Estimating Local Agricultural GDP across the World:
Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may not adequately capture the local variation in the economic activities that is useful for analyzing local economic development patterns and the exposure to natural dis...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Washington, D.C
The World Bank
2022
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may not adequately capture the local variation in the economic activities that is useful for analyzing local economic development patterns and the exposure to natural disasters. Agriculture GDP is a critical indicator for measurement of the primary sector, on which 60 percent of the world's population depends for their livelihoods. Through a data fusion method based on cross-entropy optimization, this paper disaggregates national and subnational administrative statistics of Agricultural GDP into a global gridded dataset at approximately 10 * 10 kilometers using satellite-derived indicators of the components that make up agricultural GDP, namely crop, livestock, fishery, hunting and timber production. The paper examines the exposure of areas with at least one extreme drought during 2000 to 2009 to agricultural GDP, where nearly 1.2 billion people live. The findings show an estimated USD 432 billion of agricultural GDP circa 2010 |
| Beschreibung: | 1 Online-Ressource (43 Seiten) |
| DOI: | 10.1596/1813-9450-10109 |
Internformat
MARC
| LEADER | 00000nmm a22000001c 4500 | ||
|---|---|---|---|
| 001 | BV049080159 | ||
| 003 | DE-604 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 230731s2022 xxu|||| o||u| ||||||eng d | ||
| 024 | 7 | |a 10.1596/1813-9450-10109 |2 doi | |
| 035 | |a (ZDB-1-WBA)080816371 | ||
| 035 | |a (OCoLC)1392154379 | ||
| 035 | |a (DE-599)KEP080816371 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 044 | |a xxu |c XD-US | ||
| 049 | |a DE-12 |a DE-521 |a DE-573 |a DE-523 |a DE-Re13 |a DE-19 |a DE-355 |a DE-703 |a DE-91 |a DE-706 |a DE-29 |a DE-M347 |a DE-473 |a DE-824 |a DE-20 |a DE-739 |a DE-1043 |a DE-863 |a DE-862 | ||
| 100 | 1 | |a Blankespoor, Brian |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Estimating Local Agricultural GDP across the World |c Brian Blankespoor |
| 264 | 1 | |a Washington, D.C |b The World Bank |c 2022 | |
| 300 | |a 1 Online-Ressource (43 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 520 | 3 | |a Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may not adequately capture the local variation in the economic activities that is useful for analyzing local economic development patterns and the exposure to natural disasters. Agriculture GDP is a critical indicator for measurement of the primary sector, on which 60 percent of the world's population depends for their livelihoods. Through a data fusion method based on cross-entropy optimization, this paper disaggregates national and subnational administrative statistics of Agricultural GDP into a global gridded dataset at approximately 10 * 10 kilometers using satellite-derived indicators of the components that make up agricultural GDP, namely crop, livestock, fishery, hunting and timber production. The paper examines the exposure of areas with at least one extreme drought during 2000 to 2009 to agricultural GDP, where nearly 1.2 billion people live. The findings show an estimated USD 432 billion of agricultural GDP circa 2010 | |
| 650 | 4 | |a Agricultural Sector Economics | |
| 650 | 4 | |a Agriculture | |
| 650 | 4 | |a Crop Value | |
| 650 | 4 | |a Fishery Production | |
| 650 | 4 | |a Forestry Production | |
| 650 | 4 | |a Gross Domestic Product | |
| 650 | 4 | |a Hunting | |
| 650 | 4 | |a Livestock and Animal Husbandry | |
| 650 | 4 | |a Livestock Production | |
| 650 | 4 | |a Local Agriculture | |
| 650 | 4 | |a Macroeconomics and Economic Growth | |
| 650 | 4 | |a Natural Hazards | |
| 650 | 4 | |a Night Time Lights | |
| 650 | 4 | |a Spatial Allocation Model | |
| 650 | 4 | |a Statistics | |
| 700 | 1 | |a Kalvelagen, Erwin |e Sonstige |4 oth | |
| 700 | 1 | |a Ru, Yating |e Sonstige |4 oth | |
| 700 | 1 | |a Thomas, Timothy S. |e Sonstige |4 oth | |
| 700 | 1 | |a Wood-Sichra, Ulrike |e Sonstige |4 oth | |
| 700 | 1 | |a You, Liangzhi |e Sonstige |4 oth | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |a Blankespoor, Brian |t Estimating Local Agricultural GDP across the World |d Washington, D.C. : The World Bank, 2022 |
| 856 | 4 | 0 | |u https://doi.org/10.1596/1813-9450-10109 |x Verlag |z kostenfrei |3 Volltext |
| 912 | |a ZDB-1-WBA | ||
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-034342049 | |
Datensatz im Suchindex
| _version_ | 1812671838870831104 |
|---|---|
| adam_text | |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Blankespoor, Brian |
| author_facet | Blankespoor, Brian |
| author_role | aut |
| author_sort | Blankespoor, Brian |
| author_variant | b b bb |
| building | Verbundindex |
| bvnumber | BV049080159 |
| collection | ZDB-1-WBA |
| ctrlnum | (ZDB-1-WBA)080816371 (OCoLC)1392154379 (DE-599)KEP080816371 |
| discipline | Wirtschaftswissenschaften |
| discipline_str_mv | Wirtschaftswissenschaften |
| doi_str_mv | 10.1596/1813-9450-10109 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nmm a22000001c 4500</leader><controlfield tag="001">BV049080159</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">230731s2022 xxu|||| o||u| ||||||eng d</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1596/1813-9450-10109</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-1-WBA)080816371</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1392154379</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)KEP080816371</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="044" ind1=" " ind2=" "><subfield code="a">xxu</subfield><subfield code="c">XD-US</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-12</subfield><subfield code="a">DE-521</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-523</subfield><subfield code="a">DE-Re13</subfield><subfield code="a">DE-19</subfield><subfield code="a">DE-355</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-29</subfield><subfield code="a">DE-M347</subfield><subfield code="a">DE-473</subfield><subfield code="a">DE-824</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-739</subfield><subfield code="a">DE-1043</subfield><subfield code="a">DE-863</subfield><subfield