of Earth's most precious forests. Resumen Los bosques tropicales son los ecosistemas más diversos y productivos del mundo y entender su funcionamiento es crítico para nuestro futuro colectivo. Sin embargo, hasta hace muy poco, los esfuerzos para medirlos y monitorearlos han estado muy desconectados. El trabajo en redes es esencial para descubrir las respuestas a preguntas que trascienden las fronteras y los plazos de las agencias de financiamiento. Aquí mostramos cómo una comunidad global está respondiendo a los desafíos de la investigación en ecosistemas tropicales a través de diversos equipos realizando mediciones árbol por árbol en miles de parcelas permanentes de largo plazo. Revisamos los descubrimientos más importantes de este trabajo y discutimos cómo este proceso está cambiando la ciencia relacionada a los bosques tropicales. El enfoque central de nuestro esfuerzo implica la conexión de iniciativas locales de largo plazo con protocolos estandarizados y manejo de datos para producir resultados que se puedan trasladar a múltiples escalas. Conectando investigadores tropicales, elevando su posición y estatus, nuestro modelo de Red Social de Investigación reconoce el rol fundamental que tienen, para el descubrimiento científico, quienes generan o producen los datos. Concebida en 1999 con RAINFOR (Suramérica), nuestras redes de parcelas permanentes han sido adaptadas en África (AfriTRON) y el sureste asiático (T-FORCES) y ampliamente replicadas en el mundo. Actualmente todas estas iniciativas están integradas a través de la ciber-infraestructura de ForestPlots.net, conectando colegas de 54 países en 24 redes diferentes de parcelas. Colectivamente, estas redes están transformando nuestro conocimiento sobre los bosques tropicales y el rol de éstos en la biósfera. Juntos hemos descubierto cómo, dónde y porqué el carbono y la biodiversidad de los bosques tropicales está respondiendo al cambio climático y cómo se retroalimentan. Esta colaboración pan-tropical de largo plazo ha expuesto un gran sumidero de carbono y sus tendencias, mostrando claramente cuáles son los factores más importantes, qué procesos se ven afectados, dónde ocurren los cambios, los tiempos de reacción y las probables respuestas futuras mientras el clima continúa cambiando. Apalancando lo que realmente es una tecnología antigua, las redes de parcelas están generando una verdadera y moderna revolución en la ciencia tropical. En el futuro, la humanidad puede beneficiarse enormemente si se nutren y cultivan comunidades de investigadores de base, actualmente con la capacidad de generar información única y de largo plazo para entender los que probablemente son los bosques más preciados de la tierra. Resumo Florestas tropicais são os ecossistemas mais diversos e produtivos da Terra. Embora uma boa compreensão destas florestas seja crucial para o nosso futuro coletivo, até muito recentemente os esforços de medições e monitoramento foram amplamente desconexos. É essencial formarmos redes para obtermos respostas que transcendem fronteiras e horizontes de agências financiadoras. Neste estudo nós mostramos como uma comunidade global está respondendo aos desafios da pesquisa de ecossistemas tropicais, com equipes diversas medindo florestas, árvore por árvore, em milhares de parcelas monitoradas à longo prazo. Nós revisamos as maiores descobertas científicas deste trabalho, e mostramos também como este processo está mudando a ciência de florestas tropicais. Nossa abordagem principal envolve unir iniciativas de base a protocolos padronizados e gerenciamento de dados a fim de gerar resultados robustos em escalas ampliadas. Ao conectar pesquisadores tropicais e elevar seus status, nosso modelo de Rede de Pesquisa Social reconhece o papel-chave do produtor dos dados na descoberta científica. Concebida em 1999 com o RAINFOR (América do Sul), nossa rede de parcelas permanentes foi adaptada para África (AfriTRON) e Sudeste asiático (T-FORCES), e tem sido extensamente reproduzida em todo o mundo. Agora estas múltiplas iniciativas estão integradas através de uma infraestrutura cibernética do ForestPlots.net, conectando colegas de 54 países de 24 redes de parcelas. Estas iniciativas estão transformando coletivamente o entendimento das florestas tropicais e seus papéis na biosfera. Juntos nós descobrimos como, onde e por que o carbono e a biodiversidade da floresta estão respondendo às mudanças climáticas, e seus efeitos de retroalimentação. Esta duradoura colaboração pantropical revelou um grande sumidouro de carbono persistente e suas tendências, assim como tem evidenciado quais direcionadores são mais importantes, quais processos florestais são mais afetados, onde eles estão mudando, seus atrasos no tempo de resposta, e as prováveis respostas das florestas tropicais conforme o clima continua a mudar. Dessa forma, aproveitando uma notável tecnologia antiga, redes de parcelas acendem faíscas de uma moderna revolução na ciência das florestas tropicais. No futuro a humanidade pode se beneficiar incentivando estas comunidades basais que agora são coletivamente capazes de gerar conhecimentos únicos e duradouros sobre as florestas mais preciosas da Terra. Résume Les forêts