The topic about shared real estate and ownership of landed property has become important only in the latest years. In connection with the rise of estate tax, the land’s cadastre value and the lease of land, the contradictions have also become more aggravated in shared real estate’s situations, which had occurred at some point when land reforms and privatization took place.
This study focuses on land use in the tsunami inundation area caused by the Great East Japan Earthquake, particularly land use history in the tsunami-affected area. Hanagama District, Yamamoto City, Miyagi prefecture, was selected as the study area. Land use were examined using aerial photographs taken in 1975, 2010 and 2013. Relationships between land use change and the disaster hazard areas, natural land conditions were analyzed with GIS.
Determining areas affected by forest succession is one of the main tasks aimed at shaping rural areas. Effective determination of the parameters of the dynamics of forest succession in areas used for agriculture is the basis for understanding the phenomenon of land cultivation abandonment. Understanding it allows to implement a proper policy limiting the negative effects of giving up agricultural production. There are many methods to determine forested areas. The most popular group of the methods includes those that rely on the use of LiDAR data.
Phosphorus (P) and nitrogen (N) concentrations were measured at 75 points in the upper reaches of rivers draining into the agricultural watersheds south of the Ibaraki prefecture during the summer and winter of year 2009. A geographic information system (GIS) was used to combine the environmental information regarding the watersheds such as land use, topography, and soil with water quality data for a statistical analysis. As andosols have a stronger tendency to adsorb P than other soil types, watersheds were classified into areas with andosol and non-andosol soils.
Although advances in remote sensing have enhanced mapping and monitoring of irrigated areas, producing accurate cropping information through satellite image classification remains elusive due to the complexity of landscapes, changes in reflectance of different land-covers, the remote sensing data selected, and image processing methods used, among others. This study extracted agricultural fields in the former homelands of Venda and Gazankulu in Limpopo Province, South Africa.
The purpose of this study is to clarify the method to know key issues which green infrastructure can help to improve and targeting score for the priorities by small areas of the city in Liverpool Green Infrastructure Strategy. As a result, the planning process is divided into three steps as follows. Step 1 identifies the strategic priorities for the city. In this step, the priorities are decided based on the evidences and several meetings with stakeholders from across the city. Step 2 focuses data gathering and data mapping.
Here we propose an accurate and robust method for large-area land-use and land-cover (LULC) mapping using multi-temporal optical data. The conventional method for LULC classification usually uses time-series data at regular intervals to consider the seasonality of LULC. However, high-resolution optical data have considerable seasonal biases, making it difficult to use time-series data.
Application of the satellite remote sensing techniques to wildlife research began from discernment of the individual animal and/or evaluation of animal behavior from the photography experiments. Satellite remote sensing to wildlife research at the present has applied for the purpose of evaluating the animal habitat. Trends in satellite remote sensing for wildlife are evaluating the index of wildlife habitat and estimating relationship with an environmental variables and animal distribution.
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