Zambezi River & Omo River Basins

•Transferir como PPTX, PDF•

0 gostou•747 visualizações

This document discusses water temperature and leaf area index datasets for the Zambezi River Basin and surrounding areas derived from Landsat 8 and Sentinel-2 satellite imagery. It describes the processing steps to generate water temperature and leaf area index maps at monthly intervals from 2013 to 2016. Additional datasets provided for analysis include Landsat imagery, land use classifications, waterbody maps, and demographic data for the Zambezi and Omo River basins.

Ciências

Water temperature from Landsat 8
Case study
• Water temperature from
Landsat 8 derived for the
Lake Cahora Bassa till
western part of Lake
Cariba.
• 4 tiles needed to cover
area
• Temporal coverage:
2013
• Temporal resolution:
~monthly
• => ~50 scenes, 250GB
2

Water temperature from Landsat 8
Case study
Processing
• Generation of a multi-
temporal water mask.
• Erosion of this mask at
the borders to eliminate
influence of coastal
areas and to take into
account the spatial
resolution of LS 8
• Calculation of water
temperature from
thermal band
3
Water

Water temperature from Landsat 8
Case study
4
• Extraction of
temperature at specific
points for validation

Leaf Area Index Datasets
Luia basin
• Leaf Area Index based on
Landsat & Sentinel data for
Luia basin
• 6 Sentinel-2 tiles needed to
cover area
• Temporal coverage: 2010-
2016
• Temporal resolution:
~monthly (increasing after
2013 with LS8 and 2016 with
Sentinel 2)
• => ~350 scenes, 1.1TB (only
scenes with low cloud cover!)
5
24.4.2016
24.4.201628.3.2016
27.4.201627.4.2016
28.3.2016

Leaf Area Index Datasets
Luia basin
6
12.8.2016
12.8.201615.8.2016
05.8.201605.8.2016
15.8.2016
36LVJ 36LVK 36LWJ 36LWK 36LUK 36LUJ
150918 150918 L5
150925 150925 150925 150925 L8
151004 S2A
160108 160108
151020 151020
151112
151119
151121
151223
160108 160108 160108
160122
160308 160308
160326
160328 160328 160328
160413
160424 160424
160427 160427
160507
160513 160513
160514 160514
160515
160527
160529 160529
• Merging over whole basin
only possible taking multiple
dates

Other Datasets provided by Vista
Lunsemfwa basin
7
Data provided for the field trip of Stefaan & Fitz
• Two atmospherically corrected Landsat 8 Images (false Colour
Infrared) , Path/Row 171/70 & 172/70 from June/July 2016
• corresponding land use classification
• Leaf Area Index

Other datasets provided by Vista
Zambesi basin
8
• Landsat mosaic in full
resolution for the whole
Zambesi catchment
• Waterbodies derived by
Landsat images of the
past 32 years (dataset
by JRC)
• Globcover datasets
(300m resolution,
2006&2009)
• Various demographic
datasets(population
count, density)

OMO RIVER BASIN
Case study cover Omo River
can be used as section title

10
Turbidity Lake Omo
Case study
70 [FNU]
0

Mais conteúdo relacionado

Semelhante a Zambezi River & Omo River Basins

DSD-INT 2017 Use of RIBASIM in Lesotho - Passchier

Deltares

DSD-INT 2019 Lake Kivu - 3D hydrodynamic modelling of a deep and strongly str...

Deltares

DSD-INT 2016 Salinity and Sediment dynamics in San Francisco Estuary - Elmilady

Deltares

Climate Change Science in the Hindu-Kush-Himalayas-Tibet

International Centre for Integrated Mountain Development (ICIMOD)

DSD-INT 2017 Lake Kivu - Development of a 3D (500 z-layers) model to study st...

Deltares

Trading Off Hydropower Potential for Irrigated Agriculture-An Example from th...

CPWF Mekong

Semelhante a Zambezi River & Omo River Basins (6)

DSD-INT 2017 Use of RIBASIM in Lesotho - Passchier

DSD-INT 2019 Lake Kivu - 3D hydrodynamic modelling of a deep and strongly str...

