An Alternative Method for the Generation of Consistent Mapping to Monitoring Land Cover Change: A Case Study of Guerrero State in Mexico

Land

Rocío N. Ramos-Bernal¹  René Vázquez-Jiménez¹  Carlos J. Novillo²  Patricia Arrogante-Funes²  Raúl Romero-Calcerrada³ 

[1] Cuerpo Académico UAGro CA-93 Riesgos Naturales y Geotecnología, FI, Research Group on Technologies for Landscape Analysis and Diagnosis (TADAT), Universidad Autónoma de Guerrero, Av. Lázaro Cárdenas s/n, CU, 39070 Chilpancingo, Guerrero, Mexico;Research Group on Technologies for Landscape Analysis and Diagnosis (TADAT), Departamento de Tecnología Química y Ambiental, ESCET, Universidad Rey Juan Carlos, C/Tulipán s/n, Móstoles, 28933 Madrid, Spain;Research Group on Technologies for Landscape Analysis and Diagnosis (TADAT), Facultad de Ciencias Jurídicas y Sociales, Universidad Rey Juan Carlos, Paseo de los Artilleros s/n., Vicálvaro, 28032 Madrid, Spain;

关键词: land use/land cover (LULC);    LULC mapping;    image classification;    change detection;   

DOI  :  10.3390/land10070731

来源: DOAJ

【 摘 要 】

Land cover is crucial for ecosystems and human activities. Therefore, monitoring land cover changes has become relevant in recent years. This study proposes an alternative method based on conventional change detection techniques combined with maximum likelihood (MaxLike) supervised classification of satellite images to generate consistent Land Use/Land Cover (LULC) maps. The novelty of this method is that the supervised classification is applied in an earlier stage of change detection exclusively to identified dynamics zones. The LULC categories of the stable zones are acquired from an initial date’s previously elaborated base map. The methodology comprised the use of Landsat images from 2011 and 2016, applying the Sun Canopy Sensor (SCS + C) topographic correction model enhanced through the classification of slopes, using derived topographic corrected images with NDVI, and employing Tasseled Cap (TC) Brightness-Greenness-Wetness indices and Principal Components (PCs). The study incorporated a comparative analysis of the consistency of the LULC mapping, which is generated based on control areas. The results show that the proposed method, although slightly laborious, is viable and fully automatable. The generated LULC map is accurate and robust and achieves a Kappa concordance index of 87.53. Furthermore, the boundary consistency was visually superior to the conventional classified map.

【 授权许可】

Unknown