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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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While utmost care has been taken by ICARDA and data authors when collecting and compiling the data, the data is however offered "as is" with no express or implied warranty. In no event shall the data authors, the authoring institutions be liable for any actual, incidental or consequential damages arising from use of the data.

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4,241 to 4,250 of 4,467 Results
Sep 30, 2019 - Balkh Sub Watershed
Unknown - 1.2 MB - MD5: 62f770aaa79f62d311f985c73b0c13af
Sep 30, 2019 - Balkh Sub Watershed
Unknown - 268 B - MD5: 49ce07710d52573a087569c40c38818a
Sep 30, 2019 - Balkh Sub Watershed
JPEG Image - 4.7 MB - MD5: e830dfba7b998d89bfa648f172b5b50f
Sep 30, 2019 - Big Data and ICT
Atassi, Layal; Biradar, Chandrashekhar, 2019, "Takhwsh Sub Watershed", https://hdl.handle.net/20.500.11766.1/FK2/IEQMCM, MELDATA, V1
Takhwsh sub watershed 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 the Afghanistan Electronic Atlas, as one of the surface characterization in...
Sep 30, 2019 - Takhwsh Sub Watershed
Unknown - 5 B - MD5: ae3b3df9970b49b6523e608759bc957d
Sep 30, 2019 - Takhwsh Sub Watershed
Unknown - 7.3 KB - MD5: ebd80914a8079cc8b04405a505dfe5dd
Sep 30, 2019 - Takhwsh Sub Watershed
JPEG Image - 5.0 MB - MD5: b421b064fbcbc370cf791ca2414c1ebf
Sep 30, 2019 - Takhwsh Sub Watershed
Unknown - 145 B - MD5: c742bee3d4edfc2948a2ad08de1790a5
Sep 30, 2019 - Takhwsh Sub Watershed
Unknown - 132 B - MD5: 9b6736e682ee0487da69c822bf351054
Sep 30, 2019 - Takhwsh Sub Watershed
Unknown - 52.4 KB - MD5: ddf46842f2066a931054d9515d686841
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