DSD-INT 2016 Salinity and Sediment dynamics in San Francisco Estuary - Elmilady

Climate Change Science in the Hindu-Kush-Himalayas-Tibet

DSD-INT 2017 Lake Kivu - Development of a 3D (500 z-layers) model to study st...

Trading Off Hydropower Potential for Irrigated Agriculture-An Example from th...

Mais de DAFNE project

A multi-perspective tool to visualize relationships in the Food-Water-Energy-...

DAFNE project

A decision-analytic framework & multi-perspective visualization for participa...

DAFNE project

A multi-perspective tool to visualize relationships in the Food-Water-Energy-...

DAFNE project

Innovation for Sustainability Transition: A Challenge and an Opportunity for...

DAFNE project

DAFNE Project Presentation

DAFNE project

Poster DAFNE Project overview

DAFNE project

60 years of Kariba Dam: implications for downstream water quality

DAFNE project

How water storage for energy and food production affects the Zambezi River’s ...

DAFNE project

Social, Economic and Institutional Developments in cross-border water systems

DAFNE project

Dafne economic model

DAFNE project

Sustainable Management of the Nexus in Transboundary Systems

DAFNE project

DAFNE project presentation: Supporting decision making for sustainable resour...

DAFNE project

DAFNE case study on the Zambezi river basin

DAFNE project

DAFNE Negotiation Simulation Lab Approach & Tools

DAFNE project

Dafne project newsletter issue 2

DAFNE project

Dafne project newsletter issue1

DAFNE project

Modeling the hydrological regime of Turkana Lake (Kenya, Ethiopia) by combini...

DAFNE project

Dafne project overview Lusaka

DAFNE project

A Decision-Analytic Framework to explore the waterenergy-food NExus in comple...

DAFNE project

Resilience of a dammed tropical river.

DAFNE project

Mais de DAFNE project (20)

A multi-perspective tool to visualize relationships in the Food-Water-Energy-...

A decision-analytic framework & multi-perspective visualization for participa...

A multi-perspective tool to visualize relationships in the Food-Water-Energy-...

Innovation for Sustainability Transition: A Challenge and an Opportunity for...

DAFNE Project Presentation

Poster DAFNE Project overview

60 years of Kariba Dam: implications for downstream water quality

How water storage for energy and food production affects the Zambezi River’s ...

Social, Economic and Institutional Developments in cross-border water systems

Dafne economic model

Sustainable Management of the Nexus in Transboundary Systems

DAFNE project presentation: Supporting decision making for sustainable resour...

DAFNE case study on the Zambezi river basin

DAFNE Negotiation Simulation Lab Approach & Tools

Dafne project newsletter issue 2

Dafne project newsletter issue1

Modeling the hydrological regime of Turkana Lake (Kenya, Ethiopia) by combini...

Dafne project overview Lusaka

A Decision-Analytic Framework to explore the waterenergy-food NExus in comple...

Resilience of a dammed tropical river.

Último

The presentation first gives the brief introduction about the animal communication covering the reasons for communication. It then describes the important types of animal communication emphasizing the important points regarding auditory and visual communication. With respect to auditory communication, it covers the uses of it and mechanisms of auditory communication along with examples. Later the presentation discusses the various forms of visual communication such as gestures, postures, facial expressions, color changes , bioluminescent communication. It then describes the visual communication in bees in the form of bee dance . In bee dance it gives a brief overview of round dance , sickle dance and waggle dance .

Animal Communication- Auditory and Visual.pptx

UmerFayaz5

GUIDELINES ON SIMILAR BIOLOGICS Regulatory Requirements for Marketing Authori...

