Isabel Pocas

Evaluating the fitness for use of spatial data sets to promote quality in ecological assessment and monitoring

João Gonçalves, Bruno Marcos, João P. Honrado, 2014, Int. J. Geogr. Inf. Sci..

Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data

L. S. Pereira, Paula Paredes, Mario Cunha, 2015, Remote. Sens..

Evaluating MODIS vegetation indices using ground based measurements in mountain semi-natural meadows of Northeast Portugal

André R. S. Marçal, Arlete Rodrigues, Mario Cunha, 2010, 2010 IEEE International Geoscience and Remote Sensing Symposium.

Hyperspectral-based predictive modelling of grapevine water status in the Portuguese Douro wine region

João Gonçalves, L. S. Pereira, Mario Cunha, 2017, Int. J. Appl. Earth Obs. Geoinformation.

Mapping and Assessing the Dynamics of Shifting Agricultural Landscapes Using Google Earth Engine Cloud Computing, a Case Study in Mozambique

Isabel Pocas, Sosdito Mananze, Mário Cunha, 2020, Remote. Sens..

SegOptim - A new R package for optimizing object-based image analyses of high-spatial resolution remotely-sensed data

Caspar A. Mücher, João Gonçalves, Bruno Marcos, 2019, Int. J. Appl. Earth Obs. Geoinformation.

Retrieval of Maize Leaf Area Index Using Hyperspectral and Multispectral Data

Mario Cunha, Isabel Pocas, Sosdito Mananze, 2018, Remote. Sens..

Predicting Grapevine Water Status Based on Hyperspectral Reflectance Vegetation Indices

L. S. Pereira, Arlete Rodrigues, Mario Cunha, 2015, Remote. Sens..