Comparing time-Lapse PhenoCams with satellite observations across the Boreal forest of Quebec, Canada

Intercomparison of satellite-derived vegetation phenology is scarce in remote locations because of the limited coverage area and low temporal resolution of field observations. By their reliable near-ground observations and high-frequency data collection, PhenoCams can be a robust tool for intercomparison of land surface phenology derived from satellites. This study aims to investigate the transition dates of black spruce (Picea mariana (Mill.) B.S.P.) phenology by comparing fortnightly the MODIS normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) extracted using the Google Earth Engine (GEE) platform with the daily PhenoCam-based green chromatic coordinate (GCC) index. Data were collected from 2016 to 2019 by PhenoCams installed in six mature stands along a latitudinal gradient of the boreal forests of Quebec, Canada. All time series were fitted by double-logistic functions, and the estimated parameters were compared between NDVI, EVI, and GCC. The onset of GCC occurred in the second week of May, whereas the ending of GCC occurred in the last week of September. We demonstrated that GCC was more correlated with EVI (R2 from 0.66 to 0.85) than NDVI (R2 from 0.52 to 0.68). In addition, the onset and ending of phenology were shown to differ by 3.5 and 5.4 days between EVI and GCC, respectively. Larger differences were detected between NDVI and GCC, 17.05 and 26.89 days for the onset and ending, respectively. EVI showed better estimations of the phenological dates than NDVI. This better performance is explained by the higher spectral sensitivity of EVI for multiple canopy leaf layers due to the presence of an additional blue band and an optimized soil factor value. Our study demonstrates that the phenological observations derived from PhenoCam are comparable with the EVI index. We conclude that EVI is more suitable than NDVI to assess phenology in evergreen species of the northern boreal region, where PhenoCam data are not available. The EVI index could be used as a reliable proxy of GCC for monitoring evergreen species phenology in areas with reduced access, or where repeated data collection from remote areas are logistically difficult due to the extreme weather

Coupling UAV and satellite data for tree species identification to map the distribution of Caspian poplar

Context Mapping the distribution of species, especially those that are endemic and endangered like certain tree species, is a vital step in the effective planning and execution of conservation programs and monitoring efforts. This task gains even more significance as it directly contributes to forest conservation by highlighting the importance of species diversity. Objectives Our study objective was to assess the detection accuracy of a specific tree using different remote sensing sources and approaches. Methods Initially, individual trees were identified and classified using a canopy height model derived from UAV data. Next, we carried out the classification of satellite data within the Google Earth Engine. Lastly, we scaled the UAV-RGB dataset to match the spatial resolution of Sentinel-2, which was then employed to train random forest models using the multispectral data from Sentinel-2. Results For the UAV data, we achieved overall accuracies of 56% for automatically delineated tree crowns and 83% for manually delineated ones. Regarding the second approach using Sentinel-2 data, the classification in the Noor forest yielded an overall accuracy of 74% and a Kappa coefficient of 0.57, while in the Safrabasteh forest, the accuracy was 80% with a Kappa of 0.61. In the third approach, our findings indicate an improvement compared to the second approach, with the overall accuracy and Kappa coefficient of the classification rising to 82% and 0.68, respectively. Conclusions In this study, it was found that according to the purpose and available facilities, satellite and UAV data can be successfully used to identify a specific tree species