tropicales sont les écosystèmes les plus diversifiés et les plus productifs de la planète. Si une meilleure compréhension de ces forêts est essentielle pour notre avenir collectif, jusqu'à tout récemment, les efforts déployés pour les mesurer et les surveiller ont été largement déconnectés. La mise en réseau est essentielle pour découvrir les réponses à des questions qui dépassent les frontières et les horizons des organismes de financement. Nous montrons ici comment une communauté mondiale relève les défis de la recherche sur les écosystèmes tropicaux avec diverses équipes qui mesurent les forêts arbre après arbre dans de milliers de parcelles permanentes. Nous passons en revue les principales découvertes scientifiques de ces travaux et montrons comment ce processus modifie la science des forêts tropicales. Notre approche principale consiste à relier les initiatives de base à long terme à des protocoles standardisés et une gestion de données afin de générer des résultats solides à grande échelle. En reliant les chercheurs tropicaux et en élevant leur statut, notre modèle de réseau de recherche sociale reconnaît le rôle clé de l'auteur des données dans la découverte scientifique. Conçus en 1999 avec RAINFOR (Amérique du Sud), nos réseaux de parcelles permanentes ont été adaptés à l'Afrique (AfriTRON) et à l'Asie du Sud-Est (T-FORCES) et largement imités dans le monde entier. Ces multiples initiatives sont désormais intégrées via l'infrastructure ForestPlots.net, qui relie des collègues de 54 pays à travers 24 réseaux de parcelles. Ensemble, elles transforment la compréhension des forêts tropicales et de leur rôle biosphérique. Ensemble, nous avons découvert comment, où et pourquoi le carbone forestier et la biodiversité réagissent au changement climatique, et comment ils y réagissent. Cette collaboration pan-tropicale à long terme a révélé un important puits de carbone à long terme et ses tendances, tout en mettant en évidence les facteurs les plus importants, les processus forestiers qui sont affectés, les endroits où ils changent, les décalages et les réactions futures probables des forêts tropicales à mesure que le climat continue de changer. En tirant parti d'une technologie remarquablement ancienne, les réseaux de parcelles déclenchent une révolution très moderne dans la science des forêts tropicales. À l'avenir, l'humanité pourra grandement bénéficier du soutien des communautés de base qui sont maintenant collectivement capables de générer une compréhension unique et à long terme des forêts les plus précieuses de la Terre. Abstrak Hutan tropika adalah di antara ekosistem yang paling produktif dan mempunyai kepelbagaian biodiversiti yang tinggi di seluruh dunia. Walaupun pemahaman mengenai hutan tropika amat penting untuk masa depan kita, usaha-usaha untuk mengkaji dan mengawas hutah-hutan tersebut baru sekarang menjadi lebih diperhubungkan. Perangkaian adalah sangat penting untuk mencari jawapan kepada soalan-soalan yang menjangkaui sempadan dan batasan agensi pendanaan. Di sini kami menunjukkan bagaimana sebuah komuniti global bertindak balas terhadap cabaran penyelidikan ekosistem tropika melalui penglibatan pelbagai kumpulan yang mengukur hutan secara pokok demi pokok dalam beribu-ribu plot jangka panjang. Kami meninjau semula penemuan saintifik utama daripada kerja ini dan menunjukkan bagaimana proses ini sedang mengubah bidang sains hutan tropika. Teras pendekatan kami memberi tumpuan terhadap penghubungan inisiatif akar umbi jangka panjang dengan protokol standar serta pengurusan data untuk mendapatkan hasil skala besar yang kukuh. Dengan menghubungkan penyelidik-penyelidik tropika dan meningkatkan status mereka, model Rangkaian Penyelidikan Sosial kami mengiktiraf kepentingan peranan pengasas data dalam penemuan saintifik. Bermula dengan pengasasan RAINFOR (Amerika Selatan) pada tahun 1999, rangkaian-rangkaian plot kekal kami kemudian disesuaikan untuk Afrika (AfriTRON) dan Asia Tenggara (T-FORCES) dan selanjutnya telah banyak dicontohi di seluruh dunia. Kini, inisiatif-inisiatif tersebut disepadukan melalui infrastruktur siber ForestPlots.net yang menghubungkan rakan sekerja dari 54 negara di 24 buah rangkaian plot. Secara kolektif, rangkaian ini sedang mengubah pemahaman tentang hutan tropika dan peranannya dalam biosfera. Kami telah bekerjasama untuk menemukan bagaimana, di mana dan mengapa karbon serta biodiversiti hutan bertindak balas terhadap perubahan iklim dan juga bagaimana mereka saling bermaklum balas. Kolaborasi pan-tropika jangka panjang ini telah mendedahkan sebuah sinki karbon jangka panjang serta arah alirannya dan juga menjelaskan pemandu-pemandu perubahan yang terpenting, di mana dan bagaimana proses hutan terjejas, masa susul yang ada dan kemungkinan tindakbalas hutan tropika pada perubahan iklim secara berterusan di masa depan. Dengan memanfaatkan pendekatan lama, rangkaian plot sedang menyalakan revolusi yang amat moden dalam sains hutan tropika. Pada masa akan datang, manusia sejagat akan banyak mendapat manfaat jika memupuk komuniti-komuniti akar umbi yang kini berkemampuan secara kolektif menghasilkan pemahaman unik dan jangka panjang mengenai hutan-hutan yang paling berharga di dunia

