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The Dataverse portal of the International Center for Agricultural Research in Dry Ares (ICARDA) has been set up with the aim of making Findable, Accessible, Interoperable and Reusable (F.A.I.R.) the knowledge produced in research for development frameworks, joined by the Center and its partners. The portal is supported by the CGIAR Research Program on LIVESTOCK, the CGIAR Platform for BIGDATA in Agriculture, and is powered by CODEOBIA and hosted by Amazon Web Services (AWS). You may copy, distribute and transmit the data as long as you acknowledge the source through proper citation as shown below. You may not resale or use the data for any commercial purposes except with written permission from the respective authoring institution(s) and the author(s) concerned. By using the ICARDA Dataverse, the user expressly acknowledges that the data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. The user should always verify actual data.

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In accordance with scientific standards, all users of these data should make appropriate acknowledgement to the producer of the data as well as the distributor using bibliographic citation. Such citations will appear in footnotes or in the reference section of any such manuscript. The citation should use the citation standard documented in http://thedata.org/citation and as shown on the "Data Citation" section of the cataloguing information page for each dataverse study. ICARDA requests a copy of any material produced based on the data. This includes position papers, scientific reports, and graduate papers in addition to publications. All users of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the cataloguing information.

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4,251 to 4,260 of 4,467 Results
Sep 30, 2019 - Takhwsh Sub Watershed
Unknown - 252 B - MD5: b5aff8d32342991ba64218bc7f921a0c
Sep 30, 2019 - Big Data and ICT
Atassi, Layal; Biradar, Chandrashekhar, 2019, "Balkh Watershed Aspect", https://hdl.handle.net/20.500.11766.1/FK2/2YCRUR, MELDATA, V1
Balkh aspect was generated from digital terrain models (DTM) with 5 m resolution derived from DigitalGlobe imagery assets. The layer covers Balkh watershed. This layer is intended to be used in Afghanistan Electronic Atlas, as one of the surface characterization layers in Afghani...
Sep 30, 2019 - Balkh Watershed Aspect
TIFF Image - 40.8 MB - MD5: fdd656b024ec0624b25f06606342387f
Sep 30, 2019 - Balkh Watershed Aspect
JPEG Image - 8.0 MB - MD5: 54180000d159065ac120692d47a711ec
Sep 30, 2019 - Big Data and ICT
Atassi, Layal; Biradar, Chandrashekhar, 2019, "Balkh Watershed Slope", https://hdl.handle.net/20.500.11766.1/FK2/EOXOIZ, MELDATA, V1
Balkh slope was generated from digital terrain models (DTM) with 5 m resolution derived from DigitalGlobe imagery assets. The layer covers Balkh watershed. This layer is intended to be used in Afghanistan Electronic Atlas, as one of the surface characterization layers in Afghanis...
Sep 30, 2019 - Balkh Watershed Slope
TIFF Image - 40.3 MB - MD5: 4b8874906e9d5063e771b5fb5322f21a
Sep 30, 2019 - Balkh Watershed Slope
JPEG Image - 4.7 MB - MD5: 01358a2bc5d6bd72f419b20adf128d45
Sep 30, 2019 - Big Data and ICT
Atassi, Layal; Biradar, Chandrashekhar, 2019, "Takhwsh Watershed Aspect", https://hdl.handle.net/20.500.11766.1/FK2/HM04SV, MELDATA, V1
Takhwsh aspect was generated from digital terrain models (DTM) with 5 m resolution derived from DigitalGlobe imagery assets. The layer covers Takhwsh watershed. This layer is intended to be used in Afghanistan Electronic Atlas, as one of the surface characterization layers in Afg...
Sep 30, 2019 - Takhwsh Watershed Aspect
JPEG Image - 5.8 MB - MD5: f21fd01e21ccac52d9aae94620e61762
Sep 30, 2019 - Takhwsh Watershed Aspect
TIFF Image - 197.5 KB - MD5: 24c2b4e5a743c25dabdedd82ad0f8ff5
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