{"id":5550,"date":"2023-09-17T15:10:59","date_gmt":"2023-09-17T15:10:59","guid":{"rendered":"https:\/\/dailyai.com\/?p=5550"},"modified":"2024-03-28T00:42:58","modified_gmt":"2024-03-28T00:42:58","slug":"ai-and-machine-learning-join-the-fight-to-protect-the-amazon","status":"publish","type":"post","link":"https:\/\/dailyai.com\/da\/2023\/09\/ai-and-machine-learning-join-the-fight-to-protect-the-amazon\/","title":{"rendered":"AI og maskinl\u00e6ring g\u00e5r sammen i kampen for at beskytte Amazonas"},"content":{"rendered":"

Amazonas-regnskoven, som d\u00e6kker et omr\u00e5de p\u00e5 2,3 millioner kvadratkilometer, er verdens st\u00f8rste regnskov og den region med st\u00f8rst biologisk mangfoldighed.\u00a0<\/strong><\/p>\n

Amazonas er spredt over ni lande og er afg\u00f8rende for planetens sundhed, idet den absorberer kuldioxid, regulerer vejrm\u00f8nstre og er levested for utallige arter.\u00a0<\/span><\/p>\n

Afskovning og ulovlig brug af jorden har truet Amazonas i \u00e5rtier, hvilket har f\u00f8rt til tab af levesteder i stor skala og n\u00e6sten irreversible skader p\u00e5 \u00f8kosystemet.\u00a0<\/span><\/p>\n

If\u00f8lge <\/span>Bevarelse af Amazonas<\/span><\/a>Alene i 2022 gik n\u00e6sten 5 millioner hektar regnskov tabt, hvilket er en stigning p\u00e5 21% i forhold til \u00e5ret f\u00f8r.<\/span><\/p>\n

AI-l\u00f8sninger til naturbeskyttelse<\/span><\/h2>\n

Dybt inde i Amazonas' regnskov roder dyrene rundt i underskoven uden at vide, at de bliver fanget af kameraer og mikrofoner.\u00a0<\/span><\/p>\n

Billederne og optagelserne giver ikke bare et sp\u00e6ndende indblik i dyrenes liv i regnskoven - de er en del af et sofistikeret AI-drevet projekt, der skal l\u00f8se problemet med afskovning.<\/span><\/p>\n

\"Abouti\"
Nogle arter af Agouti-gnavere er truede i den colombianske del af Amazonas. Kilde: Shutterstock: Shutterstock.<\/figcaption><\/figure>\n

Ved at udnytte kraften i data, maskinl\u00e6ring (ML) og cloud-teknologi udvikler eksperter innovative programmer, der har til form\u00e5l at genkende afskovningsm\u00f8nstre og levere brugbare data til politiske beslutningstagere.\u00a0<\/span><\/p>\n

AI er blevet en integreret del af den globale bevaringsindsats og giver forskere mulighed for at kombinere data fra sensorer, kameraer og satellitter.<\/span><\/p>\n

Projekt Guacamaya<\/span><\/a>et samarbejde mellem Alexander von Humboldt Instituttet, CinfonIA Research Center ved Universidad de los Andes, Instituto Sinchi og <\/span>Microsofts AI for Good Lab<\/span><\/a>har til form\u00e5l at overv\u00e5ge skovrydning og biodiversitet i Colombias Amazonas.<\/span><\/p>\n

Som Juan Lavista Ferres, Vice President og Chief Data Scientist hos Microsofts AI for Good Lab, beskriver det: \"Dette projekt vil ikke l\u00f8se alle de problemer, Amazon har, men det vil l\u00f8se et, som jeg mener, er grundl\u00e6ggende: Du kan ikke l\u00f8se et problem, hvis du ikke kan m\u00e5le det.\"<\/span><\/p>\n

En trestrenget tilgang<\/span><\/h2>\n

AI's evne til at arbejde med data p\u00e5 tv\u00e6rs af flere modaliteter giver forskere en detaljeret beskrivelse af dette enorme og komplekse milj\u00f8.\u00a0<\/span><\/p>\n

Satellitdata giver f.eks. en makroanalyse af skoven, herunder afskovningsh\u00e6ndelser, ulovlig minedrift og \u00e6ndringer i arealanvendelsen.\u00a0<\/span><\/p>\n

Samtidig sporer kameraer og sensorer p\u00e5 jorden makroforandringernes indvirkning p\u00e5 den lokale biodiversitet, f.eks. ved at spore tab af levesteder.<\/span><\/p>\n

