{"id":5618,"date":"2022-10-07T15:35:41","date_gmt":"2022-10-07T13:35:41","guid":{"rendered":"https:\/\/geopard.tech\/?p=5618"},"modified":"2026-09-13T10:54:54","modified_gmt":"2026-09-13T08:54:54","slug":"normalisoitu-erotuskosteusindeksi-ndmi","status":"publish","type":"post","link":"https:\/\/geopard.tech\/fin\/blog\/normalized-difference-moisture-index-ndmi\/","title":{"rendered":"Normalisoitu kosteusindeksin ero"},"content":{"rendered":"

M\u00e4\u00e4r\u00e4 GeoPardin tukemat kasvillisuusindeksit<\/a> kasvaa jatkuvasti. GeoPard-tiimi esittelee normalisoidun kosteusindeksin (NDMI). Indeksi m\u00e4\u00e4ritt\u00e4\u00e4 kasvillisuuden vesipitoisuuden ja normalisoidun kosteusindeksin (NDWI). Se on hy\u00f6dyllinen l\u00f6ydett\u00e4ess\u00e4 kohtia, joilla on olemassa olevia kasvien vesistressi<\/strong>.<\/p>\r\n\r\n\r\n\r\n

Alemmat NDMI-arvot osoittavat kohdat, joissa kasvit ovat stressaantuneita riitt\u00e4m\u00e4tt\u00f6m\u00e4n kosteuden vuoksi.
Toisaalta kasvillisuuden huippua seuraavat alhaisemmat normalisoidut erotusvesi-indeksin arvot korostavat kohtia, jotka muuttuvat valmis sadonkorjuuseen<\/strong> ensimm\u00e4inen.<\/p>\r\n

\"Kasvillisuuden

Kasvillisuuden suhteellisen vesipitoisuuden ero kahden satelliittikuvan v\u00e4lill\u00e4 (t\u00e4ss\u00e4 tapauksessa Sentinel-2-t\u00e4hdist\u00f6)<\/p><\/div>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n

Seuraavista kuvakaappauksista l\u00f6yd\u00e4t 19. kes\u00e4kuuta (kasvillisuuden huippu) ja 6. hein\u00e4kuuta otettujen satelliittikuvien perusteella luodut NDMI-vy\u00f6hykkeet sek\u00e4 NDMI-eroa esitt\u00e4v\u00e4n yht\u00e4l\u00f6kartan.<\/p>\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n

\"NormalisoituNDMI laskettu planeetan p\u00e4\u00e4ll\u00e4 \/ Sentinel-2 \/ Landsat-kuva<\/p>\r\n

Mik\u00e4 on kosteusindeksi?<\/h2>\r\n

Se on mitta tai laskelma, jota k\u00e4ytet\u00e4\u00e4n arvioimaan kosteuspitoisuutta tai saatavuutta tietyll\u00e4 alueella tai seudulla. Se johdetaan tyypillisesti useista ymp\u00e4rist\u00f6tekij\u00f6ist\u00e4, kuten sadem\u00e4\u00e4r\u00e4st\u00e4, haihdunnasta, maaper\u00e4n ominaisuuksista ja kasvillisuudesta.<\/p>\r\n

Se antaa suhteellisen kuvan alueen kosteudesta tai kuivuudesta ja auttaa tunnistamaan mahdolliset vesistressit tai kuivuusolosuhteet.<\/p>\r\n

Se on arvokas ty\u00f6kalu vesivarojen seurantaan ja hallintaan, maatalouden suunnitteluun ja tietyn alueen ekologisten olosuhteiden ymm\u00e4rt\u00e4miseen.<\/p>\r\n

Mik\u00e4 on normalisoitu erotuskosteusindeksi?<\/h2>\r\n

Normalisoitu erotuskosteusindeksi (NDMI) on kaukokartoitusdatasta johdettu kasvillisuusindeksi, jolla arvioidaan ja seurataan kasvillisuuden kosteuspitoisuutta. Kuten muutkin kasvillisuusindeksit, se lasketaan satelliitti- tai ilmakuvien spektraalisten heijastusarvojen avulla.<\/p>\r\n

