|Statement||P.S. Roy ... [et al.].|
|Contributions||Roy, P. S., Dr., Indian Institute of Remote Sensing.|
|LC Classifications||QK341 .L366 2004|
|The Physical Object|
|Pagination||98 p. :|
|Number of Pages||98|
|LC Control Number||2004312237|
South and Southeast Asia in This paper presents a synopsis of this project. was used for preparing the mosaic and land cover map of /86 and / SPOT VEGETATION data was used for / analyses. information for land use/land cover mapping, forest cover mapping, and environmental. 2. Prepare time-series land cover maps of selected countries in South and Southeast Asia; 3. Identify ‘hot spot’ areas and investigate in detail using high resolution satellite data and ground survey; 4. Develop methodological guidelines and land cover classification system suitable for the project; 5. The land-use outcomes may bring about positive or negative environmental and socio-economic changes—or both—at the local, regional, and even global level. This Special Issue seeks to assemble papers that advance our knowledge about the drivers and effects of land-use changes in South and Southeast Asia. Land cover mapping using SPOT-VEGETATION for South central Asia: Global Land Cover (GLC) is an initiative to make Global Land Cover data sets available for the researchers involved in Global/Regional Studies for land surface parameterization. It is a major project of European Commission-Joint Research Centre (JRC), Italy with an objective.
Home > What We Do > Analytics > Land Use / Land Cover Mapping. Land management and land planning requires a knowledge of the current state of the landscape. Understanding current land cover and how it is being used, along with an accurate means of monitoring change over time, is vital to any person responsible for land management. Mapping and Analysis of Land Use and Land Cover for a Sustainable Development Using High Resolution Satellite Images and GIS FIG Working Week Environment for Sustainability Abuja, Nigeria, 6 – 10 May 3/18 pixels‟ spectral and spatial properties.,t is based on a supervised maximum likelihood classification. In India, researches on land use/land cover have been done by various scholars, especially by using remote sensing data. Pooja et al. () have quantified land use/cover of Gagas watershed, district Almora using survey of India topographic sheet of the year and LISS III satellite data for the year over a period of 43 years. We generate predictions using the official land mask (defines the prediction area) used within the SoilGrids project for the purpose of global soil mapping. The global soil mask excludes water bodies, and all areas covered with permanent ice, i.e., areas to the south of 60°S. The land mask is visible from the final prediction maps shown in.
(). Land cover map of Southeast Asia at m spatial resolution. Remote Sensing Letters: Vol. 7, No. 7, pp. Land cover maps of /86 and /93 were prepared using NOAA AVHRR and a land cover map of was prepared using VEGETATION data. "Hot Spot" areas were identified using these data . Land-use land cover information was extracted for the study area based on the land cover map of Southeast Asia derived at 1-km spatial resolution by using time series SPOT-NDVI datasets (Agrawal. Book Description. Filling the need for a comprehensive book that covers both theory and application, Remote Sensing of Land Use and Land Cover: Principles and Applications provides a synopsis of how remote sensing can be used for land-cover characterization, mapping, and monitoring from the local to the global contributions by leading scientists from around the world, this .