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Quantification of cotton water consumption by remote sensing / Jefferson Vieira José in Geocarto international, vol 35 n° 16 ([01/12/2020])  

Public [article]  inGeocarto international > vol 35 n° 16 [01/12/2020] . - pp 1800 - 1813 Titre : Quantification of cotton water consumption by remote sensing Type de document : Article/Communication Auteurs : Jefferson Vieira José, Auteur ; Niclene Ponce Rodrigues de Oliveira, Auteur ; Tonny José de Araújo da Silva, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1800 - 1813 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] biome [Termes descripteurs IGN] cultures irriguées [Termes descripteurs IGN] évapotranspiration [Termes descripteurs IGN] gestion de l'eau [Termes descripteurs IGN] Gossypium (genre) [Termes descripteurs IGN] image thermique [Termes descripteurs IGN] irrigation [Termes descripteurs IGN] Leaf Area Index [Termes descripteurs IGN] Mato Grosso Résumé : (auteur) Quantifying crop water consumption is essential for water resource management. The objective was to estimate the current evapotranspiration (ETa) of the cotton crop (Gossypium hirsutum L.) in the rainfed system, as well as the components of the radiation and energy balance in the Cerrado biome conditions using orbital images and the SEBAL algorithm and validate the estimates of evapotranspiration (ET) using FAO guidelines for crop coefficient (K c) of the cotton crop. Research was carried out in the State of Mato Grosso, Brazil, in areas with three cotton cultivars. Images of the Operational Land Imager and Thermal Infrared Sensor sensors were used and ET estimation was made based on the SEBAL algorithm. Mean ETa in the cotton cycle was 3.5 mm dia−1 and the K c values ranged from 0.22 and 1.12, on average, in the smaller and larger leaf area, respectively. Numéro de notice : A2020-726 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1583777 date de publication en ligne : 18/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1583777 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96329 [article]

School cartography in Brazil and its inclusive perspective / Imre Josef Demhardt in International journal of cartography, vol 6 n° 3 (October 2020)  

Public [article]  inInternational journal of cartography > vol 6 n° 3 (October 2020) . - pp 316 - 330 Titre : School cartography in Brazil and its inclusive perspective Type de document : Article/Communication Auteurs : Imre Josef Demhardt, Auteur Année de publication : 2020 Article en page(s) : pp 316 - 330 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] carte tactile [Termes descripteurs IGN] communication cartographique [Termes descripteurs IGN] éducation [Termes descripteurs IGN] formation [Termes descripteurs IGN] géographie [Termes descripteurs IGN] représentation cartographique [Vedettes matières IGN] Cartologie Résumé : (auteur) This article presents an overview of School Cartography in Brazil, demonstrating how academic research in the area has influenced official documents proposed by the Ministry of Education, the teaching of Cartography in Basic Education, and the curricula of undergraduate courses in Geography. The purpose of this study is to understand the role of cartography in the teaching of geography and how learning through maps has contributed more intensively to the formation of Brazilian citizens from the 1990s onward, at the same time that cartography-related content has become more and more present in schools at the primary level in Brazil, and the text discusses this process. It also presents the background of the Tactile Cartography in Brazil, discussing the importance of reflecting the process of adapting graphic/visual representations to tactile representations, in the context of Cartographic Communication and its contribution to the teaching of cartography from an inclusive perspective. Numéro de notice : A2020-652 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2020.1824565 date de publication en ligne : 06/10/2020 En ligne : https://doi.org/10.1080/23729333.2020.1824565 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96110 [article]

Carbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing / Felipe Schwerz in Annals of Forest Science [en ligne], vol 77 n° 3 (September 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 77 n° 3 (September 2020) Titre : Carbon stocks, partitioning, and wood composition in short-rotation forestry system under reduced planting spacing Type de document : Article/Communication Auteurs : Felipe Schwerz, Auteur ; Durval D. Neto, Auteur ; Braulio O. Caron, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] biomasse forestière [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] essence d'arbre [Termes descripteurs IGN] Eucalyptus grandis [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] plantation forestière [Termes descripteurs IGN] puits de carbone [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Key message: The use of reduced planting spacings is an important strategy to increase the carbon storage in the above-belowground biomass and should be recommended for future exploitation of forest energy plantations when the purpose intended is the production of biomass for energy. Context: Recent concerns about global warming have resulted in more concerted studies on quantifying carbon storage in forest systems. Forest energy plantations play an essential role in the carbon storage. Aims: We proposed to evaluate the carbon storage and partitioning in short-rotation forest plantations and to characterize the elemental composition and energetic properties of the forest species Eucalyptus grandis W. Hill ex Maiden, Mimosa scabrella Benth, and Ateleia glazioviana Baill, grown under four planting spacings in Southern Brazil. Methods: A field study was conducted in order to evaluate forest carbon stock and wood composition using samples collected by direct method. The four spacings evaluated were 2.0 × 1.0, 2.0 × 1.5, 3.0 × 1.0, and 3.0 × 1.5 m. Results: The Eucalyptus grandis stored 327.1 Mg C ha−1 at 2.0 × 1.5-m spacing. When compared with the 3.0 × 1.5-m spacing, we observed a reduction of 29% in carbon stored. All forest species showed higher carbon storage in the following partitioning pattern: trunk>roots>branches>leaves>litter. Forest species energetic properties and elemental composition were not affected by planting spacing. On the other hand, variations according the tree portions were observed. For the carbon stocks in the soil, we observed an average accumulated carbon stock for the forest species studied of 77.4 Mg C ha−1 (0–40 cm). Conclusion: Forest managers can accelerate growth and increase the forest carbon storage and biomass yield by using reduced planting spacing that are smaller than the current pattern used by the majority of the forest producers, which is 3.0 × 1.5 m. For Eucalyptus grandis and Mimosa scabrella, the planting spacings recommended to produce biomass and improve carbon stocks were 2.0 × 1.5 and 2.0 × 1.0 m, respectively. Numéro de notice : A2020-402 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00974-w date de publication en ligne : 27/06/2020 En ligne : https://doi.org/10.1007/s13595-020-00974-w Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95450 [article]