Lokesh Kothari

Presentation Vikram Lander by Vedansh Gupta.pptx

gindu3009

COST ESTIMATION FOR A RESEARCH PROJECT.pptx

FarihaAbdulRasheed

Call Girls In Safdarung Enclave Arjun Nagar Whatsapp +91 9654467111 Delhi ⛟ Open 24 Hrs, ☎ Booking Short 2000 Night 6000 ALL HOME/HOTEL SERVICE DOORSTEP SERVICE IN/CALL & OUT/CALL SERVICE WITH MANY OPTIONS AVAILABLE DELHI GURGAON & NOIDA SERVICE IN REASONABLE RATES FROM LOW TO HIGH PROFILE STAFF’S. Call Girl Number~24X7~Call Girl Services, New Delhi, Delhi OutCall Rate Call Girl Mahipalpur,Call Girl Connaught Place,Call Girl Nehru Place,Call Girl Chanakyapuri,Call Girl Paharganj,Call Girl Dhaula Kuan,Call Girl Moti Bagh,Call Girl Karol Bagh,Call Girl Greater Kailash,Call Girl Naraina, Call Girl Katwaria Sarai,Call Girl Janakpuri,Call Girl Kalkaji,Call Girl Lajpat Nagar,Call Girl Palam,Call Girl Malviya Nagar,Call Girl Mehrauli,Call Girl Govindpuri,Call Girl Sarojini Nagar ,Call Girl Neb Sarai,Call Girl South Ex,Call Girl Munirka,Call Girl Saket,Call Girl Chattarpur

9654467111 Call Girls In Raj Nagar Delhi Short 1500 Night 6000

Sapana Sha

Bacterial Identification and Classifications

Areesha Ahmad

BooK Now Call us at +918448380779 to hire a gorgeous and seductive call girl for sex. Take a Delhi Escort Service. The help of our escort agency is mostly meant for men who want sexual Indian Escorts In Delhi NCR. It should be noted that any impersonator will get 100 attention from our Young Girls Escorts in Delhi. They will assume the position of reliable allies. VIP Call Girl With Original Photos Book Tonight +918448380779 Our Cheap Price 1 Hour not available 2 Hours 5000 Full Night 8000 TAG: Call Girls in Delhi, Noida, Gurgaon, Ghaziabad, Connaught Place, Greater Kailash Delhi, Lajpat Nagar Delhi, Mayur Vihar Delhi, Chanakyapuri Delhi, New Friends Colony Delhi, Majnu Ka Tilla, Karol Bagh, Malviya Nagar, Saket, Khan Market, Noida Sector 18, Noida Sector 76, Noida Sector 51, Gurgaon Mg Road, Iffco Chowk Gurgaon, Rajiv Chowk Gurgaon All Delhi Ncr Free Home Deliver

Stunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCR

Delhi Call girls

Botany krishna series 2nd semester Only Mcq type questions

Sumit Kumar yadav

HotJupiters are amongthebest-studied exoplanets, but it is still poorly understood how their chemical composition and cloud properties vary with longitude. Theoretical models predict that clouds may condense on the nightside and that molecular abundances can be driven out of equilibrium by zonal winds. Here we report a phase-resolved emission spectrum of the hot Jupiter WASP-43b measured from 5–12µ 5–12µ 5–12µm with JWST’s Mid-Infrared Instrument (MIRI). 1524 ±35 1524 ±35 and 863±23 The spectra reveal a large day–night temperature contrast (with average brightness temperatures of 1524 ± 35 863 ±23 863 ±23Kelvin, respectively) and evidence for water absorption at all orbital phases. Comparisons with three-dimensional atmospheric models show that both the phase curve shape and emission spectra strongly suggest the presence of nightside clouds which become optically thick to thermal emission at pressures greater than ∼100mbar. The dayside is consistent with a cloudless atmosphere above the mid-infrared photosphere. Con3trary to expectations from equilibrium chemistry but consistent with disequilibrium kinetics models, methane is not detected on the nightside (2σ upper limit of 1–6 parts per million, depending on model assumptions).

