The Normalized Difference Water Index (NDWI) is sensitive to changes in liquid water content of vegetation canopies. It is derived from the Near-IR band and a second IR band, ≈1.24μm when available and the nearest available IR band otherwise. It ranges in value from -1.0 to 1.0. See Gao (1996) for details. This product is generated from the MODIS/006/MCD43A4 surface reflectance composites.

The Normalized Difference Water Index (NDWI) is sensitive to changes in liquid water content of vegetation canopies. It is derived from the Near-IR band and a second IR band, ≈1.24μm when available and the nearest available IR band otherwise. It ranges in value from -1.0 to 1.0. See Gao (1996) for details. This product is generated from the MODIS/006/MYD09GA surface reflectance composites.

Normalized Difference Water Index (NDWI) from MODIS data for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023). Source data: - MODIS/Terra Surface Reflectance 8-Day L3 Global 500 m SIN Grid (MOD09A1 v061): https://lpdaac.usgs.gov/products/mod09a1v061/ The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra MOD09A1 Version 6.1 product provides an estimate of the surface spectral reflectance of Terra MODIS Bands 1 through 7 corrected for atmospheric conditions such as gasses, aerosols, and Rayleigh scattering. Along with the seven 500 meter (m) reflectance bands are two quality layers and four observation bands. For each pixel, a value is selected from all the acquisitions within the 8-day composite period. The criteria for the pixel choice include cloud and solar zenith. When several acquisitions meet the criteria the pixel with the minimum channel 3 (blue) value is used. For the time period January 2019 - December 2023, the NDWI has been calculated from the Terra MOD09A1 Version 6.1 product. The layers B02 (near infrared) and B06 (shortwave infrared) of the original data have been processed. Bad quality pixels or pixels with snow/ice and/or cloud cover have been masked using the provided quality assurance (QA) layer. The time series has been gapfilled with a temporal and a spatial approach. Gaps in the time series were filled with a harmonic analysis of time series using six frequencies to also model relatively short-term changes in NDWI. Only missing values were replaced by modelled values. NDWI was calculated as the normalized difference of the bands B02 (near infrared) and B06 (shortwave infrared) with: NDWI = (B02 – B06) / (B02 + B06). This NDWI represents vegetation water content. The 8-day data are then aggregated to monthly temporal resolution using the average and reprojected to Latitude-Longitude/WGS84. File naming: ndwi_monthly_YYYY_MM_30arcsec.tif e.g.: ndwi_monthly_2023_12_30arcsec.tif The date within the filename are year and month of aggregated timestamp. Pixel values: Raster values are in the range [0, 2000]. Real NDWI in the range [-1, 1] can be retrieved with: NDWI = raster_value * 0.001 - 1. Projection + EPSG code: Latitude-Longitude/WGS84 (EPSG: 4326) Spatial extent: north: 28N south: 14N west: 18W east: 4W Temporal extent: January 2019 - December 2023 Spatial resolution: 30 arc seconds (approx. 1000 m) Temporal resolution: monthly Software used: GRASS GIS 8.3.2 Format: GeoTIFF Original dataset license: All data products distributed by NASA's Land Processes Distributed Active Archive Center (LP DAAC) are available at no charge. The LP DAAC requests that any author using NASA data products in their work provide credit for the data, and any assistance provided by the LP DAAC, in the data section of the paper, the acknowledgement section, and/or as a reference. The recommended citation for each data product is available on its Digital Object Identifier (DOI) Landing page, which can be accessed through the Search Data Catalog interface. For more information see: https://lpdaac.usgs.gov/products/mod13a2v061/ Processed by: mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/) Contact: mundialis GmbH & Co. KG, info@mundialis.de Acknowledgements: This study was partially funded by EU grant 874850 MOOD. The contents of this publication are the sole responsibility of the authors and don't necessarily reflect the views of the European Commission.

L'indice NDWI (Normalized Difference Water Index) est sensible aux variations de la teneur en eau liquide des canopées végétales. Il est dérivé de la bande proche infrarouge et d'une deuxième bande infrarouge, ≈1,24 μm lorsqu'elle est disponible, et de la bande infrarouge la plus proche dans le cas contraire. Sa valeur est comprise entre -1,0 et 1,0. Voir Gao (1996) …

Normalized Difference Water Index (NDWI) calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the ndwi was calculated.

