Assessment of k-Nearest Neighbor and Random Forest classifiers for mapping forest fire areas in central Portugal using Landsat-8, Sentinel-2, and Terra Imagery

Forest fires threaten the population’s health, biomass, and biodiversity, intensifying the desertification processes and causing temporary damage to conservation areas. Remote sensing has been used to detect, map, and monitor areas that are affected by forest fires due to the fact that the different areas burned by a fire have similar spectral characteristics. This study analyzes the performance of the k-Nearest Neighbor (kNN) and Random Forest (RF) classifiers for the classification of an area that is affected by fires in central Portugal. For that, image data from Landsat-8, Sentinel-2, and Terra satellites and the peculiarities of each of these platforms with the support of Jeffries–Matusita (JM) separability statistics were analyzed. The event under study was a 93.40 km2 fire that occurred on 20 July 2019 and was located in the districts of Santarém and Castelo Branco. The results showed that the problems of spectral mixing, registration date, and those associated with the spatial resolution of the sensors were the main factors that led to commission errors with variation between 1% and 15.7% and omission errors between 8.8% and 20%. The classifiers, which performed well, were assessed using the receiver operating characteristic (ROC) curve method, generating maps that were compared based on the areas under the curves (AUC). All of the AUC were greater than 0.88 and the Overall Accuracy (OA) ranged from 89 to 93%. The classification methods that were based on the kNN and RF algorithms showed satisfactory results.Research was supported by PAIUJA-2019/2020 and CEACTEMA from University of Jaen (Spain), and RNM-282 research group from the Junta de Andalucia (Spain). Special thanks to the four anonymous reviewers for their insightful comments

Viability of the UENF popcorn improvement program based on divergence in S1 families.

With the objective of evaluating the viability of the programme of recurrent selection with popcorn of the Universidade Estadual do Norte Fluminense Darcy Ribeiro carried out in Campos dos Goytacazes and Itaocara, state of Rio de Janeiro (Brazil), 40 families that originated the second cycle were evaluated for 14 morphoagronomical characteristics and random amplified polymorphic DNA (RAPD) markers, using multivariate analysis. The analyses of variance revealed the existence of variability for most evaluated morphoagronomic traits. Clustering by Tocher's optimization method for the morphoagronomic traits of Campos dos Goytacazes formed eight groups and 16 for those of Itaocara. For the RAPD markers, 18 groups of S1 families were formed by Ward's clustering method. It is concluded that there is genetic divergence in the selected families, which allows the inference that there is sufficient variability for the continuity of the recurrent selection process with the formation of new cycles.

Genetic components of combining ability in a complete diallel.

Obtained g and Sii values were associated to theoretical concepts of the respective parameters in a complete diallel with 28 parents and the simulation of five hypothetic variables with five different d/a relations (0, 0.5, 1.0, 1.5, and 2.0). These were controlled by a single gene with two alleles whose parents were represented by different frequencies of the favorable allele (1/28, 2/28,....,28/28). The conclusion was drawn that the existence of dominance deviations in the loci regulating the trait influences the GCA estimates considerably and that there is a high correlation (0.96) between the absolute Sii and the respective values. The joint evaluation of g1 and Sii estimates provides information on the genetic quality of the populations of the diallel

Germination and vigor of long-pepper seeds (Piper hispidinervum) as a function of temperature and light.

A pimenta longa é considerada uma espécie promissora por apresentar a perspectiva de tornar o Brasil autosuficiente na produção de safrol, importante óleo essencial usado como fixador de fragrâncias e com propriedades terapêuticas. Na implantação de áreas destinadas à cultura dessa espécie é necessário avaliar a qualidade fisiológica das sementes utilizadas na formação de mudas. O objetivo foi determinar as condições de temperatura e luminosidade para o teste de germinação e vigor em sementes de pimenta longa. Foram utilizadas sementes de quatro lotes para as seguintes determinações: teor de água (105 + 3 ºC por 24 horas), germinação (20; 25; 30 e 35 °C com fotoperíodo de 12 e 24 horas, e alternadas de 20-30 °C e 20-35 °C, com 12 horas de luz na temperatura mais alta), índice de velocidade de germinação, velocidade de germinação, matéria seca de plântulas, emergência de plântulas, índice de velocidade de emergência e freqüência relativa da germinação. O delineamento experimental foi o inteiramente casualizado e as médias comparadas por Tukey (P<0,05). A germinação de sementes de pimenta longa pode ser avaliada a 25 °C/12 h escuro - 12 h luz, 25 °C/24 h luz, 30 °C/12 h escuro - 12 h luz e 30 °C/24 h luz, e o potencial fisiológico a 30 °C/24 h luz

Analysis of spectral separability for detecting burned areas using Landsat-8 OLI/TIRS images under different biomes in Brazil and Portugal

