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Soil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS / Sumedh R. Kashiwar in Natural Hazards, vol 110 n° 2 (January 2022)
[article]
Titre : Soil erosion estimation of Bhandara region of Maharashtra, India, by integrated use of RUSLE, remote sensing, and GIS Type de document : Article/Communication Auteurs : Sumedh R. Kashiwar, Auteur ; Manik Chandra Kundu, Auteur ; Usha R. Dongarwar, Auteur Année de publication : 2022 Article en page(s) : pp 937 - 959 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte thématique
[Termes IGN] dégradation des sols
[Termes IGN] érosion
[Termes IGN] érosion hydrique
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] Inde
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle RUSLE
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] précipitation
[Termes IGN] rive
[Termes IGN] système d'information géographiqueRésumé : (auteur) The agricultural land of the whole world is deteriorating due to the loss of top fertile soil reducing agricultural productivity and groundwater availability. Mainly, natural conditions and human manipulations have made soils extremely prone to soil erosion. Therefore, information on soil erosion status is of paramount importance to the policymakers for land conservation planning in a limited time. Spatial information systems like GIS and RS are known for their efficiencies. With that prospect, the GIS-based RUSLE model is used in this study to assess the soil erosion losses from Bhandara regions of Maharashtra, India. The study area comes under Wainganga sub-river basin, a portion of the Godavari River basin. We have prepared the required five potential parameters (R*K*LS*C*P) of RUSLE model on pixel-to-pixel basis. We have prepared the R factor map from monthly rainfall data of Indian Meteorological Department (IMD) and K factor map by digital the soil series map of NBSS & LUP, Govt. of India. We have used the digital elevation model data (DEM) of Cartosat-1 for LS-factor map, Landsat 8 and Sentinel-2A satellite dataset to generate LULC and NDVI map to obtain C and P factors. The results and satellite data were validated using Google Earth Pro and field observations. The results showed significant soil erosion from the river banks and wastelands near water bodies, with the soil loss values ranging between 20 and 40 t ha−1 yr−1. The land under reserved forest was very slight erosion-prone soil with soil loss of Numéro de notice : A2022-180 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1007/s11069-021-04974-5 Date de publication en ligne : 16/08/2021 En ligne : https://doi.org/10.1007/s11069-021-04974-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99856
in Natural Hazards > vol 110 n° 2 (January 2022) . - pp 937 - 959[article]Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa / Mangana Rampheri in Geocarto international, vol 37 n° 2 ([15/01/2022])
[article]
Titre : Use of remotely sensed data to estimate tree species diversity as an indicator of biodiversity in Blouberg Nature Reserve, South Africa Type de document : Article/Communication Auteurs : Mangana Rampheri, Auteur ; Timothy Dube, Auteur ; Inos Dhau, Auteur Année de publication : 2022 Article en page(s) : pp 526 - 542 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique du sud (état)
[Termes IGN] arbre (flore)
[Termes IGN] bande spectrale
[Termes IGN] biodiversité végétale
[Termes IGN] conservation de la flore
[Termes IGN] détection de changement
[Termes IGN] espèce végétale
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] indice de végétation
[Termes IGN] régression
[Termes IGN] réserve naturelleRésumé : (auteur) We use remotely sensed data to estimate species diversity in Blouberg Nature Reserve (BNR) in the Limpopo province, South Africa to understand the state of biodiversity since communities’ involvement in conservation initiatives. To achieve this objective, Landsat series data collected before and after community involvement in biodiversity conservation were used in conjunction with selected diversity indices i.e., Shannon-Wiener Index (H’) and Simpson Index (D). Thirty 15 m × 15 m field plots were selected and all trees within each plot were identified, with the help of Botanists. Further, we applied regression analysis to determine the relationship between satellite derived tree species diversity and field observations. The results of the study demonstrated a significant (p Numéro de notice : A2022-052 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1080/10106049.2020.1723717 Date de publication en ligne : 16/04/2020 En ligne : https://doi.org/10.1080/10106049.2020.1723717 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99443