The Normalized Difference Water Index (NDWI) (Gao, 1996) is a satellite-derived index from the Near-Infrared (NIR) and Short Wave Infrared (SWIR) channels. Its usefulness for drought monitoring and early warning has been demonstrated in different studies (e.g., Gu et al., 2007; Ceccato et al., 2002). It is computed using the near infrared (NIR) and the short wave infrared (SWIR) reflectance, which makes it sensitive to changes in liquid water content and in spongy mesophyll of vegetation canopies (Gao, 1996 ; Ceccato et al., 2001).

https://edo.jrc.ec.europa.eu/documents/factsheets/factsheet_ndwi.pdf

Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description.

spatial resolution: 463.313m format: GeoTiff reference system:SR-ORG 6842

To easily manage the data, each file follow name structure:

YYYYMMDD_medgold_workpackage_AoI_sensor_index.

YYYYMMDD: Imagery acquisition date

medgold: Project name

sensor: sensor name

workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector)

Aoi: Andalusia, Douro Valley.

Index: NDVI, NMDI, NDWI

Example:

20000218_medgold_wp2_andalusia_MOD09A1_ndwi

O Índice de Água por Diferença Normalizada (NDWI, na sigla em inglês) é sensível a mudanças no conteúdo de água líquida das copas das árvores. Ele é derivado da banda do infravermelho próximo e de uma segunda banda de infravermelho, ≈1,24 μm quando disponível e a banda de infravermelho disponível mais próxima caso contrário. O valor varia de -1,0 a 1,0. Consulte Gao (1996) para mais detalhes. Esse produto é gerado com base nos compostos de refletância da superfície MODIS/006/MYD09GA.

Normalized Difference Water Index (NDWI) calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the ndwi was calculated.

The Normalized Difference Water Index (NDWI) (Gao, 1996) is a satellite-derived index from the Near-Infrared (NIR) and Short Wave Infrared (SWIR) channels. Its usefulness for drought monitoring and early warning has been demonstrated in different studies (e.g., Gu et al., 2007; Ceccato et al., 2002). It is computed using the near infrared (NIR) and the short wave infrared (SWIR) reflectance, which makes it sensitive to changes in liquid water content and in spongy mesophyll of vegetation canopies (Gao, 1996 ; Ceccato et al., 2001).

https://edo.jrc.ec.europa.eu/documents/factsheets/factsheet_ndwi.pdf

Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description.

spatial resolution: 463.313m format: GeoTiff reference system:SR-ORG 6842

To easily manage the data, each file follow name structure:

YYYYMMDD_medgold_workpackage_AoI_sensor_index.

YYYYMMDD: Imagery acquisition date

medgold: Project name

sensor: sensor name

workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector)

Aoi: Andalusia, Douro Valley.

Index: NDVI, NMDI, NDWI

Example:

20000218_medgold_wp3_douro_MOD09A1_ndwi

Normalized Difference Water Index (NDWI) sensitif terhadap perubahan kandungan air cair pada tajuk vegetasi. Nilai ini berasal dari band IR Dekat dan band IR kedua, ≈1,24 μm jika tersedia dan band IR terdekat yang tersedia jika tidak. Nilainya berkisar dari -1,0 hingga 1,0. Lihat Gao (1996) untuk mengetahui detailnya. Produk ini dibuat dari komposit reflektansi permukaan MODIS/006/MOD09GA.