Data supporting the findings of this study are available in the public domain. Landsat-8 data (https://earthexplorer.usgs.gov/, accessed on 20 April 2020). BDQueimadas vector data (https://queimadas.dgi.inpe.br/queimadas/aq30m/, accessed on 20 April 2020). ICNF burned areas vector data (https://www.icnf.pt/florestas/gfr/gfrgestaoinformacao/dfciinformacaocartgrafica, accessed on 20 April 2020).Fire is one of the natural agents with the greatest impact on the terrestrial ecosystem and plays an important ecological role in a large part of the terrestrial surface. Remote sensing is an important technique applied in mapping and monitoring changes in forest landscapes affected by fires. This study presents a spectral separability analysis for the detection of burned areas using Landsat-8 OLI/TIRS images in the context of fires that occurred in different biomes of Brazil (dry ecosystem) and Portugal (temperate forest). The research is based on a fusion of spectral indices and automatic classification algorithms scientifically proven to be effective with as little human interaction as possible. The separability index (M) and the Reed–Xiaoli automatic anomaly detection classifier (RXD) allowed the evaluation of the spectral separability and the thematic accuracy of the burned areas for the different spectral indices tested (Burn Area Index (BAI), Normalized Burn Ratio (NBR), Mid-Infrared Burn Index (MIRBI), Normalized Burn Ratio 2 (NBR2), Normalized Burned Index (NBI), and Normalized Burn Ratio Thermal (NBRT)). The analysis parameters were based on spatial dispersion with validation data, commission error (CE), omission error (OE), and the Sørensen–Dice coefficient (DC). The results indicated that the indices based exclusively on the SWIR1 and SWIR2 bands showed a high degree of separability and were more suitable for detecting burned areas, although it was observed that the characteristics of the soil affected the performance of the indices. The classification method based on bitemporal anomalous changes using the RXD anomaly proved to be effective in increasing the burned area in terms of temporal alteration and performing unsupervised detection without relying on the ground truth. On the other hand, the main limitations of RXD were observed in non-abrupt changes, which is very common in fires with low spectral signal, especially in the context of using Landsat-8 images with a 16-day revisit period. The results obtained in this work were able to provide critical information for fire mapping algorithms and for an accurate post-fire spatial estimation in dry ecosystems and temperate forests. The study presents a new comparative approach to classify burned areas in dry ecosystems and temperate forests with the least possible human interference, thus helping investigations when there is little available data on fires in addition to favoring a reduction in fieldwork and gross errors in the classification of burned areas.The article processing charge (APC) was funded by the University of Jaén through the Center for Advanced Studies on Earth Sciences, Energy and Environment CEACTEMA and the University of Minho.Research was supported by the project “Applied Remote Sensing in the Study of Hot Spots in Forests in Brazil and the Iberian Peninsula” from the Department of Cartographic Engineering and Surveying (DECart) of the Federal University of Pernambuco (UFPE/Brazil), by POIUJA-2023/2024 and CEACTEMA from University of Jaén (Spain), and RNM-282 research group from the Junta de Andalucía (Spain). This work was also supported by national funding awarded by FCT—Foundation for Science and Technology, I.P., projects UIDB/04683/2020 and UIDP/04683/2020

Shifts in microbial and physicochemical parameters associated with increasing soil quality in a tropical Ultisol under high seasonal variation.

Combination of conservation agricultural practices such as reduced tillage and complex cropping systems can improve soil quality. However, the different effects of conservation practices on soil physicochemical and microbiological parameters need to be monitored, since distinct managements, crops, regions and soil types can lead to different responses. In addition, seasonality can also affect these parameters, leading to changes associated with the environmental conditions, such as temperature and moisture. To better detect differences in soil quality between agricultural practices, the most appropriate season of sampling must be identified. Therefore, the objective of this study was to assess the changes in soil physicochemical and microbiological parameters between four different agricultural practices from a 7-year experiment along two seasons with contrasting soil water content. We analyzed the differences in physicochemical and microbiological parameters, including soil organic matter (SOM), aggregates mean weight diameter (MWD), water stability of aggregates (WSA), soil pH, total nitrogen (soil N), soil C:N ratio, microbial biomass-C (MB-C), N (MB-N), and C:N ratio (MB-C:N), basal respiration, metabolic quotient (qCO2) and microbial quotient (MB-C:soil C), between the agricultural practices of conventional tillage with maize monoculture (CTM), no-till with maize monoculture (NTM), no-till with annual rotation of maize and soybean monoculture (NTM/S), no-till with annual rotation of maize intercropped with Brachiaria rhuziziensis and soybean monoculture (NTMB/S) compared to a long-term fallow (>40 years secondary forest) at the Brazilian coastal tablelands in both winter (rainy) and summer (dry) seasons. Results indicated that the physicochemical and mostly the microbiological variables were changed between seasons. Among the practices, NTMB/S and fallow showed higher, while NTM/S and CTM showed lower soil physicochemical quality. The differences between agricultural practices were most obvious in the summer. Moreover, the microbiological and physicochemical data were correlated in the summer, but not in the winter. WSA was the variable most distinctive between practices, stable between seasons and correlated with the changes in microbial biomass/activity. On the other hand, qCO2 and mainly MB-C were the microbial parameters more associated with the increase in soil quality between the practices. In sum, we show that the benefits of conservation agriculture for soil quality in this region were most obvious in the summer and depended on the agricultural practices, with NTMB/S showing the greatest conservation of soil physicochemical qualit

Design of experimental design as a tool for the processing and characterization of HDPE composites with sponge-gourds (Luffa-Cylindrica) agrofiber residue.

Sponge-gourd (Luffa-Cylindrica) agrofiber residue (LC)-HDPE composites were manufactured by extrusion and injection moulding. The effects of fiber content, fiber size, screw speed and barrel zones temperatures on tensile strength at yield (TS) point, modulus of elasticity (MOE), flexure stress (FS) and Izod pendulum impact resistance were evaluated by using a design of experiments (DOE)-24 Factorial with centerpoint. Furthermore, a model was also determined for each response variable as well as to generate foreknowledge for additional combinations of the experimental factors. The design analysis showed that the LC-fiber content is the most important experimental factor, since it significantly affected three out of the four mechanical properties studied, specifically MOE, FS and Izod Impact resistance. The second most important parameter is the LC-fiber size. Additionally, the design analysis showed that screw speed and temperature of barrel zones did not present any influence on the properties investigated. Finally, the models were validated by comparing the results from additional experimental runs with the predicted values obtained from the respective model