{"cited_by_count":2179219,"description":"This cluster of papers focuses on the use of remote sensing technology, particularly MODIS and Landsat data, for monitoring vegetation dynamics, phenology, and biomass estimation in response to global change and climate variability. The papers also explore the application of machine learning techniques for land cover classification and the assessment of ecological responses to environmental change.","display_name":"Remote Sensing in Agriculture","domain_id":"3","external_ids":{"openalex":"https://openalex.org/T10111","wikipedia":"https://en.wikipedia.org/wiki/Remote_sensing"},"field_id":"23","id":"T10111","keywords":[{"display_name":"NDVI","id":"normalized-difference-vegetation-index","score":0.3544,"url":"https://openalex.org/keywords/normalized-difference-vegetation-index"},{"display_name":"satellite imagery","id":"satellite-imagery","score":0.2511,"url":"https://openalex.org/keywords/satellite-imagery"},{"display_name":"vegetation indices","id":"vegetation-index","score":0.5721,"url":"https://openalex.org/keywords/vegetation-index"},{"display_name":"Landsat Enhanced Thematic Mapper","id":"landsat-etm","score":0.7485,"url":"https://openalex.org/keywords/landsat-etm"},{"display_name":"surface reflectance","id":"surface-reflectance","score":0.4757,"url":"https://openalex.org/keywords/surface-reflectance"},{"display_name":"LEDAPS atmospheric correction","id":"ledaps-atmospheric-correction","score":0.9009,"url":"https://openalex.org/keywords/ledaps-atmospheric-correction"},{"display_name":"land cover","id":"land-cover","score":0.2084,"url":"https://openalex.org/keywords/land-cover"},{"display_name":"Sentinel-2","id":"sentinel-2","score":0.2848,"url":"https://openalex.org/keywords/sentinel-2"},{"display_name":"remote sensing of vegetation","id":"vegetation-remote-sensing","score":0.707,"url":"https://openalex.org/keywords/vegetation-remote-sensing"},{"display_name":"MODIS","id":"modis","score":0.2492,"url":"https://openalex.org/keywords/modis"},{"display_name":"crop monitoring","id":"crop-monitoring","score":0.3864,"url":"https://openalex.org/keywords/crop-monitoring"},{"display_name":"crop yield prediction","id":"crop-yield-prediction","score":0.2517,"url":"https://openalex.org/keywords/crop-yield-prediction"},{"display_name":"vegetation phenology","id":"vegetation-phenology","score":0.657,"url":"https://openalex.org/keywords/vegetation-phenology"},{"display_name":"EVI","id":"enhanced-vegetation-index","score":0.5742,"url":"https://openalex.org/keywords/enhanced-vegetation-index"},{"display_name":"crop classification","id":"crop-classification","score":0.5153,"url":"https://openalex.org/keywords/crop-classification"},{"display_name":"canopy reflectance","id":"canopy-reflectance","score":0.7445,"url":"https://openalex.org/keywords/canopy-reflectance"},{"display_name":"vegetation monitoring","id":"vegetation-monitoring","score":0.3517,"url":"https://openalex.org/keywords/vegetation-monitoring"},{"display_name":"Sevilleta LTER","id":"sevilleta-lter","score":0.9415,"url":"https://openalex.org/keywords/sevilleta-lter"},{"display_name":"Landsat","id":"landsat","score":0.247,"url":"https://openalex.org/keywords/landsat"},{"display_name":"crop phenology","id":"crop-phenology","score":0.4404,"url":"https://openalex.org/keywords/crop-phenology"},{"display_name":"AVHRR","id":"avhrr","score":0.2629,"url":"https://openalex.org/keywords/avhrr"},{"display_name":"crop mapping","id":"crop-mapping","score":0.7486,"url":"https://openalex.org/keywords/crop-mapping"},{"display_name":"solar-induced chlorophyll fluorescence","id":"solar-induced-chlorophyll-fluorescence","score":0.6669,"url":"https://openalex.org/keywords/solar-induced-chlorophyll-fluorescence"},{"display_name":"NDVI time series","id":"ndvi-time-series","score":0.7764,"url":"https://openalex.org/keywords/ndvi-time-series"},{"display_name":"Everglades","id":"everglades","score":0.289,"url":"https://openalex.org/keywords/everglades"}],"legacy_keywords":["Remote Sensing","Vegetation Monitoring","Phenology","MODIS","Landsat","NDVI","Global Change","Climate","Biomass Estimation","Machine Learning"],"openalex_id":"https://openalex.org/T10111","source_created_date":"2024-01-23T15:27:05","source_updated_date":"2026-10-17T03:02:00","subfield_id":"2303","url":"/topics/T10111","works_api_url":"https://api.openalex.org/works?filter=topics.id:T10111","works_count":157719,"label":"Remote Sensing in Agriculture","provider":"openalex","revision":"bf4c156620c1d9df","taxonomy_revision":"f050b5d4780b1289","title":"Remote Sensing in Agriculture","kind":"topic-directory","aeo_cohort":"topic-directory","catalogue_revision":"f050b5d4780b1289","numeric_address":"36108547260337919","address_version":"morton4x16-v1","coordinates":[3,23,2303,10111],"answer_status":"Directory metadata; local answer requires separate source review","truth_status":"Subject descriptor, not a factual answer or a demonstrated knowledge gap","reviewed_answer":null}