This is version 2 of quality checked and gap-filled daily MODIS observations of surface reflectance and land surface temperature at global eddy co-variance sites for the time period 2000-2022. Two product versions: one features all MODIS pixels within 2km radius around a given site, and a second version consists of an average time series that represents the area within 1km2 around a site. All data layers have a complementary layer with gap-fill information. MODIS data comprise 647 eddy covariance sites (see a detailed list in the README of version 2). FluxnetEO v2 MODIS reflectance products: enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), generalized NDVI (kNDVI), near infra-red reflectance of vegetation (NIRv), normalized difference water index (NDWI) with band 5, 6, or 7 as reference, the scaled wide dynamic range vegetation index (sWDRVI), surface reflectance in MODIS bands 1-7. Based on the NASA MCD43A4 and MCD43A2 collection 6 products with a pixel size of 500m. FluxnetEO v2 MODIS land surface temperature: Terra and Aqua, day and night, at native viewing zenith angle as well as corrected to viewing zenith angles of 0 and 40degrees (Ermida et al., 2018, RS, https://www.mdpi.com/2072-4292/10/7/1114). Based on NASA MOD11A1 and MYD11A1 collection 6 at a pixel size of 1km. This is version 2 of the data described in Walther* & Besnard* et al. 2022. A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset, Biogeosciences, https://doi.org/10.5194/bg-19-2805-2022. Please refer to the README of version2 to understand the details of the updates between version1 (described in the paper) and version2. The data are separated in zip-files by continents and groups of countries. ZIP archive of netcdf files for stations in Americas: US-Men, US-Mj1, US-Mj2, US-Mpj, US-Myb, US-NC1, US-NC2, US-NC3, US-NC4, US-NGB, US-NGC, US-NMj, US-NOG, US-NR1, US-NR2, US-Ne1, US-Ne2, US-Ne3, US-Nrf, US-Nrs, US-OF1, US-OF2, US-ONA, US-ORv, US-OSB, US-OWC, US-Oho, US-PFa, US-PHM, US-PLM, US-Pnp, US-Pon, US-Prr, US-RFE, US-RFW, US-RRC, US-Rls, US-Rms, US-Ro1, US-Ro2, US-Ro3, US-Ro4, US-Ro5, US-Ro6, US-Rwe, US-Rwf, US-Rws, US-SB1, US-SB2, US-SCc, US-SCd, US-SCf, US-SCg, US-SCs, US-SCw, US-SDU, US-SER, US-SFP, US-SHC, US-SHS, US-SJ1, US-SJ2, US-SO2, US-SO3, US-SO4, US-SP1, US-SP2, US-SP3, US-SP4, US-SRC, US-SRE, US-SRG, US-SRM, US-SSH, US-SdH, US-Seg, US-Ses, US-Shd, US-Skr, US-Slt, US-Snd, US-Sne, US-Snf, US-Srr, US-StJ, US-StS, US-Sta Nelson, J., Walther, S., Weber, U. (2023). The FluxnetEO dataset (MODIS) for American stations located in United States (2), 2000-01-01–2022-12-30, https://hdl.handle.net/11676/FYxwSpDKveXLmD7vhJD0Xchy

Normalized Difference Vegetation Index (NDVI) calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the ndvi was calculated.

NDVI quantifies vegetation by measuring the difference between near-infrared and red light (which vegetation absorbs). NDVI is a standardized way to measure healthy vegetation. High NDVI values indicates healthy vegetation.

Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description.

spatial resolution: 463.313m format: GeoTiff reference system:SR-ORG 6842

To easily manage the data, each file follow name structure:

YYYYMMDD_medgold_workpackage_AoI_sensor_index.

YYYYMMDD: Imagery acquisition date

medgold: Project name

sensor: sensor name

workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector)

Aoi: Andalusia, Douro Valley.

Index: NDVI, NMDI, NDWI

Example:

