Results 21 to 30 of about 111,278 (179)
Who gets what, where, and how much? Composite index of spatial inequality for small areas in Tehran
Abstract Urban spatial inequality is multidimensional and complex. The extant literature identifies three main theoretically‐informed dimensions of spatial inequality—accessibility, environmental conditions, and socio‐economic conditions. We combine geospatial data on measures across these three theoretical dimensions to derive a composite index for ...
Hamidreza Rabiei‐Dastjerdi +1 more
wiley +1 more source
Se evaluó la mejor dimensión de la escala espacial (dimensión de cuadrantes) y resolución espacial de imágenes (1 y 4 km), con respecto a la frecuencia y permanencia de frentes oceánicos de temperatura que caracterizan la variabilidad estacional e ...
Amelia De la O-Navarrete +2 more
semanticscholar +1 more source
Utilización de imágenes de satélite en el manejo forestal del noreste de México
This work presents a methodological alternative for the generation of information used in the planning of forestry activities. A forest venue located in the south of the state of Nuevo Leon was taken as a site of research. The methodologies were based on
Lucio Ancira-Sánchez +1 more
openalex +3 more sources
En este estudio se analiza espacialmente la fenología vegetal y sus variaciones a lo largo del tiempo en la España peninsular e Islas Baleares. Para realizar el análisis se ha generado una serie temporal de casi 40 años (1983-2020) a partir de la fusión
María Adell-Michavila +4 more
openalex +3 more sources
Los aguajales, son ecosistemas con presencia predominante de aguaje Mauritia flexuosa, aportan importantes beneficios socioeconómicos y ambientales a los pobladores de la Amazonía peruana.
Jorge Manuel Revilla Chávez +7 more
semanticscholar +1 more source
The results obtained with a machine learning method to classify satellite imagery: Random Forest and a contextual classification method: SMAP are compared with those obtained using maximum likelihood.
N. del Toro Espín +3 more
openalex +2 more sources
Clasificación de la salinidad del suelo mediante imágenes de satélite y las redes neuronales artificiales. Classification of soil salinity using satellite images and artificial neural networks Lic. Rolando Renee Badaracco Meza y Dr.
R. R. B. Meza, Joel Rojas Acuña
openalex +2 more sources
Phenological dynamics of vegetation is considered as an important biological indicator for understanding the functioning of terrestrial ecosystems. Land surface phenology (LSP), the study of vegetation phenology from time series of vegetation indices (IV)
J. A. Caparrós-Santiago +1 more
semanticscholar +1 more source
Gracias a técnicas de colorimetría y métodos de clasificación no supervisada, pueden ser vectorizada y trazada la evolución de contaminantes vertidos en el mar con res- pecto al tiempo y al espacio, lo que, en la práctica, abarata el costo de ...
González-Luna Carlos +3 more
openalex +3 more sources
Abstract Habitat loss is a key driver of biodiversity loss. However, hardly any long‐term time series analyses of habitat loss are available above the local scale for finer‐level habitat categories. We analysed, from a long‐term perspective, the habitat specificity of habitat‐area loss, the change in trends in habitat loss since 1989 (dissolution of ...
Marianna Biró +2 more
wiley +1 more source

