Niina Käyhkö
Biographic Data
| ID | 6316609 |
|---|---|
| NAME | Niina Käyhkö |
| GIVEN NAMES | Niina |
| FAMILY NAME | Käyhkö |
| SIGNATURE | KÄYHKÖ N |
| AFFILIATIONS | University of Turku |
| ORCID | 0000-0003-2482-5085 |
| VERIFIED | Yes |
| TOTAL WORKS | 9 |
| TOTAL CITATIONS | 17 |
| WORKS AS AUTHOR | 9 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2011 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 3 |
Automated geovisualization of flood disaster impacts in the global South cities with open geospatial data sets and Iceye SAR flood data
Flooding is a highly destructive natural disaster affecting millions of people annually, causing substantial global economic losses. Especially in the Global South, vulnerable populations with limited resources for flood protection and recovery suffer the most. However, effective flood impact analysis and standardized geospatial data processing and visualization is lacking, hindering effective disaster risk reduction. This study employs Python to…
Self-assessment in student’s learning and developing teaching in geoinformatics – case of Geoportti self-assessment tool
In successful geoinformatics education, students’ active role in the learning process, e.g. through applying self-assessment, show an increasing interest but the evidence of benefits and challenges of self-assessment are sporadic. In this article, we examine the usefulness of an online self-assessment tool developed for geoinformatics education. We gathered data in two Finnish universities on five courses (n = 11–73 students/course) between 2019 …
Residential greenness and risks of depression
We carried out a longitudinal study on the associations between residential greenness and depression risk in urban areas in Finland. Residential greenness indicators were estimated within various buffer sizes around individuals' home locations (selected n = 14424) using time-series of normalized differential vegetation index (NDVI) and CORINE land cover data (CLC). We estimated individuals' cumulative exposure to residential greenness over a 5-ye…
Modeling direct above-ground carbon loss due to urban expansion in Zanzibar City Region, Tanzania
Expansion of urban fabric on carbon storages is estimated to cause loss of 1.38 Pg of Above-Ground Carbon (AGC) in pan-tropics between 2000 and 2030. This would be approximately 5% of all emissions caused by tropical land use changes. Despite the significance of the phenomenon, these emissions are rarely measured, monitored, or addressed in climate change mitigation plans, especially in Sub-Saharan Africa. Therefore, we demonstrated a state-of-th…
Lessons learned from participatory land use planning with high-resolution remote sensing images in Tanzania
Participatory mapping (PM) solutions have become common in many sectors of society to enhance engagement of the local communities in planning processes. Especially in data scarce regions, like Africa, PM that captures local knowledge in spatially explicit form is an important tool for integrating previously non-existent spatial knowledge in to collaborative planning. Despite the increasing usage of PM solutions, there still lies a gap in our know…
Biophysical regions of the Southern Highlands, Tanzania
Spatially explicit, evidence-based and regionally contextualized data on biophysical landscape characteristics is an essential basis for regionally sustainable landscape management schemes. In many regions of the Global South, the availability of such information is poor, especially at the subnational level, and the spatial management is often based on generic and outdated information, leading to severe threats for land sustainability. We have de…
Urban expansion in Zanzibar City, Tanzania
Community stakeholders’ knowledge in landscape assessments – Mapping indicators for landscape services
Dynamic land use and land cover changes and their effect on forest resources in a coastal village of Matemwe, Zanzibar, Tanzania
Urban expansion in Zanzibar City, Tanzania
Dynamic land use and land cover changes and their effect on forest resources in a coastal village of Matemwe, Zanzibar, Tanzania
Modeling direct above-ground carbon loss due to urban expansion in Zanzibar City Region, Tanzania
Expansion of urban fabric on carbon storages is estimated to cause loss of 1.38 Pg of Above-Ground Carbon (AGC) in pan-tropics between 2000 and 2030. This would be approximately 5% of all emissions caused by tropical land use changes. Despite the significance of the phenomenon, these emissions are rarely measured, monitored, or addressed in climate change mitigation plans, especially in Sub-Saharan Africa. Therefore, we demonstrated a state-of-th…
Dynamic land use and land cover changes and their effect on forest resources in a coastal village of Matemwe, Zanzibar, Tanzania
Community stakeholders’ knowledge in landscape assessments – Mapping indicators for landscape services
Urban expansion in Zanzibar City, Tanzania
Biophysical regions of the Southern Highlands, Tanzania
Spatially explicit, evidence-based and regionally contextualized data on biophysical landscape characteristics is an essential basis for regionally sustainable landscape management schemes. In many regions of the Global South, the availability of such information is poor, especially at the subnational level, and the spatial management is often based on generic and outdated information, leading to severe threats for land sustainability. We have de…
Lessons learned from participatory land use planning with high-resolution remote sensing images in Tanzania
Participatory mapping (PM) solutions have become common in many sectors of society to enhance engagement of the local communities in planning processes. Especially in data scarce regions, like Africa, PM that captures local knowledge in spatially explicit form is an important tool for integrating previously non-existent spatial knowledge in to collaborative planning. Despite the increasing usage of PM solutions, there still lies a gap in our know…
Residential greenness and risks of depression
We carried out a longitudinal study on the associations between residential greenness and depression risk in urban areas in Finland. Residential greenness indicators were estimated within various buffer sizes around individuals' home locations (selected n = 14424) using time-series of normalized differential vegetation index (NDVI) and CORINE land cover data (CLC). We estimated individuals' cumulative exposure to residential greenness over a 5-ye…
Modeling direct above-ground carbon loss due to urban expansion in Zanzibar City Region, Tanzania
Expansion of urban fabric on carbon storages is estimated to cause loss of 1.38 Pg of Above-Ground Carbon (AGC) in pan-tropics between 2000 and 2030. This would be approximately 5% of all emissions caused by tropical land use changes. Despite the significance of the phenomenon, these emissions are rarely measured, monitored, or addressed in climate change mitigation plans, especially in Sub-Saharan Africa. Therefore, we demonstrated a state-of-th…
Self-assessment in student’s learning and developing teaching in geoinformatics – case of Geoportti self-assessment tool
In successful geoinformatics education, students’ active role in the learning process, e.g. through applying self-assessment, show an increasing interest but the evidence of benefits and challenges of self-assessment are sporadic. In this article, we examine the usefulness of an online self-assessment tool developed for geoinformatics education. We gathered data in two Finnish universities on five courses (n = 11–73 students/course) between 2019 …
Automated geovisualization of flood disaster impacts in the global South cities with open geospatial data sets and Iceye SAR flood data
Flooding is a highly destructive natural disaster affecting millions of people annually, causing substantial global economic losses. Especially in the Global South, vulnerable populations with limited resources for flood protection and recovery suffer the most. However, effective flood impact analysis and standardized geospatial data processing and visualization is lacking, hindering effective disaster risk reduction. This study employs Python to…
Geography (9 works) · Land Use and Ecosystem Services (7 works) · Environmental planning (5 works) · Environmental resource management (5 works) · Geospatial analysis (4 works) · Land use (4 works) · Tanzania (4 works) · Computer Science (3 works) · Ecology (3 works) · Environmental Science (3 works)