Análise espacial dos focos de calor e do desflorestamento do Estado de Roraima

O presente trabalho visa analisar o comportamento espaço-temporal de focos de calor e de desmatamento utilizando os dados gerados pelo Projeto Queimadas e pelo PRODES (INPE) para o Estado de Roraima, durante o período de 2001 a 2006. Foram utilizadas técnicas de análise espacial aplicadas a dados pontuais como estimador de intensidade de Kernel, além da análise do padrão dos dados de focos, através do método do vizinho mais próximo. As superfícies de intensidade foram fatiadas e classificadas em extrema, muito alta, alta e moderada. Para adequação espacial aos dados de desmatamento, com os mesmos foram geradas zonas de proximidade (4000m). As regiões geradas pelos dados de focos e de desmatamento foram cruzadas e os resultados melhoraram qualitativamente a análise dos eventos em questão. Os resultados indicaram uma superfície de intensidade de focos maior nas áreas florestais do que nas áreas desmatadas, principalmente nos anos mais secos, chegando à classe extrema em 2003. Nesse ano, incêndios florestais ocorreram em vastas áreas na região, associados à ação antrópica e efeito do El Niño. ABSTRACT This study aims to analyze the spatiotemporal behavior of hotspots and deforestation using data generated by Projeto Queimadas and PRODES (INPE) in the State of Roraima, during the period of 2001 to 2006. We used spatial analysis techniques applied to data points as Kernel estimator of intensity, and pattern analysis of data, through the method of nearest neighbor. The areas of intensity were sliced and scored in extreme, very high, high and moderate. To match hotspots with deforestation data, it was made buffers (4000m). The regions generated by hotspots and deforestation were crossed and the results improved qualitative analysis of the events in question. The results indicated a more intensity surface of hotspots in forest areas than in deforested areas, especially in drier years, reaching the extreme class in 2003. This year, forest fires occurred in vast areas in the region, linked to human action and effect of El Niño.Pages: 387-39

Análise das mudanças de uso e cobertura da terra no sudeste de Roraima – Brasil

Land use and land cover change (LUCC) is one of human activities that demand the most attention from the scientific community, according to global environmental change. Human occupations in forest ecosystems of the Amazon are important topic of study in LUCC, due to the dynamic characteristic of these agricultural frontier regions. Thus, this study aims to analyze changes in land use and land cover and the processes involved in southeastern Roraima, in the period 1994 to 2009, through the classification of multitemporal satellite images. TM/Landsat-5 digital images, IBGE and ZEE-RR data were used and it was selected three colonization areas: São João da Baliza, Caroebe and Entre Rios. The images were segmented and classified using the algorithm Bhattacharya, based on field research conducted in February 2010. The land use and cover classes were: forest, capoeira, agriculture, pasture, water/shade, urban/soil and cloud. Quantification of class area for each analyzed area revealed that, in the colonization period from 1994 to 2009, there was no qualitative difference between them. There was an increase in pasture and agriculture and a decline in capoeira and forest. The analysis of class transition in the different colonization areas indicated that distinct processes occurred in this region, such as extensification, cattle raising, agricultural maintenance, restoration and forest degradation.Pages: 6779-678