Nightside clouds and disequilibrium chemistry on the hot Jupiter WASP-43b

Sérgio Sacani

Kochi CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL IN We are Providing :- ● – Private independent collage Going girls . ● – independent Models . ● – House Wife’s . ● – Private Independent House Wife’s ● – Corporate M.N.C Working Profiles . ● – Call Center Girls . ● – Live Band Girls . ●- Foreigners & Many More . Service type: 1.In call 2.out call 3. full Lip to Lip kiss 4.69 5.b-job without Condom 6. Hard Core sex & Much More. 7 Body to Body Touch 8 Kissing 9 Sucking Boobs and More 10 Enjoy by Hand 11 Relax By Oral 12 Sex with Happy Ending • In Call and Out Call Service • 3* 5* 7* Hotels Service • 24 Hours Available • Indian, Russian, Punjabi, Kashmiri Escorts • Real Models, College Girls, House Wife, Also Available • Short Time and Full Time Service Available • Hygienic Full AC Neat and Clean Rooms Avail. In Hotel 24 hours • Daily Escorts Staff Available • Minimum to Maximum Range Available.

Kochi ❤CALL GIRL 84099*07087 ❤CALL GIRLS IN Kochi ESCORT SERVICE❤CALL GIRL

kantirani197

High Class Escorts in Hyderabad ₹7.5k Pick Up & Drop With Cash Payment 969456...

chandars293

Cotton crops are vulnerable to a variety of sucking pests, which can severely impact plant health, yield, and fiber quality. These pests primarily feed on plant sap, extracting nutrients directly from the plant's vascular system. Here's a breakdown of some of the most significant sucking pests in cotton cultivation: Aphids: Cotton aphids or melon aphids can cause direct damage by sucking sap and indirect damage by secreting honeydew, which encourages sooty mold growth. This can interfere with photosynthesis and weaken the plant. Aphids can also transmit viral diseases. Whiteflies: Two species, the silverleaf whitefly and the bandedwinged whitefly, are particularly troublesome. They not only suck sap from the underside of leaves, causing yellowing and leaf drop, but their honeydew excretion promotes sooty mold and they can transmit several plant viruses. Thrips: While thrips can chew on plants, their primary damage to cotton is through sucking. They attack the cotton plant during its seedling stage, which can stunt growth and reduce vigor. Thrips are also capable of transmitting the Cotton Bud disease. Spider Mites: These are not insects but arachnids. Spider mites, such as the two-spotted spider mite, suck cell contents from the leaves, leading to speckled discoloration and potentially significant leaf loss if infestations are severe. Leafhoppers: Including various species, leafhoppers can cause direct damage through feeding, which results in leaf curling and stunted growth. They can also be vectors for plant diseases. Mealybugs: These pests are less common but can be problematic, especially in clustered planting conditions. They suck sap and secrete honeydew, which leads to sooty mold. Mealybugs can also spread viruses. Stink Bugs: Although primarily known for their chewing mouthparts, certain stink bugs can cause damage similar to sucking pests by injecting saliva into the plant and sucking out nutrients, leading to boll damage and stained lint. Management Strategies: Cultural Controls: This includes practices such as crop rotation, using resistant varieties, and managing planting and harvesting times to avoid peak pest populations. Biological Controls: Beneficial insects like lady beetles, lacewings, and predatory mites can naturally control sucking pest populations. Parasitic wasps also play a role in controlling aphid and whitefly populations. Chemical Controls: Insecticides may be used but should be chosen carefully to minimize resistance development and preserve beneficial insects. Systemic insecticides can be particularly effective against sucking pests. Integrated Pest Management (IPM): Combining multiple control strategies based on monitoring and thresholds to apply the most effective and environmentally sensitive approach. Effective management of sucking pests in cotton requires a thorough understanding of the pest species present, their life cycles, and the ecological balance of the field environment.

