Item talk:Q268112

{

 "USGS Publications Warehouse": {
   "@context": "https://schema.org",
   "@type": "Article",
   "additionalType": "Journal Article",
   "name": "Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation",
   "identifier": [
     {
       "@type": "PropertyValue",
       "propertyID": "USGS Publications Warehouse IndexID",
       "value": "70156740",
       "url": "https://pubs.usgs.gov/publication/70156740"
     },
     {
       "@type": "PropertyValue",
       "propertyID": "USGS Publications Warehouse Internal ID",
       "value": 70156740
     },
     {
       "@type": "PropertyValue",
       "propertyID": "DOI",
       "value": "10.14358/PERS.71.9.1053",
       "url": "https://doi.org/10.14358/PERS.71.9.1053"
     }
   ],
   "journal": {
     "@type": "Periodical",
     "name": "Photogrammetric Engineering and Remote Sensing",
     "volumeNumber": "71",
     "issueNumber": "9"
   },
   "inLanguage": "en",
   "isPartOf": [
     {
       "@type": "CreativeWorkSeries",
       "name": "Photogrammetric Engineering and Remote Sensing"
     }
   ],
   "datePublished": "2005",
   "dateModified": "2015-08-27",
   "abstract": "Assessment of the relationship between the normalized difference vegetation index (NDVI) and precipitation is important in understanding vegetation and climate interaction at a large scale. NDVI response to precipitation, however, is difficult to quantify due to the lag and seasonality effects, which will vary due to vegetation cover type, soils and climate. A time series analysis was performed on biweekly NDVI and precipitation around weather stations in the northern and central U.S. Great Plains. Regression models that incorporate lag and seasonality effects were used to quantify the relationship between NDVI and lagged precipitation in grasslands and croplands. It was found that the time lag was shorter in the early growing season, but longer in the mid- to late-growing season for most locations. The regression models with seasonal adjustment indicate that the relationship between NDVI and precipitation over the entire growing season was strong, with R2\u00a0values of 0.69 and 0.72 for grasslands and croplands, respectively. We conclude that vegetation greenness can be predicted using current and antecedent precipitation, if seasonal effects are taken into account.",
   "description": "9 p.",
   "publisher": {
     "@type": "Organization",
     "name": "American Society for Photogrammetry and Remote Sensing"
   },
   "author": [
     {
       "@type": "Person",
       "name": "Ji, Lei lji@usgs.gov",
       "givenName": "Lei",
       "familyName": "Ji",
       "email": "lji@usgs.gov",
       "identifier": {
         "@type": "PropertyValue",
         "propertyID": "ORCID",
         "value": "0000-0002-6133-1036",
         "url": "https://orcid.org/0000-0002-6133-1036"
       },
       "affiliation": [
         {
           "@type": "Organization",
           "name": "Earth Resources Observation and Science (EROS) Center",
           "url": "https://www.usgs.gov/centers/eros"
         },
         {
           "@type": "Organization",
           "name": "Earth Resources Observation and Science (EROS) Center (Geography)",
           "url": "https://www.usgs.gov/centers/eros"
         }
       ]
     },
     {
       "@type": "Person",
       "name": "Peters, Albert J.",
       "givenName": "Albert J.",
       "familyName": "Peters"
     }
   ],
   "funder": [
     {
       "@type": "Organization",
       "name": "Earth Resources Observation and Science (EROS) Center",
       "url": "https://www.usgs.gov/centers/eros"
     }
   ]
 }

}