Estimativa de biomassa acima do solo de caatinga através de imagens SAR

A Caatinga é um bioma de ocorrência do semiárido do Brasil, tendo uma das maiores ocupações populacionais em terras secas no mundo. Porém, ainda há carência da aplicação de novas técnicas de estimativa de sua biomassa a partir de dados remotos. Sendo assim, o objetivo da tese foi avaliar a acurácia das imagens do Sentinel-1 na estimativa da biomassa acima do solo (BAS) da Caatinga no Alto Sertão do estado de Sergipe. A distribuição espacial e fenológica da Caatinga na região estudada foi analisada utilizando o Normalized Difference Vegetation Index (NDVI). A análise florística e fitossociológica foi realizada por meio do inventário florestal, utilizado também para calcular a BAS nos fragmentos de Caatinga. Foram testados diferentes métodos de filtragem para avaliar a eficácia na redução do speckle na imagem do Sentinel-1 analisando o número equivalente de looks (NEL). A estimativa da BAS utilizando imagens do Sentinel-1 utilizou dados do inventário em campo, comparando as acurácias das respostas de filtros a partir da decomposição polarimétrica e, posteriormente, testando os atributos: VV, VH, VH/VV, Radar Vegetation Index (RVI), Dual Polarization SAR Vegetation Index (DPSVI), Entropia (H), Ângulo Alpha (α), por meio de regressões lineares simples e múltiplas, na Caatinga Verde, Intermediária e Seca. A Caatinga estudada não é influenciada pelos fatores fisiográficos: declividade, altimetria, proximidade ao rio e tipo de solo. A Caatinga densa apresenta curvas fenológicas com maior condição de verdor que a aberta. A espécie Cenostigma pyramidale é a mais abundante entre as 25 identificadas. O filtro Gamma apresentou melhor desempenho na redução do speckle. A comparação da BAS estimada e observada indicou que a regressão múltipla fornece melhor acurácia nos períodos de Verdor (R2: 0,72) e Intermediário (R2: 0,73) da vegetação, com a contribuição de atributos coerentes e incoerentes. Portanto, o estudo permitiu analisar espacialmente a Caatinga estudada, caracterizando-a fenologicamente bem como sua composição e fitossociologia. Também foi possível verificar as diferentes atenuações do speckle no pré- processamento das imagens. Por fim, constatou-se que as imagens do Sentinel-1 podem ser utilizadas para a estimar a BAS.The Caatinga is a biome occurring in the semiarid region of Brazil, having one of the largest population occupations in dry lands in the world. However, there is still a lack of application of new techniques for estimating its biomass from remote data. Therefore, the objective of the thesis was to evaluate the accuracy of Sentinel-1 images in estimating the aboveground biomass (BAS) of the Caatinga in the Alto Sertão of the state of Sergipe. The spatial and phenological distribution of the Caatinga in the studied region was analyzed using the Normalized Difference Vegetation Index (NDVI). The floristic and phytosociological analysis was carried out through the forest inventory, also used to calculate the BAS in the Caatinga fragments. Different filtering methods were tested to evaluate the effectiveness of speckle reduction in the Sentinel-1 image by analyzing the equivalent number of looks (NEL). The BAS estimate using Sentinel-1 images used field inventory data comparing the accuracy of filter responses from the polarimetric decomposition and, later, testing the attributes: VV, VH, VH/VV, Radar Vegetation Index (RVI), Dual Polarization SAR Vegetation Index (DPSVI), Entropy (H), Alpha Angle (α), through simple and multiple linear regressions, in the Greenness, Intermediate and Dry Caatinga. The studied Caatinga is not influenced by physiographic factors: slope, altimetry, proximity to the river and type of soil. Dense Caatinga has phenological curves with greater greenness than open one. The Cenostigma pyramidale species is the most abundant among the 25 identified. The Gamma filter showed better performance in speckle reduction. The comparison of the estimated and observed BAS indicated that the multiple regression provides better accuracy in the Greenness (R2: 0.72) and Intermediate (R2: 0.73) periods of the vegetation, with the contribution of coherent and incoherent attributes. Therefore, the study allowed the spatial analysis of the studied Caatinga, characterizing it phenologically as well as its composition and phytosociology. It was also possible to verify the different attenuations of the speckle in the pre-processing of the images. Finally, it was found that Sentinel-1 images can be used to estimate BAS

Remote Sensing in Mangroves

The book highlights recent advancements in the mapping and monitoring of mangrove forests using earth observation satellite data. New and historical satellite data and aerial photographs have been used to map the extent, change and bio-physical parameters, such as phenology and biomass. Research was conducted in different parts of the world. Knowledge and understanding gained from this book can be used for the sustainable management of mangrove forests of the worl

The global tree carrying capacity (keynote)

editorial reviewe

Adaptation of the Root System to the Environment

This book is a collection of fundamental and applied research on the plant root response to environmental clues. In particular, the continued adaptation of both fine and coarse roots to modifications due to natural and anthropogenic causes were investigated from different viewpoints. Additionally, specific root traits were investigated as an optimal indicator of responses to the environment at the whole-plant level. Aspects such as an innovative methodological approach, the root morphology, gene expression, and primary and secondary metabolite concentrations were at the center of the investigations conducted in this collection

Do Red Edge and Texture Attributes from High-Resolution Satellite Data Improve Wood Volume Estimation in a Semi-Arid Mountainous Region?