Pests of cotton_Sucking_Pests_Dr.UPR.pdf

PirithiRaju

Bollworms are among the most damaging pests in cotton cultivation, affecting the bolls where the cotton fibers are formed. There are several species of bollworms, each capable of causing significant yield loss and quality degradation if not effectively managed. Here’s a detailed look at the primary bollworm species affecting cotton: Cotton Bollworm (Helicoverpa armigera): Also known as the corn earworm or the Old World bollworm, this pest is found in many regions around the world. It is highly polyphagous (feeds on many different plants) and poses a threat not only to cotton but also to maize, tomatoes, and legumes. The larvae bore into the cotton bolls, feeding on the developing seeds and fibers, which can lead to boll rot. Pink Bollworm (Pectinophora gossypiella): A significant pest of cotton, the pink bollworm larvae infest the cotton bolls, feeding on the seeds and lint. This can severely damage or destroy the bolls. In regions where pink bollworms are prevalent, they have been a major driver for the adoption of genetically engineered Bt cotton, which expresses a bacterium gene toxic to certain insects. Tobacco Budworm (Heliothis virescens): Closely related to the cotton bollworm, the tobacco budworm primarily attacks tobacco but is also a common pest in cotton. It primarily damages the flowers and bolls of the cotton plant. Differentiating between the tobacco budworm and the cotton bollworm based on appearance can be challenging, but it is crucial for effective management. American Bollworm (Helicoverpa zea): Known in some regions as the corn earworm, it is similar in behavior to Helicoverpa armigera and poses a threat to a variety of crops, including cotton. The larvae attack the cotton bolls, leading to direct damage to the cotton lint and seeds. Management Strategies: Cultural Controls: Crop rotation, destruction of crop residues, and deep plowing can help break the pest’s life cycle. Timing of planting can also be adjusted to avoid peak pest infestation. Biological Controls: Natural enemies like Trichogramma wasps, which parasitize bollworm eggs, and predators such as lacewings and ladybugs can be encouraged. Bacillus thuringiensis (Bt) products can also be sprayed, which are particularly effective against young larvae. Chemical Controls: Insecticides may be required when infestation levels exceed economic thresholds. However, resistance management must be considered, alternating modes of action to avoid developing resistance. Genetic Approaches: Bt cotton, genetically modified to express Bacillus thuringiensis toxin, has been highly effective in controlling bollworms and has dramatically reduced the reliance on chemical insecticides. Monitoring and Scouting: Regular field scouting and using pheromone traps to monitor adult populations can help in timely and targeted application of control measures. The effective management of bollworms often requires an integrated approach

Pests of cotton_Borer_Pests_Binomics_Dr.UPR.pdf

PirithiRaju

Green chemistry and Sustainable development.pptx

RajatChauhan518211

Biological Classification BioHack (3).pdf

muntazimhurra

Botany is the branch of biology that deals with the scientific study of plants, including their structure, growth, reproduction, metabolism, development, and classification. It encompasses a wide range of topics, from the molecular biology of plant cells to the ecological relationships between plants and their environments. Botany is essential for understanding plant diversity, ecology, evolution, and the roles plants play in ecosystems and human societies.

Botany 4th semester series (krishna).pdf

Sumit Kumar yadav

A botany file is similar to a chemistry practical file but specifically focuses on experiments and observations related to plants. It typically includes detailed descriptions of plant-related experiments, such as germination studies, growth experiments, tissue culture techniques, plant anatomy investigations, and ecological surveys. The file may contain records of plant specimens collected, their classification, characteristics, and ecological significance. Additionally, it may include diagrams, photographs, drawings, tables, and data analysis related to plant research. Like a chemistry practical file, a botany file serves as a documentation of practical work conducted in the field of botany and is often used for assessment and educational purposes.

Botany 4th semester file By Sumit Kumar yadav.pdf

Sumit Kumar yadav

Forensic Biology & Its biological significance.pdf

rohankumarsinghrore1

Chemistry is the scientific study of matter, its properties, composition, structure, and the changes it undergoes. It's often divided into various sub-disciplines such as organic chemistry, inorganic chemistry, physical chemistry, analytical chemistry, and biochemistry. Chemistry plays a crucial role in understanding the world around us and has applications in various fields such as medicine, materials science, environmental science, and industry.