S\u00e5dan g\u00f8r du Projekt Guacamaya kombinerer forskellige AI-systemer:<\/span><\/p>\n

Trin 1: Satellitdata til makrojordanalyse<\/span><\/h3>\n

Den f\u00f8rste del af Project Guacamaya udnytter satellitdata fra <\/span>Planet Labs<\/span><\/a>.\u00a0<\/span><\/p>\n

Satellitdata forsyner projektet med daglige billeder i h\u00f8j opl\u00f8sning af Amazonas' regnskov, hvilket muligg\u00f8r overv\u00e5gning i n\u00e6sten realtid. Det er afg\u00f8rende for at opdage hurtige \u00e6ndringer i skovd\u00e6kket eller tegn p\u00e5 ulovlige aktiviteter.<\/span><\/p>\n

\"Amazon
Satellitdata giver forskere mulighed for at analysere regnskoven i Amazonas i n\u00e6sten realtid. Kilde: Shutterstock: Shutterstock.<\/figcaption><\/figure>\n

De AI-modeller, der er udviklet til denne fase, er tr\u00e6net til at s\u00f8ge efter indikatorer for skovrydning eller ulovlig minedrift, f.eks. uautoriserede veje eller rydninger.\u00a0<\/span><\/p>\n

Ved at automatisere satellitoverv\u00e5gningen kan teamet advare de colombianske myndigheder, n\u00e6sten lige s\u00e5 snart der opst\u00e5r mist\u00e6nkelig aktivitet.\u00a0<\/span><\/p>\n

Trin 2: Skjulte kameraer giver indsigt p\u00e5 jordniveau<\/span><\/h3>\n

Skjulte kameraer er strategisk placeret i hele den colombianske Amazonas for at supplere satellitdata.\u00a0<\/span><\/p>\n

Disse kameraer tager tusindvis af billeder hver dag og sender dem til AI-modeller, der identificerer og klassificerer dyr.\u00a0<\/span><\/p>\n

Ud over at spore arternes bev\u00e6gelser i regnskoven fungerer det ogs\u00e5 som et varslingssystem. <\/span>Hvis der f.eks. findes dyr uden for deres naturlige \u00f8kosystemer, kan det v\u00e6re tegn p\u00e5 lokale \u00e6ndringer, som kr\u00e6ver yderligere unders\u00f8gelser.<\/p>\n

Trin 3: Bioakustik til klassificering af dyr<\/span><\/h3>\n

Endelig indeholder Project Guacamaya lyddata, eller bioakustik, der er indsamlet direkte fra Amazonas' regnskov.\u00a0<\/span><\/p>\n

Specialiseret udstyr bruges til at optage de naturlige lyde i skoven og f\u00f8re data ind i AI-modeller.<\/span> tr\u00e6net til at skelne mellem fugle- og ikke-fuglelyde og klassificere dem i specifikke arter.<\/span><\/p>\n

\"Amazon
En truet stor gr\u00f8n ara. Kilde: Shutterstock: Shutterstock.<\/figcaption><\/figure>\n

Med en identifikationssikkerhed p\u00e5 over 80% hj\u00e6lper disse AI-modeller forskere med at forst\u00e5 dyrs adf\u00e6rd, spore arters migration og opdage tilstedev\u00e6relsen af invasive eller truede arter.<\/span><\/p>\n

Bek\u00e6mpelse af skovrydning i Brasilien<\/span><\/h2>\n

I et separat projekt samarbejder Microsoft med milj\u00f8organisationen Imazon og nonprofit-organisationen <\/span>PrevisIA<\/span><\/a> i Brasilien for at opdage ulovlig minedrift og skovrydning via satellitanalyse.<\/span><\/p>\n

\"Vi bruger PrevisIA til at forudse risikoomr\u00e5derne og gennemf\u00f8re tiltag for at undg\u00e5 afskovning\", siger Carlos Souza, seniorforsker hos Imazon.<\/span><\/p>\n

Tidligere i \u00e5r blev skovomr\u00e5det i Triunfo do Xingu decimeret og mistede et omr\u00e5de svarende til 700 fodboldbaner p\u00e5 bare en m\u00e5ned. <\/span>If\u00f8lge PrevisIA er det ogs\u00e5 den region, der har st\u00f8rst risiko for yderligere afskovning i 2023. <\/span><\/p>\n

