{"title":"利用Sentinel-1系列图像对厄瓜多尔Churute红树林生态保护区周围的土地利用和覆盖进行分类和变化分析","authors":"D.A. Vélez-Alvarado, J. Álvarez-Mozos","doi":"10.4995/raet.2020.14099","DOIUrl":null,"url":null,"abstract":"Management practices adopted in protected natural areas often ignore the relevance of the territory surrounding the actual protected land (buffer area). These areas can be the source of impacts that threaten the protected ecosystems. This paper reports a case study where a time series of Sentinel-1 imagery was used to classify the land-use/land-cover and to evaluate its change between 2015 and 2018 in the buffer area around the Manglares Churute Ecological Reserve (REMCh) in Ecuador. Sentinel-1 scenes were processed and ground-truth data were collected consisting of samples of the main land-use/land-cover classes in the region. Then, a Random Forests (RF) classification algorithm was built and optimized, following a five-fold cross validation scheme using the training dataset (70% of the ground truth). The remaining 30% was used for validation, achieving an Overall Accuracy of 84%, a Kappa coefficient of 0.8 and successful class performance metrics for the main crops and land use classes. Results were poorer for heterogeneous and minor classes, nevertheless the performance of the classification was deemed sufficient for the targeted change analysis. Between 2015 and 2018, an increase in the area covered by intensive land uses was evidenced, such as shrimp farms and sugarcane, which replaced traditional crops (mainly rice and banana). Even though such changes only affected the land area around the natural reserve, they might affect its water quality due to the use of fertilizers and pesticides that easily. Therefore, it is recommended that these buffer areas around natural protected areas be taken into account when designing adequate environmental protection measures and polices.","PeriodicalId":43626,"journal":{"name":"Revista de Teledeteccion","volume":"1 1","pages":""},"PeriodicalIF":0.4000,"publicationDate":"2020-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Clasificación de usos y cubiertas del suelo y análisis de cambios en los alrededores de la Reserva Ecológica Manglares Churute (Ecuador) mediante una serie de imágenes Sentinel-1\",\"authors\":\"D.A. Vélez-Alvarado, J. Álvarez-Mozos\",\"doi\":\"10.4995/raet.2020.14099\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Management practices adopted in protected natural areas often ignore the relevance of the territory surrounding the actual protected land (buffer area). These areas can be the source of impacts that threaten the protected ecosystems. This paper reports a case study where a time series of Sentinel-1 imagery was used to classify the land-use/land-cover and to evaluate its change between 2015 and 2018 in the buffer area around the Manglares Churute Ecological Reserve (REMCh) in Ecuador. Sentinel-1 scenes were processed and ground-truth data were collected consisting of samples of the main land-use/land-cover classes in the region. Then, a Random Forests (RF) classification algorithm was built and optimized, following a five-fold cross validation scheme using the training dataset (70% of the ground truth). The remaining 30% was used for validation, achieving an Overall Accuracy of 84%, a Kappa coefficient of 0.8 and successful class performance metrics for the main crops and land use classes. Results were poorer for heterogeneous and minor classes, nevertheless the performance of the classification was deemed sufficient for the targeted change analysis. Between 2015 and 2018, an increase in the area covered by intensive land uses was evidenced, such as shrimp farms and sugarcane, which replaced traditional crops (mainly rice and banana). Even though such changes only affected the land area around the natural reserve, they might affect its water quality due to the use of fertilizers and pesticides that easily. Therefore, it is recommended that these buffer areas around natural protected areas be taken into account when designing adequate environmental protection measures and polices.\",\"PeriodicalId\":43626,\"journal\":{\"name\":\"Revista de Teledeteccion\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.4000,\"publicationDate\":\"2020-11-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Revista de Teledeteccion\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4995/raet.2020.14099\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista de Teledeteccion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4995/raet.2020.14099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Clasificación de usos y cubiertas del suelo y análisis de cambios en los alrededores de la Reserva Ecológica Manglares Churute (Ecuador) mediante una serie de imágenes Sentinel-1
Management practices adopted in protected natural areas often ignore the relevance of the territory surrounding the actual protected land (buffer area). These areas can be the source of impacts that threaten the protected ecosystems. This paper reports a case study where a time series of Sentinel-1 imagery was used to classify the land-use/land-cover and to evaluate its change between 2015 and 2018 in the buffer area around the Manglares Churute Ecological Reserve (REMCh) in Ecuador. Sentinel-1 scenes were processed and ground-truth data were collected consisting of samples of the main land-use/land-cover classes in the region. Then, a Random Forests (RF) classification algorithm was built and optimized, following a five-fold cross validation scheme using the training dataset (70% of the ground truth). The remaining 30% was used for validation, achieving an Overall Accuracy of 84%, a Kappa coefficient of 0.8 and successful class performance metrics for the main crops and land use classes. Results were poorer for heterogeneous and minor classes, nevertheless the performance of the classification was deemed sufficient for the targeted change analysis. Between 2015 and 2018, an increase in the area covered by intensive land uses was evidenced, such as shrimp farms and sugarcane, which replaced traditional crops (mainly rice and banana). Even though such changes only affected the land area around the natural reserve, they might affect its water quality due to the use of fertilizers and pesticides that easily. Therefore, it is recommended that these buffer areas around natural protected areas be taken into account when designing adequate environmental protection measures and polices.