The genus Saissetia Deplanche is newly reported from Laos, including two new species, Saissetia simulocoffeae Choi & Lee, sp. n. and S. quasioleae Choi & Lee sp. n., and a first record of S. miranda (Cockerell & Parrott, 1899). A key to all five species of Saissetia known from Indochina is provided. The DNA barcodes (mitochondrial cytochrome oxidase subunit I-mtCOI) of the two new species were obtained for future use.

Real-time rainfall monitoring is of great practical importance over the highly populated Indochina area, which is prone to natural disasters, in particular in association with rainfall. With the goal of d etermining near real-time half-hourlyrain estimates from satellite, the three-layer, artificial neural networks (ANN) approach was used to train the brightness temperatures at 6.7, 11, and 12-μm channels of the Japanese geostationary satellite MTSAT against passive microwavebased rain rates from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and TRMM Precipitation Radar (PR) data for the June-September 2005 period. The developed model was applied to the MTSAT data for the June-September 2006 period. The results demonstrate that the developed algorithm is comparable to the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) results and can be used for flood monitoring across the Indochina area on a half-hourly time scale.