What Is threatening forests in protected areas? A global assessment of deforestation in protected areas, 2001–2018 / Christopher M. Wade in Forests, vol 11 n° 5 (May 2020)  

Public [article]  inForests > vol 11 n° 5 (May 2020) . - 14 p. Titre : What Is threatening forests in protected areas? A global assessment of deforestation in protected areas, 2001–2018 Type de document : Article/Communication Auteurs : Christopher M. Wade, Auteur ; Kemen G. Austin, Auteur ; James Cajka, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] aire protégée [Termes descripteurs IGN] Amérique du nord [Termes descripteurs IGN] analyse diachronique [Termes descripteurs IGN] arbuste [Termes descripteurs IGN] biodiversité [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] Congo [Termes descripteurs IGN] couvert forestier [Termes descripteurs IGN] déboisement [Termes descripteurs IGN] gaz à effet de serre [Termes descripteurs IGN] habitat forestier [Termes descripteurs IGN] indicateur de service écosystémique [Termes descripteurs IGN] Indonésie [Termes descripteurs IGN] protection des forêts [Termes descripteurs IGN] risque environnemental [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) The protection of forests is crucial to providing important ecosystem services, such as supplying clean air and water, safeguarding critical habitats for biodiversity, and reducing global greenhouse gas emissions. Despite this importance, global forest loss has steadily increased in recent decades. Protected Areas (PAs) currently account for almost 15% of Earth’s terrestrial surface and protect 5% of global tree cover and were developed as a principal approach to limit the impact of anthropogenic activities on natural, intact ecosystems and habitats. We assess global trends in forest loss inside and outside of PAs, and land cover following this forest loss, using a global map of tree cover loss and global maps of land cover. While forests in PAs experience loss at lower rates than non-protected forests, we find that the temporal trend of forest loss in PAs is markedly similar to that of all forest loss globally. We find that forest loss in PAs is most commonly—and increasingly—followed by shrubland, a broad category that could represent re-growing forest, agricultural fallows, or pasture lands in some regional contexts. Anthropogenic forest loss for agriculture is common in some regions, particularly in the global tropics, while wildfires, pests, and storm blowdown are a significant and consistent cause of forest loss in more northern latitudes, such as the United States, Canada, and Russia. Our study describes a process for screening tree cover loss and agriculture expansion taking place within PAs, and identification of priority targets for further site-specific assessments of threats to PAs. We illustrate an approach for more detailed assessment of forest loss in four case study PAs in Brazil, Indonesia, Democratic Republic of Congo, and the United States. Numéro de notice : A2020-655 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.3390/f11050539 date de publication en ligne : 12/05/2020 En ligne : https://doi.org/10.3390/f11050539 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96119 [article]

A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery / Lucas Prado Osco in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 97 - 106 Titre : A convolutional neural network approach for counting and geolocating citrus-trees in UAV multispectral imagery Type de document : Article/Communication Auteurs : Lucas Prado Osco, Auteur ; Mauro Dos Santos de Arruda, Auteur ; José Marcato Junior, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 97 - 106 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] carte de confiance [Termes descripteurs IGN] citrus (genre) [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] géolocalisation [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] inventaire de la végétation [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] verger Résumé : (Auteur) Visual inspection has been a common practice to determine the number of plants in orchards, which is a labor-intensive and time-consuming task. Deep learning algorithms have demonstrated great potential for counting plants on unmanned aerial vehicle (UAV)-borne sensor imagery. This paper presents a convolutional neural network (CNN) approach to address the challenge of estimating the number of citrus trees in highly dense orchards from UAV multispectral images. The method estimates a dense map with the confidence that a plant occurs in each pixel. A flight was conducted over an orchard of Valencia-orange trees planted in linear fashion, using a multispectral camera with four bands in green, red, red-edge and near-infrared. The approach was assessed considering the individual bands and their combinations. A total of 37,353 trees were adopted in point feature to evaluate the method. A variation of σ (0.5; 1.0 and 1.5) was used to generate different ground truth confidence maps. Different stages (T) were also used to refine the confidence map predicted. To evaluate the robustness of our method, we compared it with two state-of-the-art object detection CNN methods (Faster R-CNN and RetinaNet). The results show better performance with the combination of green, red and near-infrared bands, achieving a Mean Absolute Error (MAE), Mean Square Error (MSE), R2 and Normalized Root-Mean-Squared Error (NRMSE) of 2.28, 9.82, 0.96 and 0.05, respectively. This band combination, when adopting σ = 1 and a stage (T = 8), resulted in an R2, MAE, Precision, Recall and F1 of 0.97, 2.05, 0.95, 0.96 and 0.95, respectively. Our method outperforms significantly object detection methods for counting and geolocation. It was concluded that our CNN approach developed to estimate the number and geolocation of citrus trees in high-density orchards is satisfactory and is an effective strategy to replace the traditional visual inspection method to determine the number of plants in orchards trees. Numéro de notice : A2020-045 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.12.010 date de publication en ligne : 18/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.12.010 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94525 [article]

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Flowering acceleration in native Brazilian tree species for genetic conservation and breeding / Gleidson Guilherme Caldas Mende in Annals of forest research, Vol 63 n° 1 (January - June 2020)  

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Tree species classification in tropical forests using visible to shortwave infrared WorldView-3 images and texture analysis / Matheus Pinheiro Ferreira in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

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