Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, México
Agricultural transformations have significantly contributed to the global market’s year-round supply of capital-intensive greenhouse-grown crops. For instance, berry production in México is increasingly relying on greenhouse systems to meet the growing demand of international markets, particularly i...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2022-01-01
|
| Series: | Environmental Research Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1748-9326/ac9ac8 |
| _version_ | 1797747293176201216 |
|---|---|
| author | Sarah Hartman Michelle Farfán Jaime Hoogesteger Paolo D’Odorico |
| author_facet | Sarah Hartman Michelle Farfán Jaime Hoogesteger Paolo D’Odorico |
| author_sort | Sarah Hartman |
| collection | DOAJ |
| description | Agricultural transformations have significantly contributed to the global market’s year-round supply of capital-intensive greenhouse-grown crops. For instance, berry production in México is increasingly relying on greenhouse systems to meet the growing demand of international markets, particularly in the USA. It is still unclear to what extent these transformations are related to land tenure, as data on greenhouse distribution often do not exist, are incomplete, or lack spatial resolution. This paper presents a support vector machine learning algorithm tool to map greenhouse expansion using satellite images. The tool is applied to the major berry-growing region of Michoacán, México. Here agricultural areas are transforming to satisfy foreign demand for berries, altering local land and water resource use patterns. We use this tool and a unique land tenure dataset to investigate (a) the spatially explicit extent to which high-input commercial agriculture (mainly the production of berries) has expanded in this region since 1989; and (b) the extent to which smallholder ( ejidal ) land has been incorporated into the highly capitalized agro-export sector. We combine a national dataset on ejidal land (which includes both communal and parcel land) with geospatial agricultural data to quantify the land-use changes in six municipalities in the berry-growing region of Michoacán between 1989 and 2021. We find that the development of the greenhouse berry boom can be quantified and shown with spatially-explicit detail, growing from zero to over 9,500 ha over the period, using almost one-quarter of all regional agricultural land in 2020. We further find that the capital-intensive market-oriented berry industry has been widely integrated into smallholder ejidal lands, so much so that over half of greenhouses are found there. |
| first_indexed | 2024-03-12T15:48:40Z |
| format | Article |
| id | doaj.art-2784e49eead2462c9b17c8e986e4dd99 |
| institution | Directory Open Access Journal |
| issn | 1748-9326 |
| language | English |
| last_indexed | 2024-03-12T15:48:40Z |
| publishDate | 2022-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Letters |
| spelling | doaj.art-2784e49eead2462c9b17c8e986e4dd992023-08-09T15:18:04ZengIOP PublishingEnvironmental Research Letters1748-93262022-01-01171111500410.1088/1748-9326/ac9ac8Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, MéxicoSarah Hartman0https://orcid.org/0000-0002-2427-8440Michelle Farfán1https://orcid.org/0000-0002-4948-1453Jaime Hoogesteger2https://orcid.org/0000-0002-6784-0552Paolo D’Odorico3https://orcid.org/0000-0002-0007-5833University of California Berkeley, Environmental Science, Policy, and Management , Berkeley, CA, United States of AmericaUniversidad de Guanajuato, Geomatics and Hydraulic Engineering , Guanajuato City, MexicoWageningen University, Water Resources Management , Wageningen, The NetherlandsUniversity of California Berkeley, Environmental Science, Policy, and Management , Berkeley, CA, United States of AmericaAgricultural transformations have significantly contributed to the global market’s year-round supply of capital-intensive greenhouse-grown crops. For instance, berry production in México is increasingly relying on greenhouse systems to meet the growing demand of international markets, particularly in the USA. It is still unclear to what extent these transformations are related to land tenure, as data on greenhouse distribution often do not exist, are incomplete, or lack spatial resolution. This paper presents a support vector machine learning algorithm tool to map greenhouse expansion using satellite images. The tool is applied to the major berry-growing region of Michoacán, México. Here agricultural areas are transforming to satisfy foreign demand for berries, altering local land and water resource use patterns. We use this tool and a unique land tenure dataset to investigate (a) the spatially explicit extent to which high-input commercial agriculture (mainly the production of berries) has expanded in this region since 1989; and (b) the extent to which smallholder ( ejidal ) land has been incorporated into the highly capitalized agro-export sector. We combine a national dataset on ejidal land (which includes both communal and parcel land) with geospatial agricultural data to quantify the land-use changes in six municipalities in the berry-growing region of Michoacán between 1989 and 2021. We find that the development of the greenhouse berry boom can be quantified and shown with spatially-explicit detail, growing from zero to over 9,500 ha over the period, using almost one-quarter of all regional agricultural land in 2020. We further find that the capital-intensive market-oriented berry industry has been widely integrated into smallholder ejidal lands, so much so that over half of greenhouses are found there.https://doi.org/10.1088/1748-9326/ac9ac8machine learninggreenhouse agricultureremote sensingmappingagro-exportland tenure |
| spellingShingle | Sarah Hartman Michelle Farfán Jaime Hoogesteger Paolo D’Odorico Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, México Environmental Research Letters machine learning greenhouse agriculture remote sensing mapping agro-export land tenure |
| title | Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, México |
| title_full | Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, México |
| title_fullStr | Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, México |
| title_full_unstemmed | Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, México |
| title_short | Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, México |
| title_sort | mapping the expansion of berry greenhouses onto michoacan s ejido lands mexico |
| topic | machine learning greenhouse agriculture remote sensing mapping agro-export land tenure |
| url | https://doi.org/10.1088/1748-9326/ac9ac8 |
| work_keys_str_mv | AT sarahhartman mappingtheexpansionofberrygreenhousesontomichoacansejidolandsmexico AT michellefarfan mappingtheexpansionofberrygreenhousesontomichoacansejidolandsmexico AT jaimehoogesteger mappingtheexpansionofberrygreenhousesontomichoacansejidolandsmexico AT paolododorico mappingtheexpansionofberrygreenhousesontomichoacansejidolandsmexico |