Inden \u00e5rets udgang ansl\u00e5r AI, at cirka 271,52 kvadratkilometer skov vil v\u00e6re g\u00e5et tabt.\u00a0<\/span><\/p>\n

\"Amazon
Amazonas st\u00e5r over for en konstant risiko for afskovning, som ikke har vist tegn p\u00e5 at blive mindre i de seneste \u00e5r. Kilde: Shutterstock: Shutterstock.<\/figcaption><\/figure>\n

Carlos Souza Jr, seniorforsker hos Imazon og projektkoordinator for PrevisIA, fremh\u00e6vede den proaktive kraft i denne tilgang: <\/span>\"Eksisterende modeller til forudsigelse af skovrydning var langsigtede og s\u00e5 p\u00e5, hvad der ville ske om \u00e5rtier. Vi havde brug for et nyt v\u00e6rkt\u00f8j, der kunne komme \u00f8del\u00e6ggelserne i fork\u00f8bet.\"<\/p>\n

Ved hj\u00e6lp af en kombination af geostatistik og historiske data tager modellen h\u00f8jde for variabler, der h\u00e6mmer eller fremmer afskovning, s\u00e5som jord, der er beskyttet af oprindelige samfund.<\/span><\/p>\n

\"\"
PrevisIA-kort og -statistik. Kilde: Imazon<\/a>.<\/figcaption><\/figure>\n

PrevisIA er ogs\u00e5 til gavn for lokale interessenter, herunder banker og virksomheder, som bruger dataene til at tr\u00e6ffe milj\u00f8m\u00e6ssigt ansvarlige beslutninger.<\/span><\/p>\n

Fra reaktiv til proaktiv konservering<\/span><\/h3>\n

AI's evne til at arbejde med komplekse data i n\u00e6sten realtid underst\u00f8tter et nyt paradigme for proaktiv bevarelse.\u00a0<\/span><\/p>\n

Tidligere var forskere prim\u00e6rt afh\u00e6ngige af manuelt indsamlede feltdata, som ikke kan g\u00f8re sig h\u00e5b om at indfange dynamikken i et omr\u00e5de s\u00e5 stort som Amazonas.<\/span><\/p>\n

Jos\u00e9 Godofredo Pires dos Santos, offentlig anklager i Par\u00e1, beskrev behovet for forebyggende foranstaltninger og sagde: \"Vi \u00f8nsker ikke at blive ved med at komme ind, n\u00e5r skaden allerede er sket.\"<\/span><\/p>\n

Forskerne bem\u00e6rker, at det endelige m\u00e5l er at g\u00f8re disse modeller til open source til brug i andre globale projekter.\u00a0<\/span><\/p>\n

AI's rolle i naturbevarelse: eksempler fra 2023<\/span><\/h2>\n

I en verden, der k\u00e6mper med klimaforandringer, tab af levesteder og nedgang i biodiversiteten, kommer de traditionelle bevaringsmetoder ofte til kort.<\/span><\/p>\n

2023 har budt p\u00e5 en r\u00e6kke fascinerende bevarelsesprojekter, der udnytter AI og maskinl\u00e6ring.<\/p>\n

Her er tre eksempler fra de sidste par m\u00e5neder:<\/p>\n

Akustisk overv\u00e5gning af floddelfiner i Amazonas<\/span><\/h3>\n

Forskere ved Cataloniens Tekniske Universitet i Barcelona har tr\u00e6net et neuralt netv\u00e6rk til at skelne mellem to truede delfinarter i Amazonfloden - Boto og Tucuxi - ud fra deres unikke akustiske kommunikation.<\/span><\/p>\n

Ved at installere undervandsmikrofoner i Mamirau\u00e1-reservatet i den brasilianske Amazonas-regnskov kan teamet overv\u00e5ge floddelfiner med minimal forstyrrelse.\u00a0<\/span><\/p>\n

Den <\/span>AI-teknologi<\/span><\/a> hj\u00e6lper med at skelne delfinlyde fra andre milj\u00f8lyde.<\/span><\/p>\n

Norges AI-drevne kontrol af fiskeindvandring<\/span><\/h3>\n

Stillehavslaksen, en invasiv art, truer de oprindelige atlantiske laksebestande i europ\u00e6iske vandl\u00f8b.\u00a0<\/span><\/p>\n

Huawei og Berlev\u00e5g Jeger-og Fiskerforening (BJFF) byggede et AI-fiskefiltreringssystem i Storelva i Norge.\u00a0<\/span><\/p>\n

