Геопространственная информация в поддержку устойчивых продовольственных систем

Land Cover Atlas of Jordan provides valuable baseline to monitor future land changes

A new atlas expanding the coverage database of the Hashemite Kingdom of Jordan is providing valuable baseline reference data that will support monitoring of land changes in the future.

The atlas, recently published by the FAO geospatial unit. represents a substantial contribution to the understanding of land cover and land processes in Jordan. It provides information on territorial [land] cover distribution, [according to] sub-national (governorates and districts) administrative boundaries [based on] data provided by the Royal Jordanian Geographic Center (RJGC).

The atlas was developed as part of a Regional Food Security Analysis Network (RFSAN) project. Its main objective is increasing and improving the supply of goods and services from Jordan’s agriculture, forestry and fisheries sectors in a sustainable way, while increasing understanding of the biophysical conditions of the land in the country.

The land-cover database complies with the FAO/ISO standard (ISO 19144-2: 2012) based on the Land Cover Classification System (LCCS): Land Cover Meta Language (LCML). LCML has been implemented to support the standardization and integration of national land cover classification systems worldwide. It also provides a set of standard diagnostic attributes independent of the interpretation scale. Use of the LCML supports a more transparent and comparable way of reporting information on land cover. The LCML land cover legend was designed with the LCCSv3 software.

Data was drawn primarily from multi-spectral Sentinel-2 images at 10 m spatial resolution and was acquired between April 2016 and November 2016. Data sources also included geo-referenced ancillary data (land cover and land-use map, vegetation cover, soil map) obtained from various institutions.

Sentinel-2 imagery was pre-processed and mosaicked to provide a temporal sequence of free-cloud, calibrated images. Then, an Object-Based Image Analysis workflow was applied to segment the images into homogeneous polygons, which were interpreted based on their spectral, texture and shape characteristics supported by vegetation indices and ancillary datasets.

Post-processing removed the inconsistent classifications, cutting and dissolving polygons to official boundaries. The final database includes 1 million polygons, classified according to the LCCS Legend, divided into 34 classes (23 aggregated classes).
The statistical analysis of the aggregate distribution of land cover classes has been organized into two sections:
•    National Land Cover Database (LCDB);
•    LCDB from the governorates.

For more information, please download the atlas here.