Deforestation is the replacement of forest by other land use while degradation a reduction long-term canopy cover and/or stock. Forest in Brazilian Amazon mainly due to selective logging intact/un-managed forests and uncontrolled fires. The deforestation contribution carbon emission already known but determining remains challenge. Discrimination from fires, both which produce different levels damage, important for UNFCCC (United Nations Framework Convention on Climate Change) REDD+ (Reducing...

Quantifying forest fires remain a challenging task for the implementation of public policies aimed to mitigate climate change. In this paper, we propose new method provide an annual burned area map Mato Grosso State located in Brazilian Amazon region, taking advantage high spatial and temporal resolution sensors. The consists generating vegetation, soil, shade fraction images by applying Linear Spectral Mixing Model (LSMM) Landsat-8 OLI (Operational Land Imager), PROBA-V (Project On-Board...

Fire is a major forest degradation component in the Amazon forests. Therefore, it important to improve our understanding of how post-fire canopy structure changes cascade through spectral signals registered by medium-resolution satellite sensors over time. We contrasted accumulated yearly temporal aboveground biomass (AGB), measured permanent plots, and traditional indices derived from Landsat-8 images. tested if can Random Forest (RF) models AGB losses based on pre-fire AGB, proxied data...

The Pantanal biome—a tropical wetland area—has been suffering a prolonged drought that started in 2019 and peaked 2020. This favored the occurrence of natural disasters led to 2020 fire crisis. purpose this work was map burned area’s extent during crisis Brazilian portion biome using Sentinel-2 MSI images. classification areas performed machine learning algorithm (Random Forest) Google Earth Engine platform. Input variables were percentiles 10, 25, 50, 75, 90 monthly (July December) mosaics...

The scientific grasp of the distribution and dynamics land use cover (LULC) changes in South America is still limited. This especially true for continent’s hyperarid, arid, semiarid, dry subhumid zones, collectively known as drylands, which are under-represented ecosystems that highly threatened by climate change human activity. Maps LULC drylands are, thus, essential order to investigate their vulnerability both natural anthropogenic impacts. paper comprehensively reviewed existing mapping...

Brazil, with more than 8 million km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , presents six different biomes, ranging from natural grasslands (Pampa biome) to tropical rainfall forests (Amazônia biome), land-use types (mostly pasturelands and croplands) pressures (mainly in the Cerrado biome). The objective of this article is present a new method discriminate most representative land use cover (LULC) classes based on PROBA-V...

This article presents a method, based on orbital remote sensing, to map the extent of forest plantations in São Paulo State (Southeast Brazil). The proposed method uses random machine learning algorithm available Google Earth Engine (GEE) cloud computing platform. We used 30 m annual mosaics derived from Landsat-5 Thematic Mapper (TM) images and Landsat-8 Operational Land Imager (OLI) for 1985 1995 2013 2021 time periods, respectively. These periods were selected planted areas’ rotation,...

This work aims to develop a new method map Land Use and Cover (LULC) classes in the São Paulo State, Brazil, using Landsat-8 Operational Imager (OLI) data. The novelty of proposed consists selecting images based on spectral temporal characteristics LULC classes. First, we defined six be mapped year 2020 as forest, forest plantation, water bodies, urban areas, agriculture, pasture. Second, visually analyzed their variability over year. Then, pre-processed these highlight each class. For...

This paper presents a new approach for rapidly assessing the extent of land use and cover (LULC) areas in Mato Grosso state, Brazil. The novel idea is an annual time series fraction images derived from linear spectral mixing model (LSMM) instead original bands. LSMM was applied to Project On-Board Autonomy-Vegetation (PROBA-V) 100-m data composites 2015 (~73 scenes/year, cloud-free images, theory), generating vegetation, soil, shade images. These highlight LULC components inside pixels....

This paper presents a new method for rapid assessment of the extent annual croplands in Brazil. The proposed applies linear spectral mixing model (LSMM) to PROBA-V time series images derive vegetation, soil, and shade fraction regional analysis. We used S10-TOC (10 days synthesis, 1 km spatial resolution, top-of-canopy) products Brazil S5-TOC (five 100 m Mato Grosso State (Brazilian Legal Amazon). Using vegetation whole year (2015 this case), only one mosaic composed with maximum values was...

In this work we present a procedure to analyze the forest degradation by fire in Brazilian Amazon using Landsat-8 Operational Land Imager (OLI) time series, taking advantage of resources Google Earth Engine platform. The study area is municipality Porto dos Gaúchos located state Mato Grosso, "arc deforestation" Legal Amazon. We used OLI images acquired between January 1st, 2017 and last available image from 2018. generated fraction soil, vegetation shade Linear Spectral Mixing Model...

O bioma Caatinga representa cerca de 10% do território nacional e tem uma população estimada em 28 milhões habitantes. Sua vegetação arbóreo-arbustiva, adaptada às condições semiaridez, exerce um papel fundamental na manutenção balanço hidrológico, alimentação da matriz energética geração receitas para o país. No entanto, ainda é dos que recebe menor atenção comunidade científica. Diante disso, presente artigo revisão visa apresentar elementos contribuam a atualização estado arte sobre uso...

