GIS-based modeling of Javan Hawk-Eagle distribution using logistic and autologistic regression models. Syartinilia & Tsuyuki, S. Biological Conservation, 141(3):756–769, March, 2008. ![GIS-based modeling of Javan Hawk-Eagle distribution using logistic and autologistic regression models [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Few attempts have been made to model the distribution of the Javan Hawk-Eagle (Spizaetus bartelsi) based on predictions formulated from habitat requirements in West Java or throughout Java Island. This paper proposes a new approach to predicting probability models of Javan Hawk-Eagle (JHE) distribution using the application of logistic regression (LR) and autologistic regression (ALR) coupled with RAMAS GIS, and creating pseudo-absence data using a normalized difference vegetation index from remote sensing data. Habitat requirements of 11 nest-sites in Gunung Gede-Pangrango National Park (TNGP) and its surrounding areas were analyzed and quantified, and the model was validated in southern parts of West Java. The final LR model was used as the starting point for fitting ALR models that account for spatial autocorrelation through the addition of an autocovariate variable using several different neighborhood sizes ranging from 450 m (15 × 15 moving window size, or equal to 20.25 ha) to 1500 m (50 × 50 moving window size, or equal to 225 ha) using 300 m interval. The best model was the ALR model with a 1500 m autocovariate that agreed with the distance between nests in TNGP and the mean home range size in Java. This model showed a significant increase in overall accuracy and successfully removed misclassified pixels. Based on our results, we recommend five strategies for the management and conservation of JHE habitat, including integrated conservation management and increased regulation of wildlife reserves.
@article{syartinilia_gis-based_2008,
title = {{GIS}-based modeling of {Javan} {Hawk}-{Eagle} distribution using logistic and autologistic regression models},
volume = {141},
issn = {0006-3207},
url = {http://www.sciencedirect.com/science/article/B6V5X-4S035C9-1/2/233f638cf365d2d5fe5928fc70c2bfa5},
doi = {10.1016/j.biocon.2007.12.030},
abstract = {Few attempts have been made to model the distribution of the Javan Hawk-Eagle (Spizaetus bartelsi) based on predictions formulated from habitat requirements in West Java or throughout Java Island. This paper proposes a new approach to predicting probability models of Javan Hawk-Eagle (JHE) distribution using the application of logistic regression (LR) and autologistic regression (ALR) coupled with RAMAS GIS, and creating pseudo-absence data using a normalized difference vegetation index from remote sensing data. Habitat requirements of 11 nest-sites in Gunung Gede-Pangrango National Park (TNGP) and its surrounding areas were analyzed and quantified, and the model was validated in southern parts of West Java. The final LR model was used as the starting point for fitting ALR models that account for spatial autocorrelation through the addition of an autocovariate variable using several different neighborhood sizes ranging from 450 m (15 × 15 moving window size, or equal to 20.25 ha) to 1500 m (50 × 50 moving window size, or equal to 225 ha) using 300 m interval. The best model was the ALR model with a 1500 m autocovariate that agreed with the distance between nests in TNGP and the mean home range size in Java. This model showed a significant increase in overall accuracy and successfully removed misclassified pixels. Based on our results, we recommend five strategies for the management and conservation of JHE habitat, including integrated conservation management and increased regulation of wildlife reserves.},
number = {3},
urldate = {2009-09-04TZ},
journal = {Biological Conservation},
author = {Syartinilia and Tsuyuki, Satoshi},
month = mar,
year = {2008},
keywords = {Autocovariate, Habitat patch occupancy, Habitat suitability, Predicted probability distribution, Spizaetus bartelsi},
pages = {756--769}
}
Downloads: 0
{"_id":"D3oKH3X6Mpp4r9sr9","bibbaseid":"syartinilia-tsuyuki-gisbasedmodelingofjavanhawkeagledistributionusinglogisticandautologisticregressionmodels-2008","downloads":0,"creationDate":"2019-03-08T07:06:41.573Z","title":"GIS-based modeling of Javan Hawk-Eagle distribution using logistic and autologistic regression models","author_short":["Syartinilia","Tsuyuki, S."],"year":2008,"bibtype":"article","biburl":"https://bibbase.org/zotero/mkoo","bibdata":{"bibtype":"article","type":"article","title":"GIS-based modeling of Javan Hawk-Eagle distribution using logistic and autologistic regression models","volume":"141","issn":"0006-3207","url":"http://www.sciencedirect.com/science/article/B6V5X-4S035C9-1/2/233f638cf365d2d5fe5928fc70c2bfa5","doi":"10.1016/j.biocon.2007.12.030","abstract":"Few attempts have been made to model the distribution of the Javan Hawk-Eagle (Spizaetus bartelsi) based on