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License: CC BY 4.0

1 to 10 of 675 Results

Dataset for comparing agricultural and forestry profitability at the parcel level Feb 10, 2026 - Social Sciences Bilande, Kristine; Veipane, Una Diana; Nipers, Aleksejs; Pilvere, Irina, 2026, "Dataset for comparing agricultural and forestry profitability at the parcel level", https://doi.org/10.71782/DATA/KINURI, DataverseLV, V2 This study develops a spatial distribution of profitability across agricultural and forestry land use in Latvia. The profitability at the individual parcel level has been calculated, taking into account the characteristics of each plot and management practices. However, to ensure a clear and transparent spatial visualisation, the parcel-level resul...
Profitability_grid.gpkg Feb 10, 2026 - Dataset for comparing agricultural and forestry profitability at the parcel level Unknown - 15.0 MB - MD5: d19bc25342bfa7eb77285e5678a9cbc0 Parcel-level results in a single grid with 100-hectare cells
ReadMe_profitability_Latvia.txt Feb 10, 2026 - Dataset for comparing agricultural and forestry profitability at the parcel level Plain Text - 4.0 KB - MD5: 80bd2912047598b3f5d5b1d8601c4b0b ReadMe file with dataset description
Multispectral skin lesion images Feb 9, 2026 - Medical and Health Sciences Spigulis, Janis; Rubins, Uldis, 2026, "Multispectral skin lesion images", https://doi.org/10.71782/DATA/J0RMKK, DataverseLV, V1 This project aims at developing an advanced diagnostic methodology for fast grouping of whole-body detected skin malformations and identifying of dermal-invaded malignancies, including skin melanomas. The proposed method is based on combining the triple spectral line whole-body imaging at the visible spectral range with parallel imaging within a ne...
ReadMe-1.txt Feb 9, 2026 - Multispectral skin lesion images Plain Text - 2.2 KB - MD5: b549fe55c4a75a0d8759722184a38ca5
Skin Lesions.7z Feb 9, 2026 - Multispectral skin lesion images 7Z Archive - 56.5 MB - MD5: 8d08d88a272abe183d459a1992097c16 Spectral Images of various skin lesions
Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green DealEmbargoed Jan 26, 2026 - Social Sciences Muska, Aina; Pilvere, Irina; Muska, Kristaps; Nipers, Aleksejs, 2026, "Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green Deal", https://doi.org/10.71782/DATA/GATVHS, DataverseLV, V1, UNF:6:X3N1WKsN8DiHe0ORT+bgIg== [fileUNF] The contributions of EU Member States were assessed over two periods: (1) the progress period, defined as the change between the averages for 2012–2015 and 2016–2019; and (2) the target period, defined as the change between the averages for 2020–2024 and 2024–2027. During the progress period, the differentiation of Member States was based on two in...
description.pdf Jan 26, 2026 - Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green Deal Adobe PDF - 150.4 KB - MD5: 114e5331ed744dc7ba1df60e6faf6704 Description of indicators
progress_period.tabEmbargoed Jan 26, 2026 - Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green Deal Tabular Data - 741 B - 4 Variables, 27 Observations - UNF:6:z2GeW9lKajCDIvBUWr/xaw== Actual data - the change between the averages for 2012–2015 and 2016–2019
ReadMe.txt Jan 26, 2026 - Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green Deal Plain Text - 4.9 KB - MD5: bb42435dcad1a08009906da292f32de6 ReadMe file

Dataset for comparing agricultural and forestry profitability at the parcel level

Feb 10, 2026 - Social Sciences

Bilande, Kristine; Veipane, Una Diana; Nipers, Aleksejs; Pilvere, Irina, 2026, "Dataset for comparing agricultural and forestry profitability at the parcel level", https://doi.org/10.71782/DATA/KINURI, DataverseLV, V2

This study develops a spatial distribution of profitability across agricultural and forestry land use in Latvia. The profitability at the individual parcel level has been calculated, taking into account the characteristics of each plot and management practices. However, to ensure a clear and transparent spatial visualisation, the parcel-level resul...

Profitability_grid.gpkg

Feb 10, 2026 - Dataset for comparing agricultural and forestry profitability at the parcel level

Unknown - 15.0 MB -

Parcel-level results in a single grid with 100-hectare cells

ReadMe_profitability_Latvia.txt

Feb 10, 2026 - Dataset for comparing agricultural and forestry profitability at the parcel level

Plain Text - 4.0 KB -

ReadMe file with dataset description

Multispectral skin lesion images

Feb 9, 2026 - Medical and Health Sciences

Spigulis, Janis; Rubins, Uldis, 2026, "Multispectral skin lesion images", https://doi.org/10.71782/DATA/J0RMKK, DataverseLV, V1

This project aims at developing an advanced diagnostic methodology for fast grouping of whole-body detected skin malformations and identifying of dermal-invaded malignancies, including skin melanomas. The proposed method is based on combining the triple spectral line whole-body imaging at the visible spectral range with parallel imaging within a ne...

ReadMe-1.txt

Feb 9, 2026 - Multispectral skin lesion images

Plain Text - 2.2 KB -

Skin Lesions.7z

Feb 9, 2026 - Multispectral skin lesion images

7Z Archive - 56.5 MB -

Spectral Images of various skin lesions

Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green DealEmbargoed

Jan 26, 2026 - Social Sciences

Muska, Aina; Pilvere, Irina; Muska, Kristaps; Nipers, Aleksejs, 2026, "Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green Deal", https://doi.org/10.71782/DATA/GATVHS, DataverseLV, V1, UNF:6:X3N1WKsN8DiHe0ORT+bgIg== [fileUNF]

The contributions of EU Member States were assessed over two periods: (1) the progress period, defined as the change between the averages for 2012–2015 and 2016–2019; and (2) the target period, defined as the change between the averages for 2020–2024 and 2024–2027. During the progress period, the differentiation of Member States was based on two in...

description.pdf

Jan 26, 2026 - Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green Deal

Adobe PDF - 150.4 KB -

Description of indicators

progress_period.tabEmbargoed

Jan 26, 2026 - Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green Deal

Tabular Data - 741 B - 4 Variables, 27 Observations -

Actual data - the change between the averages for 2012–2015 and 2016–2019

ReadMe.txt

Jan 26, 2026 - Datasets for EU Member State Contribution to Reducing Agricultural Nutrient Losses under the European Green Deal

Plain Text - 4.9 KB -

ReadMe file

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