O Cerrado é o segundo maior bioma brasileiro, sendo reconhecido como a savana mais biodiversa do mundo. Após 1970, as dinâmicas de uso e cobertura da terra têm sido marcadas por atividades agropecuárias extensivas, resultando em taxas desmatamento historicamente superiores às Amazônia. Esse cenário reforça necessidade investigar metodologia das iniciativas mapeamento vegetação Cerrado, fim identificar lacunas desafios ainda existentes para avanço científico conhecimento no âmbito...

Fire dynamics in the Brazilian Savannas (Cerrado) is related to climatic conditions and management interventions by human activities. Thus, fire occurrence conservation units (UCs) may be different when compared with their buffer zones. Our results, obtained burned area analysis, demonstrate that zones have most significant variation over years inside UC, such as Jalapão State Park. In contrast, zone presents agricultural activities, occurs Chapada dos Veadeiros das Mesas National Parks, or...

The complexity of pixel composition orbital images has been commonly referred to the spectral mixture problem. acquisition endmembers (pure pixels) direct from image under study is one most employed approaches. However, it becomes limited in low or moderate spatial resolutions due lower probability finding those pixels. In this way, work proposes combined use with different estimate responses resolution image, obtained proportions derived higher-resolution images. proposed methodology was...

This article presents a land use and cover (LULC) classification map based on Random Forest (RF) classifier algorithm in the São Paulo State (Brazil), using Landsat-8 OLI data. The method consists time series images from January to December of 2020 spectral temporal characteristics LULC classes. We performed class by considering: water, urban area, forest, agriculture, forest plantation pasture. Then, we pre-processed selected targets highlight each class. After that, was RF for individually...

The objective of this paper is to present a method assess the extent annual land use/land cover in Brazil, South America. proposed applies Linear Spectral Mixing Model (LSMM) PROBA-V datasets derive vegetation, soil and shade fraction images for global regional analysis. We used 1 km composites 10 days (S10-TOC - 10-daily composites, Top-Of-Canopy) America 100 m 5 (S5-TOC 5-daily Mato Grosso State, Brazilian Amazon. Then we built 1km 100m corresponding three endmembers with highest values...

O presente estudo tem como objetivo avaliar a distribuição espacial e temporal da cobertura de nuvens no Nordeste brasileiro, mensal anualmente, partir 2000 2019, afim determinar se há um padrão na existe entre em relação à quantidade chuva. Para isso, foram utilizadas imagens diárias adquiridas para o período analisado pelo sensor MODIS, que incluem garantia qualidade (QA) desses dados quanto (pixel livre nuvens, com total ou mistura nuvens). fins comparativos, QA dos sensores OLI...

This article presents a method to map the extent of forest plantation in an area located São Paulo State (Brazil). The proposed applies Linear Spectral Mixing Model (LSMM) Landsat Thematic Mapper (TM) datasets derive annually vegetation, soil and shade fraction images for local analysis. We used 30 m annual mosaics TM during 1985 1995 time period. These have advantage reduce volume data be analyzed highlighting target characteristics. Then, we generated only one mosaic each dataset computing...

This article presents a land use and cover (LULC) classification map using Random Forest algorithm in the São Paulo State (Brazil), an assessment of burned areas two products (MCD64A1 MapBiomas Fire). The method uses Landsat Operational Land Imager (OLI) time series images from January to December 2020. We performed class by considering: water, urban area, forest formation, sugarcane, agriculture, plantation pasture. For each class, we used different spectral bands image fraction according...

Unmanned aerial vehicles (UAVs) have been advancing in precision and cost-benefit for remote sensing studies, including height biomass estimations. This article presents a preliminary experiment to explore UAV photogrammetry estimate canopy savanna grassland phytophysiognomies the Brazilian Cerrado biome. For this purpose, it was generated dense cloud points obtain digital terrain surface models used calculate height. The spatial distribution of ranged from 0 4 meters, which most values were...

This article presents a new method for monitoring forest cover in the state of Rondônia, Brazilian Amazon. The proposed applies Linear Spectral Mixing Model (LSMM) to Landsat datasets (MSS, TM and OLI) derive annual vegetation, soil, shade fraction images period 1980 – 2020. These have advantages reducing volume data be analyzed highlighting target characteristics. Then, we applied threshold classify forest, non-forest, hydrography, deforestation areas. showed consistent flexible allowing...

Quantifying and monitoring woody cover distribution in semiarid regions is challenging, due to their scattered distribution. Data mining has been widely used with remote sensing data for the information extraction of spectral temporal analysis change detection. The main objective this study was characterize land use over 2000–2010 time period Brazilian Caatinga seasonal biome using a Normalized Difference Vegetation Index (NDVI) series Geographic Object-Based Image Analysis (GEOBIA). For...