in Geocarto international > vol 37 n° 2 [15/01/2022] . - pp 526 - 542[article]Variations of urban NO2 pollution during the COVID-19 outbreak and post-epidemic era in China: A synthesis of remote sensing and In situ measurements / Chunhui Zhao in Remote sensing, vol 14 n° 2 (January-2 2022)
[article]
Titre : Variations of urban NO2 pollution during the COVID-19 outbreak and post-epidemic era in China: A synthesis of remote sensing and In situ measurements Type de document : Article/Communication Auteurs : Chunhui Zhao, Auteur ; Chengzin Zhang, Auteur ; Jinan Lin, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 419 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] dioxyde d'azote
[Termes IGN] épidémie
[Termes IGN] image Sentinel-5P-TROPOMI
[Termes IGN] impact sur l'environnement
[Termes IGN] pollution atmosphérique
[Termes IGN] qualité de l'air
[Termes IGN] variation temporelleRésumé : (auteur) Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production. Numéro de notice : A2022-102 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14020419 Date de publication en ligne : 17/01/2022 En ligne : https://doi.org/10.3390/rs14020419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99567
in Remote sensing > vol 14 n° 2 (January-2 2022) . - n° 419[article]3D stem modelling in tropical forest: towards improved biomass and biomass change estimates / Sébastien Bauwens (2022)
Titre : 3D stem modelling in tropical forest: towards improved biomass and biomass change estimates Type de document : Thèse/HDR Auteurs : Sébastien Bauwens, Auteur Editeur : Gembloux [Belgique] : Université de Liège - Gembloux Agro-Bio Tech Année de publication : 2022 Importance : 146 p. Format : 21 x 30 cm Note générale : Bibliographie
Dissertation originale présentée en vue de l'obtention du grade de Docteur en Sciences Agronomiques et Ingénierie BiologiqueLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse comparative
[Termes IGN] biomasse aérienne
[Termes IGN] cartographie et localisation simultanées
[Termes IGN] Congo
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] dioxyde de carbone
[Termes IGN] données lidar
[Termes IGN] écosystème forestier
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lidar mobile
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle numérique de terrain
[Termes IGN] placette d'échantillonnage
[Termes IGN] puits de carbone
[Termes IGN] semis de points
[Termes IGN] stéréoscopie
[Termes IGN] structure-from-motion
[Termes IGN] télémétrie laser terrestreRésumé : (auteur) Tropical forests are the main contributors of CO2 emissions between the biosphere and the atmosphere in the land use sector. The deforestation and degradation of these forests are the main sources of emissions from this sector, which accounts for 15% of the world's CO2 emissions. The monitoring of CO2 emissions and removals from tropical forests requires fine measurements of their trees. These measurements are then used as inputs in allometric model to predict the tree aboveground biomass and thus indirectly their equivalent in CO2. However, a significant proportion of trees in tropical forests show morphological singularities on the stem such as buttresses or other irregularities. The height (HPOM) of the diameter measured (DPOM) is therefore commonly raised above the buttresses to reach a circular part of the stem. The standard of measuring the diameter at breast height (DBH) is then lost. In this context, this thesis aims to improve the monitoring of tropical trees with stem irregularities by using recent three-dimensional (3D) measurement tools and developing a model-based approach to harmonize height measurements of the diameterdo. First, we evaluated the potential of the close-range terrestrial photogrammetric approach (CRTP) to measure irregular shaped stems. The advantage of this 3D approach is its low cost and ease of implementation as it only requires a camera and targets. Following the convincing results of this approach, we studied the quality of the allometric relationship between variables extracted from the stem cross-section at 1.3 m height and above-ground biomass. We found that the equivalent diameter of the basal area at 1.3 m height (DBH') correlates better with aboveground tree biomass and thus its carbon content than does diameter above buttress (DPOM). Therefore, harmonization of HPOM to 1.3 m height should be further studied to improve biomass estimates. Secondly, we investigated the potential of a hand-held mobile lidar scanner (HMLS) to measure in 3D not only one tree at a time but many trees from forest plots with a 15 m radius in Belgian temperate forest. To assess the HMLS, we compared it to 3D measurements made with a more commonly used static terrestrial laser scanning (TLS) and with conventional forest inventory diameter and position measurements. The HMLS has a better 3D spatial coverage of the stems than the TLS and the precision of the