Item talk:Q246100
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "A remote sensing approach for estimating the location and rate of urban irrigation in semi-arid climates", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70007512", "url": "https://pubs.usgs.gov/publication/70007512" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70007512 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1016/j.jhydrol.2011.10.016", "url": "https://doi.org/10.1016/j.jhydrol.2011.10.016" } ], "journal": { "@type": "Periodical", "name": "Journal of Hydrology", "volumeNumber": "414-415", "issueNumber": null }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Journal of Hydrology" } ], "datePublished": "2012", "dateModified": "2021-03-25", "abstract": "Urban irrigation is an important component of the hydrologic cycle in many areas of the arid and semiarid western United States. This paper describes a new approach that uses readily available datasets to estimate the location and rate of urban irrigation. The approach provides a repeatable methodology at 1/3 km2 resolution across a large urbanized area (500 km2). For this study, Landsat Thematic Mapper satellite imagery, air photos, climatic records, and a land-use map were used to: (1) identify the fraction of irrigated landscaping in urban areas, and (2) estimate the monthly rate of irrigation being applied to those areas. The area chosen for this study was the San Fernando Valley in Southern California.\n\nIdentifying irrigated areas involved the use of 29 satellite images, air photos, and a land-use map. The fraction of a pixel that consists of irrigated landscaping (Firr) was estimated using a linear-mixture model of two land-cover endmembers (selected pixels within a satellite image that represent a targeted land-cover). The two endmembers were impervious and fully-irrigated landscaping. In the San Fernando Valley, we used airport buildings, runways, and pavement to represent the impervious endmember; golf courses and parks were used to represent the fully irrigated endmember. The average Firr using all 29 satellite scenes was 44%. Firr calculated from hand-digitizing using air photos for 13 randomly selected single-family-residential neighborhoods showed similar results (42%).\n\nEstimating the rate of irrigation required identification of a third endmember: areas that consisted of urban vegetation but were not irrigated. This \"nonirrigated\" endmember was used to compute a Normalized Difference Vegetation Index (NDVI) surplus, defined as the difference between the NDVI signals of the irrigated and nonirrigated endmembers. The NDVI signals from irrigated areas remains relatively constant throughout the year, whereas the signal from nonirrigated areas rises and falls seasonally due to precipitation. The areas between airport runways were chosen to represent the nonirrigated endmember. Water-delivery records from 65 spatially-distributed single-family neighborhoods, consisting of nearly 1800 homes, were correlated with the NDVI surplus. The results show a strong exponential correlation (r2 = 0.94).\n\nIn the absence of water-delivery records, which can be difficult to obtain, a surrogate was identified: the landscape evapotranspiration rate (ETL). ETL was used to scale NDVI surplus (which is dimensionless) to irrigation rates using an exponential scaling function. The monthly irrigation rates calculated from satellite and climatic data compared well with irrigation rates calculated from actual water-delivery data using a paired Wilcoxan signed-rank test (p = 0.0063).\n\nIdentification of Firr at the pixel scale, along with identification of the irrigation rate for a fully-irrigated pixel, allows for mapping of urban irrigation over large areas. Maps showing the location and rate of monthly irrigation for the San Fernando study area were computed for January and August 1997.", "description": "13 p.", "publisher": { "@type": "Organization", "name": "Elsevier" }, "author": [ { "@type": "Person", "name": "Johnson, Tyler D.", "givenName": "Tyler D.", "familyName": "Johnson", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-7334-9188", "url": "https://orcid.org/0000-0002-7334-9188" } }, { "@type": "Person", "name": "Belitz, Kenneth kbelitz@usgs.gov", "givenName": "Kenneth", "familyName": "Belitz", "email": "kbelitz@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0003-4481-2345", "url": "https://orcid.org/0000-0003-4481-2345" }, "affiliation": [ { "@type": "Organization", "name": "National Water Quality Assessment Program", "url": "https://www.usgs.gov/programs/national-water-quality-program" }, { "@type": "Organization", "name": "New England Water Science Center", "url": "https://www.usgs.gov/centers/new-england-water-science-center" }, { "@type": "Organization", "name": "Office of Water Quality", "url": "https://www.usgs.gov/mission-areas/water-resources" }, { "@type": "Organization", "name": "National Water Quality Program", "url": "https://www.usgs.gov/programs/national-water-quality-program" }, { "@type": "Organization", "name": "Massachusetts Water Science Center", "url": "https://www.usgs.gov/centers/new-england-water-science-center" } ] } ], "funder": [ { "@type": "Organization", "name": "California Water Science Center", "url": "https://www.usgs.gov/centers/california-water-science-center" } ], "spatialCoverage": [ { "@type": "Place", "additionalType": "country", "name": "United States", "url": "https://geonames.org/4074035" }, { "@type": "Place", "additionalType": "state", "name": "California" }, { "@type": "Place", "additionalType": "unknown", "name": "San Fernando Valley", "url": "https://geonames.org/5391956" }, { "@type": "Place", "geo": [ { "@type": "GeoShape", "additionalProperty": { "@type": "PropertyValue", "name": "GeoJSON", "value": { "type": "FeatureCollection", "features": [ { "type": "Feature", "properties": {}, "geometry": { "type": "Polygon", "coordinates": [ [ [ -118.608119, 34.038848 ], [ -118.608119, 34.287715 ], [ -118.280568, 34.287715 ], [ -118.280568, 34.038848 ], [ -118.608119, 34.038848 ] ] ] } } ] } } }, { "@type": "GeoCoordinates", "latitude": 34.163281500000004, "longitude": -118.4443435 } ] } ] }, "OpenAlex": { "abstract_inverted_index": { "Urban": [ 0 ], "irrigation": [ 1, 94, 230, 372, 381, 392, 420, 431, 443 ], "is": [ 2, 369 ], "an": [ 3, 375 ], "important": [ 4 ], "component": [ 5 ], "of": [ 6, 13, 38, 81, 93, 120, 132, 137, 147, 229, 233, 240, 269, 320, 343, 409, 418, 429, 441 ], "the": [ 7, 14, 34, 79, 90, 107, 118, 171, 184, 195, 227, 263, 266, 270, 285, 288, 309, 327, 341, 356, 412, 419, 437, 445 ], "hydrologic": [ 8 ], "cycle": [ 9 ], "in": [ 10, 84, 111 ], 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