Long-Term Land Cover Dynamics (1986–2016) of Northeast China Derived from a Multi-Temporal Landsat Archive

Northeast China is a major grain production area, an ecological important forest area, and the largest old industrial base which is now suffering from economic growth slowdown and brain drain. Accurate and long-term dynamic land cover maps are highly demanded for many regional applications. In this study, we developed a set of continuous annual land cover mapping product at 30 m resolution using multi-temporal Landsat images. The maps in year 2000 and 2015 were tested using another independent validation dataset and the overall accuracies were 80.69% and 88.38%, respectively. The accuracies of the maps were improved by the integration of multi-temporal Landsat images and post-classification strategies. We found a general trend that the total area of land that experienced a change in land cover each year increased over time. The area change of each land cover type is also detected. The area of forests was 3.92 × 10 5 km 2 in 1986, fluctuated under fire disturbance, but declined in a quite high rate over the period of 1989 to 2006, and finally stayed relatively stable in area around 3.58 × 10 5 km 2 . The expansion of croplands was the leading land cover change from 1986 to 2000, and then the total area of croplands slightly declined under the Grain to Green Project of China, while shrublands, grasslands and wetlands began to increase. The area of impervious surfaces increased by more than 502% during the last three decades, and about 73% of the new built-up area was converted from croplands. We also demonstrated the our maps could capture the important land cover conversion processes, such as urbanization, forest logging activities, and agricultural expansion

Modelling seagrass blue carbon stock in seagrass-mangrove habitats using remote sensing approach

Modelling seagrass blue carbon stocks are essential to complement the satellitebased remote sensing in detecting the underground seagrass carbon stocks. The green carbon initiatives have for long reported the detailed mapping and estimation procedural as well as the audit protocol of the global terrestrial carbon stocks. Research on the blue carbon mapping and its related modelling and estimation, on the other hand, is rarely if ever published as part of its importance is realised but remained scattered. Therefore, this study aimed at investigating blue carbon stocks in seagrass habitats by estimating the total carbon stored in seagrass using the satellite-based technique. The specific objectives are to : 1) assess and adapt some selected models for deriving seagrass total above-ground carbon (STAGC); 2) formulate new approach based-on selected models to combine with in-situ data, to model and estimate blue carbon stocks from seagrass total below-ground carbon (STBGC); 3) develop a novel technique using the selected models with soil organic carbon (SOC) to model and estimate the blue carbon stocks from seagrass total soil organic carbon (STSOC); and 4) integrate all the models (STAGC, STBGC, and STSOC) to produce a framework for the mapping and estimation of seagrass total blue carbon stock (STBCS). Suitable logistic functions were selected and applied on the satellite images to investigate seagrass, and soil carbon stocks along the seagrass meadows of Peninsular Malaysia (PM) coastline All the Landsat ETM+’s shortwave visible bands (blue, green, red) were employed for detecting and mapping seagrass stocks boundary within the coastline of PM. The derivation of STAGC was adopted from the existing bottom reflectance index (BRI) based technique via establishing a strong relationship between BRI with seagrass total aboveground biomass (STAGB). While for STBGC estimation, the STAGB^ (STAGB obtained from BRI image) were correlated with seagrass total below-ground biomass derived from insitu measurement (STBGB^^ro). Both these STAGB^ and STBGB^.^ro were converted into STAGC and STBGC using a conversion factor. Furthermore, the derivation of seagrass total soil organic carbon derived via laboratory test (STSOCi^b) was achieved through correlating BRI values with corresponding in-situ samples of soil organic carbon (SOC) obtained from the laboratory analysis by the Carbon-Hydrogen Nitrogen Sulphur (CHNS) analyser. These models were generated from the three major sample areas (Johor, Penang, and Terengganu), which were used to estimate the entire seagrass carbon stocks in the coastline of PM. The models revealed a robust correlation results for BRI versus STAGB (R2 = 0.962, p< 0.001), STAGB^, versus STBGB/A,wro (R2 = 0.933, p< 0.001,), and BRI and STSOC (R2 = 0 .989, p< 0.001) respectively. The STBCS for the whole seagrass meadows along the coastline of PM was finally realised, demonstrating a good agreement in accuracy assessment (Root Mean Square Error (RMSE) = +- <1MtC/ha\). It is, therefore, concluded that the new approach introduced by this research on STBGC and STSOC estimation was tested and proved significant on the entire STBCS quantification for the PM coastline. The contributions are critical to fast-track the United Nations Framework Convention on Climate Change (UNFCCC) agreement to report the STBCS contents. Hence, this study has managed to propose a new fundamental initiative for estimating STBCS for speedy realisation of 2020 agenda on targets 14.2 and 14.5 of United Nations’ Sustainable Development Goal 14th (life below the water)

Análisis geoambiental aplicado a la evaluación estratégica de la ciudad de Salamanca y alrededores. Cartografías temáticas mediante SIG

[ES]La Tesis consiste en el planificación territorial de la ciudad de Salamanca y alrededores mediante la Evaluación Ambiental Estratégica. A partir de una caracterización adecuada del medio físico, socioeconómico y al estudio detallado de los riesgos que pudieran afectar a la población, se realiza el diagnóstico y ordenación territorial, con la identificación de la problemática, recomendaciones de conservación, limitaciones de uso y potencialidad de uso. Por otro lado, se formula el modelo territorial objetivo el cual queremos alcanzar a partir de la planificación territorial. Finalmente se asignan los nuevos usos del suelo de acuerdo a la capacidad vocacional del territorio y se determinan medidas concretas de planificación. Se desarrollan, además, metodologías novedosas para la obtención de información relevante y complementaria a los procesos de planificación que usualmente no son empleados. Los SIG, Sistemas de Información Geográfica, son herramientas fundamentales para el desarrollo del proceso planificador