stem diameter measurements is also better with the HMLS. Setting up the plot and scanning it from five locations with the TLS takes three times longer than scanning with HMLS. This pioneering work shows us the potential of using HMLS in tropical forests through its speed of execution and its important spatial coverage at the stem level, an important issue for irregular shaped tree stems. Thirdly, we developed and assessed a model-based approach for harmonizing HPOM to correct the bias induced by irregular stems in the aboveground biomass estimates of forest inventory plots. Following the estimation of DBH' using a taper model proposed in our study, we find that conventional aboveground biomass estimates (i.e. with only DPOM), compared to estimates made with DBH', show an increasing divergence with the increase of irregular stems proportion within plots and going up to -15% in our study. These results show the importance of considering HPOM when estimating aboveground biomass in tropical forests, especially in forests with many irregular stems. Estimates of the evolution of plot above-ground biomass over time should also be revised to better consider the biomass growth of irregular shaped tree stems, which has been underestimated until now. Finally, based on the results of this research, we summarize the 3D measurement tools currently available and describe their advantages and disadvantages in the case of irregular stems. Based on available human and technical resources, we also give recommendations on the harmonization method to use in permanent sampling plots to correct the bias induced by irregular stems. Improved monitoring of these tropical trees may provide a better understanding of some of the residual, i.e. unexplained, terrestrial ecosystem CO2 sink currently noted in IPCC reports. Note de contenu : 1- General introduction
2- 3D measurements of irregularly shaped stems
3- 3D stem measurements at the plot level
4- Making tropical forest plots comparable
5- DiscussionNuméro de notice : 24037 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse étrangère Note de thèse : Thèse de Doctorat : Sciences Agronomiques et Ingénierie Biologique : Liège : 2022 DOI : sans En ligne : https://hdl.handle.net/2268/293900 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101855 An assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 / Darius Phiri in Geomatics, Natural Hazards and Risk, vol 13 (2022)
[article]
Titre : An assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 Type de document : Article/Communication Auteurs : Darius Phiri, Auteur ; Collins Chanda, Auteur ; Vincent R. Nyirenda, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 148 - 166 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aire protégée
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse diachronique
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte thématique
[Termes IGN] classification par arbre de décision
[Termes IGN] couvert forestier
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] gestion forestière durable
[Termes IGN] protection de la biodiversité
[Termes IGN] ZambieRésumé : (auteur) In sub-Saharan Africa, protected areas provide a platform for conserving biodiversity. However, these areas are facing massive pressure due to deforestation, and information on forest dynamics and factors driving the changes in protected areas is generally lacking. This study has two objectives: (1) to assess forest cover changes that have occurred between 1972 and 2016 in Copperbelt Province’s protected areas, and (2) understand the drivers of forest cover changes. The study used thematic land cover maps for six selected years, which were classified using an object-based image analysis (OBIA) approach. We also applied a Classification Tree (CT) approach to assess the drivers of forest cover changes using R statistical software. The findings showed that forest cover in protected areas has been characterised by massive deforestation due to various factors. Between 1972 and 2016, primary and secondary forests showed a decrease of 2,226.43 km2 (11.06%) and an increase of 1,082.93 km2 (4.05%), respectively. The major factors driving forest changes include the levels of precipitation, human population density, elevation, distance from roads, towns and rivers. This study presents consistent information for long-term forest monitoring in protected areas, and informs decision-makers on the levels of deforestation and their drivers for effective forest management. Numéro de notice : A2022-092 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1080/19475705.2021.2017021 Date de publication en ligne : 21/12/2021 En ligne : https://doi.org/10.1080/19475705.2021.2017021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99515
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