20000218_medgold_wpe_douro_MOD09A1_ndvi

This is version 2 of quality checked and gap-filled daily MODIS observations of surface reflectance and land surface temperature at global eddy co-variance sites for the time period 2000-2022. Two product versions: one features all MODIS pixels within 2km radius around a given site, and a second version consists of an average time series that represents the area within 1km2 around a site. All data layers have a complementary layer with gap-fill information. MODIS data comprise 647 eddy covariance sites (see a detailed list in the README of version 2). FluxnetEO v2 MODIS reflectance products: enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), generalized NDVI (kNDVI), near infra-red reflectance of vegetation (NIRv), normalized difference water index (NDWI) with band 5, 6, or 7 as reference, the scaled wide dynamic range vegetation index (sWDRVI), surface reflectance in MODIS bands 1-7. Based on the NASA MCD43A4 and MCD43A2 collection 6 products with a pixel size of 500m. FluxnetEO v2 MODIS land surface temperature: Terra and Aqua, day and night, at native viewing zenith angle as well as corrected to viewing zenith angles of 0 and 40degrees (Ermida et al., 2018, RS, https://www.mdpi.com/2072-4292/10/7/1114). Based on NASA MOD11A1 and MYD11A1 collection 6 at a pixel size of 1km. This is version 2 of the data described in Walther & Besnard et al. 2022. A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset, Biogeosciences, https://doi.org/10.5194/bg-19-2805-2022. Please refer to the README of version2 to understand the details of the updates between version1 (described in the paper) and version2: https://meta.icos-cp.eu/objects/j9fusMYfwG3-3oLrutSe4f8t

This dataset comprises phenological observations (peak flight period) of five moth species (Orthosia gothica, Ectropis crepuscularia, Cabera exanthemata, Dysstroma citrata and Operophtera brumata) collected through the Finnish moth monitoring scheme in 1993-2012. In addition the dataset includes several temperature-derived and remote sensing variables used modelling phenological patterns of the moth species. Temperature-derived variables include an index of weekly accumulating growing degree days (GDD) for each species. Remote sensing variables include (1) snow melt date derived from MODIS data, (2) vegetation greening date based on Normalized Difference Water Index (NDWI) derived from MODIS data, and (3) dates of start (FSGS), maximum (FMD) and end (ESGS) of growing season based on the Joint Research Centre (JRC) Fraction of Absorbed Photosyntically Active Radiation (FAPAR) products.

This is version 2 of quality checked and gap-filled daily MODIS observations of surface reflectance and land surface temperature at global eddy co-variance sites for the time period 2000-2022. Two product versions: one features all MODIS pixels within 2km radius around a given site, and a second version consists of an average time series that represents the area within 1km2 around a site. All data layers have a complementary layer with gap-fill information. MODIS data comprise 647 eddy covariance sites (see a detailed list in the README of version 2). FluxnetEO v2 MODIS reflectance products: enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), generalized NDVI (kNDVI), near infra-red reflectance of vegetation (NIRv), normalized difference water index (NDWI) with band 5, 6, or 7 as reference, the scaled wide dynamic range vegetation index (sWDRVI), surface reflectance in MODIS bands 1-7. Based on the NASA MCD43A4 and MCD43A2 collection 6 products with a pixel size of 500m. FluxnetEO v2 MODIS land surface temperature: Terra and Aqua, day and night, at native viewing zenith angle as well as corrected to viewing zenith angles of 0 and 40degrees (Ermida et al., 2018, RS, https://www.mdpi.com/2072-4292/10/7/1114). Based on NASA MOD11A1 and MYD11A1 collection 6 at a pixel size of 1km. This is version 2 of the data described in Walther* & Besnard* et al. 2022. A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset, Biogeosciences, https://doi.org/10.5194/bg-19-2805-2022. Please refer to the README of version2 to understand the details of the updates between version1 (described in the paper) and version2. The data are separated in zip-files by continents and groups of countries. ZIP archive of netcdf files for stations in Europe: DE-Akm, DE-Bay, DE-Fen, DE-Geb, DE-Gri, DE-GsB, DE-Gwg, DE-Hai, DE-Har, DE-HoH, DE-Hte, DE-Hzd, DE-Kli, DE-Lkb, DE-Lnf, DE-Meh, DE-Obe, DE-RuR, DE-RuS, DE-RuW, DE-Seh, DE-SfN, DE-Spw, DE-Tha, DE-Wet, DE-Zrk Nelson, J., Walther, S., Weber, U. (2023). The FluxnetEO dataset (MODIS) for European stations located in Germany, 2000-01-01–2022-12-30, https://hdl.handle.net/11676/jWVxI35I_zdduuXVLyaPh81u