Remote sensing-based woody biomass quantification in sparsely-vegetated areas is often limited when using only common broadband vegetation indices as input data for correlation with ground-based measured biomass information. Red edge indices and texture attributes are often suggested as a means to overcome this issue. However, clear recommendations on the suitability of specific proxies to provide accurate biomass information in semi-arid to arid environments are still lacking. This study contributes to the understanding of using multispectral high-resolution satellite data (RapidEye), specifically red edge and texture attributes, to estimate wood volume in semi-arid ecosystems characterized by scarce vegetation. LASSO (Least Absolute Shrinkage and Selection Operator) and random forest were used as predictive models relating in situ-measured aboveground standing wood volume to satellite data. Model performance was evaluated based on cross-validation bias, standard deviation and Root Mean Square Error (RMSE) at the logarithmic and non-logarithmic scales. Both models achieved rather limited performances in wood volume prediction. Nonetheless, model performance increased with red edge indices and texture attributes, which shows that they play an important role in semi-arid regions with sparse vegetation

Bosques creciendo en su límite de distribución: cambio en la cubierta forestal y relaciones clima-crecimiento en el Parque Natural del Moncayo

El cambio global afecta a los bosques en numerosas formas, poniendo en compromiso su situación actual en todo el mundo. En concreto, para el mundo mediterráneo se pronostican cambios sustanciales en las temperaturas, régimen de precipitaciones y recurrencia de eventos climáticos extremos que, unidos a los cambios en el clima que ya se han producido durante el último siglo, aumentan la vulnerabilidad de los bosques y ponen en peligro su supervivencia. Esto es especialmente relevante para aquellas especies forestales adaptadas a condiciones más frescas y húmedas, que encuentran en el mundo mediterráneo su límite de distribución debido a los condicionantes climáticos de la zona. La velocidad a la cual se producen los cambios en el clima hace necesaria la intervención antrópica para hacer frente a sus consecuencias mediante la gestión forestal, ya que los mecanismos naturales de adaptación de los bosques son procesos más lentos que el actual cambio global. En esta tesis se propone un análisis espacial integrador mediante diversas técnicas orientadas a analizar tanto la distribución como el crecimiento del bosque persiguiendo como fin la aplicabilidad de sus resultados a la gestión y manejo forestal. El análisis se centra en las principales especies forestales presentes en el Parque Natural del Moncayo, como son el pino silvestre, el haya y el rebollo, que son especies muy importantes a nivel europeo debido a su valor ecológico y económico. Los resultados obtenidos en la presente tesis ponen de manifiesto que la distribución espacial de estas masas forestales no es estable en el tiempo y está sujeta a cambios sustanciales que pueden ser detectados en un periodo relativamente corto de tiempo de poco más de dos décadas. Las especies están todavía inmersas en procesos de adaptación dinámica, relacionados principalmente con la situación de partida, con las prácticas de gestión forestal, con la competencia entre especies y con la adecuación al clima prevalente.El hecho de que estas especies se encuentren en su límite de distribución no hace que las restricciones climáticas sean muy diferentes a las restricciones propias de cada especie. A grandes rasgos, estos limitantes son similares a los encontrados en otras regiones situadas a lo largo del rango de distribución, y por tanto son específicos de cada especie. Sin embargo, existen matices que restringen en mayor medida el desarrollo de estas especies en este límite de distribución. Además, determinados limitantes varían significativamente en función del gradiente altitudinal (i.e. climático), actuando en algunas zonas como potenciadores y en otras como inhibidores de crecimiento. En cambio, su situación de límite de distribución en el caso de las hayas y pinos silvestres sí que afecta enormemente a la duración del periodo de crecimiento, siendo muy diferente su efecto en estas dos especies y con sus matices dentro del gradiente ambiental de la zona de estudio. En el caso del haya las condiciones con carácter más mediterráneo influyen negativamente, restringiendo el periodo de crecimiento a poco más de dos meses, pero en el caso del pino se alarga considerablemente comparándolo con el crecimiento en la región eurosiberiana. Ambas estrategias son útiles para el desarrollo de la especie, pero al mismo tiempo podrían ser problemáticas en años determinados donde las condiciones climáticas sean desfavorables en los momentos críticos para cada especie.El potencial de los resultados obtenidos en esta tesis en el terreno de la ordenación medioambiental es considerable, pudiéndose usar para planificar medidas de gestión forestal para cada especie orientadas a disminuir la influencia que el cambio global ejerce sobre ellas.<br /