Jonathan Rizzi

Forsker

(+47) 483 47 537
jonathan.rizzi@nibio.no

Sted
Ås - Bygg O43

Besøksadresse
Oluf Thesens vei 43, 1433 Ås (Varelevering: Elizabeth Stephansens vei 21)

Biografi

Se vedlegg for en komplett liste over vitenskapelige publikasjoner.
 
PhD i miljøvitenskap, arbeidet siden mer enn 15 år i GIS-sektoren. Erfaring som konsulent, lærer, forsker og prosjektleder for nasjonale og internasjonale prosjekt og grupper og har arbeidserfaring fra land som Kina og Ecuador.

De viktigste forskningsområdene er bruk av GIS i flere miljøsektorer, inkludert klimaendringer, forurenset grunn og vannkvalitet. Bidratt til utvikliing av GIS-baserte verktøy som Spatial Decision Support System konsekvensutredning for klimaendringer (DESYCO) og WebGIS for klimadata. Har også jobbet med metoder og tilpasningstiltak for å møte klimaendringene ved kystsoner. Arbeidserfaring fra MultiCriteria Decision Analysis (MCDA).

I de siste årene har han deltatt i internasjonale samarbeidsprosjekter i utviklingsland.

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Til dokument

Sammendrag

Urban green structures (UGS) play important roles in enhancing urban ecosystems by providing benefits such as mitigating the urban heat island effect, improving air quality, supporting biodiversity, and aiding in stormwater management. Accurately mapping UGS is important for sustainable urban planning and management. Traditional methods of mapping such as manual mapping, aerial photography interpretation and pixel-based classification have limitations in terms of coverage, accuracy, and efficiency. Object-based image analysis (OBIA) has gained prominence due to its ability to incorporate both spectral and spatial information making it particularly effective for classification of high-resolution satellite data. This paper reviews the application of OBIA on satellite images for UGS mapping, focusing on various data sources, popular segmentation methods, and classification techniques, highlighting their respective advantages and limitations. Key segmentation methodologies discussed include multi-resolution segmentation and watershed segmentation. For classification, the review covers machine learning techniques such as random forests, support vector machines, and convolutional neural networks, among others. Several case studies highlight the successful implementation of OBIA in diverse urban environments by demonstrating improvements in classification accuracy and detail. The review also addresses the challenges associated with OBIA, such as dealing with heterogenous urban landscapes, data sources and with OBIA methods itself. Future directions for UGS mapping include the integration of deep learning algorithms, advancements in satellite data technologies, and the development of standardized classification frameworks. By providing a detailed analysis of the current state-of-the-art in object-based UGS mapping, this review aims to guide future research and practical applications in UGS management.

Sammendrag

Rapporten beskriver resultatene av arbeidet som er gjort i arbeidspakke 1 «Økt verdiskaping i norsk grøntnæring – Veivalg GS35 (GrøntStrategi mot 2035)», oppgavene 1.1 og 1.4. De naturlige betingelsene for grønnsaksdyrking er identifisert ved hjelp av stedfestet informasjon om jordsmonnets egenskaper, klimadata og terreng. Resultatene er framstilt i kartløsninga prosjektkilden Veivalg (https://kart19.nibio.no/kilden3). I tillegg er den geografiske utbredelsen av eksisterende grønnsaksdyrking undersøkt og sammenliknet med den geografiske fordelinga av de arealene som har høyt potensial for dyrking av grønnsaker. Det har også blitt utført bærekraftsanalyser på gårdsnivå.

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Divisjon for kart og statistikk

Considering the Environment and Nature when Building and Operating Ground Mounted Solar Power Plants in Norway


EnviSol's mission is to harmonize the growth of ground-mounted solar power plants in Norway with the imperative to protect biodiversity and ecosystem services. With renewable energy production, preserving nature, and supporting ecosystems all in mind, EnviSol aims to pinpoint the ideal methods and locations for these solar installations, mitigating clashes over land use.

Active Updated: 30.01.2024
End: juli 2027
Start: aug 2023
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Divisjon for miljø og naturressurser

CANALLS Agroecological practices for sustainable transition


Agroecology covers all activities and actors involved in food systems. It also places the well-being of people (producers and consumers of crops and products) at its core. The EU-funded CANALLS project will focus on the agroecological zones and diverse farming systems in the humid tropics of Central and Eastern Africa. It will explore the complex environmental, social and economic challenges, which in some cases are exacerbated by conflict and high vulnerability. Moreover, it will advance agroecological transitions in these regions through multi-actor transdisciplinary agroecology Living Labs at eight sites in four countries. The focus will be on crops such as cocoa, coffee and cassava, which are vital for subsistence and economic development.

Active Updated: 30.01.2024
End: des 2026
Start: jan 2023