\"AI
Stillehavslaks har s\u00e6rlige kendetegn, som AI kan opfange. Kilde: Wikimedia Commons<\/a>.<\/figcaption><\/figure>\n

Ved hj\u00e6lp af en computersynsmodel (CV), <\/span>dette system<\/span><\/a> kan skelne mellem atlanterhavs- og stillehavslaks med 90% n\u00f8jagtighed og omdirigere de invasive arter til en opsamlingsbugt, f\u00f8r de slippes fri i havet.\u00a0<\/span><\/p>\n

Dette innovative system \"ser\" de invasive stillehavslaks og forhindrer dem sikkert i at invadere europ\u00e6iske vandveje.<\/p>\n

Opt\u00e6lling af lunder i Storbritannien<\/span><\/h3>\n

S\u00f8papeg\u00f8jer, som er elskede, men s\u00e5rbare havfugle i Storbritannien, har historisk set v\u00e6ret vanskelige at overv\u00e5ge.\u00a0<\/span><\/p>\n

Rangers har traditionelt talt dem manuelt - en besv\u00e6rlig og tidskr\u00e6vende opgave. <\/span><\/p>\n

I partnerskab med Microsoft, Avanade og NatureScot er SSE Renewables styring af et AI-system<\/a> for at t\u00e6lle s\u00f8papeg\u00f8jer p\u00e5 Isle of May ud for Skotlands kyst.\u00a0<\/span><\/p>\n

Kameraer fanger live-optagelser af s\u00f8papeg\u00f8jer, og en <\/span>AI <\/span>model tr\u00e6net\u00a0p\u00e5 m\u00e6rkede billeder kan skelne mellem individuelle fugle med minimal menneskelig indblanding.\u00a0<\/span><\/p>\n

Fremtiden for kunstig intelligens inden for naturbeskyttelse<\/span><\/h2>\n

Den spirende rolle, som kunstig intelligens spiller i bevaringsarbejdet, har vist sig at v\u00e6re effektiv p\u00e5 tv\u00e6rs af forskellige \u00f8kosystemer - fra Amazonfloden til europ\u00e6iske vandveje og skotske kystlinjer.\u00a0<\/span><\/p>\n

AI er en kraftmultiplikator, der hj\u00e6lper forskere med at holde styr p\u00e5 komplekse biodynamiske data. <\/span><\/p>\n

Efterh\u00e5nden som den infrastruktur, der kr\u00e6ves for at tr\u00e6ne og implementere AI-modeller, bliver mere tilg\u00e6ngelig, vil det blive lettere at opbygge modeller til unikke bevaringsproblemer, selv uden betydelige ressourcer.\u00a0<\/span><\/p>\n

I fremtiden vil milj\u00f8fork\u00e6mpere kunne bygge sofistikerede, lette AI-systemer med minimal ekspertise.<\/p>","protected":false},"excerpt":{"rendered":"

Amazonas-regnskoven, der d\u00e6kker et stort omr\u00e5de p\u00e5 2,3 millioner kvadratkilometer, er verdens st\u00f8rste regnskov og den region, der har den st\u00f8rste biodiversitet. Spredt over ni lande er Amazonas afg\u00f8rende for planetens sundhed, idet den absorberer kuldioxid, regulerer vejrm\u00f8nstre og udg\u00f8r et levested for utallige arter. Skovrydning og ulovlig brug af jorden har truet Amazonas i \u00e5rtier, hvilket har f\u00f8rt til tab af levesteder i stor skala og n\u00e6sten uoprettelige skader p\u00e5 \u00f8kosystemet. If\u00f8lge Amazon Conservation gik n\u00e6sten 5 millioner hektar regnskov tabt alene i 2022, hvilket er en stigning p\u00e5 21% i forhold til \u00e5ret f\u00f8r. AI-l\u00f8sninger til bevarelse Dybt inde i Amazonas' regnskov roder dyrene rundt i<\/p>","protected":false},"author":2,"featured_media":5556,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[141,166,182,382,105,121],"class_list":["post-5550","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-amazon","tag-computer-vision","tag-conservation","tag-ecology","tag-machine-learning","tag-microsoft"],"yoast_head":"\nAI and machine learning join the fight to protect the Amazon | DailyAI<\/title>\n<meta name=\"description\" content=\"The Amazon Rainforest, stretching across nine countries and covering a vast 2.3 million square miles, is the world\u2019s largest rainforest and most biodiverse region on the planet.\u00a0\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link 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