Regional Forest Land Cover Characterisation using Medium Spatial Resolution Satellite Data

2003 ◽  
pp. 389-410 ◽  
Author(s):  
Chengquan Huang ◽  
Collin Homer ◽  
Limin Yang
Keyword(s):  
Land Cover ◽  
Spatial Resolution ◽  
Satellite Data ◽  
Forest Land ◽  
Forest Land Cover ◽  
Regional Forest

scholarly journals Geographic Object-Based Image Analysis Framework for Mapping Vegetation Physiognomic Types at Fine Scales in Neotropical Savannas

2020 ◽  
Vol 12 (11) ◽  
pp. 1721 ◽  
Author(s):  
Fernanda F. Ribeiro ◽  
Dar A. Roberts ◽  
Laura L. Hess ◽  
Frank W. Davis ◽  
Kelly K. Caylor ◽  
...  
Keyword(s):  
Land Cover ◽  
Spatial Resolution ◽  
Forest Land ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Fine Spatial Resolution ◽  
Neotropical Savannas ◽  
Geographic Object ◽  
Forest Land Cover ◽  
Map Accuracy

Regional maps of vegetation structure are necessary for delineating species habitats and for supporting conservation and ecological analyses. A systematic approach that can discriminate a wide range of meaningful and detailed vegetation classes is still lacking for neotropical savannas. Detailed vegetation mapping of savannas is challenged by seasonal vegetation dynamics and substantial heterogeneity in vegetation structure and composition, but fine spatial resolution imagery (<10 m) can improve map accuracy in these heterogeneous landscapes. Traditional pixel-based classification methods have proven problematic for fine spatial resolution data due to increased within-class spectral variability. Geographic Object-Based Image Analysis (GEOBIA) is a robust alternative method to overcome these issues. We developed a systematic GEOBIA framework accounting for both spectral and spatial features to map Cerrado structural types at 5-m resolution. This two-step framework begins with image segmentation and a Random Forest land cover classification based on spectral information, followed by spatial contextual and topological rules developed in a systematic manner in a GEOBIA knowledge-based approach. Spatial rules were defined a priori based on descriptions of environmental characteristics of 11 different physiognomic types and their relationships to edaphic conditions represented by stream networks (hydrography), topography, and substrate. The Random Forest land cover classification resulted in 10 land cover classes with 84.4% overall map accuracy and was able to map 7 of the 11 vegetation classes. The second step resulted in mapping 13 classes with 87.6% overall accuracy, of which all 11 vegetation classes were identified. Our results demonstrate that 5-m spatial resolution imagery is adequate for mapping land cover types of savanna structural elements. The GEOBIA framework, however, is essential for refining land cover categories to ecological classes (physiognomic types), leading to a higher number of vegetation classes while improving overall accuracy.

scholarly journals The Analysis of Forest Land Cover Change And Area Determination of Land Rehabilitation Based on Geographic Information System in Magelang Regency

2018 ◽  
Vol 73 ◽  
pp. 03004
Author(s):  
Lidya Ernawati ◽  
Sutrisno Anggoro
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Land Cover ◽  
Land Cover Change ◽  
Geographic Information ◽  
Forest Land ◽  
Land Rehabilitation ◽  
Forest Land Cover ◽  
Area Determination

Population increased has consequences for the economic development of land demands for agriculture, settlement and other infrastructure. This resulted the change of area land cover which impact on the climate change and decline the environmental quality. Therefore, it is necessary to improve the environment through the land rehabilitation activities. The analysis of land cover change is needed as the first step to identify areas targeted by the land rehabilitation. Geographic information system is used as a spatial based on the appropriate determination of rehabilitation activities

scholarly journals Linking Changes in Land Cover and Land Use of the Lower Mekong Basin to Instream Nitrate and Total Suspended Solids Variations

2020 ◽  
Vol 12 (7) ◽  
pp. 2992 ◽  
Author(s):  
Kongmeng Ly ◽  
Graciela Metternicht ◽  
Lucy Marshall
Keyword(s):  
Water Quality ◽  
Land Use ◽  
Land Cover ◽  
Suspended Solids ◽  
Total Suspended Solids ◽  
Mekong River ◽  
Forest Land ◽  
Lulc Changes ◽  
Correlation Analyses ◽  
Forest Land Cover

Population growth and economic development are driving changes in land use/land cover (LULC) of the transboundary Lower Mekong River Basin (LMB), posing a serious threat to the integrity of the river system. Using data collected on a monthly basis over 30 years (1985–2015) at 14 stations located along the Lower Mekong river, this study explores whether spatiotemporal relationships exist between LULC changes and instream concentrations of total suspended solids (TSS) and nitrate—as proxies of water quality. The results show seasonal influences where temporal patterns of instream TSS and nitrate concentrations mirror patterns detected for discharge. Changes in LULC influenced instream TSS and nitrate levels differently over time and space. The seasonal Mann–Kendall (SMK) confirmed significant reduction of instream TSS concentrations at six stations (p < 0.05), while nitrate levels increased at five stations (p < 0.05), predominantly in stations located in the upper section of the basin where forest areas and mountainous topography dominate the landscape. Temporal correlation analyses point to the conversion of grassland (r = −0.61, p < 0.01) to paddy fields (r = 0.63, p < 0.01) and urban areas (r = 0.44, p < 0.05) as the changes in LULC that mostly impact instream nitrate contents. The reduction of TSS appears influenced by increased forest land cover (r = −0.72, p < 0.01) and by the development and operation of hydropower projects in the upper Mekong River. Spatial correlation analyses showed positive associations between forest land cover and instream concentrations of TSS (r = 0.64, p = 0.01) and nitrate (r = 0.54, p < 0.05), indicating that this type of LULC was heavily disturbed and harvested, resulting in soil erosion and runoff of nitrate rich sediment during the Wet season. Our results show that enhanced understanding of how LULC changes influence instream water quality at spatial and temporal scales is vital for assessing potential impacts of future land and water resource development on freshwater resources of the LMB.

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