Quality checked and gap-filled daily MODIS observations of surface reflectance and land surface temperature at global eddy co-variance sites for the time period 2000-2020. Two product versions: one features all MODIS pixels within 2km radius around a given site, and a second version consists of an average time series that represents the area within 1km2 around a site. All data layers have a complementary layer with gap-fill information. MODIS data comprise all sites in the Fluxnet La Thuile, Berkeley and ICOS Drought 2018 data releases. FluxnetEO MODIS reflectance products: enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), generalized NDVI (kNDVI), near infra-red reflectance of vegetation (NIRv), normalized difference water index (NDWI) with band 5, 6, or 7 as reference, the scaled wide dynamic range vegetation index (sWDRVI), surface reflectance in MODIS bands 1-7. Based on the NASA MCD43A4 and MCD43A2 collection 6 products with a pixel size of 500m. FluxnetEO MODIS land surface temperature: Terra and Aqua, day and night, at native viewing zenith angle as well as corrected to viewing zenith angles of 0 and 40degrees (Ermida et al., 2018, RSE). Based on NASA MOD11A1 and MYD11A1 collection 6 at a pixel size of 1km. Supplementary data to Walther, S., Besnard, S., Nelson, J.A., El-Madany, T. S., Migliavacca, M., Weber, U., Ermida, S. L., Brümmer, C., Schrader, F., Prokushkin, A., Panov, A., Jung, M. , 2021. A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset, in preparation for Biogeosciences Discussions. The data are separated in zip-files by continents and groups of countries.

يُعدّ "مؤشر الاختلاف القياسي للمياه" (NDWI) حساسًا للتغيّرات في محتوى المياه السائلة في مظلات الغطاء النباتي. ويتم اشتقاقها من النطاق القريب من الأشعة تحت الحمراء ونطاق ثانٍ من الأشعة تحت الحمراء، ويبلغ طوله الموجي 1.24 ميكرومتر تقريبًا عند توفّره، أو يتم استخدام أقرب نطاق متوفّر من الأشعة تحت الحمراء. وتتراوح قيمتها بين -1.0 و1.0. يمكنك الاطّلاع على Gao (1996) للحصول على التفاصيل. يتم إنشاء هذا المنتج من مركّبات انعكاس السطح MODIS/006/MOD09GA.

This is version 2 of quality checked and gap-filled daily MODIS observations of surface reflectance and land surface temperature at global eddy co-variance sites for the time period 2000-2022. Two product versions: one features all MODIS pixels within 2km radius around a given site, and a second version consists of an average time series that represents the area within 1km2 around a site. All data layers have a complementary layer with gap-fill information. MODIS data comprise 647 eddy covariance sites (see a detailed list in the README of version 2). FluxnetEO v2 MODIS reflectance products: enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), generalized NDVI (kNDVI), near infra-red reflectance of vegetation (NIRv), normalized difference water index (NDWI) with band 5, 6, or 7 as reference, the scaled wide dynamic range vegetation index (sWDRVI), surface reflectance in MODIS bands 1-7. Based on the NASA MCD43A4 and MCD43A2 collection 6 products with a pixel size of 500m. FluxnetEO v2 MODIS land surface temperature: Terra and Aqua, day and night, at native viewing zenith angle as well as corrected to viewing zenith angles of 0 and 40degrees (Ermida et al., 2018, RS, https://www.mdpi.com/2072-4292/10/7/1114). Based on NASA MOD11A1 and MYD11A1 collection 6 at a pixel size of 1km. This is version 2 of the data described in Walther* & Besnard* et al. 2022. A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset, Biogeosciences, https://doi.org/10.5194/bg-19-2805-2022. Please refer to the README of version2 to understand the details of the updates between version1 (described in the paper) and version2. The data are separated in zip-files by continents and groups of countries. ZIP archive of netcdf files for stations in Europe: AT-Neu, BE-Bra, BE-Dor, BE-Jal, BE-Lcr, BE-Lon, BE-Maa, BE-Vie, CH-Aws, CH-Cha, CH-Dav, CH-Fru, CH-Lae, CH-Oe1, CH-Oe2, CZ-BK1, CZ-BK2, CZ-KrP, CZ-Lnz, CZ-RAJ, CZ-Stn, CZ-wet, DK-Eng, DK-Fou, DK-Gds, DK-Lva, DK-NuF, DK-RCW, DK-Ris, DK-Skj, DK-Sor, DK-Vng, DK-ZaF, DK-ZaH, HU-Bug, HU-Mat, IE-Ca1, IE-Cra, IE-Dri, IS-Gun Nelson, J., Walther, S., Weber, U. (2023). The FluxnetEO dataset (MODIS) for European stations located in Austria, Belgium, Switzerland, Czechia, Denmark, Hungary, Ireland, and Iceland, 2000-01-01–2022-12-30, https://hdl.handle.net/11676/FE89EVf8g-ZGoD41nbqUYXga