Chemistry 4th semester series (krishna).pdf

Sumit Kumar yadav

Wepresent Atacama Large Millimeter/submillimeter Array 12-m, 7-m, and Total Power Array observations of the FUOrionis outbursting system, covering spatial scales ranging from 160 to 25,000 au. The high-resolution interferometric data reveal an elongated 12CO(2–1) feature previously observed at lower resolution in 12CO(3–2). Kinematic modeling indicates that this feature can be interpreted as an accretion streamer feeding the binary system. The mass infall rate provided by the streamer is significantly lower than the typical stellar accretion rates (even in quiescent states), suggesting that this streamer alone is not massive enough to sustain the enhanced accretion rates characteristic of the outbursting class prototype. The observed streamer may not be directly linked to the current outburst, but rather a remnant of a previous, more massive streamer that may have contributed enough to the disk mass to render it unstable and trigger the FU Orionis outburst. The new data detect, for the first time, a vast, slow-moving carbon monoxide molecular outflow emerging from this object. To accurately assess the outflow properties (mass, momentum, and kinetic energy), we employ 13CO(2–1) data to correct for optical depth effects. The analysis indicates that the outflow corresponds to swept-up material not associated with the current outburst, similar to the slow molecular outflows observed around other FUor and Class I protostellar objects.

Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...

Sérgio Sacani

Zambezi River & Omo River Basins

1. ZAMBEZI RIVER BASIN

2. Water temperature from Landsat 8 Case study • Water temperature from Landsat 8 derived for the Lake Cahora Bassa till western part of Lake Cariba. • 4 tiles needed to cover area • Temporal coverage: 2013 • Temporal resolution: ~monthly • => ~50 scenes, 250GB 2

3. Water temperature from Landsat 8 Case study Processing • Generation of a multi- temporal water mask. • Erosion of this mask at the borders to eliminate influence of coastal areas and to take into account the spatial resolution of LS 8 • Calculation of water temperature from thermal band 3 Water

4. Water temperature from Landsat 8 Case study 4 • Extraction of temperature at specific points for validation

5. Leaf Area Index Datasets Luia basin • Leaf Area Index based on Landsat & Sentinel data for Luia basin • 6 Sentinel-2 tiles needed to cover area • Temporal coverage: 2010- 2016 • Temporal resolution: ~monthly (increasing after 2013 with LS8 and 2016 with Sentinel 2) • => ~350 scenes, 1.1TB (only scenes with low cloud cover!) 5 24.4.2016 24.4.201628.3.2016 27.4.201627.4.2016 28.3.2016

6. Leaf Area Index Datasets Luia basin 6 12.8.2016 12.8.201615.8.2016 05.8.201605.8.2016 15.8.2016 36LVJ 36LVK 36LWJ 36LWK 36LUK 36LUJ 150918 150918 L5 150925 150925 150925 150925 L8 151004 S2A 160108 160108 151020 151020 151112 151119 151121 151223 160108 160108 160108 160122 160308 160308 160326 160328 160328 160328 160413 160424 160424 160427 160427 160507 160513 160513 160514 160514 160515 160527 160529 160529 • Merging over whole basin only possible taking multiple dates

7. Other Datasets provided by Vista Lunsemfwa basin 7 Data provided for the field trip of Stefaan & Fitz • Two atmospherically corrected Landsat 8 Images (false Colour Infrared) , Path/Row 171/70 & 172/70 from June/July 2016 • corresponding land use classification • Leaf Area Index

8. Other datasets provided by Vista Zambesi basin 8 • Landsat mosaic in full resolution for the whole Zambesi catchment • Waterbodies derived by Landsat images of the past 32 years (dataset by JRC) • Globcover datasets (300m resolution, 2006&2009) • Various demographic datasets(population count, density)

9. OMO RIVER BASIN Case study cover Omo River can be used as section title

10. 10 Turbidity Lake Omo Case study 70 [FNU] 0

Zambezi River & Omo River Basins

Recomendados

Recomendados

Mais conteúdo relacionado

Semelhante a Zambezi River & Omo River Basins

Semelhante a Zambezi River & Omo River Basins (6)

Mais de DAFNE project

Mais de DAFNE project (20)

Último

Último (20)

Zambezi River & Omo River Basins