predictions formulated from habitat requirements in West Java or throughout Java Island. This paper proposes a new approach to predicting probability models of Javan Hawk-Eagle (JHE) distribution using the application of logistic regression (LR) and autologistic regression (ALR) coupled with RAMAS GIS, and creating pseudo-absence data using a normalized difference vegetation index from remote sensing data. Habitat requirements of 11 nest-sites in Gunung Gede-Pangrango National Park (TNGP) and its surrounding areas were analyzed and quantified, and the model was validated in southern parts of West Java. The final LR model was used as the starting point for fitting ALR models that account for spatial autocorrelation through the addition of an autocovariate variable using several different neighborhood sizes ranging from 450 m (15 × 15 moving window size, or equal to 20.25 ha) to 1500 m (50 × 50 moving window size, or equal to 225 ha) using 300 m interval. The best model was the ALR model with a 1500 m autocovariate that agreed with the distance between nests in TNGP and the mean home range size in Java. This model showed a significant increase in overall accuracy and successfully removed misclassified pixels. Based on our results, we recommend five strategies for the management and conservation of JHE habitat, including integrated conservation management and increased regulation of wildlife reserves.","number":"3","urldate":"2009-09-04TZ","journal":"Biological Conservation","author":[{"firstnames":[],"propositions":[],"lastnames":["Syartinilia"],"suffixes":[]},{"propositions":[],"lastnames":["Tsuyuki"],"firstnames":["Satoshi"],"suffixes":[]}],"month":"March","year":"2008","keywords":"Autocovariate, Habitat patch occupancy, Habitat suitability, Predicted probability distribution, Spizaetus bartelsi","pages":"756–769","bibtex":"@article{syartinilia_gis-based_2008,\n\ttitle = {{GIS}-based modeling of {Javan} {Hawk}-{Eagle} distribution using logistic and autologistic regression models},\n\tvolume = {141},\n\tissn = {0006-3207},\n\turl = {http://www.sciencedirect.com/science/article/B6V5X-4S035C9-1/2/233f638cf365d2d5fe5928fc70c2bfa5},\n\tdoi = {10.1016/j.biocon.2007.12.030},\n\tabstract = {Few attempts have been made to model the distribution of the Javan Hawk-Eagle (Spizaetus bartelsi) based on predictions formulated from habitat requirements in West Java or throughout Java Island. This paper proposes a new approach to predicting probability models of Javan Hawk-Eagle (JHE) distribution using the application of logistic regression (LR) and autologistic regression (ALR) coupled with RAMAS GIS, and creating pseudo-absence data using a normalized difference vegetation index from remote sensing data. Habitat requirements of 11 nest-sites in Gunung Gede-Pangrango National Park (TNGP) and its surrounding areas were analyzed and quantified, and the model was validated in southern parts of West Java. The final LR model was used as the starting point for fitting ALR models that account for spatial autocorrelation through the addition of an autocovariate variable using several different neighborhood sizes ranging from 450 m (15 × 15 moving window size, or equal to 20.25 ha) to 1500 m (50 × 50 moving window size, or equal to 225 ha) using 300 m interval. The best model was the ALR model with a 1500 m autocovariate that agreed with the distance between nests in TNGP and the mean home range size in Java. This model showed a significant increase in overall accuracy and successfully removed misclassified pixels. Based on our results, we recommend five strategies for the management and conservation of JHE habitat, including integrated conservation management and increased regulation of wildlife reserves.},\n\tnumber = {3},\n\turldate = {2009-09-04TZ},\n\tjournal = {Biological Conservation},\n\tauthor = {Syartinilia and Tsuyuki, Satoshi},\n\tmonth = mar,\n\tyear = {2008},\n\tkeywords = {Autocovariate, Habitat patch occupancy, Habitat suitability, Predicted probability distribution, Spizaetus bartelsi},\n\tpages = {756--769}\n}\n\n","author_short":["Syartinilia","Tsuyuki, S."],"key":"syartinilia_gis-based_2008","id":"syartinilia_gis-based_2008","bibbaseid":"syartinilia-tsuyuki-gisbasedmodelingofjavanhawkeagledistributionusinglogisticandautologisticregressionmodels-2008","role":"author","urls":{"Paper":"http://www.sciencedirect.com/science/article/B6V5X-4S035C9-1/2/233f638cf365d2d5fe5928fc70c2bfa5"},"keyword":["Autocovariate","Habitat patch occupancy","Habitat suitability","Predicted probability distribution","Spizaetus bartelsi"],"downloads":0,"html":""},"search_terms":["gis","based","modeling","javan","hawk","eagle","distribution","using","logistic","autologistic","regression","models","syartinilia","tsuyuki"],"keywords":["autocovariate","habitat patch occupancy","habitat suitability","predicted probability distribution","spizaetus bartelsi"],"authorIDs":[],"dataSources":["pJXBJ7FpDvMhH6hs5"]}