Se on erityisen hy\u00f6dyllinen kasvien vesistressin seurannassa, kuivuusolosuhteiden arvioinnissa, mets\u00e4paloriskin arvioinnissa ja ilmastonmuutoksen vaikutusten tutkimisessa kasvillisuuteen.<\/p>\r\n

Se lasketaan k\u00e4ytt\u00e4m\u00e4ll\u00e4 l\u00e4hi-infrapuna- (NIR) ja lyhytaaltoinfrapuna- (SWIR) kaistaa, jotka ovat herkki\u00e4 kasvillisuuden kosteuspitoisuudelle. NDMI:n kaava on:<\/p>\r\n

NDMI<\/strong> = (l\u00e4hi-infrapuna \u2013 keskihajonta) \/ (l\u00e4hi-infrapuna + keskihajonta)<\/em><\/p>\r\n

NDWI-arvot vaihtelevat tyypillisesti v\u00e4lill\u00e4 -1 - 1, jolloin korkeammat arvot osoittavat korkeampaa kasvillisuuden kosteuspitoisuutta ja matalammat arvot matalampaa kosteuspitoisuutta tai vesistressi\u00e4 kasvillisuudessa. Negatiiviset NDMI-arvot voivat liitty\u00e4 kasvittomiin alueisiin tai alueisiin, joilla on eritt\u00e4in alhainen kosteuspitoisuus.<\/p>\r\n

Mik\u00e4 on NDWI?<\/h2>\r\n

NDWI eli Normalized Difference Water Index on kaukokartoitusindeksi, jota k\u00e4ytet\u00e4\u00e4n kasvillisuuden tai maisemien vesipitoisuuden tai veteen liittyvien ominaisuuksien kvantifiointiin ja arviointiin.<\/p>\r\n

Se lasketaan analysoimalla satelliitti- tai ilmakuvista saatujen l\u00e4hi-infrapuna- ja vihre\u00e4n valon kaistojen heijastavuutta. Se on erityisen hy\u00f6dyllinen vesist\u00f6jen tunnistamisessa, veden saatavuuden muutosten seurannassa ja kasvillisuuden terveyden arvioinnissa.<\/p>\r\n

Vertaamalla eri aallonpituuksien absorptiota ja heijastumista se tarjoaa arvokasta tietoa sovelluksiin, kuten kuivuuden seurantaan, hydrologiseen analyysiin ja ekosysteemien hallintaan.<\/p>\r\n

NDMI:n visualisointi normalisoidun erotusvesi-indeksin m\u00e4\u00e4ritt\u00e4miseksi<\/h2>\r\n

NDMI:n visualisointiin kuuluu satelliitti- tai ilmakuvien k\u00e4sittely, NDMI-arvojen laskeminen ja tulosten n\u00e4ytt\u00e4minen v\u00e4rikoodattuina karttana tai kuvana. T\u00e4ss\u00e4 ovat NDMI:n visualisoinnin yleiset vaiheet:<\/p>\r\n

