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This study focuses on land cover and land management changes in relation to food security and environmental services in a semi-arid area of East Nusa Tenggara (ENT) – Indonesia. The study was conducted in Central Sumba District of ENT Province. Classification and regression tree (CART) for land cover classification has been analyzed using machine learning techniques using Google Earth Engine. A survey with Focus Group Discussion (FGD) and followed with in-depth interviews were conducted for primary data collection involving a total of 871 respondents. The Socio-economic data analyzed statistics descriptively and non-parametric tests. The study showed that: 1). There has been a substantial land use change during the devo-lution era that has both positive and negative implications for food security and envi-ronmental services. 2). There has been population pressure in the fertile or agricultur-al land as the direct impact of the development of city infrastructures; and 3). Nation-al intervention through the Food Estate program has fostered and shaped land use change and land management in Central Sumba District. The study highlights the importance that the devolution spirit should help to well manage the limited ara-ble/agricultural land in dominated semi-arid to ensure food security and environment services.

The long drought experienced in Indonesia in the past was identified as one of the main factors in the failure of rice production. The application of rice crop insurance was introduced since 2015 to help rice farmers who suffered from farm damage. The claim was increased year by year, with the highest in 2018-2019 (12,253 ha). The main problem associated with the insurance claim is the delay of inspection of the drought-affected land. Meanwhile, various satellite data can provide relevant information more quickly for those affected areas. The purpose of this study is to examine the potential use of satellite data to detect drought to support the rice crop insurance program. Daily and monthly rainfall data derived from the Tropical Rainfall Measuring Mission (TRMM), Global Satellite Mapping of Precipitation (GSMaP) and Multifunctional Transport Satellites (MTSAT) were analyzed to identify meteorological drought. Agricultural drought is studied through the character of several indices from Moderate Resolution Imaging Spectroradiometer (MODIS) data. Preliminary results showed that up to 89.45% of the analysis comformed with field conditions. Satellite data has its potential to be utilized in the identification of claims on agricultural insurance which requires information on land damage due to drought.

Since land resource database development in 1987/1988, a large amount of digital data in spatial, tabular and metadata format has been collected and generated. There are some application softwares of soil database to manage such a large amount of data, i.e.: Side & Horizon (SHDE4), Soil Sample Analysis (SSA), and Land Unit in dbf file, while Site and Horizon is in DataEase formats. The database contains soil physics and chemical property data of each soil horizon from surface to effective soil depth, climate, land surface condi- tions, and other parameters required for soil classification. Currently, database management software for land resources is still based on DOS and is stand alone. The system is not efficient and effectively used as Agri- cultural Land Resource Information System. At present, as a key component of this system requires review and development of new database software is compatible with the development of information technology. This paper explains about development of interactive agricultural land resources information system for op- timizing land resources data utilization. Hopefully, the software can give contributions in national Agricul- tural Land Resources System Information development for supporting food security