Trees at the rural-urban interface in Bengaluru: patterns, functions, role and relevance

绿地在城市和城郊地区发挥着重要作用，是农村地区土地覆盖的主要定义。根据它们在城乡梯度和周围建成区的相对位置，它们具有不同的功能，可以预期，特定区域的社会经济变量与绿地空间格局表现出特定的关系。二氧化碳项目研究了这些关系。作为定量分析的前提条件，本文分析和检验了城乡指标是否适合将绿地格局作为综合指标。正在使用不同空间分辨率的遥感图像来绘制和分析大巴纳加洛尔的绿色空间（Landsat和RapidEye），并确定绿色空间的生物物理特征、用途和功能（世界观3，在选定的样带）。遥感图像的预处理和分类以及相应的地面真相是在与印度项目合作者密切合作下进行的；社会数据将从包括班加罗尔发展局在内的官方来源寻求。将对更大的巴纳格拉尔进行图像分割，分割成具有类似绿色空间格局的区域，作为建立生物物理和社会变量之间关系的基础。将建立一个基于Landsat的土地利用时间序列，以检验绿地配置的变化在空间和时间上都遵循类似模式的假设。将测试各种选项，以使时间序列更加准确和具体，通过使用最新的Landsat图像和高分辨率图像对绿地进行亚像素分析，作为光谱分解的基础。此外，作为整个研究小组的原型，将建立一个网络地理信息系统，容纳二氧化碳的所有空间数据，并作为一种可视化工具，可以支持确定共同的主题兴趣，从而促进生境研究所项目之间的合作。

Green spaces play an important role in urban and peri-urban areas and are the major defining land cover in rural areas. Depending on their relative position along the rural-urban gradient and the surrounding built-up areas, they serve various functions and it can be expected that social-economic variables of particular quarters exhibit a particular relationship to green spaces spatial pattern. Project C02 researches into these relationships. As a pre-condition to this quantitative analyses, urban-rural indices are analysed and tested for their suitability to integrate patterns of green spaces as indicators. Remote sensing imagery at different spatial resolutions is being used to map and analyse green spaces for greater Banagalore (Landsat and RapidEye) and to determine biophysical characteristics, uses and functions of green spaces (WorldView 3, in a selected transect). The remote sensing image pre-processing and classification as well as the corresponding ground truthing is implemented in close collaboration with the Indian project collaborators; and social data will be sought from official sources including the Bangalore Development Authority. An image segmentation of greater Banaglore will be carried out into areas of similar green spaces patterns as a basis for establishing relationships between biophysical and social variables. A Landsat based time series of land use will be built in order to test the hypothesis that the changes in green spaces configuration follow a similar pattern both over space and over time. Options will be tested to make the time series more accurate and speficic by sub-pixel analyses for green spaces using up-to-date Landsat imagery and high resolution imagery as a basis for spectral unmixing. In addition, as a prototype for the entire research group, a WebGIS will be established that accommodates all spatial data of C02 and serves as a visualization tool which may support identification of joint thematic interests and therefore foster collaboration between FOR projects.