code="a">DE-862</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Blankespoor, Brian</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Estimating Local Agricultural GDP across the World</subfield><subfield code="c">Brian Blankespoor</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Washington, D.C</subfield><subfield code="b">The World Bank</subfield><subfield code="c">2022</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (43 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">Economic statistics are frequently produced at an administrative level such as the sub-national division. However, these measures may not adequately capture the local variation in the economic activities that is useful for analyzing local economic development patterns and the exposure to natural disasters. Agriculture GDP is a critical indicator for measurement of the primary sector, on which 60 percent of the world's population depends for their livelihoods. Through a data fusion method based on cross-entropy optimization, this paper disaggregates national and subnational administrative statistics of Agricultural GDP into a global gridded dataset at approximately 10 * 10 kilometers using satellite-derived indicators of the components that make up agricultural GDP, namely crop, livestock, fishery, hunting and timber production. The paper examines the exposure of areas with at least one extreme drought during 2000 to 2009 to agricultural GDP, where nearly 1.2 billion people live. The findings show an estimated USD 432 billion of agricultural GDP circa 2010</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Agricultural Sector Economics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Agriculture</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Crop Value</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Fishery Production</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Forestry Production</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Gross Domestic Product</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Hunting</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Livestock and Animal Husbandry</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Livestock Production</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Local Agriculture</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Macroeconomics and Economic Growth</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Natural Hazards</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Night Time Lights</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Spatial Allocation Model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Kalvelagen, Erwin</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Ru, Yating</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Thomas, Timothy S.</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Wood-Sichra, Ulrike</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">You, Liangzhi</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="a">Blankespoor, Brian</subfield><subfield code="t">Estimating Local Agricultural GDP across the World</subfield><subfield code="d">Washington, D.C. : The World Bank, 2022</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1596/1813-9450-10109</subfield><subfield code="x">Verlag</subfield><subfield code="z">kostenfrei</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-1-WBA</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-034342049</subfield></datafield></record></collection> |
| id | DE-604.BV049080159 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T22:27:57Z |
| indexdate | 2024-10-12T04:02:56Z |
| institution | BVB |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034342049 |
| oclc_num | 1392154379 |
| open_access_boolean | 1 |
| owner | DE-12 DE-521 DE-573 DE-523 DE-Re13 DE-BY-UBR DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-703 DE-91 DE-BY-TUM DE-706 DE-29 DE-M347 DE-473 DE-BY-UBG DE-824 DE-20 DE-739 DE-1043 DE-863 DE-BY-FWS DE-862 DE-BY-FWS |
| owner_facet | DE-12 DE-521 DE-573 DE-523 DE-Re13 DE-BY-UBR DE-19 DE-BY-UBM DE-355 DE-BY-UBR DE-703 DE-91 DE-BY-TUM DE-706 DE-29 DE-M347 DE-473 DE-BY-UBG DE-824 DE-20 DE-739 DE-1043 DE-863 DE-BY-FWS DE-862 DE-BY-FWS |
| physical | 1 Online-Ressource (43 Seiten) |
| psigel | ZDB-1-WBA |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | The World Bank |
| record_format | marc |
| spellingShingle | Blankespoor, Brian Estimating Local Agricultural GDP across the World Agricultural Sector Economics Agriculture Crop Value Fishery Production Forestry Production Gross Domestic Product Hunting Livestock and Animal Husbandry Livestock Production Local Agriculture Macroeconomics and Economic Growth Natural Hazards Night Time Lights Spatial Allocation Model Statistics |
| title | Estimating Local Agricultural GDP across the World |
| title_auth | Estimating Local Agricultural GDP across the World |
| title_exact_search | Estimating Local Agricultural GDP across the World |
| title_exact_search_txtP | Estimating Local Agricultural GDP across the World |
| title_full | Estimating Local Agricultural GDP across the World Brian Blankespoor |
| title_fullStr | Estimating Local Agricultural GDP across the World Brian Blankespoor |
| title_full_unstemmed | Estimating Local Agricultural GDP across the World Brian Blankespoor |
| title_short | Estimating Local Agricultural GDP across the World |
| title_sort | estimating local agricultural gdp across the world |
| topic | Agricultural Sector Economics Agriculture Crop Value Fishery Production Forestry Production Gross Domestic Product Hunting Livestock and Animal Husbandry Livestock Production Local Agriculture Macroeconomics and Economic Growth Natural Hazards Night Time Lights Spatial Allocation Model Statistics |
| topic_facet | Agricultural Sector Economics Agriculture Crop Value Fishery Production Forestry Production Gross Domestic Product Hunting Livestock and Animal Husbandry Livestock Production Local Agriculture Macroeconomics and Economic Growth Natural Hazards Night Time Lights Spatial Allocation Model Statistics |
| url | https://doi.org/10.1596/1813-9450-10109 |
| work_keys_str_mv | AT blankespoorbrian estimatinglocalagriculturalgdpacrosstheworld AT kalvelagenerwin estimatinglocalagriculturalgdpacrosstheworld AT ruyating estimatinglocalagriculturalgdpacrosstheworld AT thomastimothys estimatinglocalagriculturalgdpacrosstheworld AT woodsichraulrike estimatinglocalagriculturalgdpacrosstheworld AT youliangzhi estimatinglocalagriculturalgdpacrosstheworld |