Análise da dinâmica das mudanças de uso e cobertura da terra no sudeste de Roraima-Amazônia Setentrional, através da subtração de imagens-fração

This study approached land use and land cover change dynamics in altered areas, through the study of conversions presented in agricultural colonization areas in the southeastern region of Roraima, Brazil. We used TM/Landsat optical images, processed by linear spectral mixing modeling, generating fraction images (soil, vegetation and shade) and applied as change detection technique, subtraction of fraction images. The difference-images were classified by Bhattacharyya algorithm, mapping existing conversions, according to field survey. The clustering of conversions according to the characteristics of gain and loss of biomass provided better classification performance, observed by the significant increase of Kappa. Conversions were analyzed in relation of colonization projects and distance to roads (BR-210 and vicinal roads). The results showed a predominance of opening conversions in newer colonization project areas (Entre Rios and São Luizão). São João da Baliza and Caroebe presented similar behavior in relation to the existing conversions, being the majority of them indicative of land use changes, which may explain the tendency of these regions to the livestock activity, as observed in the field survey. Entre Rios colonization project presented the highest total conversion area, with total of 28,408 ha in the studied period (2004-2010). Regarding the distance to roads, Entre Rios, Baliza and Caroebe presented new openings in more distant areas than São Luizão, featuring further advance in the forest area. Regarding the distance to BR-210, Baliza and Caroebe showed the concentration of opening conversions farther than Entre Rios, meaning greater penetration of vicinal roads in these two regions.Pages: 7523-753

Classificação de imagens de radar multipolarizadas na banda L (R99-B) para mapeamento de uso do solo em áreas urbanas e periurbanas de São José dos Campos-SP

This paper presents a study of multi-polarized SAR images to obtain maps of land use in the municipality of São José dos Campos-SP, Brazil. Radar data of high resolution may indicate good opportunity to explore remote sensing images in the spectrum of the microwaves, which can provide additional and useful information for studies of urban and periurban areas. The objective of this paper is to evaluate the use of SAR data (R99-B) in supervised classification for the discrimination land use in urban and periurban regions. The methodology included classification based on pixel to pixel (MLC-Maximum Likelihood Classification) and contextual approach (ICM- Iterated Conditional Modes). The input polarized images were HH, HV e VV (amplitude), including one texture image derived of HH polarization. The results indicated that, isolated, none of the images could distinguish enough the land use. These results generated a Kappa index bellow 0.4. When utilized in pairs the best results were VV + Texture-HH, with Kappa of 0.52. With three images the best results were the combination of VV + HV + Texture-HH, with Kappa 0.58. Utilizing all four images the results reached the same Kappa of 0.58. The ICM algorithm was superior to the MAXVER in all tested sets of images. The SAR images of the R99-B allowed mapping land use in the study area with good accuracy.Pages: 8185-819

Análise de ferramentas de SIG para estimativa de biomassa potencial: um estudo de caso em região de contato floresta/savana, Roraima

The knowledge and monitoring of the amount of forest biomass and its spatial distribution in the Amazon basin represents a key application of remote sensing and GIS (geographic information system) technologies. In order to explore these potentialities, a GIS was used to estimate the potential biomass expected if no human or natural disturbances occured in a forest/savanna contact zone in Roraima (Brazil). This value was derived from spatial weighted data on precipitation, a climate index and land agricultural capability. Initially, these layers were combined in a potential biomass index through the analytic hierarchy process (AHP). In a second step, the potential biomass index map was converted into a potential biomass density map. This calibration was done with 35 biomass samples acquired in the same area (reference values). Potential biomass for the total area (forests and savannas) was estimated to reach 5.2x10 7 Mg. The potential biomass density map was then masked with a PRODES (INPE) map of forests, non-forests and deforestation. For the area still recovered by forests until 2009, the total potential biomass estimated was 3.8x10 7 Mg, with an average of 153.13 Mg.ha -1 . In the total area, a potential loss of 1.0x107 Mg due to land conversion was estimated.Pages: 4126-413