    \r\n
  • Hanki satelliitti- tai ilmakuvia:<\/strong> Hanki monispektrikuvia satelliitista tai ilma-aluksesta, kuten Landsatista, Sentinelist\u00e4 tai MODISista. Varmista, ett\u00e4 kuvissa on kaikki tarvittavat aallot: l\u00e4hi-infrapuna (NIR) ja lyhytaaltoinfrapuna (SWIR).<\/li>\r\n
  • Kuvien esik\u00e4sittely:<\/strong> Tietol\u00e4hteest\u00e4 riippuen saatat joutua esik\u00e4sittelem\u00e4\u00e4n kuvia ilmakeh\u00e4n, geometristen ja radiometristen v\u00e4\u00e4ristymien korjaamiseksi. Muunna kuvan digitaaliset luvut (DN) spektraalisten heijastuskykyarvojen muotoon.<\/li>\r\n
  • Laske NDMI:<\/strong> K\u00e4yt\u00e4 kuvan jokaiselle pikselille NIR- ja SWIR-heijastuskykyarvoja NDMI:n laskemiseen seuraavalla kaavalla: NDMI = (NIR \u2013 SWIR) \/ (NIR + SWIR).<\/li>\r\n
  • V\u00e4rikartoitus:<\/strong> M\u00e4\u00e4rit\u00e4 NDMI-arvoille v\u00e4ripaletti. Tyypillisesti k\u00e4ytet\u00e4\u00e4n jatkuvaa v\u00e4riskaalaa, joka vaihtelee yhdest\u00e4 v\u00e4rist\u00e4 (esim. punainen) alhaisille NDMI-arvoille (mik\u00e4 osoittaa alhaista kosteuspitoisuutta) toiseen v\u00e4riin (esim. vihre\u00e4) korkeille NDMI-arvoille (mik\u00e4 osoittaa korkeaa kosteuspitoisuutta). Voit k\u00e4ytt\u00e4\u00e4 ohjelmistoja, kuten QGIS, ArcGIS tai ohjelmointikirjastoja, kuten Pythonin Rasterio ja Matplotlib, v\u00e4rikartan luomiseen.<\/li>\r\n
  • Visualisoi NDMI-kartta:<\/strong> N\u00e4yt\u00e4 NDMI-kartta tai -kuva GIS-ohjelmistolla, ohjelmointikirjastolla tai verkkoalustalla. N\u00e4in voit analysoida kasvillisuuden kosteuspitoisuuden alueellista jakautumista ja tunnistaa vesistressin tai korkean kosteuden alueet.<\/li>\r\n
  • Tulkinta ja analyysi:<\/strong> K\u00e4yt\u00e4 NDWI-visualisointia kasvillisuuden terveyden arviointiin, kuivuusolosuhteiden seurantaan tai mets\u00e4paloriskin arviointiin. Voit my\u00f6s vertailla normalisoituja erotusvesiindeksikarttoja eri ajanjaksoilta analysoidaksesi kasvillisuuden kosteuspitoisuuden muutoksia ajan kuluessa.<\/li>\r\n<\/ul>\r\n

    Muista, ett\u00e4 eri ohjelmistoty\u00f6kaluilla tai ohjelmointikirjastoilla voi olla hieman erilaisia ty\u00f6nkulkuja, mutta kokonaisprosessi on samanlainen. Lis\u00e4ksi voit lis\u00e4t\u00e4 p\u00e4\u00e4llekk\u00e4in muita tietokerroksia, kuten maank\u00e4ytt\u00f6\u00e4, korkeutta tai hallinnollisia rajoja, parantaaksesi analyysiasi ja ymm\u00e4rt\u00e4\u00e4ksesi paremmin kasvillisuuden kosteuspitoisuuden ja muiden tekij\u00f6iden v\u00e4lisi\u00e4 suhteita.\u00a0<\/p>","protected":false},"excerpt":{"rendered":"

    GeoPardin tukemien kasvillisuusindeksien m\u00e4\u00e4r\u00e4 kasvaa jatkuvasti. GeoPardin tiimi esittelee normalisoidun erotuskosteusindeksin (NDMI). Indeksi m\u00e4\u00e4ritt\u00e4\u00e4 kasvillisuuden veden\u2026<\/p>","protected":false},"author":210157960,"featured_media":5620,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","_eb_attr":"","content-type":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_wpcom_ai_launchpad_first_post":false,"_jetpack_hide_featured_image":false,"_jetpack_featured_image_duplicate_dismissed":0,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"{title}\n\n{excerpt}\n\n{url}","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"_wpas_customize_per_network":false,"jetpack_post_was_ever_published":false},"categories":[1586,1372,1377,1376,1378,1379],"tags":[1618,1619],"class_list":["post-5618","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-product-features","category-blog","category-crop-monitoring","category-management-zones","category-remote-sensing","category-soil-data","tag-crop-monitoring","tag-normalized-difference-vegetation-index"],"acf":[],"yoast_head":"\nNormalized Difference Moisture Index - GeoPard<\/title>\n<meta name=\"description\" content=\"GeoPard team introduces the Normalized Difference Moisture Index (NDMI). 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