يُعدّ "مؤشر الاختلاف القياسي للمياه" (NDWI) حساسًا للتغيّرات في محتوى المياه السائلة في مظلات الغطاء النباتي. ويتم اشتقاقها من النطاق القريب من الأشعة تحت الحمراء ونطاق ثانٍ من الأشعة تحت الحمراء، ويبلغ طوله الموجي 1.24 ميكرومتر تقريبًا عند توفّره، أو يتم استخدام أقرب نطاق متوفّر من الأشعة تحت الحمراء. وتتراوح قيمتها بين -1.0 و1.0. يمكنك الاطّلاع على Gao (1996) للحصول على التفاصيل. يتم إنشاء هذا المنتج من مركّبات انعكاس السطح MODIS/006/MYD09GA.

Normalized Multi-band Drought Index (NMDI) calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the nmdi was calculated.

NMDI uses the 860 nm channel as the reference; instead of using a single liquid water absorption channel, however, it uses the difference between two liquid water absorption channels centered at 1640 nm and 2130 nm as the soil and vegetation moisture sensitive band. Analysis revealed that by combining information from multiple near infrared, and short wave infrared channels, NMDI has enhanced the sensitivity to drought severity, and is well suited to estimate both soil and vegetation moisture.( Lingli Wang, 2007)

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007GL031021

Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description.

spatial resolution: 463.313m format: GeoTiff reference system:SR-ORG 6842

To easily manage the data, each file follow name structure:

YYYYMMDD_medgold_workpackage_AoI_sensor_index.

YYYYMMDD: Imagery acquisition date

medgold: Project name

sensor: sensor name

workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector)

Aoi: Andalusia, Douro Valley.

Index: NDVI, NMDI, NDWI

Example:

20000218_medgold_wp3_douro_MOD09A1_nmdi

归一化差异水指数(NDWI) 对植被冠层液态水含量的变化非常敏感。它源自近红外波段和第二个红外波段，如果第二个红外波段可用，则为≈1.24μm，否则为最近的可用红外波段。其值范围为-1.0 到 1.0。如需了解详情，请参阅Gao (1996)。此产品基于MODIS/006/MYD09GA 地表反射率合成数据生成。

Normalized Multi-band Drought Index (NMDI) was calculated using MODIS09 imagery provided by USGS/EROS.The original MODIS09 bands were used as data source and then the nmdi was calculated.

NMDI uses the 860 nm channel as the reference; instead of using a single liquid water absorption channel, however, it uses the difference between two liquid water absorption channels centered at 1640 nm and 2130 nm as the soil and vegetation moisture sensitive band. Analysis revealed that by combining information from multiple near infrared, and short wave infrared channels, NMDI has enhanced the sensitivity to drought severity, and is well suited to estimate both soil and vegetation moisture.(Lingli Wang, 2007)

https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2007GL031021

Each compressed file contains the NDVI by years. Internally each file have an ISO TC 211 metadata with a complete geographical description.

spatial resolution: 463.313m
format: GeoTiff
reference system:SR-ORG 6842

To easily manage the data, each file follow name structure:

YYYYMMDD_medgold_workpackage_AoI_sensor_index.

YYYYMMDD: Imagery acquisition date

medgold: Project name

sensor: sensor name

workpackage: sectorial workpackage name ( WP2 - Olive Oil Sector, WP3 – Wine Grape sector, WP4- Durum wheat pasta sector)

Aoi: Andalusia, Douro Valley.

Index: NDVI, NMDI, NDWI

Example:

20000218_medgold_wp2_andalusia_MOD09A1_nmdi